Predicting evolutionary rescue via evolving plasticity in stochastic environments

PubMed Central

Baskett, Marissa L.

2016-01-01

Phenotypic plasticity and its evolution may help evolutionary rescue in a novel and stressful environment, especially if environmental novelty reveals cryptic genetic variation that enables the evolution of increased plasticity. However, the environmental stochasticity ubiquitous in natural systems may alter these predictions, because high plasticity may amplify phenotype–environment mismatches. Although previous studies have highlighted this potential detrimental effect of plasticity in stochastic environments, they have not investigated how it affects extinction risk in the context of evolutionary rescue and with evolving plasticity. We investigate this question here by integrating stochastic demography with quantitative genetic theory in a model with simultaneous change in the mean and predictability (temporal autocorrelation) of the environment. We develop an approximate prediction of long-term persistence under the new pattern of environmental fluctuations, and compare it with numerical simulations for short- and long-term extinction risk. We find that reduced predictability increases extinction risk and reduces persistence because it increases stochastic load during rescue. This understanding of how stochastic demography, phenotypic plasticity, and evolution interact when evolution acts on cryptic genetic variation revealed in a novel environment can inform expectations for invasions, extinctions, or the emergence of chemical resistance in pests. PMID:27655762

Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification

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

Li, Chunyuan; Stevens, Andrew J.; Chen, Changyou

2016-08-10

Learning the representation of shape cues in 2D & 3D objects for recognition is a fundamental task in computer vision. Deep neural networks (DNNs) have shown promising performance on this task. Due to the large variability of shapes, accurate recognition relies on good estimates of model uncertainty, ignored in traditional training of DNNs, typically learned via stochastic optimization. This paper leverages recent advances in stochastic gradient Markov Chain Monte Carlo (SG-MCMC) to learn weight uncertainty in DNNs. It yields principled Bayesian interpretations for the commonly used Dropout/DropConnect techniques and incorporates them into the SG-MCMC framework. Extensive experiments on 2D &more » 3D shape datasets and various DNN models demonstrate the superiority of the proposed approach over stochastic optimization. Our approach yields higher recognition accuracy when used in conjunction with Dropout and Batch-Normalization.« less

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

PubMed

Zhou, Jizhong; Ning, Daliang

2017-12-01

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research. Copyright © 2017 American Society for Microbiology.

[Gene method for inconsistent hydrological frequency calculation. I: Inheritance, variability and evolution principles of hydrological genes].

PubMed

Xie, Ping; Wu, Zi Yi; Zhao, Jiang Yan; Sang, Yan Fang; Chen, Jie

2018-04-01

A stochastic hydrological process is influenced by both stochastic and deterministic factors. A hydrological time series contains not only pure random components reflecting its inheri-tance characteristics, but also deterministic components reflecting variability characteristics, such as jump, trend, period, and stochastic dependence. As a result, the stochastic hydrological process presents complicated evolution phenomena and rules. To better understand these complicated phenomena and rules, this study described the inheritance and variability characteristics of an inconsistent hydrological series from two aspects: stochastic process simulation and time series analysis. In addition, several frequency analysis approaches for inconsistent time series were compared to reveal the main problems in inconsistency study. Then, we proposed a new concept of hydrological genes origined from biological genes to describe the inconsistent hydrolocal processes. The hydrologi-cal genes were constructed using moments methods, such as general moments, weight function moments, probability weight moments and L-moments. Meanwhile, the five components, including jump, trend, periodic, dependence and pure random components, of a stochastic hydrological process were defined as five hydrological bases. With this method, the inheritance and variability of inconsistent hydrological time series were synthetically considered and the inheritance, variability and evolution principles were fully described. Our study would contribute to reveal the inheritance, variability and evolution principles in probability distribution of hydrological elements.

Suppressing relaxation in superconducting qubits by quasiparticle pumping.

PubMed

Gustavsson, Simon; Yan, Fei; Catelani, Gianluigi; Bylander, Jonas; Kamal, Archana; Birenbaum, Jeffrey; Hover, David; Rosenberg, Danna; Samach, Gabriel; Sears, Adam P; Weber, Steven J; Yoder, Jonilyn L; Clarke, John; Kerman, Andrew J; Yoshihara, Fumiki; Nakamura, Yasunobu; Orlando, Terry P; Oliver, William D

2016-12-23

Dynamical error suppression techniques are commonly used to improve coherence in quantum systems. They reduce dephasing errors by applying control pulses designed to reverse erroneous coherent evolution driven by environmental noise. However, such methods cannot correct for irreversible processes such as energy relaxation. We investigate a complementary, stochastic approach to reducing errors: Instead of deterministically reversing the unwanted qubit evolution, we use control pulses to shape the noise environment dynamically. In the context of superconducting qubits, we implement a pumping sequence to reduce the number of unpaired electrons (quasiparticles) in close proximity to the device. A 70% reduction in the quasiparticle density results in a threefold enhancement in qubit relaxation times and a comparable reduction in coherence variability. Copyright © 2016, American Association for the Advancement of Science.

A case study in evolutionary contingency.

PubMed

Blount, Zachary D

2016-08-01

Biological evolution is a fundamentally historical phenomenon in which intertwined stochastic and deterministic processes shape lineages with long, continuous histories that exist in a changing world that has a history of its own. The degree to which these characteristics render evolution historically contingent, and evolutionary outcomes thereby unpredictably sensitive to history has been the subject of considerable debate in recent decades. Microbial evolution experiments have proven among the most fruitful means of empirically investigating the issue of historical contingency in evolution. One such experiment is the Escherichia coli Long-Term Evolution Experiment (LTEE), in which twelve populations founded from the same clone of E. coli have evolved in parallel under identical conditions. Aerobic growth on citrate (Cit(+)), a novel trait for E. coli, evolved in one of these populations after more than 30,000 generations. Experimental replays of this population's evolution from various points in its history showed that the Cit(+) trait was historically contingent upon earlier mutations that potentiated the trait by rendering it mutationally accessible. Here I review this case of evolutionary contingency and discuss what it implies about the importance of historical contingency arising from the core processes of evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Density behavior of spatial birth-and-death stochastic evolution of mutating genotypes under selection rates

NASA Astrophysics Data System (ADS)

Finkelshtein, D.; Kondratiev, Yu.; Kutoviy, O.; Molchanov, S.; Zhizhina, E.

2014-10-01

We consider birth-and-death stochastic evolution of genotypes with different lengths. The genotypes might mutate, which provides a stochastic changing of lengths by a free diffusion law. The birth and death rates are length dependent, which corresponds to a selection effect. We study an asymptotic behavior of a density for an infinite collection of genotypes. The cases of space homogeneous and space heterogeneous densities are considered.

Environmental Stochasticity and the Speed of Evolution

NASA Astrophysics Data System (ADS)

Danino, Matan; Kessler, David A.; Shnerb, Nadav M.

2018-03-01

Biological populations are subject to two types of noise: demographic stochasticity due to fluctuations in the reproductive success of individuals, and environmental variations that affect coherently the relative fitness of entire populations. The rate in which the average fitness of a community increases has been considered so far using models with pure demographic stochasticity; here we present some theoretical considerations and numerical results for the general case where environmental variations are taken into account. When the competition is pairwise, fitness fluctuations are shown to reduce the speed of evolution, while under global competition the speed increases due to environmental stochasticity.

Environmental Stochasticity and the Speed of Evolution

NASA Astrophysics Data System (ADS)

Danino, Matan; Kessler, David A.; Shnerb, Nadav M.

2018-07-01

Biological populations are subject to two types of noise: demographic stochasticity due to fluctuations in the reproductive success of individuals, and environmental variations that affect coherently the relative fitness of entire populations. The rate in which the average fitness of a community increases has been considered so far using models with pure demographic stochasticity; here we present some theoretical considerations and numerical results for the general case where environmental variations are taken into account. When the competition is pairwise, fitness fluctuations are shown to reduce the speed of evolution, while under global competition the speed increases due to environmental stochasticity.

Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

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

Doubrawa, P.; Barthelmie, R. J.; Wang, H.

The contribution of wake meandering and shape asymmetry to load and power estimates is quantified by comparing aeroelastic simulations initialized with different inflow conditions: an axisymmetric base wake, an unsteady stochastic shape wake, and a large-eddy simulation with rotating actuator-line turbine representation. Time series of blade-root and tower base bending moments are analyzed. We find that meandering has a large contribution to the fluctuation of the loads. Moreover, considering the wake edge intermittence via the stochastic shape model improves the simulation of load and power fluctuations and of the fatigue damage equivalent loads. Furthermore, these results indicate that the stochasticmore » shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.« less

Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

DOE PAGES

Doubrawa, P.; Barthelmie, R. J.; Wang, H.; ...

2016-10-03

The contribution of wake meandering and shape asymmetry to load and power estimates is quantified by comparing aeroelastic simulations initialized with different inflow conditions: an axisymmetric base wake, an unsteady stochastic shape wake, and a large-eddy simulation with rotating actuator-line turbine representation. Time series of blade-root and tower base bending moments are analyzed. We find that meandering has a large contribution to the fluctuation of the loads. Moreover, considering the wake edge intermittence via the stochastic shape model improves the simulation of load and power fluctuations and of the fatigue damage equivalent loads. Furthermore, these results indicate that the stochasticmore » shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.« less

Direct imaging of nanobubble Ostwald ripening using graphene liquid cell TEM

NASA Astrophysics Data System (ADS)

Xu, Cong; Chen, Qian; Granick, Steve

We directly image the growth, morphology evolution and interaction dynamics of gas nanobubbles in a thin liquid, which are relevant to many materials and electrochemical processes. Using the recently emergent liquid phase transmission electron microscopy (TEM), we resolve the dynamics of nanobubbles in situ at nm resolution in real time. We find that nanobubbles grow through an Ostwald ripening-like process, where adjacent bubbles stochastically fluctuate to disappear or enlarge. Capability of feature tracking enables us to characterize the motions and shape fluctuations of nanobubbles, providing insights into the gas-liquid interfacial fluctuations explored at the nanoscale.

Stochastic response of human blood platelets to stimulation of shape changes and secretion.

PubMed Central

Deranleau, D A; Lüthy, R; Lüscher, E F

1986-01-01

Stopped-flow turbidimetric data indicate that platelets stimulated with low levels of thrombin undergo a shape transformation from disc to "sphere" to smaller spiny sphere that is indistinguishable from the shape change induced by ADP through different membrane receptor sites and a dissimilar receptor trigger mechanism. Under conditions where neither secretion nor aggregation occur, the extinction coefficients for total scattering by each of the three platelet forms are independent of the stimulus applied, and both reaction mechanisms can be described as stochastic (Poisson) processes in which the rate constant for the formation of the transient species is equal to the rate constant for its disappearance. This observation is independent of the shape assignment, and as the concentration of thrombin is increased and various storage organelles secrete increasing amounts of their contents into the external medium, the stochastic pattern persists. Progressively larger decreases in the extinction coefficients of the intermediate and final platelet forms, over and above those that reflect shape alterations alone, accompany or parallel the reaction induced by the higher thrombin concentrations. The excess turbidity decrease observed when full secretion occurs can be wholly accounted for by a decrease in platelet volume equal in magnitude to the fraction of the total platelet volume occupied by alpha granules. Platelet activation, as reported by the whole body light scattering of either shape changes alone or shape changes plus parallel (but not necessarily also stochastic) alpha granule secretion, thus manifests itself as a random series of transient events conceivably with its origins in the superposition of a set of more elementary stochastic processes that could include microtubule depolymerization, actin polymerization, and possibly diffusion. Although the real nature of the control mechanism remains obscure, certain properties of pooled stochastic processes suggest that a reciprocal connection between microtubule fragmentation and the assembly of actin-containing pseudopodal structures and contractile elements--processes that may exhibit reciprocal requirements for calcium--might provide a hypothetical basis for a rate-limiting step. PMID:3457375

Influence of vectors' risk-spreading strategies and environmental stochasticity on the epidemiology and evolution of vector-borne diseases: the example of Chagas' disease.

PubMed

Pelosse, Perrine; Kribs-Zaleta, Christopher M; Ginoux, Marine; Rabinovich, Jorge E; Gourbière, Sébastien; Menu, Frédéric

2013-01-01

Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas' disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control.

Influence of Vectors’ Risk-Spreading Strategies and Environmental Stochasticity on the Epidemiology and Evolution of Vector-Borne Diseases: The Example of Chagas’ Disease

PubMed Central

Pelosse, Perrine; Kribs-Zaleta, Christopher M.; Ginoux, Marine; Rabinovich, Jorge E.; Gourbière, Sébastien; Menu, Frédéric

2013-01-01

Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control. PMID:23951018

A stochastic-field description of finite-size spiking neural networks

PubMed Central

Longtin, André

2017-01-01

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity—the density of active neurons per unit time—is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics. PMID:28787447

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

Chen, Chuchu, E-mail: chenchuchu@lsec.cc.ac.cn; Hong, Jialin, E-mail: hjl@lsec.cc.ac.cn; Zhang, Liying, E-mail: lyzhang@lsec.cc.ac.cn

Stochastic Maxwell equations with additive noise are a system of stochastic Hamiltonian partial differential equations intrinsically, possessing the stochastic multi-symplectic conservation law. It is shown that the averaged energy increases linearly with respect to the evolution of time and the flow of stochastic Maxwell equations with additive noise preserves the divergence in the sense of expectation. Moreover, we propose three novel stochastic multi-symplectic methods to discretize stochastic Maxwell equations in order to investigate the preservation of these properties numerically. We make theoretical discussions and comparisons on all of the three methods to observe that all of them preserve the correspondingmore » discrete version of the averaged divergence. Meanwhile, we obtain the corresponding dissipative property of the discrete averaged energy satisfied by each method. Especially, the evolution rates of the averaged energies for all of the three methods are derived which are in accordance with the continuous case. Numerical experiments are performed to verify our theoretical results.« less

On the physical realizability of quantum stochastic walks

NASA Astrophysics Data System (ADS)

Taketani, Bruno; Govia, Luke; Schuhmacher, Peter; Wilhelm, Frank

Quantum walks are a promising framework that can be used to both understand and implement quantum information processing tasks. The recently developed quantum stochastic walk combines the concepts of a quantum walk and a classical random walk through open system evolution of a quantum system, and have been shown to have applications in as far reaching fields as artificial intelligence. However, nature puts significant constraints on the kind of open system evolutions that can be realized in a physical experiment. In this work, we discuss the restrictions on the allowed open system evolution, and the physical assumptions underpinning them. We then introduce a way to circumvent some of these restrictions, and simulate a more general quantum stochastic walk on a quantum computer, using a technique we call quantum trajectories on a quantum computer. We finally describe a circuit QED approach to implement discrete time quantum stochastic walks.

Space-time-modulated stochastic processes

NASA Astrophysics Data System (ADS)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

Stochasticity versus determinism: consequences for realistic gene regulatory network modelling and evolution.

PubMed

Jenkins, Dafyd J; Stekel, Dov J

2010-02-01

Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.

Two-dimensional electronic spectra from the hierarchical equations of motion method: Application to model dimers

NASA Astrophysics Data System (ADS)

Chen, Liping; Zheng, Renhui; Shi, Qiang; Yan, YiJing

2010-01-01

We extend our previous study of absorption line shapes of molecular aggregates using the Liouville space hierarchical equations of motion (HEOM) method [L. P. Chen, R. H. Zheng, Q. Shi, and Y. J. Yan, J. Chem. Phys. 131, 094502 (2009)] to calculate third order optical response functions and two-dimensional electronic spectra of model dimers. As in our previous work, we have focused on the applicability of several approximate methods related to the HEOM method. We show that while the second order perturbative quantum master equations are generally inaccurate in describing the peak shapes and solvation dynamics, they can give reasonable peak amplitude evolution even in the intermediate coupling regime. The stochastic Liouville equation results in good peak shapes, but does not properly describe the excited state dynamics due to the lack of detailed balance. A modified version of the high temperature approximation to the HEOM gives the best agreement with the exact result.

Dynamics of Tumor Heterogeneity Derived from Clonal Karyotypic Evolution.

PubMed

Laughney, Ashley M; Elizalde, Sergi; Genovese, Giulio; Bakhoum, Samuel F

2015-08-04

Numerical chromosomal instability is a ubiquitous feature of human neoplasms. Due to experimental limitations, fundamental characteristics of karyotypic changes in cancer are poorly understood. Using an experimentally inspired stochastic model, based on the potency and chromosomal distribution of oncogenes and tumor suppressor genes, we show that cancer cells have evolved to exist within a narrow range of chromosome missegregation rates that optimizes phenotypic heterogeneity and clonal survival. Departure from this range reduces clonal fitness and limits subclonal diversity. Mapping of the aneuploid fitness landscape reveals a highly favorable, commonly observed, near-triploid state onto which evolving diploid- and tetraploid-derived populations spontaneously converge, albeit at a much lower fitness cost for the latter. Finally, by analyzing 1,368 chromosomal translocation events in five human cancers, we find that karyotypic evolution also shapes chromosomal translocation patterns by selecting for more oncogenic derivative chromosomes. Thus, chromosomal instability can generate the heterogeneity required for Darwinian tumor evolution. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

Unified Generic Geometric-Decompositions for Consensus or Flocking Systems of Cooperative Agents and Fast Recalculations of Decomposed Subsystems Under Topology-Adjustments.

PubMed

Li, Wei

2016-06-01

This paper considers a unified geometric projection approach for: 1) decomposing a general system of cooperative agents coupled via Laplacian matrices or stochastic matrices and 2) deriving a centroid-subsystem and many shape-subsystems, where each shape-subsystem has the distinct properties (e.g., preservation of formation and stability of the original system, sufficiently simple structures and explicit formation evolution of agents, and decoupling from the centroid-subsystem) which will facilitate subsequent analyses. Particularly, this paper provides an additional merit of the approach: considering adjustments of coupling topologies of agents which frequently occur in system design (e.g., to add or remove an edge, to move an edge to a new place, and to change the weight of an edge), the corresponding new shape-subsystems can be derived by a few simple computations merely from the old shape-subsystems and without referring to the original system, which will provide further convenience for analysis and flexibility of choice. Finally, such fast recalculations of new subsystems under topology adjustments are provided with examples.

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.

Doubly stochastic radial basis function methods

NASA Astrophysics Data System (ADS)

Yang, Fenglian; Yan, Liang; Ling, Leevan

2018-06-01

We propose a doubly stochastic radial basis function (DSRBF) method for function recoveries. Instead of a constant, we treat the RBF shape parameters as stochastic variables whose distribution were determined by a stochastic leave-one-out cross validation (LOOCV) estimation. A careful operation count is provided in order to determine the ranges of all the parameters in our methods. The overhead cost for setting up the proposed DSRBF method is O (n2) for function recovery problems with n basis. Numerical experiments confirm that the proposed method not only outperforms constant shape parameter formulation (in terms of accuracy with comparable computational cost) but also the optimal LOOCV formulation (in terms of both accuracy and computational cost).

Constructive neutral evolution: exploring evolutionary theory's curious disconnect.

PubMed

Stoltzfus, Arlin

2012-10-13

Constructive neutral evolution (CNE) suggests that neutral evolution may follow a stepwise path to extravagance. Whether or not CNE is common, the mere possibility raises provocative questions about causation: in classical neo-Darwinian thinking, selection is the sole source of creativity and direction, the only force that can cause trends or build complex features. However, much of contemporary evolutionary genetics departs from the conception of evolution underlying neo-Darwinism, resulting in a widening gap between what formal models allow, and what the prevailing view of the causes of evolution suggests. In particular, a mutationist conception of evolution as a 2-step origin-fixation process has been a source of theoretical innovation for 40 years, appearing not only in the Neutral Theory, but also in recent breakthroughs in modeling adaptation (the "mutational landscape" model), and in practical software for sequence analysis. In this conception, mutation is not a source of raw materials, but an agent that introduces novelty, while selection is not an agent that shapes features, but a stochastic sieve. This view, which now lays claim to important theoretical, experimental, and practical results, demands our attention. CNE provides a way to explore its most significant implications about the role of variation in evolution. Alex Kondrashov, Eugene Koonin and Johann Peter Gogarten reviewed this article.

Constructive neutral evolution: exploring evolutionary theory’s curious disconnect

PubMed Central

2012-01-01

Abstract Constructive neutral evolution (CNE) suggests that neutral evolution may follow a stepwise path to extravagance. Whether or not CNE is common, the mere possibility raises provocative questions about causation: in classical neo-Darwinian thinking, selection is the sole source of creativity and direction, the only force that can cause trends or build complex features. However, much of contemporary evolutionary genetics departs from the conception of evolution underlying neo-Darwinism, resulting in a widening gap between what formal models allow, and what the prevailing view of the causes of evolution suggests. In particular, a mutationist conception of evolution as a 2-step origin-fixation process has been a source of theoretical innovation for 40 years, appearing not only in the Neutral Theory, but also in recent breakthroughs in modeling adaptation (the “mutational landscape” model), and in practical software for sequence analysis. In this conception, mutation is not a source of raw materials, but an agent that introduces novelty, while selection is not an agent that shapes features, but a stochastic sieve. This view, which now lays claim to important theoretical, experimental, and practical results, demands our attention. CNE provides a way to explore its most significant implications about the role of variation in evolution. Reviewers Alex Kondrashov, Eugene Koonin and Johann Peter Gogarten reviewed this article. PMID:23062217

Natural Erosion of Sandstone as Shape Optimisation.

PubMed

Ostanin, Igor; Safonov, Alexander; Oseledets, Ivan

2017-12-11

Natural arches, pillars and other exotic sandstone formations have always been attracting attention for their unusual shapes and amazing mechanical balance that leave a strong impression of intelligent design rather than the result of a stochastic process. It has been recently demonstrated that these shapes could have been the result of the negative feedback between stress and erosion that originates in fundamental laws of friction between the rock's constituent particles. Here we present a deeper analysis of this idea and bridge it with the approaches utilized in shape and topology optimisation. It appears that the processes of natural erosion, driven by stochastic surface forces and Mohr-Coulomb law of dry friction, can be viewed within the framework of local optimisation for minimum elastic strain energy. Our hypothesis is confirmed by numerical simulations of the erosion using the topological-shape optimisation model. Our work contributes to a better understanding of stochastic erosion and feasible landscape formations that could be found on Earth and beyond.

The Stochastic Evolution of a Protocell: The Gillespie Algorithm in a Dynamically Varying Volume

PubMed Central

Carletti, T.; Filisetti, A.

2012-01-01

We propose an improvement of the Gillespie algorithm allowing us to study the time evolution of an ensemble of chemical reactions occurring in a varying volume, whose growth is directly related to the amount of some specific molecules, belonging to the reactions set. This allows us to study the stochastic evolution of a protocell, whose volume increases because of the production of container molecules. Several protocell models are considered and compared with the deterministic models. PMID:22536297

First-passage times for pattern formation in nonlocal partial differential equations

NASA Astrophysics Data System (ADS)

Cáceres, Manuel O.; Fuentes, Miguel A.

2015-10-01

We describe the lifetimes associated with the stochastic evolution from an unstable uniform state to a patterned one when the time evolution of the field is controlled by a nonlocal Fisher equation. A small noise is added to the evolution equation to define the lifetimes and to calculate the mean first-passage time of the stochastic field through a given threshold value, before the patterned steady state is reached. In order to obtain analytical results we introduce a stochastic multiscale perturbation expansion. This multiscale expansion can also be used to tackle multiplicative stochastic partial differential equations. A critical slowing down is predicted for the marginal case when the Fourier phase of the unstable initial condition is null. We carry out Monte Carlo simulations to show the agreement with our theoretical predictions. Analytic results for the bifurcation point and asymptotic analysis of traveling wave-front solutions are included to get insight into the noise-induced transition phenomena mediated by invading fronts.

First-passage times for pattern formation in nonlocal partial differential equations.

PubMed

Cáceres, Manuel O; Fuentes, Miguel A

2015-10-01

We describe the lifetimes associated with the stochastic evolution from an unstable uniform state to a patterned one when the time evolution of the field is controlled by a nonlocal Fisher equation. A small noise is added to the evolution equation to define the lifetimes and to calculate the mean first-passage time of the stochastic field through a given threshold value, before the patterned steady state is reached. In order to obtain analytical results we introduce a stochastic multiscale perturbation expansion. This multiscale expansion can also be used to tackle multiplicative stochastic partial differential equations. A critical slowing down is predicted for the marginal case when the Fourier phase of the unstable initial condition is null. We carry out Monte Carlo simulations to show the agreement with our theoretical predictions. Analytic results for the bifurcation point and asymptotic analysis of traveling wave-front solutions are included to get insight into the noise-induced transition phenomena mediated by invading fronts.

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation.

PubMed

Ubaldi, Enrico; Perra, Nicola; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

2016-10-24

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals' social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks.

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Perra, Nicola; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

2016-10-01

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals’ social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks.

A damage analysis for brittle materials using stochastic micro-structural information

NASA Astrophysics Data System (ADS)

Lin, Shih-Po; Chen, Jiun-Shyan; Liang, Shixue

2016-03-01

In this work, a micro-crack informed stochastic damage analysis is performed to consider the failures of material with stochastic microstructure. The derivation of the damage evolution law is based on the Helmholtz free energy equivalence between cracked microstructure and homogenized continuum. The damage model is constructed under the stochastic representative volume element (SRVE) framework. The characteristics of SRVE used in the construction of the stochastic damage model have been investigated based on the principle of the minimum potential energy. The mesh dependency issue has been addressed by introducing a scaling law into the damage evolution equation. The proposed methods are then validated through the comparison between numerical simulations and experimental observations of a high strength concrete. It is observed that the standard deviation of porosity in the microstructures has stronger effect on the damage states and the peak stresses than its effect on the Young's and shear moduli in the macro-scale responses.

Experimentally guided models reveal replication principles that shape the mutation distribution of RNA viruses

PubMed Central

Schulte, Michael B; Draghi, Jeremy A; Plotkin, Joshua B; Andino, Raul

2015-01-01

Life history theory posits that the sequence and timing of events in an organism's lifespan are fine-tuned by evolution to maximize the production of viable offspring. In a virus, a life history strategy is largely manifested in its replication mode. Here, we develop a stochastic mathematical model to infer the replication mode shaping the structure and mutation distribution of a poliovirus population in an intact single infected cell. We measure production of RNA and poliovirus particles through the infection cycle, and use these data to infer the parameters of our model. We find that on average the viral progeny produced from each cell are approximately five generations removed from the infecting virus. Multiple generations within a single cell infection provide opportunities for significant accumulation of mutations per viral genome and for intracellular selection. DOI: http://dx.doi.org/10.7554/eLife.03753.001 PMID:25635405

Taming stochastic bifurcations in fractional-order systems via noise and delayed feedback

NASA Astrophysics Data System (ADS)

Sun, Zhongkui; Zhang, Jintian; Yang, Xiaoli; Xu, Wei

2017-08-01

The dynamics in fractional-order systems have been widely studied during the past decade due to the potential applications in new materials and anomalous diffusions, but the investigations have been so far restricted to a fractional-order system without time delay(s). In this paper, we report the first study of random responses of fractional-order system coupled with noise and delayed feedback. Stochastic averaging method has been utilized to determine the stationary probability density functions (PDFs) by means of the principle of minimum mean-square error, based on which stochastic bifurcations could be identified through recognizing the shape of the PDFs. It has been found that by changing the fractional order the shape of the PDFs can switch from unimodal distribution to bimodal one, or from bimodal distribution to unimodal one, thus announcing the onset of stochastic bifurcation. Further, we have demonstrated that by merely modulating the time delay, the feedback strengths, or the noise intensity, the shapes of PDFs can transit between a single peak and a double peak. Therefore, it provides an efficient candidate to control, say, induce or suppress, the stochastic bifurcations in fractional-order systems.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process

NASA Astrophysics Data System (ADS)

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-01

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

An upper limit on the stochastic gravitational-wave background of cosmological origin.

PubMed

Abbott, B P; Abbott, R; Acernese, F; Adhikari, R; Ajith, P; Allen, B; Allen, G; Alshourbagy, M; Amin, R S; Anderson, S B; Anderson, W G; Antonucci, F; Aoudia, S; Arain, M A; Araya, M; Armandula, H; Armor, P; Arun, K G; Aso, Y; Aston, S; Astone, P; Aufmuth, P; Aulbert, C; Babak, S; Baker, P; Ballardin, G; Ballmer, S; Barker, C; Barker, D; Barone, F; Barr, B; Barriga, P; Barsotti, L; Barsuglia, M; Barton, M A; Bartos, I; Bassiri, R; Bastarrika, M; Bauer, Th S; Behnke, B; Beker, M; Benacquista, M; Betzwieser, J; Beyersdorf, P T; Bigotta, S; Bilenko, I A; Billingsley, G; Birindelli, S; Biswas, R; Bizouard, M A; Black, E; Blackburn, J K; Blackburn, L; Blair, D; Bland, B; Boccara, C; Bodiya, T P; Bogue, L; Bondu, F; Bonelli, L; Bork, R; Boschi, V; Bose, S; Bosi, L; Braccini, S; Bradaschia, C; Brady, P R; Braginsky, V B; Brand, J F J van den; Brau, J E; Bridges, D O; Brillet, A; Brinkmann, M; Brisson, V; Van Den Broeck, C; Brooks, A F; Brown, D A; Brummit, A; Brunet, G; Bullington, A; Bulten, H J; Buonanno, A; Burmeister, O; Buskulic, D; Byer, R L; Cadonati, L; Cagnoli, G; Calloni, E; Camp, J B; Campagna, E; Cannizzo, J; Cannon, K C; Canuel, B; Cao, J; Carbognani, F; Cardenas, L; Caride, S; Castaldi, G; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Cella, G; Cepeda, C; Cesarini, E; Chalermsongsak, T; Chalkley, E; Charlton, P; Chassande-Mottin, E; Chatterji, S; Chelkowski, S; Chen, Y; Christensen, N; Chung, C T Y; Clark, D; Clark, J; Clayton, J H; Cleva, F; Coccia, E; Cokelaer, T; Colacino, C N; Colas, J; Colla, A; Colombini, M; Conte, R; Cook, D; Corbitt, T R C; Corda, C; Cornish, N; Corsi, A; Coulon, J-P; Coward, D; Coyne, D C; Creighton, J D E; Creighton, T D; Cruise, A M; Culter, R M; Cumming, A; Cunningham, L; Cuoco, E; Danilishin, S L; D'Antonio, S; Danzmann, K; Dari, A; Dattilo, V; Daudert, B; Davier, M; Davies, G; Daw, E J; Day, R; De Rosa, R; Debra, D; Degallaix, J; Del Prete, M; Dergachev, V; Desai, S; Desalvo, R; Dhurandhar, S; Di Fiore, L; Di Lieto, A; Di Paolo Emilio, M; Di Virgilio, A; Díaz, M; Dietz, A; Donovan, F; Dooley, K L; Doomes, E E; Drago, M; Drever, R W P; Dueck, J; Duke, I; Dumas, J-C; Dwyer, J G; Echols, C; Edgar, M; Effler, A; Ehrens, P; Ely, G; Espinoza, E; Etzel, T; Evans, M; Evans, T; Fafone, V; Fairhurst, S; Faltas, Y; Fan, Y; Fazi, D; Fehrmann, H; Ferrante, I; Fidecaro, F; Finn, L S; Fiori, I; Flaminio, R; Flasch, K; Foley, S; Forrest, C; Fotopoulos, N; Fournier, J-D; Franc, J; Franzen, A; Frasca, S; Frasconi, F; Frede, M; Frei, M; Frei, Z; Freise, A; Frey, R; Fricke, T; Fritschel, P; Frolov, V V; Fyffe, M; Galdi, V; Gammaitoni, L; Garofoli, J A; Garufi, F; Genin, E; Gennai, A; Gholami, I; Giaime, J A; Giampanis, S; Giardina, K D; Giazotto, A; Goda, K; Goetz, E; Goggin, L M; González, G; Gorodetsky, M L; Gobler, S; Gouaty, R; Granata, M; Granata, V; Grant, A; Gras, S; Gray, C; Gray, M; Greenhalgh, R J S; Gretarsson, A M; Greverie, C; Grimaldi, F; Grosso, R; Grote, H; Grunewald, S; Guenther, M; Guidi, G; Gustafson, E K; Gustafson, R; Hage, B; Hallam, J M; Hammer, D; Hammond, G D; Hanna, C; Hanson, J; Harms, J; Harry, G M; Harry, I W; Harstad, E D; Haughian, K; Hayama, K; Heefner, J; Heitmann, H; Hello, P; Heng, I S; Heptonstall, A; Hewitson, M; Hild, S; Hirose, E; Hoak, D; Hodge, K A; Holt, K; Hosken, D J; Hough, J; Hoyland, D; Huet, D; Hughey, B; Huttner, S H; Ingram, D R; Isogai, T; Ito, M; Ivanov, A; Johnson, B; Johnson, W W; Jones, D I; Jones, G; Jones, R; Sancho de la Jordana, L; Ju, L; Kalmus, P; Kalogera, V; Kandhasamy, S; Kanner, J; Kasprzyk, D; Katsavounidis, E; Kawabe, K; Kawamura, S; Kawazoe, F; Kells, W; Keppel, D G; Khalaidovski, A; Khalili, F Y; Khan, R; Khazanov, E; King, P; Kissel, J S; Klimenko, S; Kokeyama, K; Kondrashov, V; Kopparapu, R; Koranda, S; Kozak, D; Krishnan, B; Kumar, R; Kwee, P; La Penna, P; Lam, P K; Landry, M; Lantz, B; Laval, M; Lazzarini, A; Lei, H; Lei, M; Leindecker, N; Leonor, I; Leroy, N; Letendre, N; Li, C; Lin, H; Lindquist, P E; Littenberg, T B; Lockerbie, N A; Lodhia, D; Longo, M; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lu, P; Lubinski, M; Lucianetti, A; Lück, H; Machenschalk, B; Macinnis, M; Mackowski, J-M; Mageswaran, M; Mailand, K; Majorana, E; Man, N; Mandel, I; Mandic, V; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markosyan, A; Markowitz, J; Maros, E; Marque, J; Martelli, F; Martin, I W; Martin, R M; Marx, J N; Mason, K; Masserot, A; Matichard, F; Matone, L; Matzner, R A; Mavalvala, N; McCarthy, R; McClelland, D E; McGuire, S C; McHugh, M; McIntyre, G; McKechan, D J A; McKenzie, K; Mehmet, M; Melatos, A; Melissinos, A C; Mendell, G; Menéndez, D F; Menzinger, F; Mercer, R A; Meshkov, S; Messenger, C; Meyer, M S; Michel, C; Milano, L; Miller, J; Minelli, J; Minenkov, Y; Mino, Y; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Miyakawa, O; Moe, B; Mohan, M; Mohanty, S D; Mohapatra, S R P; Moreau, J; Moreno, G; Morgado, N; Morgia, A; Morioka, T; Mors, K; Mosca, S; Mossavi, K; Mours, B; Mowlowry, C; Mueller, G; Muhammad, D; Mühlen, H Zur; Mukherjee, S; Mukhopadhyay, H; Mullavey, A; Müller-Ebhardt, H; Munch, J; Murray, P G; Myers, E; Myers, J; Nash, T; Nelson, J; Neri, I; Newton, G; Nishizawa, A; Nocera, F; Numata, K; Ochsner, E; O'Dell, J; Ogin, G H; O'Reilly, B; O'Shaughnessy, R; Ottaway, D J; Ottens, R S; Overmier, H; Owen, B J; Pagliaroli, G; Palomba, C; Pan, Y; Pankow, C; Paoletti, F; Papa, M A; Parameshwaraiah, V; Pardi, S; Pasqualetti, A; Passaquieti, R; Passuello, D; Patel, P; Pedraza, M; Penn, S; Perreca, A; Persichetti, G; Pichot, M; Piergiovanni, F; Pierro, V; Pinard, L; Pinto, I M; Pitkin, M; Pletsch, H J; Plissi, M V; Poggiani, R; Postiglione, F; Principe, M; Prix, R; Prodi, G A; Prokhorov, L; Punken, O; Punturo, M; Puppo, P; Putten, S van der; Quetschke, V; Raab, F J; Rabaste, O; Rabeling, D S; Radkins, H; Raffai, P; Raics, Z; Rainer, N; Rakhmanov, M; Rapagnani, P; Raymond, V; Re, V; Reed, C M; Reed, T; Regimbau, T; Rehbein, H; Reid, S; Reitze, D H; Ricci, F; Riesen, R; Riles, K; Rivera, B; Roberts, P; Robertson, N A; Robinet, F; Robinson, C; Robinson, E L; Rocchi, A; Roddy, S; Rolland, L; Rollins, J; Romano, J D; Romano, R; Romie, J H; Röver, C; Rowan, S; Rüdiger, A; Ruggi, P; Russell, P; Ryan, K; Sakata, S; Salemi, F; Sandberg, V; Sannibale, V; Santamaría, L; Saraf, S; Sarin, P; Sassolas, B; Sathyaprakash, B S; Sato, S; Satterthwaite, M; Saulson, P R; Savage, R; Savov, P; Scanlan, M; Schilling, R; Schnabel, R; Schofield, R; Schulz, B; Schutz, B F; Schwinberg, P; Scott, J; Scott, S M; Searle, A C; Sears, B; Seifert, F; Sellers, D; Sengupta, A S; Sentenac, D; Sergeev, A; Shapiro, B; Shawhan, P; Shoemaker, D H; Sibley, A; Siemens, X; Sigg, D; Sinha, S; Sintes, A M; Slagmolen, B J J; Slutsky, J; van der Sluys, M V; Smith, J R; Smith, M R; Smith, N D; Somiya, K; Sorazu, B; Stein, A; Stein, L C; Steplewski, S; Stochino, A; Stone, R; Strain, K A; Strigin, S; Stroeer, A; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, K-X; Sung, M; Sutton, P J; Swinkels, B L; Szokoly, G P; Talukder, D; Tang, L; Tanner, D B; Tarabrin, S P; Taylor, J R; Taylor, R; Terenzi, R; Thacker, J; Thorne, K A; Thorne, K S; Thüring, A; Tokmakov, K V; Toncelli, A; Tonelli, M; Torres, C; Torrie, C; Tournefier, E; Travasso, F; Traylor, G; Trias, M; Trummer, J; Ugolini, D; Ulmen, J; Urbanek, K; Vahlbruch, H; Vajente, G; Vallisneri, M; Vass, S; Vaulin, R; Vavoulidis, M; Vecchio, A; Vedovato, G; van Veggel, A A; Veitch, J; Veitch, P; Veltkamp, C; Verkindt, D; Vetrano, F; Viceré, A; Villar, A; Vinet, J-Y; Vocca, H; Vorvick, C; Vyachanin, S P; Waldman, S J; Wallace, L; Ward, H; Ward, R L; Was, M; Weidner, A; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Wen, S; Wette, K; Whelan, J T; Whitcomb, S E; Whiting, B F; Wilkinson, C; Willems, P A; Williams, H R; Williams, L; Willke, B; Wilmut, I; Winkelmann, L; Winkler, W; Wipf, C C; Wiseman, A G; Woan, G; Wooley, R; Worden, J; Wu, W; Yakushin, I; Yamamoto, H; Yan, Z; Yoshida, S; Yvert, M; Zanolin, M; Zhang, J; Zhang, L; Zhao, C; Zotov, N; Zucker, M E; Zweizig, J

2009-08-20

A stochastic background of gravitational waves is expected to arise from a superposition of a large number of unresolved gravitational-wave sources of astrophysical and cosmological origin. It should carry unique signatures from the earliest epochs in the evolution of the Universe, inaccessible to standard astrophysical observations. Direct measurements of the amplitude of this background are therefore of fundamental importance for understanding the evolution of the Universe when it was younger than one minute. Here we report limits on the amplitude of the stochastic gravitational-wave background using the data from a two-year science run of the Laser Interferometer Gravitational-wave Observatory (LIGO). Our result constrains the energy density of the stochastic gravitational-wave background normalized by the critical energy density of the Universe, in the frequency band around 100 Hz, to be <6.9 x 10(-6) at 95% confidence. The data rule out models of early Universe evolution with relatively large equation-of-state parameter, as well as cosmic (super)string models with relatively small string tension that are favoured in some string theory models. This search for the stochastic background improves on the indirect limits from Big Bang nucleosynthesis and cosmic microwave background at 100 Hz.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

PubMed

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-27

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Drift-driven evolution of electric signals in a Neotropical knifefish.

PubMed

Picq, Sophie; Alda, Fernando; Bermingham, Eldredge; Krahe, Rüdiger

2016-09-01

Communication signals are highly diverse traits. This diversity is usually assumed to be shaped by selective forces, whereas the null hypothesis of divergence through drift is often not considered. In Panama, the weakly electric fish Brachyhypopomus occidentalis is widely distributed in multiple independent drainage systems, which provide a natural evolutionary laboratory for the study of genetic and signal divergence in separate populations. We quantified geographic variation in the electric signals of 109 fish from five populations, and compared it to the neutral genetic variation estimated from cytochrome oxidase I (COI) sequences of the same individuals, to test whether drift may be driving divergence of their signals. Signal distances were highly correlated with genetic distances, even after controlling for geographic distances, suggesting that drift alone is sufficient to explain geographic variation in electric signals. Significant differences at smaller geographic scales (within drainages) showed, however, that electric signals may evolve at a faster rate than expected under drift, raising the possibility that additional adaptive forces may be contributing to their evolution. Overall, our data point to stochastic forces as main drivers of signal evolution in this species and extend the role of drift in the evolution of communication systems to fish and electrocommunication. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Ecological constraint and the evolution of sexual dichromatism in darters.

PubMed

Bossu, Christen M; Near, Thomas J

2015-05-01

It is not known how environmental pressures and sexual selection interact to influence the evolution of extravagant male traits. Sexual and natural selection are often viewed as antagonistic forces shaping the evolution of visual signals, where conspicuousness is favored by sexual selection and crypsis is favored by natural selection. Although typically investigated independently, the interaction between natural and sexual selection remains poorly understood. Here, we investigate whether sexual dichromatism evolves stochastically, independent from, or in concert with habitat use in darters, a species-rich lineage of North American freshwater fish. We find the evolution of sexual dichromatism is coupled to habitat use in darter species. Comparative analyses reveal that mid-water darter lineages exhibit a narrow distribution of dichromatism trait space surrounding a low optimum, suggesting a constraint imposed on the evolution of dichromatism, potentially through predator-mediated selection. Alternatively, the transition to benthic habitats coincides with greater variability in the levels of dichromatism that surround a higher optimum, likely due to relaxation of the predator-mediated selection and heterogeneous microhabitat dependent selection regimes. These results suggest a complex interaction of sexual selection with potentially two mechanisms of natural selection, predation and sensory drive, that influence the evolution of diverse male nuptial coloration in darters. © 2015 The Author(s).

Physical realizability of continuous-time quantum stochastic walks

NASA Astrophysics Data System (ADS)

Taketani, Bruno G.; Govia, Luke C. G.; Wilhelm, Frank K.

2018-05-01

Quantum walks are a promising methodology that can be used to both understand and implement quantum information processing tasks. The quantum stochastic walk is a recently developed framework that combines the concept of a quantum walk with that of a classical random walk, through open system evolution of a quantum system. Quantum stochastic walks have been shown to have applications in as far reaching fields as artificial intelligence. However, there are significant constraints on the kind of open system evolutions that can be realized in a physical experiment. In this work, we discuss the restrictions on the allowed open system evolution and the physical assumptions underpinning them. We show that general direct implementations would require the complete solution of the underlying unitary dynamics and sophisticated reservoir engineering, thus weakening the benefits of experimental implementation.

A kinetic theory for age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Chou, Tom; Greenman, Chris

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but they are structurally unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Conversely, current theories that include size-dependent population dynamics (e.g., carrying capacity) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a BBGKY-like hierarchy. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution. NSF.

Evolutionary Game Theory in Growing Populations

NASA Astrophysics Data System (ADS)

Melbinger, Anna; Cremer, Jonas; Frey, Erwin

2010-10-01

Existing theoretical models of evolution focus on the relative fitness advantages of different mutants in a population while the dynamic behavior of the population size is mostly left unconsidered. We present here a generic stochastic model which combines the growth dynamics of the population and its internal evolution. Our model thereby accounts for the fact that both evolutionary and growth dynamics are based on individual reproduction events and hence are highly coupled and stochastic in nature. We exemplify our approach by studying the dilemma of cooperation in growing populations and show that genuinely stochastic events can ease the dilemma by leading to a transient but robust increase in cooperation.

Environmental Noise Could Promote Stochastic Local Stability of Behavioral Diversity Evolution

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2018-05-01

In this Letter, we investigate stochastic stability in a two-phenotype evolutionary game model for an infinite, well-mixed population undergoing discrete, nonoverlapping generations. We assume that the fitness of a phenotype is an exponential function of its expected payoff following random pairwise interactions whose outcomes randomly fluctuate with time. We show that the stochastic local stability of a constant interior equilibrium can be promoted by the random environmental noise even if the system may display a complicated nonlinear dynamics. This result provides a new perspective for a better understanding of how environmental fluctuations may contribute to the evolution of behavioral diversity.

Unstable Box Orbits in Cuspy Elliptical Galaxies

NASA Technical Reports Server (NTRS)

Hasan, H.; Pfenniger, D.

1996-01-01

The aim of this work is to gain physical insight into the role played by a concentrated central mass in affecting the shape of elliptical galaxies, by examining its effect on the stability of box orbits which are the backbone of triaxial elliptical galaxies. Ample observational evidence is now available for the existence of a central mass concentration or central cusps in galaxies. The central mass is expected to cause orbital stochasticity and chaotic mixing of orbits, which could have ramifications on galactic evolution. We investigate here the interplay between potential cuspiness and eccentricity on the stability of axial orbits in a scale-free potential in a simple, preliminary attempt to characterize this effect.

Controlled Quantum Packets

NASA Technical Reports Server (NTRS)

DeMartino, Salvatore; DeSiena, Silvio

1996-01-01

We look at time evolution of a physical system from the point of view of dynamical control theory. Normally we solve motion equation with a given external potential and we obtain time evolution. Standard examples are the trajectories in classical mechanics or the wave functions in Quantum Mechanics. In the control theory, we have the configurational variables of a physical system, we choose a velocity field and with a suited strategy we force the physical system to have a well defined evolution. The evolution of the system is the 'premium' that the controller receives if he has adopted the right strategy. The strategy is given by well suited laboratory devices. The control mechanisms are in many cases non linear; it is necessary, namely, a feedback mechanism to retain in time the selected evolution. Our aim is to introduce a scheme to obtain Quantum wave packets by control theory. The program is to choose the characteristics of a packet, that is, the equation of evolution for its centre and a controlled dispersion, and to give a building scheme from some initial state (for example a solution of stationary Schroedinger equation). It seems natural in this view to use stochastic approach to Quantum Mechanics, that is, Stochastic Mechanics [S.M.]. It is a quantization scheme different from ordinary ones only formally. This approach introduces in quantum theory the whole mathematical apparatus of stochastic control theory. Stochastic Mechanics, in our view, is more intuitive when we want to study all the classical-like problems. We apply our scheme to build two classes of quantum packets both derived generalizing some properties of coherent states.

Nonlinear stochastic interacting dynamics and complexity of financial gasket fractal-like lattice percolation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2018-05-01

A novel nonlinear stochastic interacting price dynamics is proposed and investigated by the bond percolation on Sierpinski gasket fractal-like lattice, aim to make a new approach to reproduce and study the complexity dynamics of real security markets. Fractal-like lattices correspond to finite graphs with vertices and edges, which are similar to fractals, and Sierpinski gasket is a well-known example of fractals. Fractional ordinal array entropy and fractional ordinal array complexity are introduced to analyze the complexity behaviors of financial signals. To deeper comprehend the fluctuation characteristics of the stochastic price evolution, the complexity analysis of random logarithmic returns and volatility are preformed, including power-law distribution, fractional sample entropy and fractional ordinal array complexity. For further verifying the rationality and validity of the developed stochastic price evolution, the actual security market dataset are also studied with the same statistical methods for comparison. The empirical results show that this stochastic price dynamics can reconstruct complexity behaviors of the actual security markets to some extent.

Enhancing the branching ratios in the dissociation channels for O{sup 16}O{sup 16}O{sup 18} molecule by designing optimum laser pulses: A study using stochastic optimization

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

Talukder, Srijeeta; Chaudhury, Pinaki, E-mail: pinakc@rediffmail.com; Sen, Shrabani

We propose a strategy of using a stochastic optimization technique, namely, simulated annealing to design optimum laser pulses (both IR and UV) to achieve greater fluxes along the two dissociating channels (O{sup 18} + O{sup 16}O{sup 16} and O{sup 16} + O{sup 16}O{sup 18}) in O{sup 16}O{sup 16}O{sup 18} molecule. We show that the integrated fluxes obtained along the targeted dissociating channel is larger with the optimized pulse than with the unoptimized one. The flux ratios are also more impressive with the optimized pulse than with the unoptimized one. We also look at the evolution contours of the wavefunctions alongmore » the two channels with time after the actions of both the IR and UV pulses and compare the profiles for unoptimized (initial) and optimized fields for better understanding the results that we achieve. We also report the pulse parameters obtained as well as the final shapes they take.« less

A stochastic evolution model for residue Insertion-Deletion Independent from Substitution.

PubMed

Lèbre, Sophie; Michel, Christian J

2010-12-01

We develop here a new class of stochastic models of gene evolution based on residue Insertion-Deletion Independent from Substitution (IDIS). Indeed, in contrast to all existing evolution models, insertions and deletions are modeled here by a concept in population dynamics. Therefore, they are not only independent from each other, but also independent from the substitution process. After a separate stochastic analysis of the substitution and the insertion-deletion processes, we obtain a matrix differential equation combining these two processes defining the IDIS model. By deriving a general solution, we give an analytical expression of the residue occurrence probability at evolution time t as a function of a substitution rate matrix, an insertion rate vector, a deletion rate and an initial residue probability vector. Various mathematical properties of the IDIS model in relation with time t are derived: time scale, time step, time inversion and sequence length. Particular expressions of the nucleotide occurrence probability at time t are given for classical substitution rate matrices in various biological contexts: equal insertion rate, insertion-deletion only and substitution only. All these expressions can be directly used for biological evolutionary applications. The IDIS model shows a strongly different stochastic behavior from the classical substitution only model when compared on a gene dataset. Indeed, by considering three processes of residue insertion, deletion and substitution independently from each other, it allows a more realistic representation of gene evolution and opens new directions and applications in this research field. Copyright © 2010 Elsevier Ltd. All rights reserved.

Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

Sources and Sinks: A Stochastic Model of Evolution in Heterogeneous Environments

NASA Astrophysics Data System (ADS)

Hermsen, Rutger; Hwa, Terence

2010-12-01

We study evolution driven by spatial heterogeneity in a stochastic model of source-sink ecologies. A sink is a habitat where mortality exceeds reproduction so that a local population persists only due to immigration from a source. Immigrants can, however, adapt to conditions in the sink by mutation. To characterize the adaptation rate, we derive expressions for the first arrival time of adapted mutants. The joint effects of migration, mutation, birth, and death result in two distinct parameter regimes. These results may pertain to the rapid evolution of drug-resistant pathogens and insects.

Stochastic Evolution Equations Driven by Fractional Noises

DTIC Science & Technology

2016-11-28

rate of convergence to zero or the error and the limit in distribution of the error fluctuations. We have studied time discrete numerical schemes...error fluctuations. We have studied time discrete numerical schemes based on Taylor expansions for rough differential equations and for stochastic...variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian

Application of stochastic processes in random growth and evolutionary dynamics

NASA Astrophysics Data System (ADS)

Oikonomou, Panagiotis

We study the effect of power-law distributed randomness on the dynamical behavior of processes such as stochastic growth patterns and evolution. First, we examine the geometrical properties of random shapes produced by a generalized stochastic Loewner Evolution driven by a superposition of a Brownian motion and a stable Levy process. The situation is defined by the usual stochastic Loewner Evolution parameter, kappa, as well as alpha which defines the power-law tail of the stable Levy distribution. We show that the properties of these patterns change qualitatively and singularly at critical values of kappa and alpha. It is reasonable to call such changes "phase transitions". These transitions occur as kappa passes through four and as alpha passes through one. Numerical simulations are used to explore the global scaling behavior of these patterns in each "phase". We show both analytically and numerically that the growth continues indefinitely in the vertical direction for alpha greater than 1, goes as logarithmically with time for alpha equals to 1, and saturates for alpha smaller than 1. The probability density has two different scales corresponding to directions along and perpendicular to the boundary. Scaling functions for the probability density are given for various limiting cases. Second, we study the effect of the architecture of biological networks on their evolutionary dynamics. In recent years, studies of the architecture of large networks have unveiled a common topology, called scale-free, in which a majority of the elements are poorly connected except for a small fraction of highly connected components. We ask how networks with distinct topologies can evolve towards a pre-established target phenotype through a process of random mutations and selection. We use networks of Boolean components as a framework to model a large class of phenotypes. Within this approach, we find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. While homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously towards the target phenotype. Moreover, we show that scale-free networks always evolve faster than homogeneous random networks; remarkably, this property does not depend on the precise value of the topological parameter. By contrast, homogeneous random networks require a specific tuning of their topological parameter in order to optimize their fitness. This model suggests that the evolutionary paths of biological networks, punctuated or continuous, may solely be determined by the network topology.

The Stochastic Evolutionary Game for a Population of Biological Networks Under Natural Selection

PubMed Central

Chen, Bor-Sen; Ho, Shih-Ju

2014-01-01

In this study, a population of evolutionary biological networks is described by a stochastic dynamic system with intrinsic random parameter fluctuations due to genetic variations and external disturbances caused by environmental changes in the evolutionary process. Since information on environmental changes is unavailable and their occurrence is unpredictable, they can be considered as a game player with the potential to destroy phenotypic stability. The biological network needs to develop an evolutionary strategy to improve phenotypic stability as much as possible, so it can be considered as another game player in the evolutionary process, ie, a stochastic Nash game of minimizing the maximum network evolution level caused by the worst environmental disturbances. Based on the nonlinear stochastic evolutionary game strategy, we find that some genetic variations can be used in natural selection to construct negative feedback loops, efficiently improving network robustness. This provides larger genetic robustness as a buffer against neutral genetic variations, as well as larger environmental robustness to resist environmental disturbances and maintain a network phenotypic traits in the evolutionary process. In this situation, the robust phenotypic traits of stochastic biological networks can be more frequently selected by natural selection in evolution. However, if the harbored neutral genetic variations are accumulated to a sufficiently large degree, and environmental disturbances are strong enough that the network robustness can no longer confer enough genetic robustness and environmental robustness, then the phenotype robustness might break down. In this case, a network phenotypic trait may be pushed from one equilibrium point to another, changing the phenotypic trait and starting a new phase of network evolution through the hidden neutral genetic variations harbored in network robustness by adaptive evolution. Further, the proposed evolutionary game is extended to an n-tuple evolutionary game of stochastic biological networks with m players (competitive populations) and k environmental dynamics. PMID:24558296

Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process.

PubMed

Greenman, C D; Cooke, S L; Marshall, J; Stratton, M R; Campbell, P J

2016-01-01

Breakage-fusion-bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. Here we study the evolution space of breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are [Formula: see text] qualitatively distinct evolutions involving [Formula: see text] breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the process to show these evolutions are not equally likely, and also describe how amplicons become localized. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples.

ENVIRONMENT: a computational platform to stochastically simulate reacting and self-reproducing lipid compartments

NASA Astrophysics Data System (ADS)

Mavelli, Fabio; Ruiz-Mirazo, Kepa

2010-09-01

'ENVIRONMENT' is a computational platform that has been developed in the last few years with the aim to simulate stochastically the dynamics and stability of chemically reacting protocellular systems. Here we present and describe some of its main features, showing how the stochastic kinetics approach can be applied to study the time evolution of reaction networks in heterogeneous conditions, particularly when supramolecular lipid structures (micelles, vesicles, etc) coexist with aqueous domains. These conditions are of special relevance to understand the origins of cellular, self-reproducing compartments, in the context of prebiotic chemistry and evolution. We contrast our simulation results with real lab experiments, with the aim to bring together theoretical and experimental research on protocell and minimal artificial cell systems.

Ecological specialization and morphological diversification in Greater Antillean boas.

PubMed

Reynolds, R Graham; Collar, David C; Pasachnik, Stesha A; Niemiller, Matthew L; Puente-Rolón, Alberto R; Revell, Liam J

2016-08-01

Colonization of islands can dramatically influence the evolutionary trajectories of organisms, with both deterministic and stochastic processes driving adaptation and diversification. Some island colonists evolve extremely large or small body sizes, presumably in response to unique ecological circumstances present on islands. One example of this phenomenon, the Greater Antillean boas, includes both small (<90 cm) and large (4 m) species occurring on the Greater Antilles and Bahamas, with some islands supporting pairs or trios of body-size divergent species. These boas have been shown to comprise a monophyletic radiation arising from a Miocene dispersal event to the Greater Antilles, though it is not known whether co-occurrence of small and large species is a result of dispersal or in situ evolution. Here, we provide the first comprehensive species phylogeny for this clade combined with morphometric and ecological data to show that small body size evolved repeatedly on separate islands in association with specialization in substrate use. Our results further suggest that microhabitat specialization is linked to increased rates of head shape diversification among specialists. Our findings show that ecological specialization following island colonization promotes morphological diversity through deterministic body size evolution and cranial morphological diversification that is contingent on island- and species-specific factors. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Calibration of a stochastic health evolution model using NHIS data

NASA Astrophysics Data System (ADS)

Gupta, Aparna; Li, Zhisheng

2011-10-01

This paper presents and calibrates an individual's stochastic health evolution model. In this health evolution model, the uncertainty of health incidents is described by a stochastic process with a finite number of possible outcomes. We construct a comprehensive health status index (HSI) to describe an individual's health status, as well as a health risk factor system (RFS) to classify individuals into different risk groups. Based on the maximum likelihood estimation (MLE) method and the method of nonlinear least squares fitting, model calibration is formulated in terms of two mixed-integer nonlinear optimization problems. Using the National Health Interview Survey (NHIS) data, the model is calibrated for specific risk groups. Longitudinal data from the Health and Retirement Study (HRS) is used to validate the calibrated model, which displays good validation properties. The end goal of this paper is to provide a model and methodology, whose output can serve as a crucial component of decision support for strategic planning of health related financing and risk management.

An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks.

PubMed

Salis, Howard; Kaznessis, Yiannis N

2005-12-01

Stochastic chemical kinetics more accurately describes the dynamics of "small" chemical systems, such as biological cells. Many real systems contain dynamical stiffness, which causes the exact stochastic simulation algorithm or other kinetic Monte Carlo methods to spend the majority of their time executing frequently occurring reaction events. Previous methods have successfully applied a type of probabilistic steady-state approximation by deriving an evolution equation, such as the chemical master equation, for the relaxed fast dynamics and using the solution of that equation to determine the slow dynamics. However, because the solution of the chemical master equation is limited to small, carefully selected, or linear reaction networks, an alternate equation-free method would be highly useful. We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. We demonstrate the accuracy and efficiency of the method using multiple interesting examples, including a highly nonlinear protein-protein interaction network. The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques.

Inertia in strategy switching transforms the strategy evolution.

PubMed

Zhang, Yanling; Fu, Feng; Wu, Te; Xie, Guangming; Wang, Long

2011-12-01

A recent experimental study [Traulsen et al., Proc. Natl. Acad. Sci. 107, 2962 (2010)] shows that human strategy updating involves both direct payoff comparison and the cost of switching strategy, which is equivalent to inertia. However, it remains largely unclear how such a predisposed inertia affects 2 × 2 games in a well-mixed population of finite size. To address this issue, the "inertia bonus" (strategy switching cost) is added to the learner payoff in the Fermi process. We find how inertia quantitatively shapes the stationary distribution and that stochastic stability under inertia exhibits three regimes, with each covering seven regions in the plane spanned by two inertia parameters. We also obtain the extended "1/3" rule with inertia and the speed criterion with inertia; these two findings hold for a population above two. We illustrate the above results in the framework of the Prisoner's Dilemma game. As inertia varies, two intriguing stationary distributions emerge: the probability of coexistence state is maximized, or those of two full states are simultaneously peaked. Our results may provide useful insights into how the inertia of changing status quo acts on the strategy evolution and, in particular, the evolution of cooperation.

Effect of the Potential Shape on the Stochastic Resonance Processes

NASA Astrophysics Data System (ADS)

Kenmoé, G. Djuidjé; Ngouongo, Y. J. Wadop; Kofané, T. C.

2015-10-01

The stochastic resonance (SR) induced by periodic signal and white noises in a periodic nonsinusoidal potential is investigated. This phenomenon is studied as a function of the friction coefficient as well as the shape of the potential. It is done through an investigation of the hysteresis loop area which is equivalent to the input energy lost by the system to the environment per period of the external force. SR is evident in some range of the shape parameter of the potential, but cannot be observed in the other range. Specially, variation of the shape potential affects significantly and not trivially the heigh of the potential barrier in the Kramers rate as well as the occurrence of SR. The finding results show crucial dependence of the temperature of occurrence of SR on the shape of the potential. It is noted that the maximum of the input energy generally decreases when the friction coefficient is increased.

Evolution of the Climate Continuum from the Mid-Miocene Climatic Optimum to the Present

NASA Astrophysics Data System (ADS)

Aswasereelert, W.; Meyers, S. R.; Hinnov, L. A.; Kelly, D.

2011-12-01

The recognition of orbital rhythms in paleoclimate data has led to a rich understanding of climate evolution during the Neogene and Quaternary. In contrast, changes in stochastic variability associated with the transition from unipolar to bipolar glaciation have received less attention, although the stochastic component likely preserves key insights about climate. In this study, we seek to evaluate the dominance and character of stochastic climate energy since the Middle Miocene Climatic Optimum (~17 Ma). These analyses extend a previous study that suggested diagnostic stochastic responses associated with Northern Hemisphere ice sheet development during the Plio-Pleistocene (Meyers and Hinnov, 2010). A critical and challenging step necessary to conduct the work is the conversion of depth data to time data. We investigate climate proxy datasets using multiple time scale hypotheses, including depth-derived time scales, sedimentologic/geochemical "tuning", minimal orbital tuning, and comprehensive orbital tuning. To extract the stochastic component of climate, and also explore potential relationships between the orbital parameters and paleoclimate response, a number of approaches rooted in Thomson's (1982) multi-taper spectral method (MTM) are applied. Importantly, the MTM technique is capable of separating the spectral "continuum" - a measure of stochastic variability - from the deterministic periodic orbital signals (spectral "lines") preserved in proxy data. Time series analysis of the proxy records using different chronologic approaches allows us to evaluate the sensitivity of our conclusion about stochastic and deterministic orbital processes during the Middle Miocene to present. Moreover, comparison of individual records permits examination of the spatial dependence of the identified climate responses. Meyers, S.R., and Hinnov, L.A. (2010), Northern Hemisphere glaciation and the evolution of Plio-Pleistocene climate noise: Paleoceanography, 25, PA3207, doi:10.1029/2009PA001834. Thomson, D.J. (1982), Spectrum estimation and harmonic analysis: IEEE Proceedings, v. 70, p. 1055-1096.

Stochastic evolution in populations of ideas

PubMed Central

Nicole, Robin; Sollich, Peter; Galla, Tobias

2017-01-01

It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games. PMID:28098244

Stochastic evolution in populations of ideas

NASA Astrophysics Data System (ADS)

Nicole, Robin; Sollich, Peter; Galla, Tobias

2017-01-01

It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games.

A Stochastic Evolutionary Model for Protein Structure Alignment and Phylogeny

PubMed Central

Challis, Christopher J.; Schmidler, Scott C.

2012-01-01

We present a stochastic process model for the joint evolution of protein primary and tertiary structure, suitable for use in alignment and estimation of phylogeny. Indels arise from a classic Links model, and mutations follow a standard substitution matrix, whereas backbone atoms diffuse in three-dimensional space according to an Ornstein–Uhlenbeck process. The model allows for simultaneous estimation of evolutionary distances, indel rates, structural drift rates, and alignments, while fully accounting for uncertainty. The inclusion of structural information enables phylogenetic inference on time scales not previously attainable with sequence evolution models. The model also provides a tool for testing evolutionary hypotheses and improving our understanding of protein structural evolution. PMID:22723302

Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

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

Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M., E-mail: abel@utk.edu

2016-01-07

Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations.more » Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules.« less

Random function representation of stationary stochastic vector processes for probability density evolution analysis of wind-induced structures

NASA Astrophysics Data System (ADS)

Liu, Zhangjun; Liu, Zenghui

2018-06-01

This paper develops a hybrid approach of spectral representation and random function for simulating stationary stochastic vector processes. In the proposed approach, the high-dimensional random variables, included in the original spectral representation (OSR) formula, could be effectively reduced to only two elementary random variables by introducing the random functions that serve as random constraints. Based on this, a satisfactory simulation accuracy can be guaranteed by selecting a small representative point set of the elementary random variables. The probability information of the stochastic excitations can be fully emerged through just several hundred of sample functions generated by the proposed approach. Therefore, combined with the probability density evolution method (PDEM), it could be able to implement dynamic response analysis and reliability assessment of engineering structures. For illustrative purposes, a stochastic turbulence wind velocity field acting on a frame-shear-wall structure is simulated by constructing three types of random functions to demonstrate the accuracy and efficiency of the proposed approach. Careful and in-depth studies concerning the probability density evolution analysis of the wind-induced structure have been conducted so as to better illustrate the application prospects of the proposed approach. Numerical examples also show that the proposed approach possesses a good robustness.

Stochastic geometry in disordered systems, applications to quantum Hall transitions

NASA Astrophysics Data System (ADS)

Gruzberg, Ilya

2012-02-01

A spectacular success in the study of random fractal clusters and their boundaries in statistical mechanics systems at or near criticality using Schramm-Loewner Evolutions (SLE) naturally calls for extensions in various directions. Can this success be repeated for disordered and/or non-equilibrium systems? Naively, when one thinks about disordered systems and their average correlation functions one of the very basic assumptions of SLE, the so called domain Markov property, is lost. Also, in some lattice models of Anderson transitions (the network models) there are no natural clusters to consider. Nevertheless, in this talk I will argue that one can apply the so called conformal restriction, a notion of stochastic conformal geometry closely related to SLE, to study the integer quantum Hall transition and its variants. I will focus on the Chalker-Coddington network model and will demonstrate that its average transport properties can be mapped to a classical problem where the basic objects are geometric shapes (loosely speaking, the current paths) that obey an important restriction property. At the transition point this allows to use the theory of conformal restriction to derive exact expressions for point contact conductances in the presence of various non-trivial boundary conditions.

Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis

PubMed Central

Meng, Xiang; Firczuk, Helena; Pietroni, Paola; Westbrook, Richard; Dacheux, Estelle; Mendes, Pedro; McCarthy, John E.G.

2017-01-01

Gene expression noise influences organism evolution and fitness. The mechanisms determining the relationship between stochasticity and the functional role of translation machinery components are critical to viability. eIF4G is an essential translation factor that exerts strong control over protein synthesis. We observe an asymmetric, approximately bell-shaped, relationship between the average intracellular abundance of eIF4G and rates of cell population growth and global mRNA translation, with peak rates occurring at normal physiological abundance. This relationship fits a computational model in which eIF4G is at the core of a multi-component–complex assembly pathway. This model also correctly predicts a plateau-like response of translation to super-physiological increases in abundance of the other cap-complex factors, eIF4E and eIF4A. Engineered changes in eIF4G abundance amplify noise, demonstrating that minimum stochasticity coincides with physiological abundance of this factor. Noise is not increased when eIF4E is overproduced. Plasmid-mediated synthesis of eIF4G imposes increased global gene expression stochasticity and reduced viability because the intrinsic noise for this factor influences total cellular gene noise. The naturally evolved eIF4G gene expression noise minimum maps within the optimal activity zone dictated by eIF4G's mechanistic role. Rate control and noise are therefore interdependent and have co-evolved to share an optimal physiological abundance point. PMID:27928055

Kinetic theory of age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Greenman, Chris D.; Chou, Tom

2016-01-01

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but are unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Stochastic theories that treat semi-Markov age-dependent processes using, e.g., the Bellman-Harris equation do not resolve a population's age structure and are unable to quantify population-size dependencies. Conversely, current theories that include size-dependent population dynamics (e.g., mathematical models that include carrying capacity such as the logistic equation) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new, fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a Bogoliubov--Born--Green--Kirkwood--Yvon-like hierarchy. Explicit solutions are derived in three limits: no birth, no death, and steady state. These are then compared with their corresponding mean-field results. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution.

Advances in planetary geology

NASA Technical Reports Server (NTRS)

Woronow, A. (Editor)

1981-01-01

Three dissertations are provided covering (1) the stochastic evolution of asteroidal regoliths and the origin of brecciated and gas-rich meteorites; (2) ridge systems on Mars; and (3) the morphology and evolution of Ganymede and Callisto.

Quasiparticle spectra from molecules to bulk

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

Vlček, Vojtěch; Rabani, Eran; Neuhauser, Daniel

We present a stochastic cumulant GW method, allowing us to map the evolution of photoemission spectra, quasiparticle energies, lifetimes, and emergence of collective excitations from molecules to bulklike systems with up to thousands of valence electrons, including Si nanocrystals and nanoplatelets. The quasiparticle energies rise due to their coupling with collective shake-up (plasmon) excitations, and this coupling leads to significant spectral weight loss (up to 50% for the low-energy states), shortening the lifetimes and shifting the spectral features to lower energies by as much as 0.6 eV. Such features are common to all the systems studied irrespective of their sizesmore » and shapes. For small and low-dimensional systems the surface plasmon resonances affect the frequency of the collective excitation and position of the satellites.« less

Quasiparticle spectra from molecules to bulk

DOE PAGES

Vlček, Vojtěch; Rabani, Eran; Neuhauser, Daniel

2018-03-16

We present a stochastic cumulant GW method, allowing us to map the evolution of photoemission spectra, quasiparticle energies, lifetimes, and emergence of collective excitations from molecules to bulklike systems with up to thousands of valence electrons, including Si nanocrystals and nanoplatelets. The quasiparticle energies rise due to their coupling with collective shake-up (plasmon) excitations, and this coupling leads to significant spectral weight loss (up to 50% for the low-energy states), shortening the lifetimes and shifting the spectral features to lower energies by as much as 0.6 eV. Such features are common to all the systems studied irrespective of their sizesmore » and shapes. For small and low-dimensional systems the surface plasmon resonances affect the frequency of the collective excitation and position of the satellites.« less

Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty

PubMed Central

Lei, Xiaohui; Wang, Chao; Yue, Dong; Xie, Xiangpeng

2017-01-01

Since wind power is integrated into the thermal power operation system, dynamic economic emission dispatch (DEED) has become a new challenge due to its uncertain characteristics. This paper proposes an adaptive grid based multi-objective Cauchy differential evolution (AGB-MOCDE) for solving stochastic DEED with wind power uncertainty. To properly deal with wind power uncertainty, some scenarios are generated to simulate those possible situations by dividing the uncertainty domain into different intervals, the probability of each interval can be calculated using the cumulative distribution function, and a stochastic DEED model can be formulated under different scenarios. For enhancing the optimization efficiency, Cauchy mutation operation is utilized to improve differential evolution by adjusting the population diversity during the population evolution process, and an adaptive grid is constructed for retaining diversity distribution of Pareto front. With consideration of large number of generated scenarios, the reduction mechanism is carried out to decrease the scenarios number with covariance relationships, which can greatly decrease the computational complexity. Moreover, the constraint-handling technique is also utilized to deal with the system load balance while considering transmission loss among thermal units and wind farms, all the constraint limits can be satisfied under the permitted accuracy. After the proposed method is simulated on three test systems, the obtained results reveal that in comparison with other alternatives, the proposed AGB-MOCDE can optimize the DEED problem while handling all constraint limits, and the optimal scheme of stochastic DEED can decrease the conservation of interval optimization, which can provide a more valuable optimal scheme for real-world applications. PMID:28961262

Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation

PubMed Central

Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

2016-01-01

Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother’s old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother’s old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington’s genetic assimilation. Our model is able to quantify the evolution of the assimilation because it characterizes the fitness consequences of variation. PMID:26761487

Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

PubMed

Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

2016-01-01

Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington's genetic assimilation. Our model is able to quantify the evolution of the assimilation because it characterizes the fitness consequences of variation.

Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

PubMed

Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

2015-01-01

It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

Tsunamis: stochastic models of occurrence and generation mechanisms

USGS Publications Warehouse

Geist, Eric L.; Oglesby, David D.

2014-01-01

The devastating consequences of the 2004 Indian Ocean and 2011 Japan tsunamis have led to increased research into many different aspects of the tsunami phenomenon. In this entry, we review research related to the observed complexity and uncertainty associated with tsunami generation, propagation, and occurrence described and analyzed using a variety of stochastic methods. In each case, seismogenic tsunamis are primarily considered. Stochastic models are developed from the physical theories that govern tsunami evolution combined with empirical models fitted to seismic and tsunami observations, as well as tsunami catalogs. These stochastic methods are key to providing probabilistic forecasts and hazard assessments for tsunamis. The stochastic methods described here are similar to those described for earthquakes (Vere-Jones 2013) and volcanoes (Bebbington 2013) in this encyclopedia.

Time Ordering in Frontal Lobe Patients: A Stochastic Model Approach

ERIC Educational Resources Information Center

Magherini, Anna; Saetti, Maria Cristina; Berta, Emilia; Botti, Claudio; Faglioni, Pietro

2005-01-01

Frontal lobe patients reproduced a sequence of capital letters or abstract shapes. Immediate and delayed reproduction trials allowed the analysis of short- and long-term memory for time order by means of suitable Markov chain stochastic models. Patients were as proficient as healthy subjects on the immediate reproduction trial, thus showing spared…

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

PubMed

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Time Evolution of the Dynamical Variables of a Stochastic System.

ERIC Educational Resources Information Center

de la Pena, L.

1980-01-01

By using the method of moments, it is shown that several important and apparently unrelated theorems describing average properties of stochastic systems are in fact particular cases of a general law; this method is applied to generalize the virial theorem and the fluctuation-dissipation theorem to the time-dependent case. (Author/SK)

Periodic modulation-based stochastic resonance algorithm applied to quantitative analysis for weak liquid chromatography-mass spectrometry signal of granisetron in plasma

NASA Astrophysics Data System (ADS)

Xiang, Suyun; Wang, Wei; Xiang, Bingren; Deng, Haishan; Xie, Shaofei

2007-05-01

The periodic modulation-based stochastic resonance algorithm (PSRA) was used to amplify and detect the weak liquid chromatography-mass spectrometry (LC-MS) signal of granisetron in plasma. In the algorithm, the stochastic resonance (SR) was achieved by introducing an external periodic force to the nonlinear system. The optimization of parameters was carried out in two steps to give attention to both the signal-to-noise ratio (S/N) and the peak shape of output signal. By applying PSRA with the optimized parameters, the signal-to-noise ratio of LC-MS peak was enhanced significantly and distorted peak shape that often appeared in the traditional stochastic resonance algorithm was corrected by the added periodic force. Using the signals enhanced by PSRA, this method extended the limit of detection (LOD) and limit of quantification (LOQ) of granisetron in plasma from 0.05 and 0.2 ng/mL, respectively, to 0.01 and 0.02 ng/mL, and exhibited good linearity, accuracy and precision, which ensure accurate determination of the target analyte.

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

Han, Yong; Lii-Rosales, A.; Zhou, Y.

Theory and stochastic lattice-gas modeling is developed for the formation of intercalated metal islands in the gallery between the top layer and the underlying layer at the surface of layered materials. Our model for this process involves deposition of atoms, some fraction of which then enter the gallery through well-separated pointlike defects in the top layer. Subsequently, these atoms diffuse within the subsurface gallery leading to nucleation and growth of intercalated islands nearby the defect point source. For the case of a single point defect, continuum diffusion equation analysis provides insight into the nucleation kinetics. However, complementary tailored lattice-gas modelingmore » produces a more comprehensive and quantitative characterization. We analyze the large spread in nucleation times and positions relative to the defect for the first nucleated island. We also consider the formation of subsequent islands and the evolution of island growth shapes. The shapes reflect in part our natural adoption of a hexagonal close-packed island structure. As a result, motivation and support for the model is provided by scanning tunneling microscopy observations of the formation of intercalated metal islands in highly-ordered pyrolytic graphite at higher temperatures.« less

Detecting evolutionary forces in language change.

PubMed

Newberry, Mitchell G; Ahern, Christopher A; Clark, Robin; Plotkin, Joshua B

2017-11-09

Both language and genes evolve by transmission over generations with opportunity for differential replication of forms. The understanding that gene frequencies change at random by genetic drift, even in the absence of natural selection, was a seminal advance in evolutionary biology. Stochastic drift must also occur in language as a result of randomness in how linguistic forms are copied between speakers. Here we quantify the strength of selection relative to stochastic drift in language evolution. We use time series derived from large corpora of annotated texts dating from the 12th to 21st centuries to analyse three well-known grammatical changes in English: the regularization of past-tense verbs, the introduction of the periphrastic 'do', and variation in verbal negation. We reject stochastic drift in favour of selection in some cases but not in others. In particular, we infer selection towards the irregular forms of some past-tense verbs, which is likely driven by changing frequencies of rhyming patterns over time. We show that stochastic drift is stronger for rare words, which may explain why rare forms are more prone to replacement than common ones. This work provides a method for testing selective theories of language change against a null model and reveals an underappreciated role for stochasticity in language evolution.

Mixed Poisson distributions in exact solutions of stochastic autoregulation models.

PubMed

Iyer-Biswas, Srividya; Jayaprakash, C

2014-11-01

In this paper we study the interplay between stochastic gene expression and system design using simple stochastic models of autoactivation and autoinhibition. Using the Poisson representation, a technique whose particular usefulness in the context of nonlinear gene regulation models we elucidate, we find exact results for these feedback models in the steady state. Further, we exploit this representation to analyze the parameter spaces of each model, determine which dimensionless combinations of rates are the shape determinants for each distribution, and thus demarcate where in the parameter space qualitatively different behaviors arise. These behaviors include power-law-tailed distributions, bimodal distributions, and sub-Poisson distributions. We also show how these distribution shapes change when the strength of the feedback is tuned. Using our results, we reexamine how well the autoinhibition and autoactivation models serve their conventionally assumed roles as paradigms for noise suppression and noise exploitation, respectively.

Numerical Simulation and Quantitative Uncertainty Assessment of Microchannel Flow

NASA Astrophysics Data System (ADS)

Debusschere, Bert; Najm, Habib; Knio, Omar; Matta, Alain; Ghanem, Roger; Le Maitre, Olivier

2002-11-01

This study investigates the effect of uncertainty in physical model parameters on computed electrokinetic flow of proteins in a microchannel with a potassium phosphate buffer. The coupled momentum, species transport, and electrostatic field equations give a detailed representation of electroosmotic and pressure-driven flow, including sample dispersion mechanisms. The chemistry model accounts for pH-dependent protein labeling reactions as well as detailed buffer electrochemistry in a mixed finite-rate/equilibrium formulation. To quantify uncertainty, the governing equations are reformulated using a pseudo-spectral stochastic methodology, which uses polynomial chaos expansions to describe uncertain/stochastic model parameters, boundary conditions, and flow quantities. Integration of the resulting equations for the spectral mode strengths gives the evolution of all stochastic modes for all variables. Results show the spatiotemporal evolution of uncertainties in predicted quantities and highlight the dominant parameters contributing to these uncertainties during various flow phases. This work is supported by DARPA.

INFRARED OBSERVATIONAL MANIFESTATIONS OF YOUNG DUSTY SUPER STAR CLUSTERS

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

Martínez-González, Sergio; Tenorio-Tagle, Guillermo; Silich, Sergiy, E-mail: sergiomtz@inaoep.mx

The growing evidence pointing at core-collapse supernovae as large dust producers makes young massive stellar clusters ideal laboratories to study the evolution of dust immersed in a hot plasma. Here we address the stochastic injection of dust by supernovae, and follow its evolution due to thermal sputtering within the hot and dense plasma generated by young stellar clusters. Under these considerations, dust grains are heated by means of random collisions with gas particles which result in the appearance of  infrared spectral signatures. We present time-dependent infrared spectral energy distributions that are to be expected from young stellar clusters. Our results aremore » based on hydrodynamic calculations that account for the stochastic injection of dust by supernovae. These also consider gas and dust radiative cooling, stochastic dust temperature fluctuations, the exit of dust grains out of the cluster volume due to the cluster wind, and a time-dependent grain size distribution.« less

Stochastic damage evolution in textile laminates

NASA Technical Reports Server (NTRS)

Dzenis, Yuris A.; Bogdanovich, Alexander E.; Pastore, Christopher M.

1993-01-01

A probabilistic model utilizing random material characteristics to predict damage evolution in textile laminates is presented. Model is based on a division of each ply into two sublaminas consisting of cells. The probability of cell failure is calculated using stochastic function theory and maximal strain failure criterion. Three modes of failure, i.e. fiber breakage, matrix failure in transverse direction, as well as matrix or interface shear cracking, are taken into account. Computed failure probabilities are utilized in reducing cell stiffness based on the mesovolume concept. A numerical algorithm is developed predicting the damage evolution and deformation history of textile laminates. Effect of scatter of fiber orientation on cell properties is discussed. Weave influence on damage accumulation is illustrated with the help of an example of a Kevlar/epoxy laminate.

Evolution and mass extinctions as lognormal stochastic processes

NASA Astrophysics Data System (ADS)

Maccone, Claudio

2014-10-01

In a series of recent papers and in a book, this author put forward a mathematical model capable of embracing the search for extra-terrestrial intelligence (SETI), Darwinian Evolution and Human History into a single, unified statistical picture, concisely called Evo-SETI. The relevant mathematical tools are: (1) Geometric Brownian motion (GBM), the stochastic process representing evolution as the stochastic increase of the number of species living on Earth over the last 3.5 billion years. This GBM is well known in the mathematics of finances (Black-Sholes models). Its main features are that its probability density function (pdf) is a lognormal pdf, and its mean value is either an increasing or, more rarely, decreasing exponential function of the time. (2) The probability distributions known as b-lognormals, i.e. lognormals starting at a certain positive instant b>0 rather than at the origin. These b-lognormals were then forced by us to have their peak value located on the exponential mean-value curve of the GBM (Peak-Locus theorem). In the framework of Darwinian Evolution, the resulting mathematical construction was shown to be what evolutionary biologists call Cladistics. (3) The (Shannon) entropy of such b-lognormals is then seen to represent the `degree of progress' reached by each living organism or by each big set of living organisms, like historic human civilizations. Having understood this fact, human history may then be cast into the language of b-lognormals that are more and more organized in time (i.e. having smaller and smaller entropy, or smaller and smaller `chaos'), and have their peaks on the increasing GBM exponential. This exponential is thus the `trend of progress' in human history. (4) All these results also match with SETI in that the statistical Drake equation (generalization of the ordinary Drake equation to encompass statistics) leads just to the lognormal distribution as the probability distribution for the number of extra-terrestrial civilizations existing in the Galaxy (as a consequence of the central limit theorem of statistics). (5) But the most striking new result is that the well-known `Molecular Clock of Evolution', namely the `constant rate of Evolution at the molecular level' as shown by Kimura's Neutral Theory of Molecular Evolution, identifies with growth rate of the entropy of our Evo-SETI model, because they both grew linearly in time since the origin of life. (6) Furthermore, we apply our Evo-SETI model to lognormal stochastic processes other than GBMs. For instance, we provide two models for the mass extinctions that occurred in the past: (a) one based on GBMs and (b) the other based on a parabolic mean value capable of covering both the extinction and the subsequent recovery of life forms. (7) Finally, we show that the Markov & Korotayev (2007, 2008) model for Darwinian Evolution identifies with an Evo-SETI model for which the mean value of the underlying lognormal stochastic process is a cubic function of the time. In conclusion: we have provided a new mathematical model capable of embracing molecular evolution, SETI and entropy into a simple set of statistical equations based upon b-lognormals and lognormal stochastic processes with arbitrary mean, of which the GBMs are the particular case of exponential growth.

Gap Junctional Blockade Stochastically Induces Different Species-Specific Head Anatomies in Genetically Wild-Type Girardia dorotocephala Flatworms

PubMed Central

Emmons-Bell, Maya; Durant, Fallon; Hammelman, Jennifer; Bessonov, Nicholas; Volpert, Vitaly; Morokuma, Junji; Pinet, Kaylinnette; Adams, Dany S.; Pietak, Alexis; Lobo, Daniel; Levin, Michael

2015-01-01

The shape of an animal body plan is constructed from protein components encoded by the genome. However, bioelectric networks composed of many cell types have their own intrinsic dynamics, and can drive distinct morphological outcomes during embryogenesis and regeneration. Planarian flatworms are a popular system for exploring body plan patterning due to their regenerative capacity, but despite considerable molecular information regarding stem cell differentiation and basic axial patterning, very little is known about how distinct head shapes are produced. Here, we show that after decapitation in G. dorotocephala, a transient perturbation of physiological connectivity among cells (using the gap junction blocker octanol) can result in regenerated heads with quite different shapes, stochastically matching other known species of planaria (S. mediterranea, D. japonica, and P. felina). We use morphometric analysis to quantify the ability of physiological network perturbations to induce different species-specific head shapes from the same genome. Moreover, we present a computational agent-based model of cell and physical dynamics during regeneration that quantitatively reproduces the observed shape changes. Morphological alterations induced in a genomically wild-type G. dorotocephala during regeneration include not only the shape of the head but also the morphology of the brain, the characteristic distribution of adult stem cells (neoblasts), and the bioelectric gradients of resting potential within the anterior tissues. Interestingly, the shape change is not permanent; after regeneration is complete, intact animals remodel back to G. dorotocephala-appropriate head shape within several weeks in a secondary phase of remodeling following initial complete regeneration. We present a conceptual model to guide future work to delineate the molecular mechanisms by which bioelectric networks stochastically select among a small set of discrete head morphologies. Taken together, these data and analyses shed light on important physiological modifiers of morphological information in dictating species-specific shape, and reveal them to be a novel instructive input into head patterning in regenerating planaria. PMID:26610482

Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations.

PubMed

Lande, Russell; Engen, Steinar; Sæther, Bernt-Erik

2017-10-31

We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., weighted by body mass) is assumed to act as the single variable of population size, [Formula: see text], exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation. We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, [Formula: see text] and [Formula: see text], and the environmental variance in population growth rate, [Formula: see text] Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, [Formula: see text], measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes [Formula: see text] This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher [Formula: see text] versus higher [Formula: see text] However, selection also acts to decrease [Formula: see text], so the simple life-history trade-off between [Formula: see text]- and [Formula: see text]-selection may be obscured by additional trade-offs between them and [Formula: see text] Under the classical logistic model of population growth with linear density dependence ([Formula: see text]), life-history evolution in a fluctuating environment tends to maximize the average population size. Published under the PNAS license.

Nonlinear Image Denoising Methodologies

DTIC Science & Technology

2002-05-01

53 5.3 A Multiscale Approach to Scale-Space Analysis . . . . . . . . . . . . . . . . 53 5.4...etc. In this thesis, Our approach to denoising is first based on a controlled nonlinear stochastic random walk to achieve a scale space analysis ( as in... stochastic treatment or interpretation of the diffusion. In addition, unless a specific stopping time is known to be adequate, the resulting evolution

Electromagnetic sinc Schell-model beams and their statistical properties.

PubMed

Mei, Zhangrong; Mao, Yonghua

2014-09-22

A class of electromagnetic sources with sinc Schell-model correlations is introduced. The conditions on source parameters guaranteeing that the source generates a physical beam are derived. The evolution behaviors of statistical properties for the electromagnetic stochastic beams generated by this new source on propagating in free space and in atmosphere turbulence are investigated with the help of the weighted superposition method and by numerical simulations. It is demonstrated that the intensity distributions of such beams exhibit unique features on propagating in free space and produce a double-layer flat-top profile of being shape-invariant in the far field. This feature makes this new beam particularly suitable for some special laser processing applications. The influences of the atmosphere turbulence with a non-Kolmogorov power spectrum on statistical properties of the new beams are analyzed in detail.

Consistent nonlinear deterministic and stochastic evolution equations for deep to shallow water wave shoaling

NASA Astrophysics Data System (ADS)

Vrecica, Teodor; Toledo, Yaron

2015-04-01

One-dimensional deterministic and stochastic evolution equations are derived for the dispersive nonlinear waves while taking dissipation of energy into account. The deterministic nonlinear evolution equations are formulated using operational calculus by following the approach of Bredmose et al. (2005). Their formulation is extended to include the linear and nonlinear effects of wave dissipation due to friction and breaking. The resulting equation set describes the linear evolution of the velocity potential for each wave harmonic coupled by quadratic nonlinear terms. These terms describe the nonlinear interactions between triads of waves, which represent the leading-order nonlinear effects in the near-shore region. The equations are translated to the amplitudes of the surface elevation by using the approach of Agnon and Sheremet (1997) with the correction of Eldeberky and Madsen (1999). The only current possibility for calculating the surface gravity wave field over large domains is by using stochastic wave evolution models. Hence, the above deterministic model is formulated as a stochastic one using the method of Agnon and Sheremet (1997) with two types of stochastic closure relations (Benney and Saffman's, 1966, and Hollway's, 1980). These formulations cannot be applied to the common wave forecasting models without further manipulation, as they include a non-local wave shoaling coefficients (i.e., ones that require integration along the wave rays). Therefore, a localization method was applied (see Stiassnie and Drimer, 2006, and Toledo and Agnon, 2012). This process essentially extracts the local terms that constitute the mean nonlinear energy transfer while discarding the remaining oscillatory terms, which transfer energy back and forth. One of the main findings of this work is the understanding that the approximated non-local coefficients behave in two essentially different manners. In intermediate water depths these coefficients indeed consist of rapidly oscillating terms, but as the water depth becomes shallow they change to an exponential growth (or decay) behavior. Hence, the formerly used localization technique cannot be justified for the shallow water region. A new formulation is devised for the localization in shallow water, it approximates the nonlinear non-local shoaling coefficient in shallow water and matches it to the one fitting to the intermediate water region. This allows the model behavior to be consistent from deep water to intermediate depths and up to the shallow water regime. Various simulations of the model were performed for the cases of intermediate, and shallow water, overall the model was found to give good results in both shallow and intermediate water depths. The essential difference between the shallow and intermediate nonlinear shoaling physics is explained via the dominating class III Bragg resonances phenomenon. By inspecting the resonance conditions and the nature of the dispersion relation, it is shown that unlike in the intermediate water regime, in shallow water depths the formation of resonant interactions is possible without taking into account bottom components. References Agnon, Y. & Sheremet, A. 1997 Stochastic nonlinear shoaling of directional spectra. J. Fluid Mech. 345, 79-99. Benney, D. J. & Saffman, P. G. 1966 Nonlinear interactions of random waves. Proc. R. Soc. Lond. A 289, 301-321. Bredmose, H., Agnon, Y., Madsen, P.A. & Schaffer, H.A. 2005 Wave transformation models with exact second-order transfer. European J. of Mech. - B/Fluids 24 (6), 659-682. Eldeberky, Y. & Madsen, P. A. 1999 Deterministic and stochastic evolution equations for fully dispersive and weakly nonlinear waves. Coastal Engineering 38, 1-24. Kaihatu, J. M. & Kirby, J. T. 1995 Nonlinear transformation of waves in infinite water depth. Phys. Fluids 8, 175-188. Holloway, G. 1980 Oceanic internal waves are not weak waves. J. Phys. Oceanogr. 10, 906-914. Stiassnie, M. & Drimer, N. 2006 Prediction of long forcing waves for harbor agitation studies. J. of waterways, port, coastal and ocean engineering 132(3), 166-171. Toledo, Y. & Agnon, Y. 2012 Stochastic evolution equations with localized nonlinear shoaling coefficients. European J. of Mech. - B/Fluids 34, 13-18.

Electron thermal confinement in a partially stochastic magnetic structure

NASA Astrophysics Data System (ADS)

Morton, L. A.; Young, W. C.; Hegna, C. C.; Parke, E.; Reusch, J. A.; Den Hartog, D. J.

2018-04-01

Using a high-repetition-rate Thomson scattering diagnostic, we observe a peak in electron temperature Te coinciding with the location of a large magnetic island in the Madison Symmetric Torus. Magnetohydrodynamic modeling of this quasi-single helicity plasma indicates that smaller adjacent islands overlap with and destroy the large island flux surfaces. The estimated stochastic electron thermal conductivity ( ≈30 m 2/s ) is consistent with the conductivity inferred from the observed Te gradient and ohmic heating power. Island-shaped Te peaks can result from partially stochastic magnetic islands.

On orthogonality preserving quadratic stochastic operators

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

Mukhamedov, Farrukh; Taha, Muhammad Hafizuddin Mohd

2015-05-15

A quadratic stochastic operator (in short QSO) is usually used to present the time evolution of differing species in biology. Some quadratic stochastic operators have been studied by Lotka and Volterra. In the present paper, we first give a simple characterization of Volterra QSO in terms of absolutely continuity of discrete measures. Further, we introduce a notion of orthogonal preserving QSO, and describe such kind of operators defined on two dimensional simplex. It turns out that orthogonal preserving QSOs are permutations of Volterra QSO. The associativity of genetic algebras generated by orthogonal preserving QSO is studied too.

On an aggregation in birth-and-death stochastic dynamics

NASA Astrophysics Data System (ADS)

Finkelshtein, Dmitri; Kondratiev, Yuri; Kutoviy, Oleksandr; Zhizhina, Elena

2014-06-01

We consider birth-and-death stochastic dynamics of particle systems with attractive interaction. The heuristic generator of the dynamics has a constant birth rate and density-dependent decreasing death rate. The corresponding statistical dynamics is constructed. Using the Vlasov-type scaling we derive the limiting mesoscopic evolution and prove that this evolution propagates chaos. We study a nonlinear non-local kinetic equation for the first correlation function (density of population). The existence of uniformly bounded solutions as well as solutions growing inside of a bounded domain and expanding in the space are shown. These solutions describe two regimes in the mesoscopic system: regulation and aggregation.

Revisiting the diffusion approximation to estimate evolutionary rates of gene family diversification.

PubMed

Gjini, Erida; Haydon, Daniel T; David Barry, J; Cobbold, Christina A

2014-01-21

Genetic diversity in multigene families is shaped by multiple processes, including gene conversion and point mutation. Because multi-gene families are involved in crucial traits of organisms, quantifying the rates of their genetic diversification is important. With increasing availability of genomic data, there is a growing need for quantitative approaches that integrate the molecular evolution of gene families with their higher-scale function. In this study, we integrate a stochastic simulation framework with population genetics theory, namely the diffusion approximation, to investigate the dynamics of genetic diversification in a gene family. Duplicated genes can diverge and encode new functions as a result of point mutation, and become more similar through gene conversion. To model the evolution of pairwise identity in a multigene family, we first consider all conversion and mutation events in a discrete manner, keeping track of their details and times of occurrence; second we consider only the infinitesimal effect of these processes on pairwise identity accounting for random sampling of genes and positions. The purely stochastic approach is closer to biological reality and is based on many explicit parameters, such as conversion tract length and family size, but is more challenging analytically. The population genetics approach is an approximation accounting implicitly for point mutation and gene conversion, only in terms of per-site average probabilities. Comparison of these two approaches across a range of parameter combinations reveals that they are not entirely equivalent, but that for certain relevant regimes they do match. As an application of this modelling framework, we consider the distribution of nucleotide identity among VSG genes of African trypanosomes, representing the most prominent example of a multi-gene family mediating parasite antigenic variation and within-host immune evasion. © 2013 Published by Elsevier Ltd. All rights reserved.

End-of-life flows of multiple cycle consumer products.

PubMed

Tsiliyannis, C A

2011-11-01

Explicit expressions for the end-of-life flows (EOL) of single and multiple cycle products (MCPs) are presented, including deterministic and stochastic EOL exit. The expressions are given in terms of the physical parameters (maximum lifetime, T, annual cycling frequency, f, number of cycles, N, and early discard or usage loss). EOL flows are also obtained for hi-tech products, which are rapidly renewed and thus may not attain steady state (e.g., electronic products, passenger cars). A ten-step recursive procedure for obtaining the dynamic EOL flow evolution is proposed. Applications of the EOL expressions and the ten-step procedure are given for electric household appliances, industrial machinery, tyres, vehicles and buildings, both for deterministic and stochastic EOL exit, (normal, Weibull and uniform exit distributions). The effect of the physical parameters and the stochastic characteristics on the EOL flow is investigated in the examples: it is shown that the EOL flow profile is determined primarily by the early discard dynamics; it also depends strongly on longevity and cycling frequency: higher lifetime or early discard/loss imply lower dynamic and steady state EOL flows. The stochastic exit shapes the overall EOL dynamic profile: Under symmetric EOL exit distribution, as the variance of the distribution increases (uniform to normal to deterministic) the initial EOL flow rise becomes steeper but the steady state or maximum EOL flow level is lower. The steepest EOL flow profile, featuring the highest steady state or maximum level, as well, corresponds to skew, earlier shifted EOL exit (e.g., Weibull). Since the EOL flow of returned products consists the sink of the reuse/remanufacturing cycle (sink to recycle) the results may be used in closed loop product lifecycle management operations for scheduling and sizing reverse manufacturing and for planning recycle logistics. Decoupling and quantification of both the full age EOL and of the early discard flows is useful, the latter being the target of enacted legislation aiming at increasing reuse. Copyright © 2011 Elsevier Ltd. All rights reserved.

Computation of direct and inverse mutations with the SEGM web server (Stochastic Evolution of Genetic Motifs): an application to splice sites of human genome introns.

PubMed

Benard, Emmanuel; Michel, Christian J

2009-08-01

We present here the SEGM web server (Stochastic Evolution of Genetic Motifs) in order to study the evolution of genetic motifs both in the direct evolutionary sense (past-present) and in the inverse evolutionary sense (present-past). The genetic motifs studied can be nucleotides, dinucleotides and trinucleotides. As an example of an application of SEGM and to understand its functionalities, we give an analysis of inverse mutations of splice sites of human genome introns. SEGM is freely accessible at http://lsiit-bioinfo.u-strasbg.fr:8080/webMathematica/SEGM/SEGM.html directly or by the web site http://dpt-info.u-strasbg.fr/~michel/. To our knowledge, this SEGM web server is to date the only computational biology software in this evolutionary approach.

Magnetohydrodynamic stability of stochastically driven accretion flows.

PubMed

Nath, Sujit Kumar; Mukhopadhyay, Banibrata; Chattopadhyay, Amit K

2013-07-01

We investigate the evolution of magnetohydrodynamic (or hydromagnetic as coined by Chandrasekhar) perturbations in the presence of stochastic noise in rotating shear flows. The particular emphasis is the flows whose angular velocity decreases but specific angular momentum increases with increasing radial coordinate. Such flows, however, are Rayleigh stable but must be turbulent in order to explain astrophysical observed data and, hence, reveal a mismatch between the linear theory and observations and experiments. The mismatch seems to have been resolved, at least in certain regimes, in the presence of a weak magnetic field, revealing magnetorotational instability. The present work explores the effects of stochastic noise on such magnetohydrodynamic flows, in order to resolve the above mismatch generically for the hot flows. We essentially concentrate on a small section of such a flow which is nothing but a plane shear flow supplemented by the Coriolis effect, mimicking a small section of an astrophysical accretion disk around a compact object. It is found that such stochastically driven flows exhibit large temporal and spatial autocorrelations and cross-correlations of perturbation and, hence, large energy dissipations of perturbation, which generate instability. Interestingly, autocorrelations and cross-correlations appear independent of background angular velocity profiles, which are Rayleigh stable, indicating their universality. This work initiates our attempt to understand the evolution of three-dimensional hydromagnetic perturbations in rotating shear flows in the presence of stochastic noise.

A Simplified Treatment of Brownian Motion and Stochastic Differential Equations Arising in Financial Mathematics

ERIC Educational Resources Information Center

Parlar, Mahmut

2004-01-01

Brownian motion is an important stochastic process used in modelling the random evolution of stock prices. In their 1973 seminal paper--which led to the awarding of the 1997 Nobel prize in Economic Sciences--Fischer Black and Myron Scholes assumed that the random stock price process is described (i.e., generated) by Brownian motion. Despite its…

A non-linear dimension reduction methodology for generating data-driven stochastic input models

NASA Astrophysics Data System (ADS)

Ganapathysubramanian, Baskar; Zabaras, Nicholas

2008-06-01

Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low-dimensional input stochastic models to represent thermal diffusivity in two-phase microstructures. This model is used in analyzing the effect of topological variations of two-phase microstructures on the evolution of temperature in heat conduction processes.

A stochastic model for early placental development†

PubMed Central

Cotter, Simon L.; Klika, Václav; Kimpton, Laura; Collins, Sally; Heazell, Alexander E. P.

2014-01-01

In the human, placental structure is closely related to placental function and consequent pregnancy outcome. Studies have noted abnormal placental shape in small-for-gestational-age infants which extends to increased lifetime risk of cardiovascular disease. The origins and determinants of placental shape are incompletely understood and are difficult to study in vivo. In this paper, we model the early development of the human placenta, based on the hypothesis that this is driven by a chemoattractant effect emanating from proximal spiral arteries in the decidua. We derive and explore a two-dimensional stochastic model, and investigate the effects of loss of spiral arteries in regions near to the cord insertion on the shape of the placenta. This model demonstrates that disruption of spiral arteries can exert profound effects on placental shape, particularly if this is close to the cord insertion. Thus, placental shape reflects the underlying maternal vascular bed. Abnormal placental shape may reflect an abnormal uterine environment, predisposing to pregnancy complications. Through statistical analysis of model placentas, we are able to characterize the probability that a given placenta grew in a disrupted environment, and even able to distinguish between different disruptions. PMID:24850904

What Shapes the Phylogenetic Structure of Anuran Communities in a Seasonal Environment? The Influence of Determinism at Regional Scale to Stochasticity or Antagonistic Forces at Local Scale

PubMed Central

Ferreira, Vanda Lúcia; Strüssmann, Christine; Tomas, Walfrido Moraes

2015-01-01

Ecological communities are structured by both deterministic and stochastic processes. We investigated phylogenetic patterns at regional and local scales to understand the influences of seasonal processes in shaping the structure of anuran communities in the southern Pantanal wetland, Brazil. We assessed the phylogenetic structure at different scales, using the Net Relatedness Index (NRI), the Nearest Taxon Index (NTI), and phylobetadiversity indexes, as well as a permutation test, to evaluate the effect of seasonality. The anuran community was represented by a non-random set of species with a high degree of phylogenetic relatedness at the regional scale. However, at the local scale the phylogenetic structure of the community was weakly related with the seasonality of the system, indicating that oriented stochastic processes (e.g. colonization, extinction and ecological drift) and/or antagonist forces drive the structure of such communities in the southern Pantanal. PMID:26102202

What Shapes the Phylogenetic Structure of Anuran Communities in a Seasonal Environment? The Influence of Determinism at Regional Scale to Stochasticity or Antagonistic Forces at Local Scale.

PubMed

Martins, Clarissa de Araújo; Roque, Fabio de Oliveira; Santos, Bráulio A; Ferreira, Vanda Lúcia; Strüssmann, Christine; Tomas, Walfrido Moraes

2015-01-01

Ecological communities are structured by both deterministic and stochastic processes. We investigated phylogenetic patterns at regional and local scales to understand the influences of seasonal processes in shaping the structure of anuran communities in the southern Pantanal wetland, Brazil. We assessed the phylogenetic structure at different scales, using the Net Relatedness Index (NRI), the Nearest Taxon Index (NTI), and phylobetadiversity indexes, as well as a permutation test, to evaluate the effect of seasonality. The anuran community was represented by a non-random set of species with a high degree of phylogenetic relatedness at the regional scale. However, at the local scale the phylogenetic structure of the community was weakly related with the seasonality of the system, indicating that oriented stochastic processes (e.g. colonization, extinction and ecological drift) and/or antagonist forces drive the structure of such communities in the southern Pantanal.

Two Stochastic Phases of Tick-wise Price Fluctuation and the Price Prediction Generator

NASA Astrophysics Data System (ADS)

Tanaka-Yamawaki, Mieko; Tokuoka, Seiji

2007-07-01

We report in this paper the existence of two different stochastic phases in the tick-wise price fluctuations. Based on this observation, we improve our old method of developing the evolutional strategy to predict the direction of the tick-wise price movements. We obtain a stable predictive power even in the region where the old method had a difficulty.

Partition-free approach to open quantum systems in harmonic environments: An exact stochastic Liouville equation

NASA Astrophysics Data System (ADS)

McCaul, G. M. G.; Lorenz, C. D.; Kantorovich, L.

2017-03-01

We present a partition-free approach to the evolution of density matrices for open quantum systems coupled to a harmonic environment. The influence functional formalism combined with a two-time Hubbard-Stratonovich transformation allows us to derive a set of exact differential equations for the reduced density matrix of an open system, termed the extended stochastic Liouville-von Neumann equation. Our approach generalizes previous work based on Caldeira-Leggett models and a partitioned initial density matrix. This provides a simple, yet exact, closed-form description for the evolution of open systems from equilibriated initial conditions. The applicability of this model and the potential for numerical implementations are also discussed.

Stochastic chaos induced by diffusion processes with identical spectral density but different probability density functions.

PubMed

Lei, Youming; Zheng, Fan

2016-12-01

Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.

Convolutionless Nakajima-Zwanzig equations for stochastic analysis in nonlinear dynamical systems.

PubMed

Venturi, D; Karniadakis, G E

2014-06-08

Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima-Zwanzig-Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection-reaction problems.

Analytical Assessment for Transient Stability Under Stochastic Continuous Disturbances

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

Ju, Ping; Li, Hongyu; Gan, Chun

Here, with the growing integration of renewable power generation, plug-in electric vehicles, and other sources of uncertainty, increasing stochastic continuous disturbances are brought to power systems. The impact of stochastic continuous disturbances on power system transient stability attracts significant attention. To address this problem, this paper proposes an analytical assessment method for transient stability of multi-machine power systems under stochastic continuous disturbances. In the proposed method, a probability measure of transient stability is presented and analytically solved by stochastic averaging. Compared with the conventional method (Monte Carlo simulation), the proposed method is many orders of magnitude faster, which makes itmore » very attractive in practice when many plans for transient stability must be compared or when transient stability must be analyzed quickly. Also, it is found that the evolution of system energy over time is almost a simple diffusion process by the proposed method, which explains the impact mechanism of stochastic continuous disturbances on transient stability in theory.« less

Convolutionless Nakajima–Zwanzig equations for stochastic analysis in nonlinear dynamical systems

PubMed Central

Venturi, D.; Karniadakis, G. E.

2014-01-01

Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima–Zwanzig–Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection–reaction problems. PMID:24910519

Phenomenology of stochastic exponential growth

NASA Astrophysics Data System (ADS)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

Stochastic modeling of Lagrangian accelerations

NASA Astrophysics Data System (ADS)

Reynolds, Andy

2002-11-01

It is shown how Sawford's second-order Lagrangian stochastic model (Phys. Fluids A 3, 1577-1586, 1991) for fluid-particle accelerations can be combined with a model for the evolution of the dissipation rate (Pope and Chen, Phys. Fluids A 2, 1437-1449, 1990) to produce a Lagrangian stochastic model that is consistent with both the measured distribution of Lagrangian accelerations (La Porta et al., Nature 409, 1017-1019, 2001) and Kolmogorov's similarity theory. The later condition is found not to be satisfied when a constant dissipation rate is employed and consistency with prescribed acceleration statistics is enforced through fulfilment of a well-mixed condition.

Provably unbounded memory advantage in stochastic simulation using quantum mechanics

NASA Astrophysics Data System (ADS)

Garner, Andrew J. P.; Liu, Qing; Thompson, Jayne; Vedral, Vlatko; Gu, mile

2017-10-01

Simulating the stochastic evolution of real quantities on a digital computer requires a trade-off between the precision to which these quantities are approximated, and the memory required to store them. The statistical accuracy of the simulation is thus generally limited by the internal memory available to the simulator. Here, using tools from computational mechanics, we show that quantum processors with a fixed finite memory can simulate stochastic processes of real variables to arbitrarily high precision. This demonstrates a provable, unbounded memory advantage that a quantum simulator can exhibit over its best possible classical counterpart.

Evolution in health and medicine Sackler colloquium: Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease.

PubMed

Feinberg, Andrew P; Irizarry, Rafael A

2010-01-26

Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease. Epigenetics is the study of nonsequence-based changes, such as DNA methylation, heritable during cell division. Previous attempts to incorporate epigenetics into evolutionary thinking have focused on Lamarckian inheritance, that is, environmentally directed epigenetic changes. Here, we propose a new non-Lamarckian theory for a role of epigenetics in evolution. We suggest that genetic variants that do not change the mean phenotype could change the variability of phenotype; and this could be mediated epigenetically. This inherited stochastic variation model would provide a mechanism to explain an epigenetic role of developmental biology in selectable phenotypic variation, as well as the largely unexplained heritable genetic variation underlying common complex disease. We provide two experimental results as proof of principle. The first result is direct evidence for stochastic epigenetic variation, identifying highly variably DNA-methylated regions in mouse and human liver and mouse brain, associated with development and morphogenesis. The second is a heritable genetic mechanism for variable methylation, namely the loss or gain of CpG dinucleotides over evolutionary time. Finally, we model genetically inherited stochastic variation in evolution, showing that it provides a powerful mechanism for evolutionary adaptation in changing environments that can be mediated epigenetically. These data suggest that genetically inherited propensity to phenotypic variability, even with no change in the mean phenotype, substantially increases fitness while increasing the disease susceptibility of a population with a changing environment.

Recent topographic evolution and erosion of the deglaciated Washington Cascades inferred from a stochastic landscape evolution model

NASA Astrophysics Data System (ADS)

Moon, Seulgi; Shelef, Eitan; Hilley, George E.

2015-05-01

In this study, we model postglacial surface processes and examine the evolution of the topography and denudation rates within the deglaciated Washington Cascades to understand the controls on and time scales of landscape response to changes in the surface process regime after deglaciation. The postglacial adjustment of this landscape is modeled using a geomorphic-transport-law-based numerical model that includes processes of river incision, hillslope diffusion, and stochastic landslides. The surface lowering due to landslides is parameterized using a physically based slope stability model coupled to a stochastic model of the generation of landslides. The model parameters of river incision and stochastic landslides are calibrated based on the rates and distribution of thousand-year-time scale denudation rates measured from cosmogenic 10Be isotopes. The probability distributions of those model parameters calculated based on a Bayesian inversion scheme show comparable ranges from previous studies in similar rock types and climatic conditions. The magnitude of landslide denudation rates is determined by failure density (similar to landslide frequency), whereas precipitation and slopes affect the spatial variation in landslide denudation rates. Simulation results show that postglacial denudation rates decay over time and take longer than 100 kyr to reach time-invariant rates. Over time, the landslides in the model consume the steep slopes characteristic of deglaciated landscapes. This response time scale is on the order of or longer than glacial/interglacial cycles, suggesting that frequent climatic perturbations during the Quaternary may produce a significant and prolonged impact on denudation and topography.

Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Tauber, Uwe C.

2012-02-01

We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.

Stochastic modeling of mode interactions via linear parabolized stability equations

NASA Astrophysics Data System (ADS)

Ran, Wei; Zare, Armin; Hack, M. J. Philipp; Jovanovic, Mihailo

2017-11-01

Low-complexity approximations of the Navier-Stokes equations have been widely used in the analysis of wall-bounded shear flows. In particular, the parabolized stability equations (PSE) and Floquet theory have been employed to capture the evolution of primary and secondary instabilities in spatially-evolving flows. We augment linear PSE with Floquet analysis to formally treat modal interactions and the evolution of secondary instabilities in the transitional boundary layer via a linear progression. To this end, we leverage Floquet theory by incorporating the primary instability into the base flow and accounting for different harmonics in the flow state. A stochastic forcing is introduced into the resulting linear dynamics to model the effect of nonlinear interactions on the evolution of modes. We examine the H-type transition scenario to demonstrate how our approach can be used to model nonlinear effects and capture the growth of the fundamental and subharmonic modes observed in direct numerical simulations and experiments.

Stochastic Feshbach Projection for the Dynamics of Open Quantum Systems

NASA Astrophysics Data System (ADS)

Link, Valentin; Strunz, Walter T.

2017-11-01

We present a stochastic projection formalism for the description of quantum dynamics in bosonic or spin environments. The Schrödinger equation in the coherent state representation with respect to the environmental degrees of freedom can be reformulated by employing the Feshbach partitioning technique for open quantum systems based on the introduction of suitable non-Hermitian projection operators. In this picture the reduced state of the system can be obtained as a stochastic average over pure state trajectories, for any temperature of the bath. The corresponding non-Markovian stochastic Schrödinger equations include a memory integral over the past states. In the case of harmonic environments and linear coupling the approach gives a new form of the established non-Markovian quantum state diffusion stochastic Schrödinger equation without functional derivatives. Utilizing spin coherent states, the evolution equation for spin environments resembles the bosonic case with, however, a non-Gaussian average for the reduced density operator.

Evolutionary stability concepts in a stochastic environment

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2017-09-01

Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

Hill functions for stochastic gene regulatory networks from master equations with split nodes and time-scale separation

NASA Astrophysics Data System (ADS)

Lipan, Ovidiu; Ferwerda, Cameron

2018-02-01

The deterministic Hill function depends only on the average values of molecule numbers. To account for the fluctuations in the molecule numbers, the argument of the Hill function needs to contain the means, the standard deviations, and the correlations. Here we present a method that allows for stochastic Hill functions to be constructed from the dynamical evolution of stochastic biocircuits with specific topologies. These stochastic Hill functions are presented in a closed analytical form so that they can be easily incorporated in models for large genetic regulatory networks. Using a repressive biocircuit as an example, we show by Monte Carlo simulations that the traditional deterministic Hill function inaccurately predicts time of repression by an order of two magnitudes. However, the stochastic Hill function was able to capture the fluctuations and thus accurately predicted the time of repression.

Ultrafast generation of skyrmionic defects with vortex beams: Printing laser profiles on magnets

NASA Astrophysics Data System (ADS)

Fujita, Hiroyuki; Sato, Masahiro

2017-02-01

Controlling electric and magnetic properties of matter by laser beams is actively explored in the broad region of condensed matter physics, including spintronics and magneto-optics. Here we theoretically propose an application of optical and electron vortex beams carrying intrinsic orbital angular momentum to chiral ferro- and antiferromagnets. We analyze the time evolution of spins in chiral magnets under irradiation of vortex beams by using the stochastic Landau-Lifshitz-Gilbert equation. We show that beam-driven nonuniform temperature leads to a class of ring-shaped magnetic defects, what we call skyrmion multiplex, as well as conventional skyrmions. We discuss the proper beam parameters and the optimal way of applying the beams for the creation of these topological defects. Our findings provide an ultrafast scheme of generating topological magnetic defects in a way applicable to both metallic and insulating chiral (anti-) ferromagnets.

Computation material science of structural-phase transformation in casting aluminium alloys

NASA Astrophysics Data System (ADS)

Golod, V. M.; Dobosh, L. Yu

2017-04-01

Successive stages of computer simulation the formation of the casting microstructure under non-equilibrium conditions of crystallization of multicomponent aluminum alloys are presented. On the basis of computer thermodynamics and heat transfer during solidification of macroscale shaped castings are specified the boundary conditions of local heat exchange at mesoscale modeling of non-equilibrium formation the solid phase and of the component redistribution between phases during coalescence of secondary dendrite branches. Computer analysis of structural - phase transitions based on the principle of additive physico-chemical effect of the alloy components in the process of diffusional - capillary morphological evolution of the dendrite structure and the o of local dendrite heterogeneity which stochastic nature and extent are revealed under metallographic study and modeling by the Monte Carlo method. The integrated computational materials science tools at researches of alloys are focused and implemented on analysis the multiple-factor system of casting processes and prediction of casting microstructure.

BRITE-Constellation high-precision time-dependent photometry of the early O-type supergiant ζ Puppis unveils the photospheric drivers of its small- and large-scale wind structures

NASA Astrophysics Data System (ADS)

Ramiaramanantsoa, Tahina; Moffat, Anthony F. J.; Harmon, Robert; Ignace, Richard; St-Louis, Nicole; Vanbeveren, Dany; Shenar, Tomer; Pablo, Herbert; Richardson, Noel D.; Howarth, Ian D.; Stevens, Ian R.; Piaulet, Caroline; St-Jean, Lucas; Eversberg, Thomas; Pigulski, Andrzej; Popowicz, Adam; Kuschnig, Rainer; Zocłońska, Elżbieta; Buysschaert, Bram; Handler, Gerald; Weiss, Werner W.; Wade, Gregg A.; Rucinski, Slavek M.; Zwintz, Konstanze; Luckas, Paul; Heathcote, Bernard; Cacella, Paulo; Powles, Jonathan; Locke, Malcolm; Bohlsen, Terry; Chené, André-Nicolas; Miszalski, Brent; Waldron, Wayne L.; Kotze, Marissa M.; Kotze, Enrico J.; Böhm, Torsten

2018-02-01

From 5.5 months of dual-band optical photometric monitoring at the 1 mmag level, BRITE-Constellation has revealed two simultaneous types of variability in the O4I(n)fp star ζ Puppis: one single periodic non-sinusoidal component superimposed on a stochastic component. The monoperiodic component is the 1.78-d signal previously detected by Coriolis/Solar Mass Ejection Imager, but this time along with a prominent first harmonic. The shape of this signal changes over time, a behaviour that is incompatible with stellar oscillations but consistent with rotational modulation arising from evolving bright surface inhomogeneities. By means of a constrained non-linear light-curve inversion algorithm, we mapped the locations of the bright surface spots and traced their evolution. Our simultaneous ground-based multisite spectroscopic monitoring of the star unveiled cyclical modulation of its He II λ4686 wind emission line with the 1.78-d rotation period, showing signatures of corotating interaction regions that turn out to be driven by the bright photospheric spots observed by BRITE. Traces of wind clumps are also observed in the He II λ4686 line and are correlated with the amplitudes of the stochastic component of the light variations probed by BRITE at the photosphere, suggesting that the BRITE observations additionally unveiled the photospheric drivers of wind clumps in ζ Pup and that the clumping phenomenon starts at the very base of the wind. The origins of both the bright surface inhomogeneities and the stochastic light variations remain unknown, but a subsurface convective zone might play an important role in the generation of these two types of photospheric variability.

Stochastic modelling of microstructure formation in solidification processes

NASA Astrophysics Data System (ADS)

Nastac, Laurentiu; Stefanescu, Doru M.

1997-07-01

To relax many of the assumptions used in continuum approaches, a general stochastic model has been developed. The stochastic model can be used not only for an accurate description of the fraction of solid evolution, and therefore accurate cooling curves, but also for simulation of microstructure formation in castings. The advantage of using the stochastic approach is to give a time- and space-dependent description of solidification processes. Time- and space-dependent processes can also be described by partial differential equations. Unlike a differential formulation which, in most cases, has to be transformed into a difference equation and solved numerically, the stochastic approach is essentially a direct numerical algorithm. The stochastic model is comprehensive, since the competition between various phases is considered. Furthermore, grain impingement is directly included through the structure of the model. In the present research, all grain morphologies are simulated with this procedure. The relevance of the stochastic approach is that the simulated microstructures can be directly compared with microstructures obtained from experiments. The computer becomes a `dynamic metallographic microscope'. A comparison between deterministic and stochastic approaches has been performed. An important objective of this research was to answer the following general questions: (1) `Would fully deterministic approaches continue to be useful in solidification modelling?' and (2) `Would stochastic algorithms be capable of entirely replacing purely deterministic models?'

Dispersal similarly shapes both population genetics and community patterns in the marine realm

NASA Astrophysics Data System (ADS)

Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Fernández de Puelles, María L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Veríssimo, Helena; Zervoudaki, Soultana; Borja, Angel

2016-06-01

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

Generalized moment analysis of magnetic field correlations for accumulations of spherical and cylindrical magnetic pertubers

NASA Astrophysics Data System (ADS)

Kurz, Felix; Kampf, Thomas; Buschle, Lukas; Schlemmer, Heinz-Peter; Bendszus, Martin; Heiland, Sabine; Ziener, Christian

2016-12-01

In biological tissue, an accumulation of similarly shaped objects with a susceptibility difference to the surrounding tissue generates a local distortion of the external magnetic field in magnetic resonance imaging. It induces stochastic field fluctuations that characteristically influence proton spin diffusion in the vicinity of these magnetic perturbers. The magnetic field correlation that is associated with such local magnetic field inhomogeneities can be expressed in the form of a dynamic frequency autocorrelation function that is related to the time evolution of the measured magnetization. Here, an eigenfunction expansion for two simple magnetic perturber shapes, that of spheres and cylinders, is considered for restricted spin diffusion in a simple model geometry. Then, the concept of generalized moment analysis, an approximation technique that is applied in the study of (non-)reactive processes that involve Brownian motion, allows to provide analytical expressions for the correlation function for different exponential decay forms. Results for the biexponential decay for both spherical and cylindrical magnetized objects are derived and compared with the frequently used (less accurate) monoexponential decay forms. They are in asymptotic agreement with the numerically exact value of the correlation function for long and short times.

Nucleation and growth kinetics for intercalated islands during deposition on layered materials with isolated pointlike surface defects

DOE PAGES

Han, Yong; Lii-Rosales, A.; Zhou, Y.; ...

2017-10-13

Theory and stochastic lattice-gas modeling is developed for the formation of intercalated metal islands in the gallery between the top layer and the underlying layer at the surface of layered materials. Our model for this process involves deposition of atoms, some fraction of which then enter the gallery through well-separated pointlike defects in the top layer. Subsequently, these atoms diffuse within the subsurface gallery leading to nucleation and growth of intercalated islands nearby the defect point source. For the case of a single point defect, continuum diffusion equation analysis provides insight into the nucleation kinetics. However, complementary tailored lattice-gas modelingmore » produces a more comprehensive and quantitative characterization. We analyze the large spread in nucleation times and positions relative to the defect for the first nucleated island. We also consider the formation of subsequent islands and the evolution of island growth shapes. The shapes reflect in part our natural adoption of a hexagonal close-packed island structure. As a result, motivation and support for the model is provided by scanning tunneling microscopy observations of the formation of intercalated metal islands in highly-ordered pyrolytic graphite at higher temperatures.« less

On convergence of differential evolution over a class of continuous functions with unique global optimum.

PubMed

Ghosh, Sayan; Das, Swagatam; Vasilakos, Athanasios V; Suresh, Kaushik

2012-02-01

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms of current interest. Since its inception in the mid 1990s, DE has been finding many successful applications in real-world optimization problems from diverse domains of science and engineering. This paper takes a first significant step toward the convergence analysis of a canonical DE (DE/rand/1/bin) algorithm. It first deduces a time-recursive relationship for the probability density function (PDF) of the trial solutions, taking into consideration the DE-type mutation, crossover, and selection mechanisms. Then, by applying the concepts of Lyapunov stability theorems, it shows that as time approaches infinity, the PDF of the trial solutions concentrates narrowly around the global optimum of the objective function, assuming the shape of a Dirac delta distribution. Asymptotic convergence behavior of the population PDF is established by constructing a Lyapunov functional based on the PDF and showing that it monotonically decreases with time. The analysis is applicable to a class of continuous and real-valued objective functions that possesses a unique global optimum (but may have multiple local optima). Theoretical results have been substantiated with relevant computer simulations.

Simulating galactic dust grain evolution on a moving mesh

NASA Astrophysics Data System (ADS)

McKinnon, Ryan; Vogelsberger, Mark; Torrey, Paul; Marinacci, Federico; Kannan, Rahul

2018-05-01

Interstellar dust is an important component of the galactic ecosystem, playing a key role in multiple galaxy formation processes. We present a novel numerical framework for the dynamics and size evolution of dust grains implemented in the moving-mesh hydrodynamics code AREPO suited for cosmological galaxy formation simulations. We employ a particle-based method for dust subject to dynamical forces including drag and gravity. The drag force is implemented using a second-order semi-implicit integrator and validated using several dust-hydrodynamical test problems. Each dust particle has a grain size distribution, describing the local abundance of grains of different sizes. The grain size distribution is discretised with a second-order piecewise linear method and evolves in time according to various dust physical processes, including accretion, sputtering, shattering, and coagulation. We present a novel scheme for stochastically forming dust during stellar evolution and new methods for sub-cycling of dust physics time-steps. Using this model, we simulate an isolated disc galaxy to study the impact of dust physical processes that shape the interstellar grain size distribution. We demonstrate, for example, how dust shattering shifts the grain size distribution to smaller sizes resulting in a significant rise of radiation extinction from optical to near-ultraviolet wavelengths. Our framework for simulating dust and gas mixtures can readily be extended to account for other dynamical processes relevant in galaxy formation, like magnetohydrodynamics, radiation pressure, and thermo-chemical processes.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Cosmological stochastic Higgs field stabilization

NASA Astrophysics Data System (ADS)

Gong, Jinn-Ouk; Kitajima, Naoya

2017-09-01

We show that the stochastic evolution of an interacting system of the Higgs field and a spectator scalar field naturally gives rise to an enhanced probability of settling down at the electroweak vacuum at the end of inflation. Subsequent destabilization due to parametric resonance between the Higgs field and the spectator field can be avoided in a wide parameter range. We further argue that the spectator field can play the role of dark matter.

Biophysics, environmental stochasticity, and the evolution of thermal safety margins in intertidal limpets.

PubMed

Denny, M W; Dowd, W W

2012-03-15

As the air temperature of the Earth rises, ecological relationships within a community might shift, in part due to differences in the thermal physiology of species. Prediction of these shifts - an urgent task for ecologists - will be complicated if thermal tolerance itself can rapidly evolve. Here, we employ a mechanistic approach to predict the potential for rapid evolution of thermal tolerance in the intertidal limpet Lottia gigantea. Using biophysical principles to predict body temperature as a function of the state of the environment, and an environmental bootstrap procedure to predict how the environment fluctuates through time, we create hypothetical time-series of limpet body temperatures, which are in turn used as a test platform for a mechanistic evolutionary model of thermal tolerance. Our simulations suggest that environmentally driven stochastic variation of L. gigantea body temperature results in rapid evolution of a substantial 'safety margin': the average lethal limit is 5-7°C above the average annual maximum temperature. This predicted safety margin approximately matches that found in nature, and once established is sufficient, in our simulations, to allow some limpet populations to survive a drastic, century-long increase in air temperature. By contrast, in the absence of environmental stochasticity, the safety margin is dramatically reduced. We suggest that the risk of exceeding the safety margin, rather than the absolute value of the safety margin, plays an underappreciated role in the evolution of thermal tolerance. Our predictions are based on a simple, hypothetical, allelic model that connects genetics to thermal physiology. To move beyond this simple model - and thereby potentially to predict differential evolution among populations and among species - will require significant advances in our ability to translate the details of thermal histories into physiological and population-genetic consequences.

Numerical simulations of piecewise deterministic Markov processes with an application to the stochastic Hodgkin-Huxley model.

PubMed

Ding, Shaojie; Qian, Min; Qian, Hong; Zhang, Xuejuan

2016-12-28

The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Markov processes (PDMPs), in which the electrical potential across a cell membrane, V(t), is coupled with a mesoscopic Markov jump process representing the stochastic opening and closing of ion channels embedded in the membrane. The rates of the channel kinetics, in turn, are voltage-dependent. Due to this interdependence, an accurate and efficient sampling of the time evolution of the hybrid stochastic systems has been challenging. The current exact simulation methods require solving a voltage-dependent hitting time problem for multiple path-dependent intensity functions with random thresholds. This paper proposes a simulation algorithm that approximates an alternative representation of the exact solution by fitting the log-survival function of the inter-jump dwell time, H(t), with a piecewise linear one. The latter uses interpolation points that are chosen according to the time evolution of the H(t), as the numerical solution to the coupled ordinary differential equations of V(t) and H(t). This computational method can be applied to all PDMPs. Pathwise convergence of the approximated sample trajectories to the exact solution is proven, and error estimates are provided. Comparison with a previous algorithm that is based on piecewise constant approximation is also presented.

Stochastic hybrid systems for studying biochemical processes.

PubMed

Singh, Abhyudai; Hespanha, João P

2010-11-13

Many protein and mRNA species occur at low molecular counts within cells, and hence are subject to large stochastic fluctuations in copy numbers over time. Development of computationally tractable frameworks for modelling stochastic fluctuations in population counts is essential to understand how noise at the cellular level affects biological function and phenotype. We show that stochastic hybrid systems (SHSs) provide a convenient framework for modelling the time evolution of population counts of different chemical species involved in a set of biochemical reactions. We illustrate recently developed techniques that allow fast computations of the statistical moments of the population count, without having to run computationally expensive Monte Carlo simulations of the biochemical reactions. Finally, we review different examples from the literature that illustrate the benefits of using SHSs for modelling biochemical processes.

A Generative Angular Model of Protein Structure Evolution

PubMed Central

Golden, Michael; García-Portugués, Eduardo; Sørensen, Michael; Mardia, Kanti V.; Hamelryck, Thomas; Hein, Jotun

2017-01-01

Abstract Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modeled using a novel angular diffusion process on the two-dimensional torus. Coupling sequence and structure evolution in our model allows for modeling both “smooth” conformational changes and “catastrophic” conformational jumps, conditioned on the amino acid changes. The model has interpretable parameters and is comparatively more realistic than previous stochastic models, providing new insights into the relationship between sequence and structure evolution. For example, using the trained model we were able to identify an apparent sequence–structure evolutionary motif present in a large number of homologous protein pairs. The generative nature of our model enables us to evaluate its validity and its ability to simulate aspects of protein evolution conditioned on an amino acid sequence, a related amino acid sequence, a related structure or any combination thereof. PMID:28453724

A General Model for Estimating Macroevolutionary Landscapes.

PubMed

Boucher, Florian C; Démery, Vincent; Conti, Elena; Harmon, Luke J; Uyeda, Josef

2018-03-01

The evolution of quantitative characters over long timescales is often studied using stochastic diffusion models. The current toolbox available to students of macroevolution is however limited to two main models: Brownian motion and the Ornstein-Uhlenbeck process, plus some of their extensions. Here, we present a very general model for inferring the dynamics of quantitative characters evolving under both random diffusion and deterministic forces of any possible shape and strength, which can accommodate interesting evolutionary scenarios like directional trends, disruptive selection, or macroevolutionary landscapes with multiple peaks. This model is based on a general partial differential equation widely used in statistical mechanics: the Fokker-Planck equation, also known in population genetics as the Kolmogorov forward equation. We thus call the model FPK, for Fokker-Planck-Kolmogorov. We first explain how this model can be used to describe macroevolutionary landscapes over which quantitative traits evolve and, more importantly, we detail how it can be fitted to empirical data. Using simulations, we show that the model has good behavior both in terms of discrimination from alternative models and in terms of parameter inference. We provide R code to fit the model to empirical data using either maximum-likelihood or Bayesian estimation, and illustrate the use of this code with two empirical examples of body mass evolution in mammals. FPK should greatly expand the set of macroevolutionary scenarios that can be studied since it opens the way to estimating macroevolutionary landscapes of any conceivable shape. [Adaptation; bounds; diffusion; FPK model; macroevolution; maximum-likelihood estimation; MCMC methods; phylogenetic comparative data; selection.].

Hierarchical analysis of species distributions and abundance across environmental gradients

Treesearch

Jeffery Diez; Ronald H. Pulliam

2007-01-01

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

Boson Hamiltonians and stochasticity for the vorticity equation

NASA Technical Reports Server (NTRS)

Shen, Hubert H.

1990-01-01

The evolution of the vorticity in time for two-dimensional inviscid flow and in Lagrangian time for three-dimensional viscous flow is written in Hamiltonian form by introducing Bose operators. The addition of the viscous and convective terms, respectively, leads to an interpretation of the Hamiltonian contribution to the evolution as Langevin noise.

Far from Equilibrium Percolation, Stochastic and Shape Resonances in the Physics of Life

PubMed Central

Poccia, Nicola; Ansuini, Alessio; Bianconi, Antonio

2011-01-01

Key physical concepts, relevant for the cross-fertilization between condensed matter physics and the physics of life seen as a collective phenomenon in a system out-of-equilibrium, are discussed. The onset of life can be driven by: (a) the critical fluctuations at the protonic percolation threshold in membrane transport; (b) the stochastic resonance in biological systems, a mechanism that can exploit external and self-generated noise in order to gain efficiency in signal processing; and (c) the shape resonance (or Fano resonance or Feshbach resonance) in the association and dissociation processes of bio-molecules (a quantum mechanism that could play a key role to establish a macroscopic quantum coherence in the cell). PMID:22072921

Mean Field Games for Stochastic Growth with Relative Utility

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

Huang, Minyi, E-mail: mhuang@math.carleton.ca; Nguyen, Son Luu, E-mail: sonluu.nguyen@upr.edu

This paper considers continuous time stochastic growth-consumption optimization in a mean field game setting. The individual capital stock evolution is determined by a Cobb–Douglas production function, consumption and stochastic depreciation. The individual utility functional combines an own utility and a relative utility with respect to the population. The use of the relative utility reflects human psychology, leading to a natural pattern of mean field interaction. The fixed point equation of the mean field game is derived with the aid of some ordinary differential equations. Due to the relative utility interaction, our performance analysis depends on some ratio based approximation errormore » estimate.« less

Evolution of probability densities in stochastic coupled map lattices

NASA Astrophysics Data System (ADS)

Losson, Jérôme; Mackey, Michael C.

1995-08-01

This paper describes the statistical properties of coupled map lattices subjected to the influence of stochastic perturbations. The stochastic analog of the Perron-Frobenius operator is derived for various types of noise. When the local dynamics satisfy rather mild conditions, this equation is shown to possess either stable, steady state solutions (i.e., a stable invariant density) or density limit cycles. Convergence of the phase space densities to these limit cycle solutions explains the nonstationary behavior of statistical quantifiers at equilibrium. Numerical experiments performed on various lattices of tent, logistic, and shift maps with diffusivelike interelement couplings are examined in light of these theoretical results.

Selective sweeps of mitochondrial DNA can drive the evolution of uniparental inheritance.

PubMed

Christie, Joshua R; Beekman, Madeleine

2017-08-01

Although the uniparental (or maternal) inheritance of mitochondrial DNA (mtDNA) is widespread, the reasons for its evolution remain unclear. Two main hypotheses have been proposed: selection against individuals containing different mtDNAs (heteroplasmy) and selection against "selfish" mtDNA mutations. Recently, uniparental inheritance was shown to promote adaptive evolution in mtDNA, potentially providing a third hypothesis for its evolution. Here, we explore this hypothesis theoretically and ask if the accumulation of beneficial mutations provides a sufficient fitness advantage for uniparental inheritance to invade a population in which mtDNA is inherited biparentally. In a deterministic model, uniparental inheritance increases in frequency but cannot replace biparental inheritance if only a single beneficial mtDNA mutation sweeps through the population. When we allow successive selective sweeps of mtDNA, however, uniparental inheritance can replace biparental inheritance. Using a stochastic model, we show that a combination of selection and drift facilitates the fixation of uniparental inheritance (compared to a neutral trait) when there is only a single selective mtDNA sweep. When we consider multiple mtDNA sweeps in a stochastic model, uniparental inheritance becomes even more likely to replace biparental inheritance. Our findings thus suggest that selective sweeps of beneficial mtDNA haplotypes can drive the evolution of uniparental inheritance. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

A non-linear dimension reduction methodology for generating data-driven stochastic input models

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

Ganapathysubramanian, Baskar; Zabaras, Nicholas

Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem ofmore » manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R{sup n}. An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R{sup d}(d<

Schrödinger problem, Lévy processes, and noise in relativistic quantum mechanics

NASA Astrophysics Data System (ADS)

Garbaczewski, Piotr; Klauder, John R.; Olkiewicz, Robert

1995-05-01

The main purpose of the paper is an essentially probabilistic analysis of relativistic quantum mechanics. It is based on the assumption that whenever probability distributions arise, there exists a stochastic process that is either responsible for the temporal evolution of a given measure or preserves the measure in the stationary case. Our departure point is the so-called Schrödinger problem of probabilistic evolution, which provides for a unique Markov stochastic interpolation between any given pair of boundary probability densities for a process covering a fixed, finite duration of time, provided we have decided a priori what kind of primordial dynamical semigroup transition mechanism is involved. In the nonrelativistic theory, including quantum mechanics, Feynman-Kac-like kernels are the building blocks for suitable transition probability densities of the process. In the standard ``free'' case (Feynman-Kac potential equal to zero) the familiar Wiener noise is recovered. In the framework of the Schrödinger problem, the ``free noise'' can also be extended to any infinitely divisible probability law, as covered by the Lévy-Khintchine formula. Since the relativistic Hamiltonians ||∇|| and √-Δ+m2 -m are known to generate such laws, we focus on them for the analysis of probabilistic phenomena, which are shown to be associated with the relativistic wave (D'Alembert) and matter-wave (Klein-Gordon) equations, respectively. We show that such stochastic processes exist and are spatial jump processes. In general, in the presence of external potentials, they do not share the Markov property, except for stationary situations. A concrete example of the pseudodifferential Cauchy-Schrödinger evolution is analyzed in detail. The relativistic covariance of related wave equations is exploited to demonstrate how the associated stochastic jump processes comply with the principles of special relativity.

Stochastic dynamic programming illuminates the link between environment, physiology, and evolution.

PubMed

Mangel, Marc

2015-05-01

I describe how stochastic dynamic programming (SDP), a method for stochastic optimization that evolved from the work of Hamilton and Jacobi on variational problems, allows us to connect the physiological state of organisms, the environment in which they live, and how evolution by natural selection acts on trade-offs that all organisms face. I first derive the two canonical equations of SDP. These are valuable because although they apply to no system in particular, they share commonalities with many systems (as do frictionless springs). After that, I show how we used SDP in insect behavioral ecology. I describe the puzzles that needed to be solved, the SDP equations we used to solve the puzzles, and the experiments that we used to test the predictions of the models. I then briefly describe two other applications of SDP in biology: first, understanding the developmental pathways followed by steelhead trout in California and second skipped spawning by Norwegian cod. In both cases, modeling and empirical work were closely connected. I close with lessons learned and advice for the young mathematical biologists.

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Stochastic-field cavitation model

NASA Astrophysics Data System (ADS)

Dumond, J.; Magagnato, F.; Class, A.

2013-07-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

A cavitation model based on Eulerian stochastic fields

NASA Astrophysics Data System (ADS)

Magagnato, F.; Dumond, J.

2013-12-01

Non-linear phenomena can often be described using probability density functions (pdf) and pdf transport models. Traditionally the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and in particular to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. Firstly, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

Stochastic-field cavitation model

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

Dumond, J., E-mail: julien.dumond@areva.com; AREVA GmbH, Erlangen, Paul-Gossen-Strasse 100, D-91052 Erlangen; Magagnato, F.

2013-07-15

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-fieldmore » cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.« less

Stochastic modification of the Schrödinger-Newton equation

NASA Astrophysics Data System (ADS)

Bera, Sayantani; Mohan, Ravi; Singh, Tejinder P.

2015-07-01

The Schrödinger-Newton (SN) equation describes the effect of self-gravity on the evolution of a quantum system, and it has been proposed that gravitationally induced decoherence drives the system to one of the stationary solutions of the SN equation. However, the equation itself lacks a decoherence mechanism, because it does not possess any stochastic feature. In the present work we derive a stochastic modification of the Schrödinger-Newton equation, starting from the Einstein-Langevin equation in the theory of stochastic semiclassical gravity. We specialize this equation to the case of a single massive point particle, and by using Karolyhazy's phase variance method, we derive the Diósi-Penrose criterion for the decoherence time. We obtain a (nonlinear) master equation corresponding to this stochastic SN equation. This equation is, however, linear at the level of the approximation we use to prove decoherence; hence, the no-signaling requirement is met. Lastly, we use physical arguments to obtain expressions for the decoherence length of extended objects.

Self-organized behavior of modeled shoreline shapes

NASA Astrophysics Data System (ADS)

Ashton, A.; Murray, A. B.

2003-04-01

Whenever waves approach a coast and break at oblique angles, they drive a current along the shore. This current, along with wave-induced sediment suspension, transports relatively large amounts of sediment, affecting the shape and evolution of a coastline. Traditionally, researchers have assumed that alongshore sediment transport will diffuse, or smooth, bumps along a shoreline. Recent research, however, shows that when the angle between wave crests in deep water and the shoreline is sufficiently high (greater than approximately 45 degrees), a shoreline is unstable. Linear stability analysis does not predict that this instability will cause a preferred wavelength of shoreline perturbation growth or that organized patterns will emerge. However, a simple numerical model of shoreline change shows those when there is a predominance of high angle waves approaching a shoreline, finite-amplitude features will develop that interact with each other and increase in wavelength over time, translating in the direction of net alongshore sediment transport. Some of these simulated features resemble naturally occurring shoreline features, such as 'alongshore sandwaves', 'ords', 'cuspate spits', and 'cuspate forelands'. By varying two wave climate parameters, one describing the relative dominance of waves approaching at high angles and the other controlling the signs of the approach angle of incoming waves (i.e., the asymmetry of waves approaching from the right vs. the left), we investigate how the attributes of the input wave climate determine the aspect ratio and characteristic form of the simulated features. Varying these two parameters also affects the wavelength of the initially fastest growing perturbation. By tracking the average wavelength of simulated features, which increases over time for all simulations, we show that more complicated phenomena, such as rapid period doubling, can dominate simulated shoreline evolution. These rich behaviors result from large-scale emergent interactions. Although the wave distribution determines the character of shoreline features, their specific configuration and evolution is sensitively dependant on both initial conditions and the stochastic sequencing of wave approach angles.

Stochastic processes constrain the within and between host evolution of influenza virus.

PubMed

McCrone, John T; Woods, Robert J; Martin, Emily T; Malosh, Ryan E; Monto, Arnold S; Lauring, Adam S

2018-05-03

The evolutionary dynamics of influenza virus ultimately derive from processes that take place within and between infected individuals. Here we define influenza virus dynamics in human hosts through sequencing of 249 specimens from 200 individuals collected over 6290 person-seasons of observation. Because these viruses were collected from individuals in a prospective community-based cohort, they are broadly representative of natural infections with seasonal viruses. Consistent with a neutral model of evolution, sequence data from 49 serially sampled individuals illustrated the dynamic turnover of synonymous and nonsynonymous single nucleotide variants and provided little evidence for positive selection of antigenic variants. We also identified 43 genetically-validated transmission pairs in this cohort. Maximum likelihood optimization of multiple transmission models estimated an effective transmission bottleneck of 1-2 genomes. Our data suggest that positive selection is inefficient at the level of the individual host and that stochastic processes dominate the host-level evolution of influenza viruses. © 2018, McCrone et al.

Chaotic ion motion in magnetosonic plasma waves

NASA Technical Reports Server (NTRS)

Varvoglis, H.

1984-01-01

The motion of test ions in a magnetosonic plasma wave is considered, and the 'stochasticity threshold' of the wave's amplitude for the onset of chaotic motion is estimated. It is shown that for wave amplitudes above the stochasticity threshold, the evolution of an ion distribution can be described by a diffusion equation with a diffusion coefficient D approximately equal to 1/v. Possible applications of this process to ion acceleration in flares and ion beam thermalization are discussed.

Solving multistage stochastic programming models of portfolio selection with outstanding liabilities

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

Edirisinghe, C.

1994-12-31

Models for portfolio selection in the presence of an outstanding liability have received significant attention, for example, models for pricing options. The problem may be described briefly as follows: given a set of risky securities (and a riskless security such as a bond), and given a set of cash flows, i.e., outstanding liability, to be met at some future date, determine an initial portfolio and a dynamic trading strategy for the underlying securities such that the initial cost of the portfolio is within a prescribed wealth level and the expected cash surpluses arising from trading is maximized. While the tradingmore » strategy should be self-financing, there may also be other restrictions such as leverage and short-sale constraints. Usually the treatment is limited to binomial evolution of uncertainty (of stock price), with possible extensions for developing computational bounds for multinomial generalizations. Posing as stochastic programming models of decision making, we investigate alternative efficient solution procedures under continuous evolution of uncertainty, for discrete time economies. We point out an important moment problem arising in the portfolio selection problem, the solution (or bounds) on which provides the basis for developing efficient computational algorithms. While the underlying stochastic program may be computationally tedious even for a modest number of trading opportunities (i.e., time periods), the derived algorithms may used to solve problems whose sizes are beyond those considered within stochastic optimization.« less

Time series analysis for minority game simulations of financial markets

NASA Astrophysics Data System (ADS)

Ferreira, Fernando F.; Francisco, Gerson; Machado, Birajara S.; Muruganandam, Paulsamy

2003-04-01

The minority game (MG) model introduced recently provides promising insights into the understanding of the evolution of prices, indices and rates in the financial markets. In this paper we perform a time series analysis of the model employing tools from statistics, dynamical systems theory and stochastic processes. Using benchmark systems and a financial index for comparison, several conclusions are obtained about the generating mechanism for this kind of evolution. The motion is deterministic, driven by occasional random external perturbation. When the interval between two successive perturbations is sufficiently large, one can find low dimensional chaos in this regime. However, the full motion of the MG model is found to be similar to that of the first differences of the SP500 index: stochastic, nonlinear and (unit root) stationary.

Mechanisms for the target patterns formation in a stochastic bistable excitable medium

NASA Astrophysics Data System (ADS)

Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

2018-04-01

We study the features of formation and evolution of spatiotemporal chaotic regime generated by autonomous pacemakers in excitable deterministic and stochastic bistable active media using the example of the FitzHugh - Nagumo biological neuron model under discrete medium conditions. The following possible mechanisms for the formation of autonomous pacemakers have been studied: 1) a temporal external force applied to a small region of the medium, 2) geometry of the solution region (the medium contains regions with Dirichlet or Neumann boundaries). In our work we explore the conditions for the emergence of pacemakers inducing target patterns in a stochastic bistable excitable system and propose the algorithm for their analysis.

Reduced equations of motion for quantum systems driven by diffusive Markov processes.

PubMed

Sarovar, Mohan; Grace, Matthew D

2012-09-28

The expansion of a stochastic Liouville equation for the coupled evolution of a quantum system and an Ornstein-Uhlenbeck process into a hierarchy of coupled differential equations is a useful technique that simplifies the simulation of stochastically driven quantum systems. We expand the applicability of this technique by completely characterizing the class of diffusive Markov processes for which a useful hierarchy of equations can be derived. The expansion of this technique enables the examination of quantum systems driven by non-Gaussian stochastic processes with bounded range. We present an application of this extended technique by simulating Stark-tuned Förster resonance transfer in Rydberg atoms with nonperturbative position fluctuations.

Lognormals for SETI, Evolution and Mass Extinctions

NASA Astrophysics Data System (ADS)

Maccone, Claudio

2014-12-01

In a series of recent papers (Refs. [1-5,7,8]) and in a book (Ref. [6]), this author suggested a new mathematical theory capable of merging Darwinian Evolution and SETI into a unified statistical framework. In this new vision, Darwinian Evolution, as it unfolded on Earth over the last 3.5 billion years, is defined as just one particular realization of a certain lognormal stochastic process in the number of living species on Earth, whose mean value increased in time exponentially. SETI also may be brought into this vision since the number of communicating civilizations in the Galaxy is given by a lognormal distribution (Statistical Drake Equation). Now, in this paper we further elaborate on all that particularly with regard to two important topics: The introduction of the general lognormal stochastic process L(t) whose mean value may be an arbitrary continuous function of the time, m(t), rather than just the exponential mGBM (t) =N0eμt typical of the Geometric Brownian Motion (GBM). This is a considerable generalization of the GBM-based theory used in Refs. [1-8]. The particular application of the general stochastic process L(t) to the understanding of Mass Extinctions like the K-Pg one that marked the dinosaurs' end 65 million years ago. We first model this Mass Extinction as a decreasing Geometric Brownian Motion (GBM) extending from the asteroid's impact time all through the ensuing 'nuclear winter'. However, this model has a flaw: the 'final value' of the GBM cannot have a horizontal tangent, as requested to enable the recovery of life again after this 'final extinction value'. That flaw, however, is removed if the rapidly decreasing mean value function of L(t) is the left branch of a parabola extending from the asteroid's impact time all through the ensuing 'nuclear winter' and up to the time when the number of living species on Earth started growing up again, as we show mathematically in Section 3. In conclusion, we have uncovered an important generalization of the GBM into the general lognormal stochastic process L(t), paving the way to a better, future understanding the evolution of life on Exoplanets on the basis of what Evolution unfolded on Earth in the last 3.5 billion years. That will be the goal of further research papers in the future.

Solute concentration at a well in non-Gaussian aquifers under constant and time-varying pumping schedule

NASA Astrophysics Data System (ADS)

Libera, Arianna; de Barros, Felipe P. J.; Riva, Monica; Guadagnini, Alberto

2017-10-01

Our study is keyed to the analysis of the interplay between engineering factors (i.e., transient pumping rates versus less realistic but commonly analyzed uniform extraction rates) and the heterogeneous structure of the aquifer (as expressed by the probability distribution characterizing transmissivity) on contaminant transport. We explore the joint influence of diverse (a) groundwater pumping schedules (constant and variable in time) and (b) representations of the stochastic heterogeneous transmissivity (T) field on temporal histories of solute concentrations observed at an extraction well. The stochastic nature of T is rendered by modeling its natural logarithm, Y = ln T, through a typical Gaussian representation and the recently introduced Generalized sub-Gaussian (GSG) model. The latter has the unique property to embed scale-dependent non-Gaussian features of the main statistics of Y and its (spatial) increments, which have been documented in a variety of studies. We rely on numerical Monte Carlo simulations and compute the temporal evolution at the well of low order moments of the solute concentration (C), as well as statistics of the peak concentration (Cp), identified as the environmental performance metric of interest in this study. We show that the pumping schedule strongly affects the pattern of the temporal evolution of the first two statistical moments of C, regardless the nature (Gaussian or non-Gaussian) of the underlying Y field, whereas the latter quantitatively influences their magnitude. Our results show that uncertainty associated with C and Cp estimates is larger when operating under a transient extraction scheme than under the action of a uniform withdrawal schedule. The probability density function (PDF) of Cp displays a long positive tail in the presence of time-varying pumping schedule. All these aspects are magnified in the presence of non-Gaussian Y fields. Additionally, the PDF of Cp displays a bimodal shape for all types of pumping schemes analyzed, independent of the type of heterogeneity considered.

Stochastic response and bifurcation of periodically driven nonlinear oscillators by the generalized cell mapping method

NASA Astrophysics Data System (ADS)

Han, Qun; Xu, Wei; Sun, Jian-Qiao

2016-09-01

The stochastic response of nonlinear oscillators under periodic and Gaussian white noise excitations is studied with the generalized cell mapping based on short-time Gaussian approximation (GCM/STGA) method. The solutions of the transition probability density functions over a small fraction of the period are constructed by the STGA scheme in order to construct the GCM over one complete period. Both the transient and steady-state probability density functions (PDFs) of a smooth and discontinuous (SD) oscillator are computed to illustrate the application of the method. The accuracy of the results is verified by direct Monte Carlo simulations. The transient responses show the evolution of the PDFs from being Gaussian to non-Gaussian. The effect of a chaotic saddle on the stochastic response is also studied. The stochastic P-bifurcation in terms of the steady-state PDFs occurs with the decrease of the smoothness parameter, which corresponds to the deterministic pitchfork bifurcation.

Perspectives on the Genetic Architecture of Divergence in Body Shape in Sticklebacks

PubMed Central

Reid, Duncan T.; Peichel, Catherine L.

2010-01-01

The body shape of fishes encompasses a number of morphological traits that are intrinsically linked to functional systems and affect various measures of performance, including swimming, feeding, and avoiding predators. Changes in shape can allow a species to exploit a new ecological niche and can lead to ecological speciation. Body shape results from the integration of morphological, behavioral and physiological traits. It has been well established that functional interdependency among traits plays a large role in constraining the evolution of shape, affecting both the speed and the repeated evolution of particular body shapes. However, it is less clear what role genetic or developmental constraints might play in biasing the rate or direction of the evolution of body shape. Here, we suggest that the threespine stickleback (Gasterosteus aculeatus) is a powerful model system in which to address the extent to which genetic or developmental constraints play a role in the evolution of body shape in fishes. We review the existing data that begins to address these issues in sticklebacks and provide suggestions for future areas of research that will be particularly fruitful for illuminating the mechanisms that contribute to the evolution of body shape in fishes. PMID:21082067

Integrated Multiscale Modeling of Molecular Computing Devices. Final Report

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

Tim Schulze

2012-11-01

The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.

Stochastic 2-D galaxy disk evolution models. Resolved stellar populations in the galaxy M33

NASA Astrophysics Data System (ADS)

Mineikis, T.; Vansevičius, V.

We improved the stochastic 2-D galaxy disk models (Mineikis & Vansevičius 2014a) by introducing enriched gas outflows from galaxies and synthetic color-magnitude diagrams of stellar populations. To test the models, we use the HST/ACS stellar photometry data in four fields located along the major axis of the galaxy M33 (Williams et al. 2009) and demonstrate the potential of the models to derive 2-D star formation histories in the resolved disk galaxies.

Exact solution for a non-Markovian dissipative quantum dynamics.

PubMed

Ferialdi, Luca; Bassi, Angelo

2012-04-27

We provide the exact analytic solution of the stochastic Schrödinger equation describing a harmonic oscillator interacting with a non-Markovian and dissipative environment. This result represents an arrival point in the study of non-Markovian dynamics via stochastic differential equations. It is also one of the few exactly solvable models for infinite-dimensional systems. We compute the Green's function; in the case of a free particle and with an exponentially correlated noise, we discuss the evolution of Gaussian wave functions.

Dispersal similarly shapes both population genetics and community patterns in the marine realm

PubMed Central

Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Fernández de Puelles, María L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Veríssimo, Helena; Zervoudaki, Soultana; Borja, Angel

2016-01-01

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns. PMID:27344967

Spatial Selection and Local Adaptation Jointly Shape Life-History Evolution during Range Expansion.

PubMed

Van Petegem, Katrien H P; Boeye, Jeroen; Stoks, Robby; Bonte, Dries

2016-11-01

In the context of climate change and species invasions, range shifts increasingly gain attention because the rates at which they occur in the Anthropocene induce rapid changes in biological assemblages. During range shifts, species experience multiple selection pressures. For poleward expansions in particular, it is difficult to interpret observed evolutionary dynamics because of the joint action of evolutionary processes related to spatial selection and to adaptation toward local climatic conditions. To disentangle the effects of these two processes, we integrated stochastic modeling and data from a common garden experiment, using the spider mite Tetranychus urticae as a model species. By linking the empirical data with those derived form a highly parameterized individual-based model, we infer that both spatial selection and local adaptation contributed to the observed latitudinal life-history divergence. Spatial selection best described variation in dispersal behavior, while variation in development was best explained by adaptation to the local climate. Divergence in life-history traits in species shifting poleward could consequently be jointly determined by contemporary evolutionary dynamics resulting from adaptation to the environmental gradient and from spatial selection. The integration of modeling with common garden experiments provides a powerful tool to study the contribution of these evolutionary processes on life-history evolution during range expansion.

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

Zhu, Z. W., E-mail: zhuzhiwen@tju.edu.cn; Li, X. M., E-mail: lixinmiaotju@163.com; Xu, J., E-mail: xujia-ld@163.com

A kind of magnetic shape memory alloy (MSMA) microgripper is proposed in this paper, and its nonlinear dynamic characteristics are studied when the stochastic perturbation is considered. Nonlinear differential items are introduced to explain the hysteretic phenomena of MSMA, and the constructive relationships among strain, stress, and magnetic field intensity are obtained by the partial least-square regression method. The nonlinear dynamic model of a MSMA microgripper subjected to in-plane stochastic excitation is developed. The stationary probability density function of the system’s response is obtained, the transition sets of the system are determined, and the conditions of stochastic bifurcation are obtained.more » The homoclinic and heteroclinic orbits of the system are given, and the boundary of the system’s safe basin is obtained by stochastic Melnikov integral method. The numerical and experimental results show that the system’s motion depends on its parameters, and stochastic Hopf bifurcation appears in the variation of the parameters; the area of the safe basin decreases with the increase of the stochastic excitation, and the boundary of the safe basin becomes fractal. The results of this paper are helpful for the application of MSMA microgripper in engineering fields.« less

Probability density function evolution of power systems subject to stochastic variation of renewable energy

NASA Astrophysics Data System (ADS)

Wei, J. Q.; Cong, Y. C.; Xiao, M. Q.

2018-05-01

As renewable energies are increasingly integrated into power systems, there is increasing interest in stochastic analysis of power systems.Better techniques should be developed to account for the uncertainty caused by penetration of renewables and consequently analyse its impacts on stochastic stability of power systems. In this paper, the Stochastic Differential Equations (SDEs) are used to represent the evolutionary behaviour of the power systems. The stationary Probability Density Function (PDF) solution to SDEs modelling power systems excited by Gaussian white noise is analysed. Subjected to such random excitation, the Joint Probability Density Function (JPDF) solution to the phase angle and angular velocity is governed by the generalized Fokker-Planck-Kolmogorov (FPK) equation. To solve this equation, the numerical method is adopted. Special measure is taken such that the generalized FPK equation is satisfied in the average sense of integration with the assumed PDF. Both weak and strong intensities of the stochastic excitations are considered in a single machine infinite bus power system. The numerical analysis has the same result as the one given by the Monte Carlo simulation. Potential studies on stochastic behaviour of multi-machine power systems with random excitations are discussed at the end.

Spatially heterogeneous stochasticity and the adaptive diversification of dormancy.

PubMed

Rajon, E; Venner, S; Menu, F

2009-10-01

Diversified bet-hedging, a strategy that leads several individuals with the same genotype to express distinct phenotypes in a given generation, is now well established as a common evolutionary response to environmental stochasticity. Life-history traits defined as diversified bet-hedging (e.g. germination or diapause strategies) display marked differences between populations in spatial proximity. In order to find out whether such differences can be explained by local adaptations to spatially heterogeneous environmental stochasticity, we explored the evolution of bet-hedging dormancy strategies in a metapopulation using a two-patch model with patch differences in stochastic juvenile survival. We found that spatial differences in the level of environmental stochasticity, restricted dispersal, increased fragmentation and intermediate survival during dormancy all favour the adaptive diversification of bet-hedging dormancy strategies. Density dependency also plays a major role in the diversification of dormancy strategies because: (i) it may interact locally with environmental stochasticity and amplify its effects; however, (ii) it can also generate chaotic population dynamics that may impede diversification. Our work proposes new hypotheses to explain the spatial patterns of bet-hedging strategies that we hope will encourage new empirical studies of this topic.

Exact and approximate many-body dynamics with stochastic one-body density matrix evolution

NASA Astrophysics Data System (ADS)

Lacroix, Denis

2005-06-01

We show that the dynamics of interacting fermions can be exactly replaced by a quantum jump theory in the many-body density matrix space. In this theory, jumps occur between densities formed of pairs of Slater determinants, Dab=|Φa><Φb|, where each state evolves according to the stochastic Schrödinger equation given by O. Juillet and Ph. Chomaz [Phys. Rev. Lett. 88, 142503 (2002)]. A stochastic Liouville-von Neumann equation is derived as well as the associated. Bogolyubov-Born-Green-Kirwood-Yvon hierarchy. Due to the specific form of the many-body density along the path, the presented theory is equivalent to a stochastic theory in one-body density matrix space, in which each density matrix evolves according to its own mean-field augmented by a one-body noise. Guided by the exact reformulation, a stochastic mean-field dynamics valid in the weak coupling approximation is proposed. This theory leads to an approximate treatment of two-body effects similar to the extended time-dependent Hartree-Fock scheme. In this stochastic mean-field dynamics, statistical mixing can be directly considered and jumps occur on a coarse-grained time scale. Accordingly, numerical effort is expected to be significantly reduced for applications.

The adaptation rate of a quantitative trait in an environmental gradient

NASA Astrophysics Data System (ADS)

Hermsen, R.

2016-12-01

The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform. Here, we use a minimal stochastic model of discrete, interacting organisms evolving in continuous space to study how the rate of adaptation of a quantitative trait depends on the steepness of the gradient and various population parameters. We discuss analytical results for the mean-field limit as well as extensive stochastic simulations. These simulations were performed using an exact, event-driven simulation scheme that can deal with continuous time-, density- and coordinate-dependent reaction rates and could be used for a wide variety of stochastic systems. The results reveal two qualitative regimes. If the gradient is shallow, the rate of adaptation is limited by dispersion and increases linearly with the gradient slope. If the gradient is steep, the adaptation rate is limited by mutation. In this regime, the mean-field result is highly misleading: it predicts that the adaptation rate continues to increase with the gradient slope, whereas stochastic simulations show that it in fact decreases with the square root of the slope. This discrepancy underscores the importance of discreteness and stochasticity even at high population densities; mean-field results, including those routinely used in quantitative genetics, should be interpreted with care.

The adaptation rate of a quantitative trait in an environmental gradient.

PubMed

Hermsen, R

2016-11-30

The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform. Here, we use a minimal stochastic model of discrete, interacting organisms evolving in continuous space to study how the rate of adaptation of a quantitative trait depends on the steepness of the gradient and various population parameters. We discuss analytical results for the mean-field limit as well as extensive stochastic simulations. These simulations were performed using an exact, event-driven simulation scheme that can deal with continuous time-, density- and coordinate-dependent reaction rates and could be used for a wide variety of stochastic systems. The results reveal two qualitative regimes. If the gradient is shallow, the rate of adaptation is limited by dispersion and increases linearly with the gradient slope. If the gradient is steep, the adaptation rate is limited by mutation. In this regime, the mean-field result is highly misleading: it predicts that the adaptation rate continues to increase with the gradient slope, whereas stochastic simulations show that it in fact decreases with the square root of the slope. This discrepancy underscores the importance of discreteness and stochasticity even at high population densities; mean-field results, including those routinely used in quantitative genetics, should be interpreted with care.

SIApopr: a computational method to simulate evolutionary branching trees for analysis of tumor clonal evolution.

PubMed

McDonald, Thomas O; Michor, Franziska

2017-07-15

SIApopr (Simulating Infinite-Allele populations) is an R package to simulate time-homogeneous and inhomogeneous stochastic branching processes under a very flexible set of assumptions using the speed of C ++. The software simulates clonal evolution with the emergence of driver and passenger mutations under the infinite-allele assumption. The software is an application of the Gillespie Stochastic Simulation Algorithm expanded to a large number of cell types and scenarios, with the intention of allowing users to easily modify existing models or create their own. SIApopr is available as an R library on Github ( https://github.com/olliemcdonald/siapopr ). Supplementary data are available at Bioinformatics online. michor@jimmy.harvard.edu. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The molecular and mathematical basis of Waddington's epigenetic landscape: a framework for post-Darwinian biology?

PubMed

Huang, Sui

2012-02-01

The Neo-Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo-Darwinism. It needs to incorporate the non-linear, stochastic dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric 'epigenetic landscape', which actually represents the quasi-potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re-wiring of regulatory interactions - offering a link between genetic mutation and sudden, broad evolutionary changes. Copyright © 2012 WILEY Periodicals, Inc.

Preemptive spatial competition under a reproduction-mortality constraint.

PubMed

Allstadt, Andrew; Caraco, Thomas; Korniss, G

2009-06-21

Spatially structured ecological interactions can shape selection pressures experienced by a population's different phenotypes. We study spatial competition between phenotypes subject to antagonistic pleiotropy between reproductive effort and mortality rate. The constraint we invoke reflects a previous life-history analysis; the implied dependence indicates that although propagation and mortality rates both vary, their ratio is fixed. We develop a stochastic invasion approximation predicting that phenotypes with higher propagation rates will invade an empty environment (no biotic resistance) faster, despite their higher mortality rate. However, once population density approaches demographic equilibrium, phenotypes with lower mortality are favored, despite their lower propagation rate. We conducted a set of pairwise invasion analyses by simulating an individual-based model of preemptive competition. In each case, the phenotype with the lowest mortality rate and (via antagonistic pleiotropy) the lowest propagation rate qualified as evolutionarily stable among strategies simulated. This result, for a fixed propagation to mortality ratio, suggests that a selective response to spatial competition can extend the time scale of the population's dynamics, which in turn decelerates phenotypic evolution.

Stochastic stability in three-player games.

PubMed

Kamiński, Dominik; Miekisz, Jacek; Zaborowski, Marcin

2005-11-01

Animal behavior and evolution can often be described by game-theoretic models. Although in many situations the number of players is very large, their strategic interactions are usually decomposed into a sum of two-player games. Only recently were evolutionarily stable strategies defined for multi-player games and their properties analyzed [Broom, M., Cannings, C., Vickers, G.T., 1997. Multi-player matrix games. Bull. Math. Biol. 59, 931-952]. Here we study the long-run behavior of stochastic dynamics of populations of randomly matched individuals playing symmetric three-player games. We analyze the stochastic stability of equilibria in games with multiple evolutionarily stable strategies. We also show that, in some games, a population may not evolve in the long run to an evolutionarily stable equilibrium.

Fractional Stochastic Field Theory

NASA Astrophysics Data System (ADS)

Honkonen, Juha

2018-02-01

Models describing evolution of physical, chemical, biological, social and financial processes are often formulated as differential equations with the understanding that they are large-scale equations for averages of quantities describing intrinsically random processes. Explicit account of randomness may lead to significant changes in the asymptotic behaviour (anomalous scaling) in such models especially in low spatial dimensions, which in many cases may be captured with the use of the renormalization group. Anomalous scaling and memory effects may also be introduced with the use of fractional derivatives and fractional noise. Construction of renormalized stochastic field theory with fractional derivatives and fractional noise in the underlying stochastic differential equations and master equations and the interplay between fluctuation-induced and built-in anomalous scaling behaviour is reviewed and discussed.

Compressible cavitation with stochastic field method

NASA Astrophysics Data System (ADS)

Class, Andreas; Dumond, Julien

2012-11-01

Non-linear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally the simulation of pdf transport requires Monte-Carlo codes based on Lagrange particles or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic field method solving pdf transport based on Euler fields has been proposed which eliminates the necessity to mix Euler and Lagrange techniques or prescribed pdf assumptions. In the present work, part of the PhD Design and analysis of a Passive Outflow Reducer relying on cavitation, a first application of the stochastic field method to multi-phase flow and in particular to cavitating flow is presented. The application considered is a nozzle subjected to high velocity flow so that sheet cavitation is observed near the nozzle surface in the divergent section. It is demonstrated that the stochastic field formulation captures the wide range of pdf shapes present at different locations. The method is compatible with finite-volume codes where all existing physical models available for Lagrange techniques, presumed pdf or binning methods can be easily extended to the stochastic field formulation.

Predicting the Stochastic Properties of the Shallow Subsurface for Improved Geophysical Modeling

NASA Astrophysics Data System (ADS)

Stroujkova, A.; Vynne, J.; Bonner, J.; Lewkowicz, J.

2005-12-01

Strong ground motion data from numerous explosive field experiments and from moderate to large earthquakes show significant variations in amplitude and waveform shape with respect to both azimuth and range. Attempts to model these variations using deterministic models have often been unsuccessful. It has been hypothesized that a stochastic description of the geological medium is a more realistic approach. To estimate the stochastic properties of the shallow subsurface, we use Measurement While Drilling (MWD) data, which are routinely collected by mines in order to facilitate design of blast patterns. The parameters, such as rotation speed of the drill, torque, and penetration rate, are used to compute the rock's Specific Energy (SE), which is then related to a blastability index. We use values of SE measured at two different mines and calibrated to laboratory measurements of rock properties to determine correlation lengths of the subsurface rocks in 2D, needed to obtain 2D and 3D stochastic models. The stochastic models are then combined with the deterministic models and used to compute synthetic seismic waveforms.

Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations

NASA Astrophysics Data System (ADS)

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2018-07-01

Continuous noise caused by mutation is widely present in evolutionary systems. Considering the noise effects and under the optional participation mechanism, a stochastic model for evolutionary public goods game in a finite size population is established. The evolutionary process of strategies in the population is described as a multidimensional ergodic and continuous time Markov process. The stochastic stable state of the system is analyzed by the limit distribution of the stochastic process. By numerical experiments, the influences of the fixed income coefficient for non-participants and the investment income coefficient of the public goods on the stochastic stable equilibrium of the system are analyzed. Through the numerical calculation results, we found that the optional participation mechanism can change the evolutionary dynamics and the equilibrium of the public goods game, and there is a range of parameters which can effectively promote the evolution of cooperation. Further, we obtain the accurate quantitative relationship between the parameters and the probabilities for the system to choose different stable equilibriums, which can be used to realize the control of cooperation.

Stochastic Evolution of Augmented Born-Infeld Equations

NASA Astrophysics Data System (ADS)

Holm, Darryl D.

2018-06-01

This paper compares the results of applying a recently developed method of stochastic uncertainty quantification designed for fluid dynamics to the Born-Infeld model of nonlinear electromagnetism. The similarities in the results are striking. Namely, the introduction of Stratonovich cylindrical noise into each of their Hamiltonian formulations introduces stochastic Lie transport into their dynamics in the same form for both theories. Moreover, the resulting stochastic partial differential equations retain their unperturbed form, except for an additional term representing induced Lie transport by the set of divergence-free vector fields associated with the spatial correlations of the cylindrical noise. The explanation for this remarkable similarity lies in the method of construction of the Hamiltonian for the Stratonovich stochastic contribution to the motion in both cases, which is done via pairing spatial correlation eigenvectors for cylindrical noise with the momentum map for the deterministic motion. This momentum map is responsible for the well-known analogy between hydrodynamics and electromagnetism. The momentum map for the Maxwell and Born-Infeld theories of electromagnetism treated here is the 1-form density known as the Poynting vector. Two appendices treat the Hamiltonian structures underlying these results.

Non-Markovian stochastic Schrödinger equations: Generalization to real-valued noise using quantum-measurement theory

NASA Astrophysics Data System (ADS)

Gambetta, Jay; Wiseman, H. M.

2002-07-01

Do stochastic Schrödinger equations, also known as unravelings, have a physical interpretation? In the Markovian limit, where the system on average obeys a master equation, the answer is yes. Markovian stochastic Schrödinger equations generate quantum trajectories for the system state conditioned on continuously monitoring the bath. For a given master equation, there are many different unravelings, corresponding to different sorts of measurement on the bath. In this paper we address the non-Markovian case, and in particular the sort of stochastic Schrödinger equation introduced by Strunz, Diósi, and Gisin [Phys. Rev. Lett. 82, 1801 (1999)]. Using a quantum-measurement theory approach, we rederive their unraveling that involves complex-valued Gaussian noise. We also derive an unraveling involving real-valued Gaussian noise. We show that in the Markovian limit, these two unravelings correspond to heterodyne and homodyne detection, respectively. Although we use quantum-measurement theory to define these unravelings, we conclude that the stochastic evolution of the system state is not a true quantum trajectory, as the identity of the state through time is a fiction.

Alternate pathways of body shape evolution translate into common patterns of locomotor evolution in two clades of lizards.

PubMed

Bergmann, Philip J; Irschick, Duncan J

2010-06-01

Body shape has a fundamental impact on organismal function, but it is unknown how functional morphology and locomotor performance and kinematics relate across a diverse array of body shapes. We showed that although patterns of body shape evolution differed considerably between lizards of the Phrynosomatinae and Lerista, patterns of locomotor evolution coincided between clades. Specifically, we found that the phrynosomatines evolved a stocky phenotype through body widening and limb shortening, whereas Lerista evolved elongation through body lengthening and limb shortening. In both clades, relative limb length played a key role in locomotor evolution and kinematic strategies, with long-limbed species moving faster and taking longer strides. In Lerista, the body axis also influenced locomotor evolution. Similar patterns of locomotor evolution were likely due to constraints on how the body can move. However, these common patterns of locomotor evolution between the two clades resulted in different kinematic strategies and levels of performance among species because of their morphological differences. Furthermore, we found no evidence that distinct body shapes are adaptations to different substrates, as locomotor kinematics did not change on loose or solid substrates. Our findings illustrate the importance of studying kinematics to understand the mechanisms of locomotor evolution and phenotype-function relationships.

Continuum Model for River Networks

NASA Astrophysics Data System (ADS)

Giacometti, Achille; Maritan, Amos; Banavar, Jayanth R.

1995-07-01

The effects of erosion, avalanching, and random precipitation are captured in a simple stochastic partial differential equation for modeling the evolution of river networks. Our model leads to a self-organized structured landscape and to abstraction and piracy of the smaller tributaries as the evolution proceeds. An algebraic distribution of the average basin areas and a power law relationship between the drainage basin area and the river length are found.

A stochastic model for tumor geometry evolution during radiation therapy in cervical cancer

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

Liu, Yifang; Lee, Chi-Guhn; Chan, Timothy C. Y., E-mail: tcychan@mie.utoronto.ca

2014-02-15

Purpose: To develop mathematical models to predict the evolution of tumor geometry in cervical cancer undergoing radiation therapy. Methods: The authors develop two mathematical models to estimate tumor geometry change: a Markov model and an isomorphic shrinkage model. The Markov model describes tumor evolution by investigating the change in state (either tumor or nontumor) of voxels on the tumor surface. It assumes that the evolution follows a Markov process. Transition probabilities are obtained using maximum likelihood estimation and depend on the states of neighboring voxels. The isomorphic shrinkage model describes tumor shrinkage or growth in terms of layers of voxelsmore » on the tumor surface, instead of modeling individual voxels. The two proposed models were applied to data from 29 cervical cancer patients treated at Princess Margaret Cancer Centre and then compared to a constant volume approach. Model performance was measured using sensitivity and specificity. Results: The Markov model outperformed both the isomorphic shrinkage and constant volume models in terms of the trade-off between sensitivity (target coverage) and specificity (normal tissue sparing). Generally, the Markov model achieved a few percentage points in improvement in either sensitivity or specificity compared to the other models. The isomorphic shrinkage model was comparable to the Markov approach under certain parameter settings. Convex tumor shapes were easier to predict. Conclusions: By modeling tumor geometry change at the voxel level using a probabilistic model, improvements in target coverage and normal tissue sparing are possible. Our Markov model is flexible and has tunable parameters to adjust model performance to meet a range of criteria. Such a model may support the development of an adaptive paradigm for radiation therapy of cervical cancer.« less

From quantum to classical modeling of radiation reaction: A focus on stochasticity effects

NASA Astrophysics Data System (ADS)

Niel, F.; Riconda, C.; Amiranoff, F.; Duclous, R.; Grech, M.

2018-04-01

Radiation reaction in the interaction of ultrarelativistic electrons with a strong external electromagnetic field is investigated using a kinetic approach in the nonlinear moderately quantum regime. Three complementary descriptions are discussed considering arbitrary geometries of interaction: a deterministic one relying on the quantum-corrected radiation reaction force in the Landau and Lifschitz (LL) form, a linear Boltzmann equation for the electron distribution function, and a Fokker-Planck (FP) expansion in the limit where the emitted photon energies are small with respect to that of the emitting electrons. The latter description is equivalent to a stochastic differential equation where the effect of the radiation reaction appears in the form of the deterministic term corresponding to the quantum-corrected LL friction force, and by a diffusion term accounting for the stochastic nature of photon emission. By studying the evolution of the energy moments of the electron distribution function with the three models, we are able to show that all three descriptions provide similar predictions on the temporal evolution of the average energy of an electron population in various physical situations of interest, even for large values of the quantum parameter χ . The FP and full linear Boltzmann descriptions also allow us to correctly describe the evolution of the energy variance (second-order moment) of the distribution function, while higher-order moments are in general correctly captured with the full linear Boltzmann description only. A general criterion for the limit of validity of each description is proposed, as well as a numerical scheme for the inclusion of the FP description in particle-in-cell codes. This work, not limited to the configuration of a monoenergetic electron beam colliding with a laser pulse, allows further insight into the relative importance of various effects of radiation reaction and in particular of the discrete and stochastic nature of high-energy photon emission and its back-reaction in the deformation of the particle distribution function.

Social evolution and genetic interactions in the short and long term.

PubMed

Van Cleve, Jeremy

2015-08-01

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work. Copyright © 2015 Elsevier Inc. All rights reserved.

Shortcuts to adiabaticity using flow fields

NASA Astrophysics Data System (ADS)

Patra, Ayoti; Jarzynski, Christopher

2017-12-01

A shortcut to adiabaticity is a recipe for generating adiabatic evolution at an arbitrary pace. Shortcuts have been developed for quantum, classical and (most recently) stochastic dynamics. A shortcut might involve a counterdiabatic (CD) Hamiltonian that causes a system to follow the adiabatic evolution at all times, or it might utilize a fast-forward (FF) potential, which returns the system to the adiabatic path at the end of the process. We develop a general framework for constructing shortcuts to adiabaticity from flow fields that describe the desired adiabatic evolution. Our approach encompasses quantum, classical and stochastic dynamics, and provides surprisingly compact expressions for both CD Hamiltonians and FF potentials. We illustrate our method with numerical simulations of a model system, and we compare our shortcuts with previously obtained results. We also consider the semiclassical connections between our quantum and classical shortcuts. Our method, like the FF approach developed by previous authors, is susceptible to singularities when applied to excited states of quantum systems; we propose a simple, intuitive criterion for determining whether these singularities will arise, for a given excited state.

An analysis of the daily precipitation variability in the Himalayan orogen using a statistical parameterisation and its potential in driving landscape evolution models with stochastic climatic forcing

NASA Astrophysics Data System (ADS)

Deal, Eric; Braun, Jean

2015-04-01

A current challenge in landscape evolution modelling is to integrate realistic precipitation patterns and behaviour into longterm fluvial erosion models. The effect of precipitation on fluvial erosion can be subtle as well as nonlinear, implying that changes in climate (e.g. precipitation magnitude or storminess) may have unexpected outcomes in terms of erosion rates. For example Tucker and Bras (2000) show theoretically that changes in the variability of precipitation (storminess) alone can influence erosion rate across a landscape. To complicate the situation further, topography, ultimately driven by tectonic uplift but shaped by erosion, has a major influence on the distribution and style of precipitation. Therefore, in order to untangle the coupling between climate, erosion and tectonics in an actively uplifting orogen where fluvial erosion is dominant it is important to understand how the 'rain dial' used in a landscape evolution model (LEM) corresponds to real precipitation patterns. One issue with the parameterisation of rainfall for use in an LEM is the difference between the timescales for precipitation (≤ 1 year) and landscape evolution (> 103 years). As a result, precipitation patterns must be upscaled before being integrated into a model. The relevant question then becomes: What is the most appropriate measure of precipitation on a millennial timescale? Previous work (Tucker and Bras, 2000; Lague, 2005) has shown that precipitation can be properly upscaled by taking into account its variable nature, along with its average magnitude. This captures the relative size and frequency of extreme events, ensuring a more accurate characterisation of the integrated effects of precipitation on erosion over long periods of time. In light of this work, we present a statistical parameterisation that accurately models the mean and daily variability of ground based (APHRODITE) and remotely sensed (TRMM) precipitation data in the Himalayan orogen with only a few parameters. We also demonstrate over what spatial and temporal scales this parameterisation applies and is stable. Applying the parameterisation over the Himalayan orogen reveals large-scale strike-perpendicular gradients in precipitation variability in addition to the long observed strike-perpendicular gradient in precipitation magnitude. This observation, combined with the theoretical work mentioned above, suggests that variability is an integral part of the interaction between climate and erosion. References Bras, R. L., & Tucker, G. E. (2000). A stochastic approach to modeling the role of rainfall variability in drainage basin evolution. Water Resources Research, 36(7), 1953-1964. doi:10.1029/2000WR900065 Lague, D. (2005). Discharge, discharge variability, and the bedrock channel profile. Journal of Geophysical Research, 110(F4), F04006. doi:10.1029/2004JF000259

Stochastic description of quantum Brownian dynamics

NASA Astrophysics Data System (ADS)

Yan, Yun-An; Shao, Jiushu

2016-08-01

Classical Brownian motion has well been investigated since the pioneering work of Einstein, which inspired mathematicians to lay the theoretical foundation of stochastic processes. A stochastic formulation for quantum dynamics of dissipative systems described by the system-plus-bath model has been developed and found many applications in chemical dynamics, spectroscopy, quantum transport, and other fields. This article provides a tutorial review of the stochastic formulation for quantum dissipative dynamics. The key idea is to decouple the interaction between the system and the bath by virtue of the Hubbard-Stratonovich transformation or Itô calculus so that the system and the bath are not directly entangled during evolution, rather they are correlated due to the complex white noises introduced. The influence of the bath on the system is thereby defined by an induced stochastic field, which leads to the stochastic Liouville equation for the system. The exact reduced density matrix can be calculated as the stochastic average in the presence of bath-induced fields. In general, the plain implementation of the stochastic formulation is only useful for short-time dynamics, but not efficient for long-time dynamics as the statistical errors go very fast. For linear and other specific systems, the stochastic Liouville equation is a good starting point to derive the master equation. For general systems with decomposable bath-induced processes, the hierarchical approach in the form of a set of deterministic equations of motion is derived based on the stochastic formulation and provides an effective means for simulating the dissipative dynamics. A combination of the stochastic simulation and the hierarchical approach is suggested to solve the zero-temperature dynamics of the spin-boson model. This scheme correctly describes the coherent-incoherent transition (Toulouse limit) at moderate dissipation and predicts a rate dynamics in the overdamped regime. Challenging problems such as the dynamical description of quantum phase transition (local- ization) and the numerical stability of the trace-conserving, nonlinear stochastic Liouville equation are outlined.

Effects of conformism on the cultural evolution of social behaviour.

PubMed

Molleman, Lucas; Pen, Ido; Weissing, Franz J

2013-01-01

Models of cultural evolution study how the distribution of cultural traits changes over time. The dynamics of cultural evolution strongly depends on the way these traits are transmitted between individuals by social learning. Two prominent forms of social learning are payoff-based learning (imitating others that have higher payoffs) and conformist learning (imitating locally common behaviours). How payoff-based and conformist learning affect the cultural evolution of cooperation is currently a matter of lively debate, but few studies systematically analyse the interplay of these forms of social learning. Here we perform such a study by investigating how the interaction of payoff-based and conformist learning affects the outcome of cultural evolution in three social contexts. First, we develop a simple argument that provides insights into how the outcome of cultural evolution will change when more and more conformist learning is added to payoff-based learning. In a social dilemma (e.g. a Prisoner's Dilemma), conformism can turn cooperation into a stable equilibrium; in an evasion game (e.g. a Hawk-Dove game or a Snowdrift game) conformism tends to destabilize the polymorphic equilibrium; and in a coordination game (e.g. a Stag Hunt game), conformism changes the basin of attraction of the two equilibria. Second, we analyse a stochastic event-based model, revealing that conformism increases the speed of cultural evolution towards pure equilibria. Individual-based simulations as well as the analysis of the diffusion approximation of the stochastic model by and large confirm our findings. Third, we investigate the effect of an increasing degree of conformism on cultural group selection in a group-structured population. We conclude that, in contrast to statements in the literature, conformism hinders rather than promotes the evolution of cooperation.

Mantle convection and the distribution of geochemical reservoirs in the silicate shell of the Earth

NASA Astrophysics Data System (ADS)

Walzer, Uwe; Hendel, Roland

2010-05-01

We present a dynamic 3-D spherical-shell model of mantle convection and the evolution of the chemical reservoirs of the Earth`s silicate shell. Chemical differentiation, convection, stirring and thermal evolution constitute an inseparable dynamic system. Our model is based on the solution of the balance equations of mass, momentum, energy, angular momentum, and four sums of the number of atoms of the pairs 238U-206Pb, 235U-207Pb, 232Th-208Pb, and 40K-40Ar. Similar to the present model, the continental crust of the real Earth was not produced entirely at the start of the evolution but developed episodically in batches [1-7]. The details of the continental distribution of the model are largely stochastic, but the spectral properties are quite similar to the present real Earth. The calculated Figures reveal that the modeled present-day mantle has no chemical stratification but we find a marble-cake structure. If we compare the observational results of the present-day proportion of depleted MORB mantle with the model then we find a similar order of magnitude. The MORB source dominates under the lithosphere. In our model, there are nowhere pure unblended reservoirs in the mantle. It is, however, remarkable that, in spite of 4500 Ma of solid-state mantle convection, certain strong concentrations of distributed chemical reservoirs continue to persist in certain volumes, although without sharp abundance boundaries. We deal with the question of predictable and stochastic portions of the phenomena. Although the convective flow patterns and the chemical differentiation of oceanic plateaus are coupled, the evolution of time-dependent Rayleigh number, Rat , is relatively well predictable and the stochastic parts of the Rat(t)-curves are small. Regarding the juvenile growth rates of the total mass of the continents, predictions are possible only in the first epoch of the evolution. Later on, the distribution of the continental-growth episodes is increasingly stochastic. Independently of the varying individual runs, our model shows that the total mass of the present-day continents is not generated in a single process at the beginning of the thermal evolution of the Earth but in episodically distributed processes in the course of geological time. This is in accord with observation. Finally, we present results regarding the numerical method, implementation, scalability and performance. References [1] Condie, K. C., Episodie continental growth models: Afterthoughts and extensions, Tectonophysics, 322 (2000), 153-162. [2] Davidson, J. P. and Arculus, R. J., The significance of Phanerozoic arc magmatism in generating continental crust, in Evolution and Differentiation of the Continental Crust, edited by M. Brown and T. Rushmer (2006), 135-172, Cambridge Univ. Press, Cambridge, UK. [3] Hofmann, A. W., Sampling mantle heterogeneity through oceanic basalts: Isotopes and trace elements, in Treatise on Geochemistry, Vol. 2: The Mantle and the Core, edited by R. W. Carlson (2003), 61-101, Elsevier, Amsterdam. [4] Rollinson, H., Crustal generation in the Archean, in Evolution and Differentiation of the Continental Crust, edited by M. Brown and T. Rushmer (2006), 173-230, Cambridge Univ. Press, Cambridge, UK: [5] Taylor, S. R. and McLennan, S. M., Planetary Crusts. Their Composition, Origin and Evolution. (2009), 1-378, Cambridge Univ. Press, Cambridge, UK. [6] Walzer, U. and Hendel, R., Mantle convection and evolution with growing continents. J. Geophys. Res. 113 (2008), B09405, doi: 10.1029/2007JB005459 [7] http://www.igw.uni-jena.de/geodyn

The role of pollinator diversity in the evolution of corolla-shape integration in a pollination-generalist plant clade

PubMed Central

Gómez, José María; Perfectti, Francisco; Klingenberg, Christian Peter

2014-01-01

Flowers of animal-pollinated plants are integrated structures shaped by the action of pollinator-mediated selection. It is widely assumed that pollination specialization increases the magnitude of floral integration. However, empirical evidence is still inconclusive. In this study, we explored the role of pollinator diversity in shaping the evolution of corolla-shape integration in Erysimum, a plant genus with generalized pollination systems. We quantified floral integration in Erysimum using geometric morphometrics and explored its evolution using phylogenetic comparative methods. Corolla-shape integration was low but significantly different from zero in all study species. Spatial autocorrelation and phylogenetic signal in corolla-shape integration were not detected. In addition, integration in Erysimum seems to have evolved in a way that is consistent with Brownian motion, but with frequent convergent evolution. Corolla-shape integration was negatively associated with the number of pollinators visiting the flowers of each Erysimum species. That is, it was lower in those species having a more generalized pollination system. This negative association may occur because the co-occurrence of many pollinators imposes conflicting selection and cancels out any consistent selection on specific floral traits, preventing the evolution of highly integrated flowers. PMID:25002702

Sexual selection and the evolution of genital shape and complexity in water striders.

PubMed

Rowe, Locke; Arnqvist, Göran

2012-01-01

Animal genitalia show two striking but incompletely understood evolutionary trends: a great evolutionary divergence in the shape of genitalic structures, and characteristic structural complexity. Both features are thought to result from sexual selection, but explicit comparative tests are hampered by the fact that it is difficult to quantify both morphological complexity and divergence in shape. We undertake a comparative study of multiple nongenitalic and male genital traits in a clade of 15 water strider species to quantify complexity and shape divergence. We show that genital structures are more complex and their shape more divergent among species than nongenital traits. Further, intromittent genital traits are more complex and have evolved more divergently than nonintromittent genital traits. More importantly, shape and complexity of nonintromittent genital traits show correlated evolution with indices of premating sexual selection and intromittent genital traits with postmating sexual selection, suggesting that the evolution of different components of genital morphology are shaped independently by distinct forms of sexual selection. Our quantitative results provide direct comparative support for the hypothesis that sexual selection is associated with morphological complexity in genitalic traits and highlight the importance of quantifying morphological shape and complexity, rather than size in studies of genital evolution. © 2011 The Author(s). Evolution © 2011 The Society for the Study of Evolution.

Stochastic simulation and analysis of biomolecular reaction networks

PubMed Central

Frazier, John M; Chushak, Yaroslav; Foy, Brent

2009-01-01

Background In recent years, several stochastic simulation algorithms have been developed to generate Monte Carlo trajectories that describe the time evolution of the behavior of biomolecular reaction networks. However, the effects of various stochastic simulation and data analysis conditions on the observed dynamics of complex biomolecular reaction networks have not recieved much attention. In order to investigate these issues, we employed a a software package developed in out group, called Biomolecular Network Simulator (BNS), to simulate and analyze the behavior of such systems. The behavior of a hypothetical two gene in vitro transcription-translation reaction network is investigated using the Gillespie exact stochastic algorithm to illustrate some of the factors that influence the analysis and interpretation of these data. Results Specific issues affecting the analysis and interpretation of simulation data are investigated, including: (1) the effect of time interval on data presentation and time-weighted averaging of molecule numbers, (2) effect of time averaging interval on reaction rate analysis, (3) effect of number of simulations on precision of model predictions, and (4) implications of stochastic simulations on optimization procedures. Conclusion The two main factors affecting the analysis of stochastic simulations are: (1) the selection of time intervals to compute or average state variables and (2) the number of simulations generated to evaluate the system behavior. PMID:19534796

Stochastic evolutionary voluntary public goods game with punishment in a Quasi-birth-and-death process.

PubMed

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2017-11-23

Traditional replication dynamic model and the corresponding concept of evolutionary stable strategy (ESS) only takes into account whether the system can return to the equilibrium after being subjected to a small disturbance. In the real world, due to continuous noise, the ESS of the system may not be stochastically stable. In this paper, a model of voluntary public goods game with punishment is studied in a stochastic situation. Unlike the existing model, we describe the evolutionary process of strategies in the population as a generalized quasi-birth-and-death process. And we investigate the stochastic stable equilibrium (SSE) instead. By numerical experiments, we get all possible SSEs of the system for any combination of parameters, and investigate the influence of parameters on the probabilities of the system to select different equilibriums. It is found that in the stochastic situation, the introduction of the punishment and non-participation strategies can change the evolutionary dynamics of the system and equilibrium of the game. There is a large range of parameters that the system selects the cooperative states as its SSE with a high probability. This result provides us an insight and control method for the evolution of cooperation in the public goods game in stochastic situations.

Modelling the evolution and diversity of cumulative culture

PubMed Central

Enquist, Magnus; Ghirlanda, Stefano; Eriksson, Kimmo

2011-01-01

Previous work on mathematical models of cultural evolution has mainly focused on the diffusion of simple cultural elements. However, a characteristic feature of human cultural evolution is the seemingly limitless appearance of new and increasingly complex cultural elements. Here, we develop a general modelling framework to study such cumulative processes, in which we assume that the appearance and disappearance of cultural elements are stochastic events that depend on the current state of culture. Five scenarios are explored: evolution of independent cultural elements, stepwise modification of elements, differentiation or combination of elements and systems of cultural elements. As one application of our framework, we study the evolution of cultural diversity (in time as well as between groups). PMID:21199845

Evolution of Skull and Mandible Shape in Cats (Carnivora: Felidae)

PubMed Central

Christiansen, Per

2008-01-01

The felid family consists of two major subgroups, the sabretoothed and the feline cats, to which all extant species belong, and are the most anatomically derived of all carnivores for predation on large prey with a precision killing bite. There has been much controversy and uncertainty about why the skulls and mandibles of sabretoothed and feline cats evolved to become so anatomically divergent, but previous models have focused on single characters and no unifying hypothesis of evolutionary shape changes has been formulated. Here I show that the shape of the skull and mandible in derived sabrecats occupy entirely different positions within overall morphospace from feline cats, and that the evolution of skull and mandible shape has followed very different paths in the two subgroups. When normalised for body-size differences, evolution of bite forces differ markedly in the two groups, and are much lower in derived sabrecats, and they show a significant relationship with size and cranial shape, whereas no such relationship is present in feline cats. Evolution of skull and mandible shape in modern cats has been governed by the need for uniform powerful biting irrespective of body size, whereas in sabrecats, shape evolution was governed by selective pressures for efficient predation with hypertrophied upper canines at high gape angles, and bite forces were secondary and became progressively weaker during sabrecat evolution. The current study emphasises combinations of new techniques for morphological shape analysis and biomechanical studies to formulate evolutionary hypotheses for difficult groups. PMID:18665225

First-passage dynamics of linear stochastic interface models: weak-noise theory and influence of boundary conditions

NASA Astrophysics Data System (ADS)

Gross, Markus

2018-03-01

We consider a one-dimensional fluctuating interfacial profile governed by the Edwards–Wilkinson or the stochastic Mullins-Herring equation for periodic, standard Dirichlet and Dirichlet no-flux boundary conditions. The minimum action path of an interfacial fluctuation conditioned to reach a given maximum height M at a finite (first-passage) time T is calculated within the weak-noise approximation. Dynamic and static scaling functions for the profile shape are obtained in the transient and the equilibrium regime, i.e. for first-passage times T smaller or larger than the characteristic relaxation time, respectively. In both regimes, the profile approaches the maximum height M with a universal algebraic time dependence characterized solely by the dynamic exponent of the model. It is shown that, in the equilibrium regime, the spatial shape of the profile depends sensitively on boundary conditions and conservation laws, but it is essentially independent of them in the transient regime.

Stochastic Averaging Principle for Spatial Birth-and-Death Evolutions in the Continuum

NASA Astrophysics Data System (ADS)

Friesen, Martin; Kondratiev, Yuri

2018-06-01

We study a spatial birth-and-death process on the phase space of locally finite configurations Γ^+ × Γ^- over R}^d. Dynamics is described by an non-equilibrium evolution of states obtained from the Fokker-Planck equation and associated with the Markov operator L^+(γ ^-) + 1/ɛ L^-, ɛ > 0. Here L^- describes the environment process on Γ^- and L^+(γ ^-) describes the system process on Γ^+, where γ ^- indicates that the corresponding birth-and-death rates depend on another locally finite configuration γ ^- \\in Γ^-. We prove that, for a certain class of birth-and-death rates, the corresponding Fokker-Planck equation is well-posed, i.e. there exists a unique evolution of states μ _t^{ɛ } on Γ^+ × Γ^-. Moreover, we give a sufficient condition such that the environment is ergodic with exponential rate. Let μ _{inv} be the invariant measure for the environment process on Γ^-. In the main part of this work we establish the stochastic averaging principle, i.e. we prove that the marginal of μ _t^{ɛ } onto Γ^+ converges weakly to an evolution of states on {Γ}^+ associated with the averaged Markov birth-and-death operator {\\overline{L}} = \\int _{Γ}^- L^+(γ ^-)d μ _{inv}(γ ^-).

Stochastic Averaging Principle for Spatial Birth-and-Death Evolutions in the Continuum

NASA Astrophysics Data System (ADS)

Friesen, Martin; Kondratiev, Yuri

2018-04-01

We study a spatial birth-and-death process on the phase space of locally finite configurations Γ^+ × Γ^- over R^d . Dynamics is described by an non-equilibrium evolution of states obtained from the Fokker-Planck equation and associated with the Markov operator L^+(γ ^-) + 1/ɛ L^- , ɛ > 0 . Here L^- describes the environment process on Γ^- and L^+(γ ^-) describes the system process on Γ^+ , where γ ^- indicates that the corresponding birth-and-death rates depend on another locally finite configuration γ ^- \\in Γ^- . We prove that, for a certain class of birth-and-death rates, the corresponding Fokker-Planck equation is well-posed, i.e. there exists a unique evolution of states μ _t^{ɛ } on Γ^+ × Γ^- . Moreover, we give a sufficient condition such that the environment is ergodic with exponential rate. Let μ _{inv} be the invariant measure for the environment process on Γ^- . In the main part of this work we establish the stochastic averaging principle, i.e. we prove that the marginal of μ _t^{ɛ } onto Γ^+ converges weakly to an evolution of states on Γ^+ associated with the averaged Markov birth-and-death operator \\overline{L} = \\int _{Γ}^-}L^+(γ ^-)d μ _{inv}(γ ^-).

Concepts in solid tumor evolution.

PubMed

Sidow, Arend; Spies, Noah

2015-04-01

Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neutral evolution in a biological population as diffusion in phenotype space: reproduction with local mutation but without selection.

PubMed

Lawson, Daniel John; Jensen, Henrik Jeldtoft

2007-03-02

The process of "evolutionary diffusion," i.e., reproduction with local mutation but without selection in a biological population, resembles standard diffusion in many ways. However, evolutionary diffusion allows the formation of localized peaks that undergo drift, even in the infinite population limit. We relate a microscopic evolution model to a stochastic model which we solve fully. This allows us to understand the large population limit, relates evolution to diffusion, and shows that independent local mutations act as a diffusion of interacting particles taking larger steps.

Simulation of Heterogeneous Atom Probe Tip Shapes Evolution during Field Evaporation Using a Level Set Method and Different Evaporation Models

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

Xu, Zhijie; Li, Dongsheng; Xu, Wei

2015-04-01

In atom probe tomography (APT), accurate reconstruction of the spatial positions of field evaporated ions from measured detector patterns depends upon a correct understanding of the dynamic tip shape evolution and evaporation laws of component atoms. Artifacts in APT reconstructions of heterogeneous materials can be attributed to the assumption of homogeneous evaporation of all the elements in the material in addition to the assumption of a steady state hemispherical dynamic tip shape evolution. A level set method based specimen shape evolution model is developed in this study to simulate the evaporation of synthetic layered-structured APT tips. The simulation results ofmore » the shape evolution by the level set model qualitatively agree with the finite element method and the literature data using the finite difference method. The asymmetric evolving shape predicted by the level set model demonstrates the complex evaporation behavior of heterogeneous tip and the interface curvature can potentially lead to the artifacts in the APT reconstruction of such materials. Compared with other APT simulation methods, the new method provides smoother interface representation with the aid of the intrinsic sub-grid accuracy. Two evaporation models (linear and exponential evaporation laws) are implemented in the level set simulations and the effect of evaporation laws on the tip shape evolution is also presented.« less

Thermal and Driven Stochastic Growth of Langmuir Waves in the Solar Wind and Earth's Foreshock

NASA Technical Reports Server (NTRS)

Cairns, Iver H.; Robinson, P. A.; Anderson, R. R.

2000-01-01

Statistical distributions of Langmuir wave fields in the solar wind and the edge of Earth's foreshock are analyzed and compared with predictions for stochastic growth theory (SGT). SGT quantitatively explains the solar wind, edge, and deep foreshock data as pure thermal waves, driven thermal waves subject to net linear growth and stochastic effects, and as waves in a pure SGT state, respectively, plus radiation near the plasma frequency f(sub p). These changes are interpreted in terms of spatial variations in the beam instability's growth rate and evolution toward a pure SGT state. SGT analyses of field distributions are shown to provide a viable alternative to thermal noise spectroscopy for wave instruments with coarse frequency resolution, and to separate f(sub p) radiation from Langmuir waves.

Autoionizing states driven by stochastic electromagnetic fields

NASA Astrophysics Data System (ADS)

Mouloudakis, G.; Lambropoulos, P.

2018-01-01

We have examined the profile of an isolated autoionizing resonance driven by a pulse of short duration and moderately strong field. The analysis has been based on stochastic differential equations governing the time evolution of the density matrix under a stochastic field. Having focused our quantitative analysis on the 2{{s}}2{{p}}({}1{{P}}) resonance of helium, we have investigated the role of field fluctuations and of the duration of the pulse. We report surprisingly strong distortion of the profile, even for peak intensity below the strong field limit. Our results demonstrate the intricate connection between intensity and pulse duration, with the latter appearing to be the determining influence, even for a seemingly short pulse of 50 fs. Further effects that would arise under much shorter pulses are discussed.

How a small noise generates large-amplitude oscillations of volcanic plug and provides high seismicity

NASA Astrophysics Data System (ADS)

Alexandrov, Dmitri V.; Bashkirtseva, Irina A.; Ryashko, Lev B.

2015-04-01

A non-linear behavior of dynamic model of the magma-plug system under the action of N-shaped friction force and stochastic disturbances is studied. It is shown that the deterministic dynamics essentially depends on the mutual arrangement of an equilibrium point and the friction force branches. Variations of this arrangement imply bifurcations, birth and disappearance of stable limit cycles, changes of the stability of equilibria, system transformations between mono- and bistable regimes. A slope of the right increasing branch of the friction function is responsible for the formation of such regimes. In a bistable zone, the noise generates transitions between small and large amplitude stochastic oscillations. In a monostable zone with single stable equilibrium, a new dynamic phenomenon of noise-induced generation of large amplitude stochastic oscillations in the plug rate and pressure is revealed. A beat-type dynamics of the plug displacement under the influence of stochastic forcing is studied as well.

Higher-order stochastic differential equations and the positive Wigner function

NASA Astrophysics Data System (ADS)

Drummond, P. D.

2017-12-01

General higher-order stochastic processes that correspond to any diffusion-type tensor of higher than second order are obtained. The relationship of multivariate higher-order stochastic differential equations with tensor decomposition theory and tensor rank is explained. Techniques for generating the requisite complex higher-order noise are proved to exist either using polar coordinates and γ distributions, or from products of Gaussian variates. This method is shown to allow the calculation of the dynamics of the Wigner function, after it is extended to a complex phase space. The results are illustrated physically through dynamical calculations of the positive Wigner distribution for three-mode parametric downconversion, widely used in quantum optics. The approach eliminates paradoxes arising from truncation of the higher derivative terms in Wigner function time evolution. Anomalous results of negative populations and vacuum scattering found in truncated Wigner quantum simulations in quantum optics and Bose-Einstein condensate dynamics are shown not to occur with this type of stochastic theory.

Extinction in neutrally stable stochastic Lotka-Volterra models

NASA Astrophysics Data System (ADS)

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.

Extinction in neutrally stable stochastic Lotka-Volterra models.

PubMed

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.

Shape Evolution of Detached Bridgman Crystals Grown in Microgravity

NASA Technical Reports Server (NTRS)

Volz, M. P.; Mazuruk, K.

2015-01-01

A theory describing the shape evolution of detached Bridgman crystals in microgravity has been developed. A starting crystal of initial radius r0 will evolve to one of the following states: Stable detached gap; Attachment to the crucible wall; Meniscus collapse. Only crystals where alpha plus omega is great than 180 degrees will achieve stable detached growth in microgravity. Results of the crystal shape evolution theory are consistent with predictions of the dynamic stability of crystallization (Tatarchenko, Shaped Crystal Growth, Kluwer, 1993). Tests of transient crystal evolution are planned for ICESAGE, a series of Ge and GeSi crystal growth experiments planned to be conducted on the International Space Station (ISS).

Shaping asteroid models using genetic evolution (SAGE)

NASA Astrophysics Data System (ADS)

Bartczak, P.; Dudziński, G.

2018-02-01

In this work, we present SAGE (shaping asteroid models using genetic evolution), an asteroid modelling algorithm based solely on photometric lightcurve data. It produces non-convex shapes, orientations of the rotation axes and rotational periods of asteroids. The main concept behind a genetic evolution algorithm is to produce random populations of shapes and spin-axis orientations by mutating a seed shape and iterating the process until it converges to a stable global minimum. We tested SAGE on five artificial shapes. We also modelled asteroids 433 Eros and 9 Metis, since ground truth observations for them exist, allowing us to validate the models. We compared the derived shape of Eros with the NEAR Shoemaker model and that of Metis with adaptive optics and stellar occultation observations since other models from various inversion methods were available for Metis.

Recent topographic evolution and erosion of the deglaciated Washington Cascades inferred from a stochastic landscape evolution model

NASA Astrophysics Data System (ADS)

Moon, S.; Shelef, E.; Hilley, G. E.

2013-12-01

The Washington Cascades is currently in topographic and erosional disequilibrium after deglaciation occurred around 11- 17 ka ago. The topography still shows the features inherited from prior alpine glacial processes (e.g., cirques, steep side-valleys, and flat valley bottoms), though postglacial processes are currently denuding this landscape. Our previous study in this area calculated the thousand-year-timescale denudation rates using cosmogenic 10Be concentration (CRN-denudation rates), and showed that they were ~ four times higher than million-year-timescale uplift rates. In addition, the spatial distribution of denudation rates showed a good correlation with a factor-of-ten variation in precipitation. We interpreted this correlation as reflecting the sensitivity of landslide triggering in over-steepened deglaciated topography to precipitation, which produced high denudation rates in wet areas that experienced frequent landsliding. We explored this interpretation using a model of postglacial surface processes that predicts the evolution of the topography and denudation rates within the deglaciated Washington Cascades. Specifically, we used the model to understand the controls on and timescales of landscape response to changes in the surface process regime after deglaciation. The postglacial adjustment of this landscape is modeled using a geomorphic-transport-law-based numerical model that includes processes of river incision, hillslope diffusion, and stochastic landslides. The surface lowering due to landslides is parameterized using a physically-based slope stability model coupled to a stochastic model of the generation of landslides. The model parameters of river incision and stochastic landslides are calibrated based on the rates and distribution of thousand-year-timescale denudation rates measured from cosmogenic 10Be isotopes. The probability distribution of model parameters required to fit the observed denudation rates shows comparable ranges from previous studies in similar rock types and climatic conditions. The calibrated parameters suggest that the dominant sediment source of river sediments originates from stochastic landslides. The magnitude of landslide denudation rates is determined by failure density (similar to landslide frequency), while their spatial distribution is largely controlled by precipitation and slope angles. Simulation results show that denudation rates decay over time and take approximately 130-180 ka to reach steady-state rates. This response timescale is longer than glacial/interglacial cycles, suggesting that frequent climatic perturbations during the Quaternary may prevent these types of landscapes from reaching a dynamic equilibrium with postglacial processes.

Influence of particle shape on the microstructure evolution and the mechanical properties of granular materials

NASA Astrophysics Data System (ADS)

Tian, Jianqiu; Liu, Enlong; Jiang, Lian; Jiang, Xiaoqiong; Sun, Yi; Xu, Ran

2018-06-01

In order to study the influence of particle shape on the microstructure evolution and the mechanical properties of granular materials, a two-dimensional DEM analysis of samples with three particle shapes, including circular particles, triangular particles, and elongated particles, is proposed here to simulate the direct shear tests of coarse-grained soils. For the numerical test results, analyses are conducted in terms of particle rotations, fabric evolution, and average path length evolution. A modified Rowe's stress-dilatancy equation is also proposed and successfully fitted onto simulation data.

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Why Buckling Stellar Bars Weaken in Disk Galaxies

NASA Astrophysics Data System (ADS)

Martinez-Valpuesta, Inma; Shlosman, Isaac

2004-09-01

Young stellar bars in disk galaxies experience a vertical buckling instability that terminates their growth and thickens them, resulting in a characteristic peanut/boxy shape when viewed edge-on. Using N-body simulations of galactic disks embedded in live halos, we have analyzed the bar structure throughout this instability and found that the outer (approximately) third of the bar dissolves completely while the inner part (within the vertical inner Lindblad resonance) becomes less oval. The bar acquires the frequently observed peanut/boxy-shaped isophotes. We also find that the bar buckling is responsible for a mass injection above the plane, which is subsequently trapped by specific three-dimensional families of periodic orbits of particular shapes explaining the observed isophotes, in line with previous work. Using a three-dimensional orbit analysis and surfaces of sections, we infer that the outer part of the bar is dissolved by a rapidly widening stochastic region around its corotation radius-a process related to the bar growth. This leads to a dramatic decrease in the bar size, decrease in the overall bar strength, and a mild increase in its pattern speed but is not expected to lead to a complete bar dissolution. The buckling instability appears primarily responsible for shortening the secular diffusion timescale to a dynamical one when building the boxy isophotes. The sufficiently long timescale of the described evolution, ~1 Gyr, can affect the observed bar fraction in the local universe and at higher redshifts, both through reduced bar strength and the absence of dust offset lanes in the bar.

Constraining Stochastic Parametrisation Schemes Using High-Resolution Model Simulations

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Dawson, A.; Palmer, T.

2017-12-01

Stochastic parametrisations are used in weather and climate models as a physically motivated way to represent model error due to unresolved processes. Designing new stochastic schemes has been the target of much innovative research over the last decade. While a focus has been on developing physically motivated approaches, many successful stochastic parametrisation schemes are very simple, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) multiplicative scheme `Stochastically Perturbed Parametrisation Tendencies' (SPPT). The SPPT scheme improves the skill of probabilistic weather and seasonal forecasts, and so is widely used. However, little work has focused on assessing the physical basis of the SPPT scheme. We address this matter by using high-resolution model simulations to explicitly measure the `error' in the parametrised tendency that SPPT seeks to represent. The high resolution simulations are first coarse-grained to the desired forecast model resolution before they are used to produce initial conditions and forcing data needed to drive the ECMWF Single Column Model (SCM). By comparing SCM forecast tendencies with the evolution of the high resolution model, we can measure the `error' in the forecast tendencies. In this way, we provide justification for the multiplicative nature of SPPT, and for the temporal and spatial scales of the stochastic perturbations. However, we also identify issues with the SPPT scheme. It is therefore hoped these measurements will improve both holistic and process based approaches to stochastic parametrisation. Figure caption: Instantaneous snapshot of the optimal SPPT stochastic perturbation, derived by comparing high-resolution simulations with a low resolution forecast model.

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

Krasnobaeva, L. A., E-mail: kla1983@mail.ru; Siberian State Medical University Moscowski Trakt 2, Tomsk, 634050; Shapovalov, A. V.

Within the formalism of the Fokker–Planck equation, the influence of nonstationary external force, random force, and dissipation effects on dynamics local conformational perturbations (kink) propagating along the DNA molecule is investigated. Such waves have an important role in the regulation of important biological processes in living systems at the molecular level. As a dynamic model of DNA was used a modified sine-Gordon equation, simulating the rotational oscillations of bases in one of the chains DNA. The equation of evolution of the kink momentum is obtained in the form of the stochastic differential equation in the Stratonovich sense within the frameworkmore » of the well-known McLaughlin and Scott energy approach. The corresponding Fokker–Planck equation for the momentum distribution function coincides with the equation describing the Ornstein–Uhlenbek process with a regular nonstationary external force. The influence of the nonlinear stochastic effects on the kink dynamics is considered with the help of the Fokker– Planck nonlinear equation with the shift coefficient dependent on the first moment of the kink momentum distribution function. Expressions are derived for average value and variance of the momentum. Examples are considered which demonstrate the influence of the external regular and random forces on the evolution of the average value and variance of the kink momentum. Within the formalism of the Fokker–Planck equation, the influence of nonstationary external force, random force, and dissipation effects on the kink dynamics is investigated in the sine–Gordon model. The equation of evolution of the kink momentum is obtained in the form of the stochastic differential equation in the Stratonovich sense within the framework of the well-known McLaughlin and Scott energy approach. The corresponding Fokker–Planck equation for the momentum distribution function coincides with the equation describing the Ornstein–Uhlenbek process with a regular nonstationary external force. The influence of the nonlinear stochastic effects on the kink dynamics is considered with the help of the Fokker–Planck nonlinear equation with the shift coefficient dependent on the first moment of the kink momentum distribution function. Expressions are derived for average value and variance of the momentum. Examples are considered which demonstrate the influence of the external regular and random forces on the evolution of the average value and variance of the kink momentum.« less

Discrete stochastic simulation methods for chemically reacting systems.

PubMed

Cao, Yang; Samuels, David C

2009-01-01

Discrete stochastic chemical kinetics describe the time evolution of a chemically reacting system by taking into account the fact that, in reality, chemical species are present with integer populations and exhibit some degree of randomness in their dynamical behavior. In recent years, with the development of new techniques to study biochemistry dynamics in a single cell, there are increasing studies using this approach to chemical kinetics in cellular systems, where the small copy number of some reactant species in the cell may lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. This chapter reviews the fundamental theory related to stochastic chemical kinetics and several simulation methods based on that theory. We focus on nonstiff biochemical systems and the two most important discrete stochastic simulation methods: Gillespie's stochastic simulation algorithm (SSA) and the tau-leaping method. Different implementation strategies of these two methods are discussed. Then we recommend a relatively simple and efficient strategy that combines the strengths of the two methods: the hybrid SSA/tau-leaping method. The implementation details of the hybrid strategy are given here and a related software package is introduced. Finally, the hybrid method is applied to simple biochemical systems as a demonstration of its application.

Diffusion Processes Satisfying a Conservation Law Constraint

DOE PAGES

Bakosi, J.; Ristorcelli, J. R.

2014-03-04

We investigate coupled stochastic differential equations governing N non-negative continuous random variables that satisfy a conservation principle. In various fields a conservation law requires that a set of fluctuating variables be non-negative and (if appropriately normalized) sum to one. As a result, any stochastic differential equation model to be realizable must not produce events outside of the allowed sample space. We develop a set of constraints on the drift and diffusion terms of such stochastic models to ensure that both the non-negativity and the unit-sum conservation law constraint are satisfied as the variables evolve in time. We investigate the consequencesmore » of the developed constraints on the Fokker-Planck equation, the associated system of stochastic differential equations, and the evolution equations of the first four moments of the probability density function. We show that random variables, satisfying a conservation law constraint, represented by stochastic diffusion processes, must have diffusion terms that are coupled and nonlinear. The set of constraints developed enables the development of statistical representations of fluctuating variables satisfying a conservation law. We exemplify the results with the bivariate beta process and the multivariate Wright-Fisher, Dirichlet, and Lochner’s generalized Dirichlet processes.« less

Diffusion Processes Satisfying a Conservation Law Constraint

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

Bakosi, J.; Ristorcelli, J. R.

We investigate coupled stochastic differential equations governing N non-negative continuous random variables that satisfy a conservation principle. In various fields a conservation law requires that a set of fluctuating variables be non-negative and (if appropriately normalized) sum to one. As a result, any stochastic differential equation model to be realizable must not produce events outside of the allowed sample space. We develop a set of constraints on the drift and diffusion terms of such stochastic models to ensure that both the non-negativity and the unit-sum conservation law constraint are satisfied as the variables evolve in time. We investigate the consequencesmore » of the developed constraints on the Fokker-Planck equation, the associated system of stochastic differential equations, and the evolution equations of the first four moments of the probability density function. We show that random variables, satisfying a conservation law constraint, represented by stochastic diffusion processes, must have diffusion terms that are coupled and nonlinear. The set of constraints developed enables the development of statistical representations of fluctuating variables satisfying a conservation law. We exemplify the results with the bivariate beta process and the multivariate Wright-Fisher, Dirichlet, and Lochner’s generalized Dirichlet processes.« less

Ten reasons why a thermalized system cannot be described by a many-particle wave function

NASA Astrophysics Data System (ADS)

Drossel, Barbara

2017-05-01

It is widely believed that the underlying reality behind statistical mechanics is a deterministic and unitary time evolution of a many-particle wave function, even though this is in conflict with the irreversible, stochastic nature of statistical mechanics. The usual attempts to resolve this conflict for instance by appealing to decoherence or eigenstate thermalization are riddled with problems. This paper considers theoretical physics of thermalized systems as it is done in practice and shows that all approaches to thermalized systems presuppose in some form limits to linear superposition and deterministic time evolution. These considerations include, among others, the classical limit, extensivity, the concepts of entropy and equilibrium, and symmetry breaking in phase transitions and quantum measurement. As a conclusion, the paper suggests that the irreversibility and stochasticity of statistical mechanics should be taken as a real property of nature. It follows that a gas of a macroscopic number N of atoms in thermal equilibrium is best represented by a collection of N wave packets of a size of the order of the thermal de Broglie wave length, which behave quantum mechanically below this scale but classically sufficiently far beyond this scale. In particular, these wave packets must localize again after scattering events, which requires stochasticity and indicates a connection to the measurement process.

Morpho morphometrics: Shared ancestry and selection drive the evolution of wing size and shape in Morpho butterflies.

PubMed

Chazot, Nicolas; Panara, Stephen; Zilbermann, Nicolas; Blandin, Patrick; Le Poul, Yann; Cornette, Raphaël; Elias, Marianne; Debat, Vincent

2016-01-01

Butterfly wings harbor highly diverse phenotypes and are involved in many functions. Wing size and shape result from interactions between adaptive processes, phylogenetic history, and developmental constraints, which are complex to disentangle. Here, we focus on the genus Morpho (Nymphalidae: Satyrinae, 30 species), which presents a high diversity of sizes, shapes, and color patterns. First, we generate a comprehensive molecular phylogeny of these 30 species. Next, using 911 collection specimens, we quantify the variation of wing size and shape across species, to assess the importance of shared ancestry, microhabitat use, and sexual selection in the evolution of the wings. While accounting for phylogenetic and allometric effects, we detect a significant difference in wing shape but not size among microhabitats. Fore and hindwings covary at the individual and species levels, and the covariation differs among microhabitats. However, the microhabitat structure in covariation disappears when phylogenetic relationships are taken into account. Our results demonstrate that microhabitat has driven wing shape evolution, although it has not strongly affected forewing and hindwing integration. We also found that sexual dimorphism of forewing shape and color pattern are coupled, suggesting a common selective force. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

The role of pollinator diversity in the evolution of corolla-shape integration in a pollination-generalist plant clade.

PubMed

Gómez, José María; Perfectti, Francisco; Klingenberg, Christian Peter

2014-08-19

Flowers of animal-pollinated plants are integrated structures shaped by the action of pollinator-mediated selection. It is widely assumed that pollination specialization increases the magnitude of floral integration. However, empirical evidence is still inconclusive. In this study, we explored the role of pollinator diversity in shaping the evolution of corolla-shape integration in Erysimum, a plant genus with generalized pollination systems. We quantified floral integration in Erysimum using geometric morphometrics and explored its evolution using phylogenetic comparative methods. Corolla-shape integration was low but significantly different from zero in all study species. Spatial autocorrelation and phylogenetic signal in corolla-shape integration were not detected. In addition, integration in Erysimum seems to have evolved in a way that is consistent with Brownian motion, but with frequent convergent evolution. Corolla-shape integration was negatively associated with the number of pollinators visiting the flowers of each Erysimum species. That is, it was lower in those species having a more generalized pollination system. This negative association may occur because the co-occurrence of many pollinators imposes conflicting selection and cancels out any consistent selection on specific floral traits, preventing the evolution of highly integrated flowers. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Simulating biological processes: stochastic physics from whole cells to colonies.

PubMed

Earnest, Tyler M; Cole, John A; Luthey-Schulten, Zaida

2018-05-01

The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a 'minimal cell'. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.

Simulating biological processes: stochastic physics from whole cells to colonies

NASA Astrophysics Data System (ADS)

Earnest, Tyler M.; Cole, John A.; Luthey-Schulten, Zaida

2018-05-01

The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a ‘minimal cell’. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.

Shape coexistence, shape evolution and Gamow-Teller {beta}-decay of neutron-rich A Asymptotically-Equal-To 100 nuclei

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

Petrovici, A.; Schmid, K. W.; Faessler, A.

The structure of neutron-rich nuclei in the A Asymptotically-Equal-To 100 mass region relevant for the astrophysical r process manifests drastic changes in some isotopic chains and often sudden variations of particular nuclear properties have been identified. For a realistic description of the evolution in structure with increasing energy, spin, and isospin determined by shape coexistence and mixing beyond-mean-field approaches are required. Our recent studies represent an attempt to the self-consistent description of the shape coexistence phenomena in neutron-rich A Asymptotically-Equal-To 100 nuclei within the complex Excited Vampir variational model with symmetry projection before variation using a realistic effective interaction basedmore » on the Bonn A potential in a large model space. Results concerning the triple shape coexistence and the shape evolution in the N=58 Sr and Zr isotopes, the shape evolution in a chain of Zr nuclei, as well as the Gamow-Teller {beta}-decay properties of neutron-rich Zr and Tc nuclei are presented.« less

The role of beginner’s luck in learning to prefer risky patches by socially foraging house sparrows

PubMed Central

2013-01-01

Although there has been extensive research on the evolution of individual decision making under risk (when facing variable outcomes), little is known on how the evolution of such decision-making mechanisms has been shaped by social learning and exploitation. We presented socially foraging house sparrows with a choice between scattered feeding wells in which millet seeds were hidden under 2 types of colored sand: green sand offering ~80 seeds with a probability of 0.1 (high risk–high reward) and yellow sand offering 1 seed with certainty (low risk–low reward). Although the expected benefit of choosing variable wells was 8 times higher than that of choosing constant wells, only some sparrows developed a preference for variable wells, whereas others developed a significant preference for constant wells. We found that this dichotomy could be explained by stochastic individual differences in sampling success during foraging, rather than by social foraging strategies (active searching vs. joining others). Moreover, preference for variable or constant wells was related to the sparrows’ success during searching, rather than during joining others or when picking exposed seeds (i.e., they learn when actively searching in the sand). Finally, although for many sparrows learning resulted in an apparently maladaptive risk aversion, group living still allowed them to enjoy profitable variable wells by occasionally joining variable-preferring sparrows. PMID:24137046

Gravitational Instabilities in a Young Protoplanetary Disk with Embedded Objects

NASA Astrophysics Data System (ADS)

Desai, Karna M.

Gravitational Instabilities (GIs), a mechanism for angular momentum transport, are prominent during the early phases of protoplanetary disk evolution when the disk is relatively massive. In this dissertation, I analyze GIs by inserting different objects in a disk by employing 3D hydrodynamics simulations. GIs in a circumbinary disks are studied to determine how the presence of the companion affects the nature and strength of GIs in the disk. The circumbinary disk achieves a state of sustained marginal instability similar to an identical disk without the companion. A realistic evolution of the binary is detected. Planet and disk interactions play an important role in the evolution of planetary systems. To study this interaction during the early phases of planet formation, a migration study of Jovian planets in a GI-active disk is conducted. I find the migration timescales to be longer in a GI-active disk, when compared to laminar disks. The 3 MJupiter planet controls its own orbital evolution, while the migration of a 0.3 MJupiter planet is stochastic in nature. I define a 'critical mass' as the mass of an arm of the dominant two-armed spiral density wave within the planet's Hill diameter. Planets above this mass control their own destiny, and planets below this mass are scattered by the disk. This critical mass could provide a recipe for predicting the migration behavior of planets in GI-active disks. To understand the stochastic migration of low-mass planets, I perform a simulation of 240 zero-mass planet-tracers by inserting these at a range of locations in the disk. A Diffusion Coefficient is calculated to characterize the stochastic migration of low-mass objects. The eccentricity dispersion for the sample is also studied. I find that the diffusion of planets can be a slow process, resulting in the survival of small planetary cores.

Discrete and Continuum Approximations for Collective Cell Migration in a Scratch Assay with Cell Size Dynamics.

PubMed

Matsiaka, Oleksii M; Penington, Catherine J; Baker, Ruth E; Simpson, Matthew J

2018-04-01

Scratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.

Turbulence modeling and combustion simulation in porous media under high Peclet number

NASA Astrophysics Data System (ADS)

Moiseev, Andrey A.; Savin, Andrey V.

2018-05-01

Turbulence modelling in porous flows and burning still remains not completely clear until now. Undoubtedly, conventional turbulence models must work well under high Peclet numbers when porous channels shape is implemented in details. Nevertheless, the true turbulent mixing takes place at micro-scales only, and the dispersion mixing works at macro-scales almost independent from true turbulence. The dispersion mechanism is characterized by the definite space scale (scale of the porous structure) and definite velocity scale (filtration velocity). The porous structure is stochastic one usually, and this circumstance allows applying the analogy between space-time-stochastic true turbulence and the dispersion flow which is stochastic in space only, when porous flow is simulated at the macro-scale level. Additionally, the mentioned analogy allows applying well-known turbulent combustion models in simulations of porous combustion under high Peclet numbers.

A framework for discrete stochastic simulation on 3D moving boundary domains

DOE PAGES

Drawert, Brian; Hellander, Stefan; Trogdon, Michael; ...

2016-11-14

We have developed a method for modeling spatial stochastic biochemical reactions in complex, three-dimensional, and time-dependent domains using the reaction-diffusion master equation formalism. In particular, we look to address the fully coupled problems that arise in systems biology where the shape and mechanical properties of a cell are determined by the state of the biochemistry and vice versa. To validate our method and characterize the error involved, we compare our results for a carefully constructed test problem to those of a microscale implementation. Finally, we demonstrate the effectiveness of our method by simulating a model of polarization and shmoo formationmore » during the mating of yeast. The method is generally applicable to problems in systems biology where biochemistry and mechanics are coupled, and spatial stochastic effects are critical.« less

Model reduction for slow–fast stochastic systems with metastable behaviour

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

Bruna, Maria, E-mail: bruna@maths.ox.ac.uk; Computational Science Laboratory, Microsoft Research, Cambridge CB1 2FB; Chapman, S. Jonathan

2014-05-07

The quasi-steady-state approximation (or stochastic averaging principle) is a useful tool in the study of multiscale stochastic systems, giving a practical method by which to reduce the number of degrees of freedom in a model. The method is extended here to slow–fast systems in which the fast variables exhibit metastable behaviour. The key parameter that determines the form of the reduced model is the ratio of the timescale for the switching of the fast variables between metastable states to the timescale for the evolution of the slow variables. The method is illustrated with two examples: one from biochemistry (a fast-species-mediatedmore » chemical switch coupled to a slower varying species), and one from ecology (a predator–prey system). Numerical simulations of each model reduction are compared with those of the full system.« less

A Functional Central Limit Theorem for the Becker-Döring Model

NASA Astrophysics Data System (ADS)

Sun, Wen

2018-04-01

We investigate the fluctuations of the stochastic Becker-Döring model of polymerization when the initial size of the system converges to infinity. A functional central limit problem is proved for the vector of the number of polymers of a given size. It is shown that the stochastic process associated to fluctuations is converging to the strong solution of an infinite dimensional stochastic differential equation (SDE) in a Hilbert space. We also prove that, at equilibrium, the solution of this SDE is a Gaussian process. The proofs are based on a specific representation of the evolution equations, the introduction of a convenient Hilbert space and several technical estimates to control the fluctuations, especially of the first coordinate which interacts with all components of the infinite dimensional vector representing the state of the process.

Stochastic ice stream dynamics

PubMed Central

Bertagni, Matteo Bernard; Ridolfi, Luca

2016-01-01

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution. PMID:27457960

Mesoscale Thermodynamically motivated Statistical Mechanics based Kinetic Model for Sintering monoliths

NASA Astrophysics Data System (ADS)

Mohan, Nisha

Modeling the evolution of microstructure during sintering is a persistent challenge in ceramics science, although needed as the microstructure impacts properties of an engineered material. Bridging the gap between microscopic and continuum models, kinetic Monte Carlo (kMC) methods provide a stochastic approach towards sintering and microstructure evolution. These kMC models work at the mesoscale, with length and time-scales between those of atomistic and continuum approaches. We develop a sintering/compacting model for the two-phase sintering of boron nitride ceramics and allotropes alike. Our formulation includes mechanisms for phase transformation between h-BN and c-BN and takes into account thermodynamics of pressure and temperature on interaction energies and mechanism rates. In addition to replicating the micro-structure evolution observed in experiments, it also captures the phase diagram of Boron Nitride materials. Results have been analyzed in terms of phase diagrams and crystal growth. It also serves with insights to guide the choice of additives and conditions for the sintering process.While detailed time and spatial resolutions are lost in any MC, the progression of stochastic events still captures plausible local energy minima and long-time temporal developments. DARPA.

A stochastic model for density-dependent microwave Snow- and Graupel scattering coefficients of the NOAA JCSDA community radiative transfer model

NASA Astrophysics Data System (ADS)

Stegmann, Patrick G.; Tang, Guanglin; Yang, Ping; Johnson, Benjamin T.

2018-05-01

A structural model is developed for the single-scattering properties of snow and graupel particles with a strongly heterogeneous morphology and an arbitrary variable mass density. This effort is aimed to provide a mechanism to consider particle mass density variation in the microwave scattering coefficients implemented in the Community Radiative Transfer Model (CRTM). The stochastic model applies a bicontinuous random medium algorithm to a simple base shape and uses the Finite-Difference-Time-Domain (FDTD) method to compute the single-scattering properties of the resulting complex morphology.

Prediction of nonlinear evolution character of energetic-particle-driven instabilities

DOE PAGES

Duarte, Vinicius N.; Berk, H. L.; Gorelenkov, N. N.; ...

2017-03-17

A general criterion is proposed and found to successfully predict the emergence of chirping oscillations of unstable Alfvénic eigenmodes in tokamak plasma experiments. The model includes realistic eigenfunction structure, detailed phase-space dependences of the instability drive, stochastic scattering and the Coulomb drag. The stochastic scattering combines the effects of collisional pitch angle scattering and micro-turbulence spatial diffusion. Furthermore, the latter mechanism is essential to accurately identify the transition between the fixed-frequency mode behavior and rapid chirping in tokamaks and to resolve the disparity with respect to chirping observation in spherical and conventional tokamaks.

Stochastic modelling of non-stationary financial assets

NASA Astrophysics Data System (ADS)

Estevens, Joana; Rocha, Paulo; Boto, João P.; Lind, Pedro G.

2017-11-01

We model non-stationary volume-price distributions with a log-normal distribution and collect the time series of its two parameters. The time series of the two parameters are shown to be stationary and Markov-like and consequently can be modelled with Langevin equations, which are derived directly from their series of values. Having the evolution equations of the log-normal parameters, we reconstruct the statistics of the first moments of volume-price distributions which fit well the empirical data. Finally, the proposed framework is general enough to study other non-stationary stochastic variables in other research fields, namely, biology, medicine, and geology.

Prediction of nonlinear evolution character of energetic-particle-driven instabilities

NASA Astrophysics Data System (ADS)

Duarte, V. N.; Berk, H. L.; Gorelenkov, N. N.; Heidbrink, W. W.; Kramer, G. J.; Nazikian, R.; Pace, D. C.; Podestà, M.; Tobias, B. J.; Van Zeeland, M. A.

2017-05-01

A general criterion is proposed and found to successfully predict the emergence of chirping oscillations of unstable Alfvénic eigenmodes in tokamak plasma experiments. The model includes realistic eigenfunction structure, detailed phase-space dependences of the instability drive, stochastic scattering and the Coulomb drag. The stochastic scattering combines the effects of collisional pitch angle scattering and micro-turbulence spatial diffusion. The latter mechanism is essential to accurately identify the transition between the fixed-frequency mode behavior and rapid chirping in tokamaks and to resolve the disparity with respect to chirping observation in spherical and conventional tokamaks.

Stochastic solution to quantum dynamics

NASA Technical Reports Server (NTRS)

John, Sarah; Wilson, John W.

1994-01-01

The quantum Liouville equation in the Wigner representation is solved numerically by using Monte Carlo methods. For incremental time steps, the propagation is implemented as a classical evolution in phase space modified by a quantum correction. The correction, which is a momentum jump function, is simulated in the quasi-classical approximation via a stochastic process. The technique, which is developed and validated in two- and three- dimensional momentum space, extends an earlier one-dimensional work. Also, by developing a new algorithm, the application to bound state motion in an anharmonic quartic potential shows better agreement with exact solutions in two-dimensional phase space.

Simulation of Stochastic Processes by Coupled ODE-PDE

NASA Technical Reports Server (NTRS)

Zak, Michail

2008-01-01

A document discusses the emergence of randomness in solutions of coupled, fully deterministic ODE-PDE (ordinary differential equations-partial differential equations) due to failure of the Lipschitz condition as a new phenomenon. It is possible to exploit the special properties of ordinary differential equations (represented by an arbitrarily chosen, dynamical system) coupled with the corresponding Liouville equations (used to describe the evolution of initial uncertainties in terms of joint probability distribution) in order to simulate stochastic processes with the proscribed probability distributions. The important advantage of the proposed approach is that the simulation does not require a random-number generator.

Stochastic analysis of concentration field in a wake region.

PubMed

Yassin, Mohamed F; Elmi, Abdirashid A

2011-02-01

Identifying geographic locations in urban areas from which air pollutants enter the atmosphere is one of the most important information needed to develop effective mitigation strategies for pollution control. Stochastic analysis is a powerful tool that can be used for estimating concentration fluctuation in plume dispersion in a wake region around buildings. Only few studies have been devoted to evaluate applications of stochastic analysis to pollutant dispersion in an urban area. This study was designed to investigate the concentration fields in the wake region using obstacle model such as an isolated building model. We measured concentration fluctuations at centerline of various downwind distances from the source, and different heights with the frequency of 1 KHz. Concentration fields were analyzed stochastically, using the probability density functions (pdf). Stochastic analysis was performed on the concentration fluctuation and the pdf of mean concentration, fluctuation intensity, and crosswind mean-plume dispersion. The pdf of the concentration fluctuation data have shown a significant non-Gaussian behavior. The lognormal distribution appeared to be the best fit to the shape of concentration measured in the boundary layer. We observed that the plume dispersion pdf near the source was shorter than the plume dispersion far from the source. Our findings suggest that the use of stochastic technique in complex building environment can be a powerful tool to help understand the distribution and location of air pollutants.

Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time.

PubMed

Dhar, Amrit; Minin, Vladimir N

2017-05-01

Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences.

Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time

PubMed Central

Dhar, Amrit

2017-01-01

Abstract Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences. PMID:28177780

Northern Hemisphere glaciation and the evolution of Plio-Pleistocene climate noise

NASA Astrophysics Data System (ADS)

Meyers, Stephen R.; Hinnov, Linda A.

2010-08-01

Deterministic orbital controls on climate variability are commonly inferred to dominate across timescales of 104-106 years, although some studies have suggested that stochastic processes may be of equal or greater importance. Here we explicitly quantify changes in deterministic orbital processes (forcing and/or pacing) versus stochastic climate processes during the Plio-Pleistocene, via time-frequency analysis of two prominent foraminifera oxygen isotopic stacks. Our results indicate that development of the Northern Hemisphere ice sheet is paralleled by an overall amplification of both deterministic and stochastic climate energy, but their relative dominance is variable. The progression from a more stochastic early Pliocene to a strongly deterministic late Pleistocene is primarily accommodated during two transitory phases of Northern Hemisphere ice sheet growth. This long-term trend is punctuated by “stochastic events,” which we interpret as evidence for abrupt reorganization of the climate system at the initiation and termination of the mid-Pleistocene transition and at the onset of Northern Hemisphere glaciation. In addition to highlighting a complex interplay between deterministic and stochastic climate change during the Plio-Pleistocene, our results support an early onset for Northern Hemisphere glaciation (between 3.5 and 3.7 Ma) and reveal some new characteristics of the orbital signal response, such as the puzzling emergence of 100 ka and 400 ka cyclic climate variability during theoretical eccentricity nodes.

Stochastic volatility models and Kelvin waves

NASA Astrophysics Data System (ADS)

Lipton, Alex; Sepp, Artur

2008-08-01

We use stochastic volatility models to describe the evolution of an asset price, its instantaneous volatility and its realized volatility. In particular, we concentrate on the Stein and Stein model (SSM) (1991) for the stochastic asset volatility and the Heston model (HM) (1993) for the stochastic asset variance. By construction, the volatility is not sign definite in SSM and is non-negative in HM. It is well known that both models produce closed-form expressions for the prices of vanilla option via the Lewis-Lipton formula. However, the numerical pricing of exotic options by means of the finite difference and Monte Carlo methods is much more complex for HM than for SSM. Until now, this complexity was considered to be an acceptable price to pay for ensuring that the asset volatility is non-negative. We argue that having negative stochastic volatility is a psychological rather than financial or mathematical problem, and advocate using SSM rather than HM in most applications. We extend SSM by adding volatility jumps and obtain a closed-form expression for the density of the asset price and its realized volatility. We also show that the current method of choice for solving pricing problems with stochastic volatility (via the affine ansatz for the Fourier-transformed density function) can be traced back to the Kelvin method designed in the 19th century for studying wave motion problems arising in fluid dynamics.

Neutral Evolution in a Biological Population as Diffusion in Phenotype Space: Reproduction with Local Mutation but without Selection

NASA Astrophysics Data System (ADS)

Lawson, Daniel John; Jensen, Henrik Jeldtoft

2007-03-01

The process of “evolutionary diffusion,” i.e., reproduction with local mutation but without selection in a biological population, resembles standard diffusion in many ways. However, evolutionary diffusion allows the formation of localized peaks that undergo drift, even in the infinite population limit. We relate a microscopic evolution model to a stochastic model which we solve fully. This allows us to understand the large population limit, relates evolution to diffusion, and shows that independent local mutations act as a diffusion of interacting particles taking larger steps.

The evolution of wealth transmission in human populations: a stochastic model

NASA Astrophysics Data System (ADS)

Augustins, G.; Etienne, L.; Ferdy, J.-B.; Ferrer, R.; Godelle, B.; Pitard, E.; Rousset, F.

2014-03-01

Reproductive success and survival are influenced by wealth in human populations. Wealth is transmitted to offsprings and strategies of transmission vary over time and among populations, the main variation being how equally wealth is transmitted to children. Here we propose a model where we simulate both the dynamics of wealth in a population and the evolution of a trait that determines how wealth is transmitted from parents to offspring, in a darwinian context.

JavaGenes Molecular Evolution

NASA Technical Reports Server (NTRS)

Lohn, Jason; Smith, David; Frank, Jeremy; Globus, Al; Crawford, James

2007-01-01

JavaGenes is a general-purpose, evolutionary software system written in Java. It implements several versions of a genetic algorithm, simulated annealing, stochastic hill climbing, and other search techniques. This software has been used to evolve molecules, atomic force field parameters, digital circuits, Earth Observing Satellite schedules, and antennas. This version differs from version 0.7.28 in that it includes the molecule evolution code and other improvements. Except for the antenna code, JaveGenes is available for NASA Open Source distribution.

Stochastic parameterization for light absorption by internally mixed BC/dust in snow grains for application to climate models

NASA Astrophysics Data System (ADS)

Liou, K. N.; Takano, Y.; He, C.; Yang, P.; Leung, L. R.; Gu, Y.; Lee, W. L.

2014-06-01

A stochastic approach has been developed to model the positions of BC (black carbon)/dust internally mixed with two snow grain types: hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine BC/dust single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), the action of internal mixing absorbs substantially more light than external mixing. The snow grain shape effect on absorption is relatively small, but its effect on asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions of BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2-5 µm) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 µm, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo substantially more than external mixing and that the snow grain shape plays a critical role in snow albedo calculations through its forward scattering strength. Also, multiple inclusion of BC/dust significantly reduces snow albedo as compared to an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization involving contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountain/snow topography.

Stochastic Parameterization for Light Absorption by Internally Mixed BC/dust in Snow Grains for Application to Climate Models

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

Liou, K. N.; Takano, Y.; He, Cenlin

2014-06-27

A stochastic approach to model the positions of BC/dust internally mixed with two snow-grain types has been developed, including hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine their single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), internal mixing absorbs more light than external mixing. The snow-grain shape effect on absorption is relatively small, but its effect on the asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions ofmore » BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2 – 5 um) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 um, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo more than external mixing and that the snow-grain shape plays a critical role in snow albedo calculations through the asymmetry factor. Also, snow albedo reduces more in the case of multiple inclusion of BC/dust compared to that of an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization containing contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountains/snow topography.« less

Rates of morphological evolution, asymmetry and morphological integration of shell shape in scallops.

PubMed

Sherratt, Emma; Serb, Jeanne M; Adams, Dean C

2017-12-08

Rates of morphological evolution vary across different taxonomic groups, and this has been proposed as one of the main drivers for the great diversity of organisms on Earth. Of the extrinsic factors pertaining to this variation, ecological hypotheses feature prominently in observed differences in phenotypic evolutionary rates across lineages. But complex organisms are inherently modular, comprising distinct body parts that can be differentially affected by external selective pressures. Thus, the evolution of trait covariation and integration in modular systems may also play a prominent role in shaping patterns of phenotypic diversity. Here we investigate the role ecological diversity plays in morphological integration, and the tempo of shell shape evolution and of directional asymmetry in bivalved scallops. Overall, the shape of both valves and the magnitude of asymmetry of the whole shell (difference in shape between valves) are traits that are evolving fast in ecomorphs under strong selective pressures (gliders, recessers and nestling), compared to low rates observed in other ecomorphs (byssal-attaching, free-living and cementing). Given that different parts of an organism can be under different selective pressures from the environment, we also examined the degree of evolutionary integration between the valves as it relates to ecological shifts. We find that evolutionary morphological integration is consistent and surprisingly high across species, indicating that while the left and right valves of a scallop shell are diversifying in accordance with ecomorphology, they are doing so in a concerted fashion. Our study on scallops adds another strong piece of evidence that ecological shifts play an important role in the tempo and mode of morphological evolution. Strong selective pressures from the environment, inferred from the repeated evolution of distinct ecomorphs, have influenced the rate of morphological evolution in valve shape and the magnitude of asymmetry between valves. Our observation that morphological integration of the valves making up the shell is consistently strong suggests tight developmental pathways are responsible for the concerted evolution of these structures while environmental pressures are driving whole shell shape. Finally, our study shows that directional asymmetry in shell shape among species is an important aspect of scallop macroevolution.

Evolution of opercle shape in cichlid fishes from Lake Tanganyika - adaptive trait interactions in extant and extinct species flocks.

PubMed

Wilson, Laura A B; Colombo, Marco; Sánchez-Villagra, Marcelo R; Salzburger, Walter

2015-11-20

Phenotype-environment correlations and the evolution of trait interactions in adaptive radiations have been widely studied to gain insight into the dynamics underpinning rapid species diversification. In this study we explore the phenotype-environment correlation and evolution of operculum shape in cichlid fishes using an outline-based geometric morphometric approach combined with stable isotope indicators of macrohabitat and trophic niche. We then apply our method to a sample of extinct saurichthyid fishes, a highly diverse and near globally distributed group of actinopterygians occurring throughout the Triassic, to assess the utility of extant data to inform our understanding of ecomorphological evolution in extinct species flocks. A series of comparative methods were used to analyze shape data for 54 extant species of cichlids (N = 416), and 6 extinct species of saurichthyids (N = 44). Results provide evidence for a relationship between operculum shape and feeding ecology, a concentration in shape evolution towards present along with evidence for convergence in form, and significant correlation between the major axes of shape change and measures of gut length and body elongation. The operculum is one of few features that can be compared in extant and extinct groups, enabling reconstruction of phenotype-environment interactions and modes of evolutionary diversification in deep time.

Anthropogenic fire drives the evolution of seed traits

PubMed Central

Gómez-González, Susana; Torres-Díaz, Cristian; Bustos-Schindler, Carlos; Gianoli, Ernesto

2011-01-01

Fire is a major disturbance affecting ecosystems worldwide. Phylogenetic studies have shown that the evolution of seed persistence (fire resistance) is associated with fire frequency or severity. However, the existence of specific seed traits resulting from natural selection mediated by fire remains a key question in plant evolution. We evaluated the role of fire in the evolution of seed traits from a microevolutionary perspective, using as a study system a native forb from the Chilean matorral, where fire is a novel, anthropogenic disturbance. We show that anthropogenic fires are shaping the evolution of seed traits such as pubescence and shape. Among-population variation in seed pubescence, shape, and pericarp thickness was strongly associated with fire frequency, and within a population, fire selected those plants with more pubescent seeds, thicker pericarps, and less rounded seeds. Seed pubescence and shape were shown to be heritable traits. Our findings provide insights into the understanding of the evolution of seed traits in fire-prone environments and demonstrate that human-made fires can be driving evolutionary changes in plant species from ecosystems where fires do not occur naturally. PMID:22065739

Anthropogenic fire drives the evolution of seed traits.

PubMed

Gómez-González, Susana; Torres-Díaz, Cristian; Bustos-Schindler, Carlos; Gianoli, Ernesto

2011-11-15

Fire is a major disturbance affecting ecosystems worldwide. Phylogenetic studies have shown that the evolution of seed persistence (fire resistance) is associated with fire frequency or severity. However, the existence of specific seed traits resulting from natural selection mediated by fire remains a key question in plant evolution. We evaluated the role of fire in the evolution of seed traits from a microevolutionary perspective, using as a study system a native forb from the Chilean matorral, where fire is a novel, anthropogenic disturbance. We show that anthropogenic fires are shaping the evolution of seed traits such as pubescence and shape. Among-population variation in seed pubescence, shape, and pericarp thickness was strongly associated with fire frequency, and within a population, fire selected those plants with more pubescent seeds, thicker pericarps, and less rounded seeds. Seed pubescence and shape were shown to be heritable traits. Our findings provide insights into the understanding of the evolution of seed traits in fire-prone environments and demonstrate that human-made fires can be driving evolutionary changes in plant species from ecosystems where fires do not occur naturally.

Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Afrough, M.; Agarwal, B.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allen, G.; Allocca, A.; Altin, P. A.; Amato, A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Angelova, S. V.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Atallah, D. V.; Aufmuth, P.; Aulbert, C.; AultONeal, K.; Austin, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Bae, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Banagiri, S.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barkett, K.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bawaj, M.; Bayley, J. C.; Bazzan, M.; Bécsy, B.; Beer, C.; Bejger, M.; Belahcene, I.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Bero, J. J.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bode, N.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonilla, E.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bossie, K.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Canepa, M.; Canizares, P.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Carney, M. F.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerdá-Durán, P.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chase, E.; Chassande-Mottin, E.; Chatterjee, D.; Cheeseboro, B. D.; Chen, H. Y.; Chen, X.; Chen, Y.; Cheng, H.-P.; Chia, H.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, A. K. W.; Chung, S.; Ciani, G.; Ciolfi, R.; Cirelli, C. E.; Cirone, A.; Clara, F.; Clark, J. A.; Clearwater, P.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Cohen, D.; Colla, A.; Collette, C. G.; Cominsky, L. R.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-Carrión, I.; Corley, K. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, E.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Canton, T. Dal; Dálya, G.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davis, D.; Daw, E. J.; Day, B.; De, S.; DeBra, D.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Demos, N.; Denker, T.; Dent, T.; De Pietri, R.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; De Rossi, C.; DeSalvo, R.; de Varona, O.; Devenson, J.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Dreissigacker, C.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dupej, P.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Estevez, D.; Etienne, Z. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fee, C.; Fehrmann, H.; Feicht, J.; Fejer, M. M.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Finstad, D.; Fiori, I.; Fiorucci, D.; Fishbach, M.; Fisher, R. P.; Fitz-Axen, M.; Flaminio, R.; Fletcher, M.; Fong, H.; Font, J. A.; Forsyth, P. W. F.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Ganija, M. R.; Gaonkar, S. G.; Garcia-Quiros, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, D.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; Goncharov, B.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Gretarsson, E. M.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Halim, O.; Hall, B. R.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hinderer, T.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hreibi, A.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kapadia, S. J.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, K.; Kim, W.; Kim, W. S.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kinley-Hanlon, M.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Knowles, T. D.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kumar, S.; Kuo, L.; Kutynia, A.; Kwang, S.; Lackey, B. D.; Lai, K. H.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, H. W.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Linker, S. D.; Littenberg, T. B.; Liu, J.; Lo, R. K. L.; Lockerbie, N. A.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macas, R.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña Hernandez, I.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Markowitz, A.; Maros, E.; Marquina, A.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Mason, K.; Massera, E.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McCuller, L.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McNeill, L.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Mejuto-Villa, E.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, B. B.; Miller, J.; Millhouse, M.; Milovich-Goff, M. C.; Minazzoli, O.; Minenkov, Y.; Ming, J.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moffa, D.; Moggi, A.; Mogushi, K.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muñiz, E. A.; Muratore, M.; Murray, P. G.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Neilson, J.; Nelemans, G.; Nelson, T. J. N.; Nery, M.; Neunzert, A.; Nevin, L.; Newport, J. M.; Newton, G.; Ng, K. K. Y.; Nguyen, T. T.; Nichols, D.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; North, C.; Nuttall, L. K.; Oberling, J.; O'Dea, G. D.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Okada, M. A.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ormiston, R.; Ortega, L. F.; O'Shaughnessy, R.; Ossokine, S.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Page, M. A.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, Howard; Pan, Huang-Wei; Pang, B.; Pang, P. T. H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Parida, A.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patil, M.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pirello, M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Pratten, G.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rajbhandari, B.; Rakhmanov, M.; Ramirez, K. E.; Ramos-Buades, A.; Rapagnani, P.; Raymond, V.; Razzano, M.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Ren, W.; Reyes, S. D.; Ricci, F.; Ricker, P. M.; Rieger, S.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romel, C. L.; Romie, J. H.; Rosińska, D.; Ross, M. P.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Rutins, G.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sanchez, L. E.; Sanchis-Gual, N.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheel, M.; Scheuer, J.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schulte, B. W.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Seidel, E.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D. A.; Shaffer, T. J.; Shah, A. A.; Shahriar, M. S.; Shaner, M. B.; Shao, L.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, L. P.; Singh, A.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Somala, S.; Son, E. J.; Sonnenberg, J. A.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staats, K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stevenson, S. P.; Stone, R.; Stops, D. J.; Strain, K. A.; Stratta, G.; Strigin, S. E.; Strunk, A.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Suresh, J.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Tait, S. C.; Talbot, C.; Talukder, D.; Tanner, D. B.; Tao, D.; Tápai, M.; Taracchini, A.; Tasson, J. D.; Taylor, J. A.; Taylor, R.; Tewari, S. V.; Theeg, T.; Thies, F.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tonelli, M.; Tornasi, Z.; Torres-Forné, A.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tsang, K. W.; Tse, M.; Tso, R.; Tsukada, L.; Tsuna, D.; Tuyenbayev, D.; Ueno, K.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walet, R.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, J. Z.; Wang, W. H.; Wang, Y. F.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessel, E. K.; Weßels, P.; Westerweck, J.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Wilken, D.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wysocki, D. M.; Xiao, S.; Yamamoto, H.; Yancey, C. C.; Yang, L.; Yap, M. J.; Yazback, M.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2018-05-01

The detection of gravitational waves with Advanced LIGO and Advanced Virgo has enabled novel tests of general relativity, including direct study of the polarization of gravitational waves. While general relativity allows for only two tensor gravitational-wave polarizations, general metric theories can additionally predict two vector and two scalar polarizations. The polarization of gravitational waves is encoded in the spectral shape of the stochastic gravitational-wave background, formed by the superposition of cosmological and individually unresolved astrophysical sources. Using data recorded by Advanced LIGO during its first observing run, we search for a stochastic background of generically polarized gravitational waves. We find no evidence for a background of any polarization, and place the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background. Under log-uniform priors for the energy in each polarization, we limit the energy densities of tensor, vector, and scalar modes at 95% credibility to Ω0T<5.58 ×10-8 , Ω0V<6.35 ×10-8 , and Ω0S<1.08 ×10-7 at a reference frequency f0=25 Hz .

MEANS: python package for Moment Expansion Approximation, iNference and Simulation

PubMed Central

Fan, Sisi; Geissmann, Quentin; Lakatos, Eszter; Lukauskas, Saulius; Ale, Angelique; Babtie, Ann C.; Kirk, Paul D. W.; Stumpf, Michael P. H.

2016-01-01

Motivation: Many biochemical systems require stochastic descriptions. Unfortunately these can only be solved for the simplest cases and their direct simulation can become prohibitively expensive, precluding thorough analysis. As an alternative, moment closure approximation methods generate equations for the time-evolution of the system’s moments and apply a closure ansatz to obtain a closed set of differential equations; that can become the basis for the deterministic analysis of the moments of the outputs of stochastic systems. Results: We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis. Availability and implementation: https://github.com/theosysbio/means Contacts: m.stumpf@imperial.ac.uk or e.lakatos13@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153663

MEANS: python package for Moment Expansion Approximation, iNference and Simulation.

PubMed

Fan, Sisi; Geissmann, Quentin; Lakatos, Eszter; Lukauskas, Saulius; Ale, Angelique; Babtie, Ann C; Kirk, Paul D W; Stumpf, Michael P H

2016-09-15

Many biochemical systems require stochastic descriptions. Unfortunately these can only be solved for the simplest cases and their direct simulation can become prohibitively expensive, precluding thorough analysis. As an alternative, moment closure approximation methods generate equations for the time-evolution of the system's moments and apply a closure ansatz to obtain a closed set of differential equations; that can become the basis for the deterministic analysis of the moments of the outputs of stochastic systems. We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis. https://github.com/theosysbio/means m.stumpf@imperial.ac.uk or e.lakatos13@imperial.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Effective long wavelength scalar dynamics in de Sitter

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

Moss, Ian; Rigopoulos, Gerasimos, E-mail: ian.moss@newcastle.ac.uk, E-mail: gerasimos.rigopoulos@ncl.ac.uk

We discuss the effective infrared theory governing a light scalar's long wavelength dynamics in de Sitter spacetime. We show how the separation of scales around the physical curvature radius k / a ∼ H can be performed consistently with a window function and how short wavelengths can be integrated out in the Schwinger-Keldysh path integral formalism. At leading order, and for time scales Δ t >> H {sup −1}, this results in the well-known Starobinsky stochastic evolution. However, our approach allows for the computation of quantum UV corrections, generating an effective potential on which the stochastic dynamics takes place. Themore » long wavelength stochastic dynamical equations are now second order in time, incorporating temporal scales Δ t ∼ H {sup −1} and resulting in a Kramers equation for the probability distribution—more precisely the Wigner function—in contrast to the more usual Fokker-Planck equation. This feature allows us to non-perturbatively evaluate, within the stochastic formalism, not only expectation values of field correlators, but also the stress-energy tensor of φ.« less

Correlated evolution of body and fin morphology in the cichlid fishes.

PubMed

Feilich, Kara L

2016-10-01

Body and fin shapes are chief determinants of swimming performance in fishes. Different configurations of body and fin shapes can suit different locomotor specializations. The success of any configuration is dependent upon the hydrodynamic interactions between body and fins. Despite the importance of body-fin interactions for swimming, there are few data indicating whether body and fin configurations evolve in concert, or whether these structures vary independently. The cichlid fishes are a diverse family whose well-studied phylogenetic relationships make them ideal for the study of macroevolution of ecomorphology. This study measured body, and caudal and median fin morphology from radiographs of 131 cichlid genera, using morphometrics and phylogenetic comparative methods to determine whether these traits exhibit correlated evolution. Partial least squares canonical analysis revealed that body, caudal fin, dorsal fin, and anal fin shapes all exhibited strong correlated evolution consistent with locomotor ecomorphology. Major patterns included the evolution of deep body profiles with long fins, suggestive of maneuvering specialization; and the evolution of narrow, elongate caudal peduncles with concave tails, a combination that characterizes economical cruisers. These results demonstrate that body shape evolution does not occur independently of other traits, but among a suite of other morphological changes that augment locomotor specialization. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

The effects of self-interstitial clusters on cascade defect evolution beyond the primary damage state

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

Heinisch, H.L.

1997-04-01

The intracascade evolution of the defect distributions of cascades in copper is investigated using stochastic annealing simulations applied to cascades generated with molecular dynamics (MD). The temperature and energy dependencies of annihilation, clustering and free defect production are determined for individual cascades. The annealing simulation results illustrate the strong influence on intracascade evolution of the defect configuration existing in the primary damage state. Another factor significantly affecting the evolution of the defect distribution is the rapid one-dimensional diffusion of small, glissile interstitial loops produced directly in cascades. This phenomenon introduces a cascade energy dependence of defect evolution that is apparentmore » only beyond the primary damage state, amplifying the need for further study of the annealing phase of cascade evolution and for performing many more MD cascade simulations at higher energies.« less

A Computational Framework for Analyzing Stochasticity in Gene Expression

PubMed Central

Sherman, Marc S.; Cohen, Barak A.

2014-01-01

Stochastic fluctuations in gene expression give rise to distributions of protein levels across cell populations. Despite a mounting number of theoretical models explaining stochasticity in protein expression, we lack a robust, efficient, assumption-free approach for inferring the molecular mechanisms that underlie the shape of protein distributions. Here we propose a method for inferring sets of biochemical rate constants that govern chromatin modification, transcription, translation, and RNA and protein degradation from stochasticity in protein expression. We asked whether the rates of these underlying processes can be estimated accurately from protein expression distributions, in the absence of any limiting assumptions. To do this, we (1) derived analytical solutions for the first four moments of the protein distribution, (2) found that these four moments completely capture the shape of protein distributions, and (3) developed an efficient algorithm for inferring gene expression rate constants from the moments of protein distributions. Using this algorithm we find that most protein distributions are consistent with a large number of different biochemical rate constant sets. Despite this degeneracy, the solution space of rate constants almost always informs on underlying mechanism. For example, we distinguish between regimes where transcriptional bursting occurs from regimes reflecting constitutive transcript production. Our method agrees with the current standard approach, and in the restrictive regime where the standard method operates, also identifies rate constants not previously obtainable. Even without making any assumptions we obtain estimates of individual biochemical rate constants, or meaningful ratios of rate constants, in 91% of tested cases. In some cases our method identified all of the underlying rate constants. The framework developed here will be a powerful tool for deducing the contributions of particular molecular mechanisms to specific patterns of gene expression. PMID:24811315

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

PubMed

Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

Chaotic Excitation and Tidal Damping in the GJ 876 System

NASA Astrophysics Data System (ADS)

Puranam, Abhijit; Batygin, Konstantin

2018-04-01

The M-dwarf GJ 876 is the closest known star to harbor a multi-planetary system. With three outer planets locked in a chaotic Laplace-type resonance and an appreciably eccentric short-period super-Earth, this system represents a unique exposition of extrasolar planetary dynamics. A key question that concerns the long-term evolution of this system, and the fate of close-in planets in general, is how the significant eccentricity of the inner-most planet is maintained against tidal circularization on timescales comparable to the age of the universe. Here, we employ stochastic secular perturbation theory and N-body simulations to show that the orbit of the inner-most planet is shaped by a delicate balance between extrinsic chaotic forcing and tidal dissipation. As such, the planet’s orbital eccentricity represents an indirect measure of its tidal quality factor. Based on the system’s present-day architecture, we estimate that the extrasolar super-Earth GJ 876 d has a tidal Q ∼ 104–105, a value characteristic of solar system gas giants.

Accelerated optimization and automated discovery with covariance matrix adaptation for experimental quantum control

NASA Astrophysics Data System (ADS)

Roslund, Jonathan; Shir, Ofer M.; Bäck, Thomas; Rabitz, Herschel

2009-10-01

Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to ˜9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem’s Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape’s local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.

Size Evolution and Stochastic Models: Explaining Ostracod Size through Probabilistic Distributions

NASA Astrophysics Data System (ADS)

Krawczyk, M.; Decker, S.; Heim, N. A.; Payne, J.

2014-12-01

The biovolume of animals has functioned as an important benchmark for measuring evolution throughout geologic time. In our project, we examined the observed average body size of ostracods over time in order to understand the mechanism of size evolution in these marine organisms. The body size of ostracods has varied since the beginning of the Ordovician, where the first true ostracods appeared. We created a stochastic branching model to create possible evolutionary trees of ostracod size. Using stratigraphic ranges for ostracods compiled from over 750 genera in the Treatise on Invertebrate Paleontology, we calculated overall speciation and extinction rates for our model. At each timestep in our model, new lineages can evolve or existing lineages can become extinct. Newly evolved lineages are assigned sizes based on their parent genera. We parameterized our model to generate neutral and directional changes in ostracod size to compare with the observed data. New sizes were chosen via a normal distribution, and the neutral model selected new sizes differentials centered on zero, allowing for an equal chance of larger or smaller ostracods at each speciation. Conversely, the directional model centered the distribution on a negative value, giving a larger chance of smaller ostracods. Our data strongly suggests that the overall direction of ostracod evolution has been following a model that directionally pushes mean ostracod size down, shying away from a neutral model. Our model was able to match the magnitude of size decrease. Our models had a constant linear decrease while the actual data had a much more rapid initial rate followed by a constant size. The nuance of the observed trends ultimately suggests a more complex method of size evolution. In conclusion, probabilistic methods can provide valuable insight into possible evolutionary mechanisms determining size evolution in ostracods.

Formation of gold nanorods by a stochastic "popcorn" mechanism.

PubMed

Edgar, Jonathan A; McDonagh, Andrew M; Cortie, Michael B

2012-02-28

Gold nanorods have significant technological potential and are of broad interest to the nanotechnology community. The discovery of the seeded, wet-chemical synthetic process to produce them may be regarded as a landmark in the control of metal nanoparticle shape. However, the mechanism by which the initial spherical gold seeds acquire anisotropy is a critical, yet poorly understood, factor. Here we examine the very early stages of rod growth using a combination of techniques including cryogenic transmission electron microscopy, optical spectroscopy, and computational modeling. Reconciliation of the available experimental observations can only be achieved by invoking a stochastic, "popcorn"-like mechanism of growth, in which individual seeds lie quiescent for some time before suddenly and rapidly growing into rods. This is quite different from the steady, concurrent growth of nanorods that has been previously generally assumed. Furthermore we propose that the shape is controlled by the ratio of surface energy of rod sides to rod ends, with values of this quantity in the range of 0.3-0.8 indicated for typical growth solutions.

Stochastic effects on phase-space holes and clumps in kinetic systems near marginal stability

DOE PAGES

Woods, Benjamin J. Q.; Duarte, Vinicius N.; De-Gol, Anthony J.; ...

2018-01-23

The creation and subsequent evolution of marginally-unstable modes have been observed in a wide range of fusion devices. This behaviour has been successfully explained, for a single frequency shifting mode, in terms of phase-space structures known as a 'hole' and 'clump'. Here in this paper, we introduce stochasticity into a 1D kinetic model, affecting the formation and evolution of resonant modes in the system. We find that noise in the fast particle distribution or electric field leads to a shift in the asymptotic behaviour of a chirping resonant mode; this noise heuristically maps onto radial microturbulence via canonical toroidal momentummore » scattering, affecting hole and clump formation. While the mechanism allowing for the formation of the hole and clump is coherent, the lifetime of a hole and clump is shown to be highly sensitive to initial conditions, affecting the temporal profile of a single bursting event in mode amplitude.« less

Stochastic effects on phase-space holes and clumps in kinetic systems near marginal stability

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

Woods, Benjamin J. Q.; Duarte, Vinicius N.; De-Gol, Anthony J.

The creation and subsequent evolution of marginally-unstable modes have been observed in a wide range of fusion devices. This behaviour has been successfully explained, for a single frequency shifting mode, in terms of phase-space structures known as a 'hole' and 'clump'. Here in this paper, we introduce stochasticity into a 1D kinetic model, affecting the formation and evolution of resonant modes in the system. We find that noise in the fast particle distribution or electric field leads to a shift in the asymptotic behaviour of a chirping resonant mode; this noise heuristically maps onto radial microturbulence via canonical toroidal momentummore » scattering, affecting hole and clump formation. While the mechanism allowing for the formation of the hole and clump is coherent, the lifetime of a hole and clump is shown to be highly sensitive to initial conditions, affecting the temporal profile of a single bursting event in mode amplitude.« less

Autapse-induced multiple stochastic resonances in a modular neuronal network

NASA Astrophysics Data System (ADS)

Yang, XiaoLi; Yu, YanHu; Sun, ZhongKui

2017-08-01

This study investigates the nontrivial effects of autapse on stochastic resonance in a modular neuronal network subjected to bounded noise. The resonance effect of autapse is detected by imposing a self-feedback loop with autaptic strength and autaptic time delay to each constituent neuron. Numerical simulations have demonstrated that bounded noise with the proper level of amplitude can induce stochastic resonance; moreover, the noise induced resonance dynamics can be significantly shaped by the autapse. In detail, for a specific range of autaptic strength, multiple stochastic resonances can be induced when the autaptic time delays are appropriately adjusted. These appropriately adjusted delays are detected to nearly approach integer multiples of the period of the external weak signal when the autaptic strength is very near zero; otherwise, they do not match the period of the external weak signal when the autaptic strength is slightly greater than zero. Surprisingly, in both cases, the differences between arbitrary two adjacent adjusted autaptic delays are always approximately equal to the period of the weak signal. The phenomenon of autaptic delay induced multiple stochastic resonances is further confirmed to be robust against the period of the external weak signal and the intramodule probability of subnetwork. These findings could have important implications for weak signal detection and information propagation in realistic neural systems.

Stochastic simulation of biological reactions, and its applications for studying actin polymerization.

PubMed

Ichikawa, Kazuhisa; Suzuki, Takashi; Murata, Noboru

2010-11-30

Molecular events in biological cells occur in local subregions, where the molecules tend to be small in number. The cytoskeleton, which is important for both the structural changes of cells and their functions, is also a countable entity because of its long fibrous shape. To simulate the local environment using a computer, stochastic simulations should be run. We herein report a new method of stochastic simulation based on random walk and reaction by the collision of all molecules. The microscopic reaction rate P(r) is calculated from the macroscopic rate constant k. The formula involves only local parameters embedded for each molecule. The results of the stochastic simulations of simple second-order, polymerization, Michaelis-Menten-type and other reactions agreed quite well with those of deterministic simulations when the number of molecules was sufficiently large. An analysis of the theory indicated a relationship between variance and the number of molecules in the system, and results of multiple stochastic simulation runs confirmed this relationship. We simulated Ca²(+) dynamics in a cell by inward flow from a point on the cell surface and the polymerization of G-actin forming F-actin. Our results showed that this theory and method can be used to simulate spatially inhomogeneous events.

Comparing reactive and memory-one strategies of direct reciprocity

NASA Astrophysics Data System (ADS)

Baek, Seung Ki; Jeong, Hyeong-Chai; Hilbe, Christian; Nowak, Martin A.

2016-05-01

Direct reciprocity is a mechanism for the evolution of cooperation based on repeated interactions. When individuals meet repeatedly, they can use conditional strategies to enforce cooperative outcomes that would not be feasible in one-shot social dilemmas. Direct reciprocity requires that individuals keep track of their past interactions and find the right response. However, there are natural bounds on strategic complexity: Humans find it difficult to remember past interactions accurately, especially over long timespans. Given these limitations, it is natural to ask how complex strategies need to be for cooperation to evolve. Here, we study stochastic evolutionary game dynamics in finite populations to systematically compare the evolutionary performance of reactive strategies, which only respond to the co-player’s previous move, and memory-one strategies, which take into account the own and the co-player’s previous move. In both cases, we compare deterministic strategy and stochastic strategy spaces. For reactive strategies and small costs, we find that stochasticity benefits cooperation, because it allows for generous-tit-for-tat. For memory one strategies and small costs, we find that stochasticity does not increase the propensity for cooperation, because the deterministic rule of win-stay, lose-shift works best. For memory one strategies and large costs, however, stochasticity can augment cooperation.

Comparing reactive and memory-one strategies of direct reciprocity

PubMed Central

Baek, Seung Ki; Jeong, Hyeong-Chai; Hilbe, Christian; Nowak, Martin A.

2016-01-01

Direct reciprocity is a mechanism for the evolution of cooperation based on repeated interactions. When individuals meet repeatedly, they can use conditional strategies to enforce cooperative outcomes that would not be feasible in one-shot social dilemmas. Direct reciprocity requires that individuals keep track of their past interactions and find the right response. However, there are natural bounds on strategic complexity: Humans find it difficult to remember past interactions accurately, especially over long timespans. Given these limitations, it is natural to ask how complex strategies need to be for cooperation to evolve. Here, we study stochastic evolutionary game dynamics in finite populations to systematically compare the evolutionary performance of reactive strategies, which only respond to the co-player’s previous move, and memory-one strategies, which take into account the own and the co-player’s previous move. In both cases, we compare deterministic strategy and stochastic strategy spaces. For reactive strategies and small costs, we find that stochasticity benefits cooperation, because it allows for generous-tit-for-tat. For memory one strategies and small costs, we find that stochasticity does not increase the propensity for cooperation, because the deterministic rule of win-stay, lose-shift works best. For memory one strategies and large costs, however, stochasticity can augment cooperation. PMID:27161141

COSMIC DUST AGGREGATION WITH STOCHASTIC CHARGING

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

Matthews, Lorin S.; Hyde, Truell W.; Shotorban, Babak, E-mail: Lorin_Matthews@baylor.edu

2013-10-20

The coagulation of cosmic dust grains is a fundamental process which takes place in astrophysical environments, such as presolar nebulae and circumstellar and protoplanetary disks. Cosmic dust grains can become charged through interaction with their plasma environment or other processes, and the resultant electrostatic force between dust grains can strongly affect their coagulation rate. Since ions and electrons are collected on the surface of the dust grain at random time intervals, the electrical charge of a dust grain experiences stochastic fluctuations. In this study, a set of stochastic differential equations is developed to model these fluctuations over the surface ofmore » an irregularly shaped aggregate. Then, employing the data produced, the influence of the charge fluctuations on the coagulation process and the physical characteristics of the aggregates formed is examined. It is shown that dust with small charges (due to the small size of the dust grains or a tenuous plasma environment) is affected most strongly.« less

Stochastic analysis of pitch angle scattering of charged particles by transverse magnetic waves

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

Lemons, Don S.; Liu Kaijun; Winske, Dan

2009-11-15

This paper describes a theory of the velocity space scattering of charged particles in a static magnetic field composed of a uniform background field and a sum of transverse, circularly polarized, magnetic waves. When that sum has many terms the autocorrelation time required for particle orbits to become effectively randomized is small compared with the time required for the particle velocity distribution to change significantly. In this regime the deterministic equations of motion can be transformed into stochastic differential equations of motion. The resulting stochastic velocity space scattering is described, in part, by a pitch angle diffusion rate that ismore » a function of initial pitch angle and properties of the wave spectrum. Numerical solutions of the deterministic equations of motion agree with the theory at all pitch angles, for wave energy densities up to and above the energy density of the uniform field, and for different wave spectral shapes.« less

A Stochastic Model of Eye Lens Growth

PubMed Central

Šikić, Hrvoje; Shi, Yanrong; Lubura, Snježana; Bassnett, Steven

2015-01-01

The size and shape of the ocular lens must be controlled with precision if light is to be focused sharply on the retina. The lifelong growth of the lens depends on the production of cells in the anterior epithelium. At the lens equator, epithelial cells differentiate into fiber cells, which are added to the surface of the existing fiber cell mass, increasing its volume and area. We developed a stochastic model relating the rates of cell proliferation and death in various regions of the lens epithelium to deposition of fiber cells and lens growth. Epithelial population dynamics were modeled as a branching process with emigration and immigration between various proliferative zones. Numerical simulations were in agreement with empirical measurements and demonstrated that, operating within the strict confines of lens geometry, a stochastic growth engine can produce the smooth and precise growth necessary for lens function. PMID:25816743

Isotropic stochastic rotation dynamics

NASA Astrophysics Data System (ADS)

Mühlbauer, Sebastian; Strobl, Severin; Pöschel, Thorsten

2017-12-01

Stochastic rotation dynamics (SRD) is a widely used method for the mesoscopic modeling of complex fluids, such as colloidal suspensions or multiphase flows. In this method, however, the underlying Cartesian grid defining the coarse-grained interaction volumes induces anisotropy. We propose an isotropic, lattice-free variant of stochastic rotation dynamics, termed iSRD. Instead of Cartesian grid cells, we employ randomly distributed spherical interaction volumes. This eliminates the requirement of a grid shift, which is essential in standard SRD to maintain Galilean invariance. We derive analytical expressions for the viscosity and the diffusion coefficient in relation to the model parameters, which show excellent agreement with the results obtained in iSRD simulations. The proposed algorithm is particularly suitable to model systems bound by walls of complex shape, where the domain cannot be meshed uniformly. The presented approach is not limited to SRD but is applicable to any other mesoscopic method, where particles interact within certain coarse-grained volumes.

Resonant activation of population extinctions

NASA Astrophysics Data System (ADS)

Spalding, Christopher; Doering, Charles R.; Flierl, Glenn R.

2017-10-01

Understanding the mechanisms governing population extinctions is of key importance to many problems in ecology and evolution. Stochastic factors are known to play a central role in extinction, but the interactions between a population's demographic stochasticity and environmental noise remain poorly understood. Here we model environmental forcing as a stochastic fluctuation between two states, one with a higher death rate than the other. We find that, in general, there exists a rate of fluctuations that minimizes the mean time to extinction, a phenomenon previously dubbed "resonant activation." We develop a heuristic description of the phenomenon, together with a criterion for the existence of resonant activation. Specifically, the minimum extinction time arises as a result of the system approaching a scenario wherein the severity of rare events is balanced by the time interval between them. We discuss our findings within the context of more general forms of environmental noise and suggest potential applications to evolutionary models.

From stochastic processes to numerical methods: A new scheme for solving reaction subdiffusion fractional partial differential equations

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

Angstmann, C.N.; Donnelly, I.C.; Henry, B.I., E-mail: B.Henry@unsw.edu.au

We have introduced a new explicit numerical method, based on a discrete stochastic process, for solving a class of fractional partial differential equations that model reaction subdiffusion. The scheme is derived from the master equations for the evolution of the probability density of a sum of discrete time random walks. We show that the diffusion limit of the master equations recovers the fractional partial differential equation of interest. This limiting procedure guarantees the consistency of the numerical scheme. The positivity of the solution and stability results are simply obtained, provided that the underlying process is well posed. We also showmore » that the method can be applied to standard reaction–diffusion equations. This work highlights the broader applicability of using discrete stochastic processes to provide numerical schemes for partial differential equations, including fractional partial differential equations.« less

Variable classification in the LSST era: exploring a model for quasi-periodic light curves

NASA Astrophysics Data System (ADS)

Zinn, J. C.; Kochanek, C. S.; Kozłowski, S.; Udalski, A.; Szymański, M. K.; Soszyński, I.; Wyrzykowski, Ł.; Ulaczyk, K.; Poleski, R.; Pietrukowicz, P.; Skowron, J.; Mróz, P.; Pawlak, M.

2017-06-01

The Large Synoptic Survey Telescope (LSST) is expected to yield ˜107 light curves over the course of its mission, which will require a concerted effort in automated classification. Stochastic processes provide one means of quantitatively describing variability with the potential advantage over simple light-curve statistics that the parameters may be physically meaningful. Here, we survey a large sample of periodic, quasi-periodic and stochastic Optical Gravitational Lensing Experiment-III variables using the damped random walk (DRW; CARMA(1,0)) and quasi-periodic oscillation (QPO; CARMA(2,1)) stochastic process models. The QPO model is described by an amplitude, a period and a coherence time-scale, while the DRW has only an amplitude and a time-scale. We find that the periodic and quasi-periodic stellar variables are generally better described by a QPO than a DRW, while quasars are better described by the DRW model. There are ambiguities in interpreting the QPO coherence time due to non-sinusoidal light-curve shapes, signal-to-noise ratio, error mischaracterizations and cadence. Higher order implementations of the QPO model that better capture light-curve shapes are necessary for the coherence time to have its implied physical meaning. Independent of physical meaning, the extra parameter of the QPO model successfully distinguishes most of the classes of periodic and quasi-periodic variables we consider.

Application of stochastic differential geometry to the term structure of interst rates in developed markets

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

Taranenko, Y.; Barnes, C.

1996-12-31

This paper deals with further developments of the new theory that applies stochastic differential geometry (SDG) to dynamics of interest rates. We examine mathematical constraints on the evolution of interest rate volatilities that arise from stochastic differential calculus under assumptions of an arbitrage free evolution of zero coupon bonds and developed markets (i.e., none of the party/factor can drive the whole market). The resulting new theory incorporates the Heath-Jarrow-Morton (HJM) model of interest rates and provides new equations for volatilities which makes the system of equations for interest rates and volatilities complete and self consistent. It results in much smallermore » amount of volatility data that should be guessed for the SDG model as compared to the HJM model. Limited analysis of the market volatility data suggests that the assumption of the developed market is violated around maturity of two years. Such maturities where the assumptions of the SDG model are violated are suggested to serve as boundaries at which volatilities should be specified independently from the model. Our numerical example with two boundaries (two years and five years) qualitatively resembles the market behavior. Under some conditions solutions of the SDG model become singular that may indicate market crashes. More detail comparison with the data is needed before the theory can be established or refuted.« less

Planetary Rings

NASA Astrophysics Data System (ADS)

Esposito, Larry W.

2011-07-01

Preface; 1. Introduction: the allure of ringed planets; 2. Studies of planetary rings 1610-2004; 3. Diversity of planetary rings; 4. Individual ring particles and their collisions; 5. Large-scale ring evolution; 6. Moons confine and sculpt rings; 7. Explaining ring phenomena; 8. N-Body simulations; 9. Stochastic models; 10. Age and evolution of rings; 11. Saturn's mysterious F ring; 12. Neptune's partial rings; 13. Jupiter's ring-moon system after Galileo; 14. Ring photometry; 15. Dusty rings; 16. Cassini observations; 17. Summary: the big questions; Glossary; References; Index.

Body shape convergence driven by small size optimum in marine angelfishes.

PubMed

Frédérich, Bruno; Santini, Francesco; Konow, Nicolai; Schnitzler, Joseph; Lecchini, David; Alfaro, Michael E

2017-06-01

Convergent evolution of small body size occurs across many vertebrate clades and may reflect an evolutionary response to shared selective pressures. However it remains unclear if other aspects of phenotype undergo convergent evolution in miniaturized lineages. Here we present a comparative analysis of body size and shape evolution in marine angelfishes (Pomacanthidae), a reef fish family characterized by repeated transitions to small body size. We ask if lineages that evolve small sizes show convergent evolution in body shape. Our results reveal that angelfish lineages evolved three different stable size optima with one corresponding to the group of pygmy angelfishes ( Centropyge ). Then, we test if the observed shifts in body size are associated with changes to new adaptive peaks in shape. Our data suggest that independent evolution to small size optima have induced repeated convergence upon deeper body and steeper head profile in Centropyge These traits may favour manoeuvrability and visual awareness in these cryptic species living among corals, illustrating that functional demands on small size may be related to habitat specialization and predator avoidance. The absence of shape convergence in large marine angelfishes also suggests that more severe requirements exist for small than for large size optima. © 2017 The Author(s).

The statistical mechanics of human weight change

PubMed Central

2017-01-01

Over the past 35 years there has been a near doubling in the worldwide prevalence of obesity. Body Mass Index (BMI) distributions in high-income societies have increasingly shifted rightwards, corresponding to increases in average BMI that are due to well-studied changes in the socioeconomic environment. However, in addition to this shift, BMI distributions have also shown marked changes in their particular shape over time, exhibiting an ongoing right-skewed broadening that is not well understood. Here, we compile and analyze the largest data set so far of year-over-year BMI changes. The data confirm that, on average, heavy individuals become lighter while light individuals become heavier year-over-year, and also show that year-over-year BMI evolution is characterized by fluctuations with a magnitude that is linearly proportional to BMI. We find that the distribution of human BMIs is intrinsically dynamic—due to the short-term variability of human weight—and its shape is determined by a balance between deterministic drift towards a natural set point and diffusion resulting from random fluctuations in, e.g., diet and physical activity. We formulate a stochastic mathematical model for BMI dynamics, deriving a theoretical shape for the BMI distribution and offering a mechanism that may explain the right-skewed broadening of BMI distributions over time. An extension of the base model investigates the hypothesis that peer-to-peer social influence plays a role in BMI dynamics. While including this effect improves the fit with the data, indicating that correlations in the behavior of individuals with similar BMI may be important for BMI dynamics, testing social transmission against other plausible unmodeled effects and interpretations remains the subject of future work. Implications of our findings on the dynamics of BMI distributions for public health interventions are discussed. PMID:29253025

Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm

PubMed Central

2014-01-01

The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to compute the objective function values for each generation. Two case studies were given to illustrate the application of proposed approach. Optimum shape parameters of 2D bushing model were determined by shape optimization using differential evolution algorithm. PMID:25276848

Quantifying variability in fast and slow solar wind: From turbulence to extremes

NASA Astrophysics Data System (ADS)

Tindale, E.; Chapman, S. C.; Moloney, N.; Watkins, N. W.

2017-12-01

Fast and slow solar wind exhibit variability across a wide range of spatiotemporal scales, with evolving turbulence producing fluctuations on sub-hour timescales and the irregular solar cycle modulating the system over many years. Here, we apply the data quantile-quantile (DQQ) method [Tindale and Chapman 2016, 2017] to over 20 years of Wind data, to study the time evolution of the statistical distribution of plasma parameters in fast and slow solar wind. This model-independent method allows us to simultaneously explore the evolution of fluctuations across all scales. We find a two-part functional form for the statistical distributions of the interplanetary magnetic field (IMF) magnitude and its components, with each region of the distribution evolving separately over the solar cycle. Up to a value of 8nT, turbulent fluctuations dominate the distribution of the IMF, generating the approximately lognormal shape found by Burlaga [2001]. The mean of this core-turbulence region tracks solar cycle activity, while its variance remains constant, independent of the fast or slow state of the solar wind. However, when we test the lognormality of this core-turbulence component over time, we find the model provides a poor description of the data at solar maximum, where sharp peaks in the distribution dominate over the lognormal shape. At IMF values higher than 8nT, we find a separate, extremal distribution component, whose moments are sensitive to solar cycle phase, the peak activity of the cycle and the solar wind state. We further investigate these `extremal' values using burst analysis, where a burst is defined as a continuous period of exceedance over a predefined threshold. This form of extreme value statistics allows us to study the stochastic process underlying the time series, potentially supporting a probabilistic forecast of high-energy events. Tindale, E., and S.C. Chapman (2016), Geophys. Res. Lett., 43(11) Tindale, E., and S.C. Chapman (2017), submitted Burlaga, L.F. (2001), J. Geophys. Res., 106(A8)

Engineering stem cells into organs: Topobiological transformations demonstrated by beak, feather and other ectodermal organ morphogenesis

PubMed Central

Chuong, Cheng-Ming; Wu, Ping; Plikus, Maksim; Jiang, Ting-Xin; Widelitz, Randall Bruce

2015-01-01

To accomplish regenerative medicine, several critical issues in stem cell biology have to be solved, including the identification of sources, expanding populations, building them into organs, and assimilating them to the host. While many stem cells can now differentiate along certain lineages, knowledge on how to use them to build organs lags behind. Here we focus on topobiological events that bridge this gap, i.e., the regulation of number, size, axis, shape, arrangement, and architecture during organogenesis. Rather than reviewing detailed molecular pathways known to disrupt organogenesis when perturbed, we highlight conceptual questions at the topobiological level, and ask how cellular and molecular mechanisms can work to explain these phenomena. The avian integument is used as the Rosetta stone because the molecular activities are linked to organ forms which are visually apparent and have functional consequences during evolution as shown by the fossil record and extant diversity. For example, we show that feather pattern formation is the equilibrium of stochastic interactions among multiple activators and inhibitors. While morphogens and receptors are coded by the genome, the result is based on the summed physical-chemical properties on the whole cell surface and is self-organizing. For another example, we show developing chicken and duck beaks contain differently configured localized growth zones (LoGZ) and can modulate chicken beaks to phenocopy diverse avian beaks in Nature by altering the position, number, size, and duration of LoGZs. Different organs have their unique topology and we also discuss shaping mechanisms of the liver and different ways of branching morphogenesis. Multi-primordia organs (e.g., feathers, hairs, teeth) have additional topographic specificities across the body surface, an appendage field, or within an appendage. Promises and problems in reconstituted feather / hair follicles and other organs are discussed. Finally, simple modifications at the topobiological level may lead to novel morphologies for natural selection at the evolution level. PMID:16564337

Pathogen-mediated selection in free-ranging elk populations infected by chronic wasting disease

USDA-ARS?s Scientific Manuscript database

Pathogens can exert a large influence on the evolution of hosts via selection for alleles or genotypes that moderate pathogen virulence. Inconsistent interactions between parasites and the host genome, such as those resulting from genetic linkages and environmental stochasticity, have largely preven...

The Economics of Has-Beens

ERIC Educational Resources Information Center

MacDonald, Glenn; Weisbach, Michael S.

2004-01-01

The evolution of technology causes human capital to become obsolete. We study this phenomenon in an overlapping generations setting, assuming that technology evolves stochastically and that older workers find updating uneconomic. Experience and learning by doing may offer the old some income protection, but technology advance always turns them…

Stochasticity, succession, and environmental perturbations in a fluidic ecosystem.

PubMed

Zhou, Jizhong; Deng, Ye; Zhang, Ping; Xue, Kai; Liang, Yuting; Van Nostrand, Joy D; Yang, Yunfeng; He, Zhili; Wu, Liyou; Stahl, David A; Hazen, Terry C; Tiedje, James M; Arkin, Adam P

2014-03-04

Unraveling the drivers of community structure and succession in response to environmental change is a central goal in ecology. Although the mechanisms shaping community structure have been intensively examined, those controlling ecological succession remain elusive. To understand the relative importance of stochastic and deterministic processes in mediating microbial community succession, a unique framework composed of four different cases was developed for fluidic and nonfluidic ecosystems. The framework was then tested for one fluidic ecosystem: a groundwater system perturbed by adding emulsified vegetable oil (EVO) for uranium immobilization. Our results revealed that groundwater microbial community diverged substantially away from the initial community after EVO amendment and eventually converged to a new community state, which was closely clustered with its initial state. However, their composition and structure were significantly different from each other. Null model analysis indicated that both deterministic and stochastic processes played important roles in controlling the assembly and succession of the groundwater microbial community, but their relative importance was time dependent. Additionally, consistent with the proposed conceptual framework but contradictory to conventional wisdom, the community succession responding to EVO amendment was primarily controlled by stochastic rather than deterministic processes. During the middle phase of the succession, the roles of stochastic processes in controlling community composition increased substantially, ranging from 81.3% to 92.0%. Finally, there are limited successional studies available to support different cases in the conceptual framework, but further well-replicated explicit time-series experiments are needed to understand the relative importance of deterministic and stochastic processes in controlling community succession.

On the Radio-emitting Particles of the Crab Nebula: Stochastic Acceleration Model

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

Tanaka, Shuta J.; Asano, Katsuaki, E-mail: sjtanaka@center.konan-u.ac.jp

The broadband emission of pulsar wind nebulae (PWNe) is well described by non-thermal emissions from accelerated electrons and positrons. However, the standard shock acceleration model of PWNe does not account for the hard spectrum in radio wavelengths. The origin of the radio-emitting particles is also important to determine the pair production efficiency in the pulsar magnetosphere. Here, we propose a possible resolution for the particle energy distribution in PWNe; the radio-emitting particles are not accelerated at the pulsar wind termination shock but are stochastically accelerated by turbulence inside PWNe. We upgrade our past one-zone spectral evolution model to include themore » energy diffusion, i.e., the stochastic acceleration, and apply the model to the Crab Nebula. A fairly simple form of the energy diffusion coefficient is assumed for this demonstrative study. For a particle injection to the stochastic acceleration process, we consider the continuous injection from the supernova ejecta or the impulsive injection associated with supernova explosion. The observed broadband spectrum and the decay of the radio flux are reproduced by tuning the amount of the particle injected to the stochastic acceleration process. The acceleration timescale and the duration of the acceleration are required to be a few decades and a few hundred years, respectively. Our results imply that some unveiled mechanisms, such as back reaction to the turbulence, are required to make the energies of stochastically and shock-accelerated particles comparable.« less

Simulation of stochastic wind action on transmission power lines

NASA Astrophysics Data System (ADS)

Wielgos, Piotr; Lipecki, Tomasz; Flaga, Andrzej

2018-01-01

The paper presents FEM analysis of the wind action on overhead transmission power lines. The wind action is based on a stochastic simulation of the wind field in several points of the structure and on the wind tunnel tests on aerodynamic coefficients of the single conductor consisting of three wires. In FEM calculations the section of the transmission power line composed of three spans is considered. Non-linear analysis with deadweight of the structure is performed first to obtain the deformed shape of conductors. Next, time-dependent wind forces are applied to respective points of conductors and non-linear dynamic analysis is carried out.

Two stochastic models useful in petroleum exploration

NASA Technical Reports Server (NTRS)

Kaufman, G. M.; Bradley, P. G.

1972-01-01

A model of the petroleum exploration process that tests empirically the hypothesis that at an early stage in the exploration of a basin, the process behaves like sampling without replacement is proposed along with a model of the spatial distribution of petroleum reserviors that conforms to observed facts. In developing the model of discovery, the following topics are discussed: probabilitistic proportionality, likelihood function, and maximum likelihood estimation. In addition, the spatial model is described, which is defined as a stochastic process generating values of a sequence or random variables in a way that simulates the frequency distribution of areal extent, the geographic location, and shape of oil deposits

Stochastic optimal control of non-stationary response of a single-degree-of-freedom vehicle model

NASA Astrophysics Data System (ADS)

Narayanan, S.; Raju, G. V.

1990-09-01

An active suspension system to control the non-stationary response of a single-degree-of-freedom (sdf) vehicle model with variable velocity traverse over a rough road is investigated. The suspension is optimized with respect to ride comfort and road holding, using stochastic optimal control theory. The ground excitation is modelled as a spatial homogeneous random process, being the output of a linear shaping filter to white noise. The effect of the rolling contact of the tyre is considered by an additional filter in cascade. The non-stationary response with active suspension is compared with that of a passive system.

Chaotic Motion of Relativistic Electrons Driven by Whistler Waves

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Telnikhin, A. A.; Kronberg, Tatiana K.

2007-01-01

Canonical equations governing an electron motion in electromagnetic field of the whistler mode waves propagating along the direction of an ambient magnetic field are derived. The physical processes on which the equations of motion are based .are identified. It is shown that relativistic electrons interacting with these fields demonstrate chaotic motion, which is accompanied by the particle stochastic heating and significant pitch angle diffusion. Evolution of distribution functions is described by the Fokker-Planck-Kolmogorov equations. It is shown that the whistler mode waves could provide a viable mechanism for stochastic energization of electrons with energies up to 50 MeV in the Jovian magnetosphere.

Effects of stochastic noise on dynamical decoupling procedures

NASA Astrophysics Data System (ADS)

Bernád, J. Z.; Frydrych, H.

2014-06-01

Dynamical decoupling is an important tool to counter decoherence and dissipation effects in quantum systems originating from environmental interactions. It has been used successfully in many experiments; however, there is still a gap between fidelity improvements achieved in practice compared to theoretical predictions. We propose a model for imperfect dynamical decoupling based on a stochastic Ito differential equation which could explain the observed gap. We discuss the impact of our model on the time evolution of various quantum systems in finite- and infinite-dimensional Hilbert spaces. Analytical results are given for the limit of continuous control, whereas we present numerical simulations and upper bounds for the case of finite control.

Stochastic effects in hybrid inflation

NASA Astrophysics Data System (ADS)

Martin, Jérôme; Vennin, Vincent

2012-02-01

Hybrid inflation is a two-field model where inflation ends due to an instability. In the neighborhood of the instability point, the potential is very flat and the quantum fluctuations dominate over the classical motion of the inflaton and waterfall fields. In this article, we study this regime in the framework of stochastic inflation. We numerically solve the two coupled Langevin equations controlling the evolution of the fields and compute the probability distributions of the total number of e-folds and of the inflation exit point. Then, we discuss the physical consequences of our results, in particular, the question of how the quantum diffusion can affect the observable predictions of hybrid inflation.

Diffusion equations and the time evolution of foreign exchange rates

NASA Astrophysics Data System (ADS)

Figueiredo, Annibal; de Castro, Marcio T.; da Fonseca, Regina C. B.; Gleria, Iram

2013-10-01

We investigate which type of diffusion equation is most appropriate to describe the time evolution of foreign exchange rates. We modify the geometric diffusion model assuming a non-exponential time evolution and the stochastic term is the sum of a Wiener noise and a jump process. We find the resulting diffusion equation to obey the Kramers-Moyal equation. Analytical solutions are obtained using the characteristic function formalism and compared with empirical data. The analysis focus on the first four central moments considering the returns of foreign exchange rate. It is shown that the proposed model offers a good improvement over the classical geometric diffusion model.

Cultural evolution: The case of babies’ first names

NASA Astrophysics Data System (ADS)

Xi, Ning; Zhang, Zi-Ke; Zhang, Yi-Cheng; Ge, Zehui; She, Li; Zhang, Kui

2014-07-01

In social sciences, there is currently rare consensus on the underlying mechanism for cultural evolution, partially due to lack of suitable data. The evolution of first names of newborn babies offers a remarkable example for such researches. In this paper, we employ the historical data on baby names from the United States to investigate the evolutionary process of culture, in particular focusing on how inequality among baby names changes over time. Then we propose a stochastic model where individual choice is determined by both individual preference and social influence, and show that the decrease in the strength of social influence can account for all the observed empirical features. Therefore, we claim that the weakening of social influence drives cultural evolution.

Adaptive processes drive ecomorphological convergent evolution in antwrens (Thamnophilidae).

PubMed

Bravo, Gustavo A; Remsen, J V; Brumfield, Robb T

2014-10-01

Phylogenetic niche conservatism (PNC) and convergence are contrasting evolutionary patterns that describe phenotypic similarity across independent lineages. Assessing whether and how adaptive processes give origin to these patterns represent a fundamental step toward understanding phenotypic evolution. Phylogenetic model-based approaches offer the opportunity not only to distinguish between PNC and convergence, but also to determine the extent that adaptive processes explain phenotypic similarity. The Myrmotherula complex in the Neotropical family Thamnophilidae is a polyphyletic group of sexually dimorphic small insectivorous forest birds that are relatively homogeneous in size and shape. Here, we integrate a comprehensive species-level molecular phylogeny of the Myrmotherula complex with morphometric and ecological data within a comparative framework to test whether phenotypic similarity is described by a pattern of PNC or convergence, and to identify evolutionary mechanisms underlying body size and shape evolution. We show that antwrens in the Myrmotherula complex represent distantly related clades that exhibit adaptive convergent evolution in body size and divergent evolution in body shape. Phenotypic similarity in the group is primarily driven by their tendency to converge toward smaller body sizes. Differences in body size and shape across lineages are associated to ecological and behavioral factors. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Evolution in the Caribbean Classroom: A Critical Analysis of the Role of Biology Teachers and Science Standards in Shaping Evolution Instruction in Belize

ERIC Educational Resources Information Center

Nunez, Elvis Enrique; Pringle, Rose M.; Showalter, Kevin Tyler

2012-01-01

A survey of the literature on evolution instruction provides evidence that teachers' personal views and understandings can shape instructional approaches and content delivered in science classrooms regardless of established science standards. This study is the first to quantify evolutionary worldviews of in-service teachers in the Caribbean,…

Shape analysis of moss (Bryophyta) sporophytes: Insights into land plant evolution.

PubMed

Rose, Jeffrey P; Kriebel, Ricardo; Sytsma, Kenneth J

2016-04-01

The alternation of generations life cycle represents a key feature of land-plant evolution and has resulted in a diverse array of sporophyte forms and modifications in all groups of land plants. We test the hypothesis that evolution of sporangium (capsule) shape of the mosses-the second most diverse land-plant lineage-has been driven by differing physiological demands of life in diverse habitats. This study provides an important conceptual framework for analyzing the evolution of a single, homologous character in a continuous framework across a deep expanse of time, across all branches of the tree of life. We reconstruct ancestral sporangium shape and ancestral habitat on the largest phylogeny of mosses to date, and use phylogenetic generalized least squares regression to test the association between habitat and sporangium shape. In addition, we examine the association between shifts in sporangium shape and species diversification. We demonstrate that sporangium shape is convergent, under natural selection, and associated with habitat type, and that many shifts in speciation rate are associated with shifts in sporangium shape. Our results suggest that natural selection in different microhabitats results in the diversity of sporangium shape found in mosses, and that many increasing shifts in speciation rate result in changes in sporangium shape across their 480 million year history. Our framework provides a way to examine if diversification shifts in other land plants are also associated with massive changes in sporophyte form, among other morphological traits. © 2016 Botanical Society of America.

Evolution of a plastic quantitative trait in an age-structured population in a fluctuating environment.

PubMed

Engen, Steinar; Lande, Russell; Saether, Bernt-Erik

2011-10-01

We analyze weak fluctuating selection on a quantitative character in an age-structured population not subject to density regulation. We assume that early in the first year of life before selection, during a critical state of development, environments exert a plastic effect on the phenotype, which remains constant throughout the life of an individual. Age-specific selection on the character affects survival and fecundity, which have intermediate optima subject to temporal environmental fluctuations with directional selection in some age classes as special cases. Weighting individuals by their reproductive value, as suggested by Fisher, we show that the expected response per year in the weighted mean character has the same form as for models with no age structure. Environmental stochasticity generates stochastic fluctuations in the weighted mean character following a first-order autoregressive model with a temporally autocorrelated noise term and stationary variance depending on the amount of phenotypic plasticity. The parameters of the process are simple weighted averages of parameters used to describe age-specific survival and fecundity. The "age-specific selective weights" are related to the stable distribution of reproductive values among age classes. This allows partitioning of the change in the weighted mean character into age-specific components. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Development of the Microstructure Based Stochastic Life Prediction Models

DTIC Science & Technology

1991-06-27

sizes and shapes of the recrystallized and unrecrystallized grains and also measure sizes of subgrains. We will also determine the degree of...J. Lankford et al., STP 811, ASTM STP 811. ASTM, 1983. 5. M. R. James and W. L. Morris, "The Role of Microplastic Deformation in Fatigue Crack

LIDT-DD: A new hybrid model to understand debris discs observations - The case of massive collisions.

NASA Astrophysics Data System (ADS)

Kral, Q.; Thébault, P.; Augereau, J.-C.; Boccaletti, A.; Charnoz, S.

2014-12-01

LIDT-DD is a new hybrid model coupling the collisional and dynamical evolution in debris discs in a self-consistent way. It has been developed in a way that allows to treat a large number of different astrophysical cases where collisions and dynamics have an important role. This interplay was often totally neglected in previous studies whereas, even for the simplest configurations, the real physics of debris discs imposes strong constraints and interactions between dynamics and collisions. After presenting the LIDT-DD model, we will describe the evolution of violent stochastic collisional events with this model. These massive impacts have been invoked as a possible explanation for some debris discs displaying pronounced azimuthal asymmetries or having a luminosity excess exceeding that expected for systems at collisional steady-state. So far, no thorough modelling of the consequences of such stochastic events has been carried out, mainly because of the extreme numerical challenge of coupling the dynamical and collisional evolution of the released dust. We follow the collisional and dynamical evolution of dust released after the breakup of a Ceres-sized body at 6 AU from its central star. We investigate the duration, magnitude and spatial structure of the signature left by such a violent event, as well as its observational detectability. We use the GRaTer package to estimate the system's luminosity at different wavelengths and derive synthetic images for the SPHERE/VLT and MIRI/JWST instruments.

Stochastic dynamic modeling of regular and slow earthquakes

NASA Astrophysics Data System (ADS)

Aso, N.; Ando, R.; Ide, S.

2017-12-01

Both regular and slow earthquakes are slip phenomena on plate boundaries and are simulated by a (quasi-)dynamic modeling [Liu and Rice, 2005]. In these numerical simulations, spatial heterogeneity is usually considered not only for explaining real physical properties but also for evaluating the stability of the calculations or the sensitivity of the results on the condition. However, even though we discretize the model space with small grids, heterogeneity at smaller scales than the grid size is not considered in the models with deterministic governing equations. To evaluate the effect of heterogeneity at the smaller scales we need to consider stochastic interactions between slip and stress in a dynamic modeling. Tidal stress is known to trigger or affect both regular and slow earthquakes [Yabe et al., 2015; Ide et al., 2016], and such an external force with fluctuation can also be considered as a stochastic external force. A healing process of faults may also be stochastic, so we introduce stochastic friction law. In the present study, we propose a stochastic dynamic model to explain both regular and slow earthquakes. We solve mode III problem, which corresponds to the rupture propagation along the strike direction. We use BIEM (boundary integral equation method) scheme to simulate slip evolution, but we add stochastic perturbations in the governing equations, which is usually written in a deterministic manner. As the simplest type of perturbations, we adopt Gaussian deviations in the formulation of the slip-stress kernel, external force, and friction. By increasing the amplitude of perturbations of the slip-stress kernel, we reproduce complicated rupture process of regular earthquakes including unilateral and bilateral ruptures. By perturbing external force, we reproduce slow rupture propagation at a scale of km/day. The slow propagation generated by a combination of fast interaction at S-wave velocity is analogous to the kinetic theory of gasses: thermal diffusion appears much slower than the particle velocity of each molecule. The concept of stochastic triggering originates in the Brownian walk model [Ide, 2008], and the present study introduces the stochastic dynamics into dynamic simulations. The stochastic dynamic model has the potential to explain both regular and slow earthquakes more realistically.

Improved Upper Limits on the Stochastic Gravitational-Wave Background from 2009-2010 LIGO and Virgo Data

NASA Astrophysics Data System (ADS)

Aasi, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Accadia, T.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Affeldt, C.; Agathos, M.; Aggarwal, N.; Aguiar, O. D.; Ain, A.; Ajith, P.; Alemic, A.; Allen, B.; Allocca, A.; Amariutei, D.; Andersen, M.; Anderson, R.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C.; Areeda, J.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Austin, L.; Aylott, B. E.; Babak, S.; Baker, P. T.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barbet, M.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bauchrowitz, J.; Bauer, Th. S.; Behnke, B.; Bejger, M.; Beker, M. G.; Belczynski, C.; Bell, A. S.; Bell, C.; Bergmann, G.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Beyersdorf, P. T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biscans, S.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bloemen, S.; Blom, M.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bond, C.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, Sukanta; Bosi, L.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brückner, F.; Buchman, S.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burman, R.; Buskulic, D.; Buy, C.; Cadonati, L.; Cagnoli, G.; Bustillo, J. Calderón; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K. C.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Castiglia, A.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Celerier, C.; Cella, G.; Cepeda, C.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chu, Q.; Chua, S. S. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C.; Colombini, M.; Cominsky, L.; Constancio, M.; Conte, A.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corpuz, A.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coughlin, S.; Coulon, J.-P.; Countryman, S.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dahl, K.; Canton, T. Dal; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daveloza, H.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Dayanga, T.; Debreczeni, G.; Degallaix, J.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Dhurandhar, S.; Díaz, M.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Donath, A.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dossa, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dwyer, S.; Eberle, T.; Edo, T.; Edwards, M.; Effler, A.; Eggenstein, H.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Endrőczi, G.; Essick, R.; Etzel, T.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fehrmann, H.; Fejer, M. M.; Feldbaum, D.; Feroz, F.; Ferrante, I.; Ferrini, F.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gair, J.; Gammaitoni, L.; Gaonkar, S.; Garufi, F.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, C.; Gleason, J.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gordon, N.; Gorodetsky, M. L.; Gossan, S.; Goßler, S.; Gouaty, R.; Gräf, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Groot, P.; Grote, H.; Grover, K.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gushwa, K.; Gustafson, E. K.; Gustafson, R.; Hammer, D.; Hammond, G.; Hanke, M.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hart, M.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Heptonstall, A. W.; Heurs, M.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Hooper, S.; Hopkins, P.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hu, Y.; Huerta, E.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh, M.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Iyer, B. R.; Izumi, K.; Jacobson, M.; James, E.; Jang, H.; Jaranowski, P.; Ji, Y.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karlen, J.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Keiser, G. M.; Keitel, D.; Kelley, D. B.; Kells, W.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, C.; Kim, K.; Kim, N.; Kim, N. G.; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Koehlenbeck, S.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kremin, A.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, A.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Kwee, P.; Landry, M.; Lantz, B.; Larson, S.; Lasky, P. D.; Lawrie, C.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C.-H.; Lee, H. K.; Lee, H. M.; Lee, J.; Leonardi, M.; Leong, J. R.; Le Roux, A.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B.; Lewis, J.; Li, T. G. F.; Libbrecht, K.; Libson, A.; Lin, A. C.; Littenberg, T. B.; Litvine, V.; Lockerbie, N. A.; Lockett, V.; Lodhia, D.; Loew, K.; Logue, J.; Lombardi, A. L.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Lubinski, M. J.; Lück, H.; Luijten, E.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macarthur, J.; Macdonald, E. P.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Mageswaran, M.; Maglione, C.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Manca, G. M.; Mandel, I.; Mandic, V.; Mangano, V.; Mangini, N.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Martinelli, L.; Martynov, D.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; McLin, K.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Meinders, M.; Melatos, A.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyers, P.; Miao, H.; Michel, C.; Mikhailov, E. E.; Milano, L.; Milde, S.; Miller, J.; Minenkov, Y.; Mingarelli, C. M. F.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Moesta, P.; Mohan, M.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nagy, M. F.; Kumar, D. Nanda; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nelemans, G.; Neri, I.; Neri, M.; Newton, G.; Nguyen, T.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Ochsner, E.; O'Dell, J.; Oelker, E.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oppermann, P.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Padilla, C.; Pai, A.; Palashov, O.; Palomba, C.; Pan, H.; Pan, Y.; Pankow, C.; Paoletti, F.; Paoletti, R.; Paris, H.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Pedraza, M.; Penn, S.; Perreca, A.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pierro, V.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poeld, J.; Poggiani, R.; Poteomkin, A.; Powell, J.; Prasad, J.; Premachandra, S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Qin, J.; Quetschke, V.; Quintero, E.; Quiroga, G.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Raja, S.; Rajalakshmi, G.; Rakhmanov, M.; Ramet, C.; Ramirez, K.; Rapagnani, P.; Raymond, V.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Reid, S.; Reitze, D. H.; Rhoades, E.; Ricci, F.; Riles, K.; Robertson, N. A.; Robinet, F.; Rocchi, A.; Rodruck, M.; Rolland, L.; Rollins, J. G.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Salemi, F.; Sammut, L.; Sandberg, V.; Sanders, J. R.; Sannibale, V.; Santiago-Prieto, I.; Saracco, E.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R.; Scheuer, J.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siellez, K.; Siemens, X.; Sigg, D.; Simakov, D.; Singer, A.; Singer, L.; Singh, R.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Son, E. J.; Sorazu, B.; Souradeep, T.; Sperandio, L.; Staley, A.; Stebbins, J.; Steinlechner, J.; Steinlechner, S.; Stephens, B. C.; Steplewski, S.; Stevenson, S.; Stone, R.; Stops, D.; Strain, K. A.; Straniero, N.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, R.; ter Braack, A. P. M.; Thirugnanasambandam, M. P.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C. V.; Torrie, C. I.; Travasso, F.; Traylor, G.; Tse, M.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Urbanek, K.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Vallisneri, M.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van der Sluys, M. V.; van Heijningen, J.; van Veggel, A. A.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Verma, S. S.; Vetrano, F.; Viceré, A.; Vincent-Finley, R.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vyachanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Walker, M.; Wallace, L.; Wang, M.; Wang, X.; Ward, R. L.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Wiesner, K.; Wilkinson, C.; Williams, K.; Williams, L.; Williams, R.; Williams, T.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yancey, C. C.; Yang, H.; Yang, Z.; Yoshida, S.; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, Fan; Zhang, L.; Zhao, C.; Zhu, X. J.; Zucker, M. E.; Zuraw, S.; Zweizig, J.; LIGO; Virgo Collaboration

2014-12-01

Gravitational waves from a variety of sources are predicted to superpose to create a stochastic background. This background is expected to contain unique information from throughout the history of the Universe that is unavailable through standard electromagnetic observations, making its study of fundamental importance to understanding the evolution of the Universe. We carry out a search for the stochastic background with the latest data from the LIGO and Virgo detectors. Consistent with predictions from most stochastic gravitational-wave background models, the data display no evidence of a stochastic gravitational-wave signal. Assuming a gravitational-wave spectrum of ΩGW(f )=Ωα(f/fref ) α , we place 95% confidence level upper limits on the energy density of the background in each of four frequency bands spanning 41.5-1726 Hz. In the frequency band of 41.5-169.25 Hz for a spectral index of α =0 , we constrain the energy density of the stochastic background to be ΩGW(f )<5.6 ×1 0-6 . For the 600-1000 Hz band, ΩGW(f )<0.14 (f /900 Hz )3 , a factor of 2.5 lower than the best previously reported upper limits. We find ΩGW(f )<1.8 ×1 0-4 using a spectral index of zero for 170-600 Hz and ΩGW(f )<1.0 (f /1300 Hz )3 for 1000-1726 Hz, bands in which no previous direct limits have been placed. The limits in these four bands are the lowest direct measurements to date on the stochastic background. We discuss the implications of these results in light of the recent claim by the BICEP2 experiment of the possible evidence for inflationary gravitational waves.

Improved upper limits on the stochastic gravitational-wave background from 2009-2010 LIGO and Virgo data.

PubMed

Aasi, J; Abbott, B P; Abbott, R; Abbott, T; Abernathy, M R; Accadia, T; Acernese, F; Ackley, K; Adams, C; Adams, T; Addesso, P; Adhikari, R X; Affeldt, C; Agathos, M; Aggarwal, N; Aguiar, O D; Ain, A; Ajith, P; Alemic, A; Allen, B; Allocca, A; Amariutei, D; Andersen, M; Anderson, R; Anderson, S B; Anderson, W G; Arai, K; Araya, M C; Arceneaux, C; Areeda, J; Aston, S M; Astone, P; Aufmuth, P; Aulbert, C; Austin, L; Aylott, B E; Babak, S; Baker, P T; Ballardin, G; Ballmer, S W; Barayoga, J C; Barbet, M; Barish, B C; Barker, D; Barone, F; Barr, B; Barsotti, L; Barsuglia, M; Barton, M A; Bartos, I; Bassiri, R; Basti, A; Batch, J C; Bauchrowitz, J; Bauer, Th S; Behnke, B; Bejger, M; Beker, M G; Belczynski, C; Bell, A S; Bell, C; Bergmann, G; Bersanetti, D; Bertolini, A; Betzwieser, J; Beyersdorf, P T; Bilenko, I A; Billingsley, G; Birch, J; Biscans, S; Bitossi, M; Bizouard, M A; Black, E; Blackburn, J K; Blackburn, L; Blair, D; Bloemen, S; Blom, M; Bock, O; Bodiya, T P; Boer, M; Bogaert, G; Bogan, C; Bond, C; Bondu, F; Bonelli, L; Bonnand, R; Bork, R; Born, M; Boschi, V; Bose, Sukanta; Bosi, L; Bradaschia, C; Brady, P R; Braginsky, V B; Branchesi, M; Brau, J E; Briant, T; Bridges, D O; Brillet, A; Brinkmann, M; Brisson, V; Brooks, A F; Brown, D A; Brown, D D; Brückner, F; Buchman, S; Bulik, T; Bulten, H J; Buonanno, A; Burman, R; Buskulic, D; Buy, C; Cadonati, L; Cagnoli, G; Bustillo, J Calderón; Calloni, E; Camp, J B; Campsie, P; Cannon, K C; Canuel, B; Cao, J; Capano, C D; Carbognani, F; Carbone, L; Caride, S; Castiglia, A; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Celerier, C; Cella, G; Cepeda, C; Cesarini, E; Chakraborty, R; Chalermsongsak, T; Chamberlin, S J; Chao, S; Charlton, P; Chassande-Mottin, E; Chen, X; Chen, Y; Chincarini, A; Chiummo, A; Cho, H S; Chow, J; Christensen, N; Chu, Q; Chua, S S Y; Chung, S; Ciani, G; Clara, F; Clark, J A; Cleva, F; Coccia, E; Cohadon, P-F; Colla, A; Collette, C; Colombini, M; Cominsky, L; Constancio, M; Conte, A; Cook, D; Corbitt, T R; Cordier, M; Cornish, N; Corpuz, A; Corsi, A; Costa, C A; Coughlin, M W; Coughlin, S; Coulon, J-P; Countryman, S; Couvares, P; Coward, D M; Cowart, M; Coyne, D C; Coyne, R; Craig, K; Creighton, J D E; Crowder, S G; Cumming, A; Cunningham, L; Cuoco, E; Dahl, K; Canton, T Dal; Damjanic, M; Danilishin, S L; D'Antonio, S; Danzmann, K; Dattilo, V; Daveloza, H; Davier, M; Davies, G S; Daw, E J; Day, R; Dayanga, T; Debreczeni, G; Degallaix, J; Deléglise, S; Del Pozzo, W; Denker, T; Dent, T; Dereli, H; Dergachev, V; De Rosa, R; DeRosa, R T; DeSalvo, R; Dhurandhar, S; Díaz, M; Di Fiore, L; Di Lieto, A; Di Palma, I; Di Virgilio, A; Donath, A; Donovan, F; Dooley, K L; Doravari, S; Dossa, S; Douglas, R; Downes, T P; Drago, M; Drever, R W P; Driggers, J C; Du, Z; Dwyer, S; Eberle, T; Edo, T; Edwards, M; Effler, A; Eggenstein, H; Ehrens, P; Eichholz, J; Eikenberry, S S; Endrőczi, G; Essick, R; Etzel, T; Evans, M; Evans, T; Factourovich, M; Fafone, V; Fairhurst, S; Fang, Q; Farinon, S; Farr, B; Farr, W M; Favata, M; Fehrmann, H; Fejer, M M; Feldbaum, D; Feroz, F; Ferrante, I; Ferrini, F; Fidecaro, F; Finn, L S; Fiori, I; Fisher, R P; Flaminio, R; Fournier, J-D; Franco, S; Frasca, S; Frasconi, F; Frede, M; Frei, Z; Freise, A; Frey, R; Fricke, T T; Fritschel, P; Frolov, V V; Fulda, P; Fyffe, M; Gair, J; Gammaitoni, L; Gaonkar, S; Garufi, F; Gehrels, N; Gemme, G; Genin, E; Gennai, A; Ghosh, S; Giaime, J A; Giardina, K D; Giazotto, A; Gill, C; Gleason, J; Goetz, E; Goetz, R; Gondan, L; González, G; Gordon, N; Gorodetsky, M L; Gossan, S; Gossler, S; Gouaty, R; Gräf, C; Graff, P B; Granata, M; Grant, A; Gras, S; Gray, C; Greenhalgh, R J S; Gretarsson, A M; Groot, P; Grote, H; Grover, K; Grunewald, S; Guidi, G M; Guido, C; Gushwa, K; Gustafson, E K; Gustafson, R; Hammer, D; Hammond, G; Hanke, M; Hanks, J; Hanna, C; Hanson, J; Harms, J; Harry, G M; Harry, I W; Harstad, E D; Hart, M; Hartman, M T; Haster, C-J; Haughian, K; Heidmann, A; Heintze, M; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Heptonstall, A W; Heurs, M; Hewitson, M; Hild, S; Hoak, D; Hodge, K A; Holt, K; Hooper, S; Hopkins, P; Hosken, D J; Hough, J; Howell, E J; Hu, Y; Huerta, E; Hughey, B; Husa, S; Huttner, S H; Huynh, M; Huynh-Dinh, T; Ingram, D R; Inta, R; Isogai, T; Ivanov, A; Iyer, B R; Izumi, K; Jacobson, M; James, E; Jang, H; Jaranowski, P; Ji, Y; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; K, Haris; Kalmus, P; Kalogera, V; Kandhasamy, S; Kang, G; Kanner, J B; Karlen, J; Kasprzack, M; Katsavounidis, E; Katzman, W; Kaufer, H; Kawabe, K; Kawazoe, F; Kéfélian, F; Keiser, G M; Keitel, D; Kelley, D B; Kells, W; Khalaidovski, A; Khalili, F Y; Khazanov, E A; Kim, C; Kim, K; Kim, N; Kim, N G; Kim, Y-M; King, E J; King, P J; Kinzel, D L; Kissel, J S; Klimenko, S; Kline, J; Koehlenbeck, S; Kokeyama, K; Kondrashov, V; Koranda, S; Korth, W Z; Kowalska, I; Kozak, D B; Kremin, A; Kringel, V; Królak, A; Kuehn, G; Kumar, A; Kumar, P; Kumar, R; Kuo, L; Kutynia, A; Kwee, P; Landry, M; Lantz, B; Larson, S; Lasky, P D; Lawrie, C; Lazzarini, A; Lazzaro, C; Leaci, P; Leavey, S; Lebigot, E O; Lee, C-H; Lee, H K; Lee, H M; Lee, J; Leonardi, M; Leong, J R; Le Roux, A; Leroy, N; Letendre, N; Levin, Y; Levine, B; Lewis, J; Li, T G F; Libbrecht, K; Libson, A; Lin, A C; Littenberg, T B; Litvine, V; Lockerbie, N A; Lockett, V; Lodhia, D; Loew, K; Logue, J; Lombardi, A L; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J; Lubinski, M J; Lück, H; Luijten, E; Lundgren, A P; Lynch, R; Ma, Y; Macarthur, J; Macdonald, E P; MacDonald, T; Machenschalk, B; MacInnis, M; Macleod, D M; Magana-Sandoval, F; Mageswaran, M; Maglione, C; Mailand, K; Majorana, E; Maksimovic, I; Malvezzi, V; Man, N; Manca, G M; Mandel, I; Mandic, V; Mangano, V; Mangini, N; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markosyan, A; Maros, E; Marque, J; Martelli, F; Martin, I W; Martin, R M; Martinelli, L; Martynov, D; Marx, J N; Mason, K; Masserot, A; Massinger, T J; Matichard, F; Matone, L; Matzner, R A; Mavalvala, N; Mazumder, N; Mazzolo, G; McCarthy, R; McClelland, D E; McGuire, S C; McIntyre, G; McIver, J; McLin, K; Meacher, D; Meadors, G D; Mehmet, M; Meidam, J; Meinders, M; Melatos, A; Mendell, G; Mercer, R A; Meshkov, S; Messenger, C; Meyers, P; Miao, H; Michel, C; Mikhailov, E E; Milano, L; Milde, S; Miller, J; Minenkov, Y; Mingarelli, C M F; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moe, B; Moesta, P; Mohan, M; Mohapatra, S R P; Moraru, D; Moreno, G; Morgado, N; Morriss, S R; Mossavi, K; Mours, B; Mow-Lowry, C M; Mueller, C L; Mueller, G; Mukherjee, S; Mullavey, A; Munch, J; Murphy, D; Murray, P G; Mytidis, A; Nagy, M F; Kumar, D Nanda; Nardecchia, I; Naticchioni, L; Nayak, R K; Necula, V; Nelemans, G; Neri, I; Neri, M; Newton, G; Nguyen, T; Nitz, A; Nocera, F; Nolting, D; Normandin, M E N; Nuttall, L K; Ochsner, E; O'Dell, J; Oelker, E; Oh, J J; Oh, S H; Ohme, F; Oppermann, P; O'Reilly, B; O'Shaughnessy, R; Osthelder, C; Ottaway, D J; Ottens, R S; Overmier, H; Owen, B J; Padilla, C; Pai, A; Palashov, O; Palomba, C; Pan, H; Pan, Y; Pankow, C; Paoletti, F; Paoletti, R; Paris, H; Pasqualetti, A; Passaquieti, R; Passuello, D; Pedraza, M; Penn, S; Perreca, A; Phelps, M; Pichot, M; Pickenpack, M; Piergiovanni, F; Pierro, V; Pinard, L; Pinto, I M; Pitkin, M; Poeld, J; Poggiani, R; Poteomkin, A; Powell, J; Prasad, J; Premachandra, S; Prestegard, T; Price, L R; Prijatelj, M; Privitera, S; Prodi, G A; Prokhorov, L; Puncken, O; Punturo, M; Puppo, P; Qin, J; Quetschke, V; Quintero, E; Quiroga, G; Quitzow-James, R; Raab, F J; Rabeling, D S; Rácz, I; Radkins, H; Raffai, P; Raja, S; Rajalakshmi, G; Rakhmanov, M; Ramet, C; Ramirez, K; Rapagnani, P; Raymond, V; Re, V; Read, J; Reed, C M; Regimbau, T; Reid, S; Reitze, D H; Rhoades, E; Ricci, F; Riles, K; Robertson, N A; Robinet, F; Rocchi, A; Rodruck, M; Rolland, L; Rollins, J G; Romano, J D; Romano, R; Romanov, G; Romie, J H; Rosińska, D; Rowan, S; Rüdiger, A; Ruggi, P; Ryan, K; Salemi, F; Sammut, L; Sandberg, V; Sanders, J R; Sannibale, V; Santiago-Prieto, I; Saracco, E; Sassolas, B; Sathyaprakash, B S; Saulson, P R; Savage, R; Scheuer, J; Schilling, R; Schnabel, R; Schofield, R M S; Schreiber, E; Schuette, D; Schutz, B F; Scott, J; Scott, S M; Sellers, D; Sengupta, A S; Sentenac, D; Sequino, V; Sergeev, A; Shaddock, D; Shah, S; Shahriar, M S; Shaltev, M; Shapiro, B; Shawhan, P; Shoemaker, D H; Sidery, T L; Siellez, K; Siemens, X; Sigg, D; Simakov, D; Singer, A; Singer, L; Singh, R; Sintes, A M; Slagmolen, B J J; Slutsky, J; Smith, J R; Smith, M; Smith, R J E; Smith-Lefebvre, N D; Son, E J; Sorazu, B; Souradeep, T; Sperandio, L; Staley, A; Stebbins, J; Steinlechner, J; Steinlechner, S; Stephens, B C; Steplewski, S; Stevenson, S; Stone, R; Stops, D; Strain, K A; Straniero, N; Strigin, S; Sturani, R; Stuver, A L; Summerscales, T Z; Susmithan, S; Sutton, P J; Swinkels, B; Tacca, M; Talukder, D; Tanner, D B; Tarabrin, S P; Taylor, R; Ter Braack, A P M; Thirugnanasambandam, M P; Thomas, M; Thomas, P; Thorne, K A; Thorne, K S; Thrane, E; Tiwari, V; Tokmakov, K V; Tomlinson, C; Toncelli, A; Tonelli, M; Torre, O; Torres, C V; Torrie, C I; Travasso, F; Traylor, G; Tse, M; Ugolini, D; Unnikrishnan, C S; Urban, A L; Urbanek, K; Vahlbruch, H; Vajente, G; Valdes, G; Vallisneri, M; van den Brand, J F J; Van Den Broeck, C; van der Putten, S; van der Sluys, M V; van Heijningen, J; van Veggel, A A; Vass, S; Vasúth, M; Vaulin, R; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Verkindt, D; Verma, S S; Vetrano, F; Viceré, A; Vincent-Finley, R; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Vousden, W D; Vyachanin, S P; Wade, A; Wade, L; Wade, M; Walker, M; Wallace, L; Wang, M; Wang, X; Ward, R L; Was, M; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Welborn, T; Wen, L; Wessels, P; West, M; Westphal, T; Wette, K; Whelan, J T; White, D J; Whiting, B F; Wiesner, K; Wilkinson, C; Williams, K; Williams, L; Williams, R; Williams, T; Williamson, A R; Willis, J L; Willke, B; Wimmer, M; Winkler, W; Wipf, C C; Wiseman, A G; Wittel, H; Woan, G; Worden, J; Yablon, J; Yakushin, I; Yamamoto, H; Yancey, C C; Yang, H; Yang, Z; Yoshida, S; Yvert, M; Zadrożny, A; Zanolin, M; Zendri, J-P; Zhang, Fan; Zhang, L; Zhao, C; Zhu, X J; Zucker, M E; Zuraw, S; Zweizig, J

2014-12-05

Gravitational waves from a variety of sources are predicted to superpose to create a stochastic background. This background is expected to contain unique information from throughout the history of the Universe that is unavailable through standard electromagnetic observations, making its study of fundamental importance to understanding the evolution of the Universe. We carry out a search for the stochastic background with the latest data from the LIGO and Virgo detectors. Consistent with predictions from most stochastic gravitational-wave background models, the data display no evidence of a stochastic gravitational-wave signal. Assuming a gravitational-wave spectrum of Ω_{GW}(f)=Ω_{α}(f/f_{ref})^{α}, we place 95% confidence level upper limits on the energy density of the background in each of four frequency bands spanning 41.5-1726 Hz. In the frequency band of 41.5-169.25 Hz for a spectral index of α=0, we constrain the energy density of the stochastic background to be Ω_{GW}(f)<5.6×10^{-6}. For the 600-1000 Hz band, Ω_{GW}(f)<0.14(f/900  Hz)^{3}, a factor of 2.5 lower than the best previously reported upper limits. We find Ω_{GW}(f)<1.8×10^{-4} using a spectral index of zero for 170-600 Hz and Ω_{GW}(f)<1.0(f/1300  Hz)^{3} for 1000-1726 Hz, bands in which no previous direct limits have been placed. The limits in these four bands are the lowest direct measurements to date on the stochastic background. We discuss the implications of these results in light of the recent claim by the BICEP2 experiment of the possible evidence for inflationary gravitational waves.

Convection shapes the trade-off between antibiotic efficacy and the selection for resistance in spatial gradients.

PubMed

Gralka, Matti; Fusco, Diana; Martis, Stephen; Hallatschek, Oskar

2017-07-19

Since penicillin was discovered about 90 years ago, we have become used to using drugs to eradicate unwanted pathogenic cells. However, using drugs to kill bacteria, viruses or cancer cells has the serious side effect of selecting for mutant types that survive the drug attack. A crucial question therefore is how one could eradicate as many cells as possible for a given acceptable risk of drug resistance evolution. We address this general question in a model of drug resistance evolution in spatial drug gradients, which recent experiments and theories have suggested as key drivers of drug resistance. Importantly, our model takes into account the influence of convection, resulting for instance from blood flow. Using stochastic simulations, we study the fates of individual resistance mutations and quantify the trade-off between the killing of wild-type cells and the rise of resistance mutations: shallow gradients and convection into the antibiotic region promote wild-type death, at the cost of increasing the establishment probability of resistance mutations. We can explain these observed trends by modeling the adaptation process as a branching random walk. Our analysis reveals that the trade-off between death and adaptation depends on the relative length scales of the spatial drug gradient and random dispersal, and the strength of convection. Our results show that convection can have a momentous effect on the rate of establishment of new mutations, and may heavily impact the efficiency of antibiotic treatment.

Convection shapes the trade-off between antibiotic efficacy and the selection for resistance in spatial gradients

NASA Astrophysics Data System (ADS)

Gralka, Matti; Fusco, Diana; Martis, Stephen; Hallatschek, Oskar

2017-08-01

Since penicillin was discovered about 90 years ago, we have become used to using drugs to eradicate unwanted pathogenic cells. However, using drugs to kill bacteria, viruses or cancer cells has the serious side effect of selecting for mutant types that survive the drug attack. A crucial question therefore is how one could eradicate as many cells as possible for a given acceptable risk of drug resistance evolution. We address this general question in a model of drug resistance evolution in spatial drug gradients, which recent experiments and theories have suggested as key drivers of drug resistance. Importantly, our model takes into account the influence of convection, resulting for instance from blood flow. Using stochastic simulations, we study the fates of individual resistance mutations and quantify the trade-off between the killing of wild-type cells and the rise of resistance mutations: shallow gradients and convection into the antibiotic region promote wild-type death, at the cost of increasing the establishment probability of resistance mutations. We can explain these observed trends by modeling the adaptation process as a branching random walk. Our analysis reveals that the trade-off between death and adaptation depends on the relative length scales of the spatial drug gradient and random dispersal, and the strength of convection. Our results show that convection can have a momentous effect on the rate of establishment of new mutations, and may heavily impact the efficiency of antibiotic treatment.

Predicting Lg Coda Using Synthetic Seismograms and Media With Stochastic Heterogeneity

NASA Astrophysics Data System (ADS)

Tibuleac, I. M.; Stroujkova, A.; Bonner, J. L.; Mayeda, K.

2005-12-01

Recent examinations of the characteristics of coda-derived Sn and Lg spectra for yield estimation have shown that the spectral peak of Nevada Test Site (NTS) explosion spectra is depth-of-burial dependent, and that this peak is shifted to higher frequencies for Lop Nor explosions at the same depths. To confidently use coda-based yield formulas, we need to understand and predict coda spectral shape variations with depth, source media, velocity structure, topography, and geological heterogeneity. We present results of a coda modeling study to predict Lg coda. During the initial stages of this research, we have acquired and parameterized a deterministic 6 deg. x 6 deg. velocity and attenuation model centered on the Nevada Test Site. Near-source data are used to constrain density and attenuation profiles for the upper five km. The upper crust velocity profiles are quilted into a background velocity profile at depths greater than five km. The model is parameterized for use in a modified version of the Generalized Fourier Method in two dimensions (GFM2D). We modify this model to include stochastic heterogeneities of varying correlation lengths within the crust. Correlation length, Hurst number and fractional velocity perturbation of the heterogeneities are used to construct different realizations of the random media. We use nuclear explosion and earthquake cluster waveform analysis, as well as well log and geological information to constrain the stochastic parameters for a path between the NTS and the seismic stations near Mina, Nevada. Using multiple runs, we quantify the effects of variations in the stochastic parameters, of heterogeneity location in the crust and attenuation on coda amplitude and spectral characteristics. We calibrate these parameters by matching synthetic earthquake Lg coda envelopes to coda envelopes of local earthquakes with well-defined moments and mechanisms. We generate explosion synthetics for these calibrated deterministic and stochastic models. Secondary effects, including a compensated linear vector dipole source, are superposed on the synthetics in order to adequately characterize the Lg generation. We use this technique to characterize the effects of depth of burial on the coda spectral shapes.

Chewing on the trees: Constraints and adaptation in the evolution of the primate mandible.

PubMed

Meloro, Carlo; Cáceres, Nilton Carlos; Carotenuto, Francesco; Sponchiado, Jonas; Melo, Geruza Leal; Passaro, Federico; Raia, Pasquale

2015-07-01

Chewing on different food types is a demanding biological function. The classic assumption in studying the shape of feeding apparatuses is that animals are what they eat, meaning that adaptation to different food items accounts for most of their interspecific variation. Yet, a growing body of evidence points against this concept. We use the primate mandible as a model structure to investigate the complex interplay among shape, size, diet, and phylogeny. We find a weak but significant impact of diet on mandible shape variation in primates as a whole but not in anthropoids and catarrhines as tested in isolation. These clades mainly exhibit allometric shape changes, which are unrelated to diet. Diet is an important factor in the diversification of strepsirrhines and platyrrhines and a phylogenetic signal is detected in all primate clades. Peaks in morphological disparity occur during the Oligocene (between 37 and 25 Ma) supporting the notion that an adaptive radiation characterized the evolution of South American monkeys. In all primate clades, the evolution of mandible size is faster than its shape pointing to a strong effect of allometry on ecomorphological diversification in this group. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Synthesis and visible light photocatalytic property of polyhedron-shaped AgNbO3.

PubMed

Li, Guoqiang; Yan, Shicheng; Wang, Zhiqiang; Wang, Xiangyan; Li, Zhaosheng; Ye, Jinhua; Zou, Zhigang

2009-10-28

Polyhedron-shaped AgNbO3 photocatalysts were synthesized by solvothermal and liquid-solid methods. Their photocatalytic properties were evaluated from the photocatalytic O2 evolution under visible light irradiation. The polyhedron-shaped AgNbO3 was induced to grow by shaped silver particles followed by the free-growth model. The photocatalytic results indicate that the polyhedron-shaped morphology is favourable for the photocatalytic O2 evolution under visible light irradiation in comparison with the spherical one. Furthermore, the Cu doping on the surface would enhance the visible light photocatalytic activity significantly.

STOCHASTIC OPTICS: A SCATTERING MITIGATION FRAMEWORK FOR RADIO INTERFEROMETRIC IMAGING

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

Johnson, Michael D., E-mail: mjohnson@cfa.harvard.edu

2016-12-10

Just as turbulence in the Earth’s atmosphere can severely limit the angular resolution of optical telescopes, turbulence in the ionized interstellar medium fundamentally limits the resolution of radio telescopes. We present a scattering mitigation framework for radio imaging with very long baseline interferometry (VLBI) that partially overcomes this limitation. Our framework, “stochastic optics,” derives from a simplification of strong interstellar scattering to separate small-scale (“diffractive”) effects from large-scale (“refractive”) effects, thereby separating deterministic and random contributions to the scattering. Stochastic optics extends traditional synthesis imaging by simultaneously reconstructing an unscattered image and its refractive perturbations. Its advantages over direct imagingmore » come from utilizing the many deterministic properties of the scattering—such as the time-averaged “blurring,” polarization independence, and the deterministic evolution in frequency and time—while still accounting for the stochastic image distortions on large scales. These distortions are identified in the image reconstructions through regularization by their time-averaged power spectrum. Using synthetic data, we show that this framework effectively removes the blurring from diffractive scattering while reducing the spurious image features from refractive scattering. Stochastic optics can provide significant improvements over existing scattering mitigation strategies and is especially promising for imaging the Galactic Center supermassive black hole, Sagittarius A*, with the Global mm-VLBI Array and with the Event Horizon Telescope.« less

Characteristic effects of stochastic oscillatory forcing on neural firing: analytical theory and comparison to paddlefish electroreceptor data.

PubMed

Bauermeister, Christoph; Schwalger, Tilo; Russell, David F; Neiman, Alexander B; Lindner, Benjamin

2013-01-01

Stochastic signals with pronounced oscillatory components are frequently encountered in neural systems. Input currents to a neuron in the form of stochastic oscillations could be of exogenous origin, e.g. sensory input or synaptic input from a network rhythm. They shape spike firing statistics in a characteristic way, which we explore theoretically in this report. We consider a perfect integrate-and-fire neuron that is stimulated by a constant base current (to drive regular spontaneous firing), along with Gaussian narrow-band noise (a simple example of stochastic oscillations), and a broadband noise. We derive expressions for the nth-order interval distribution, its variance, and the serial correlation coefficients of the interspike intervals (ISIs) and confirm these analytical results by computer simulations. The theory is then applied to experimental data from electroreceptors of paddlefish, which have two distinct types of internal noisy oscillators, one forcing the other. The theory provides an analytical description of their afferent spiking statistics during spontaneous firing, and replicates a pronounced dependence of ISI serial correlation coefficients on the relative frequency of the driving oscillations, and furthermore allows extraction of certain parameters of the intrinsic oscillators embedded in these electroreceptors.

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

NASA Astrophysics Data System (ADS)

Sposini, Vittoria; Chechkin, Aleksei V.; Seno, Flavio; Pagnini, Gianni; Metzler, Ralf

2018-04-01

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential (Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time-dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.

Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background.

PubMed

Abbott, B P; Abbott, R; Abbott, T D; Acernese, F; Ackley, K; Adams, C; Adams, T; Addesso, P; Adhikari, R X; Adya, V B; Affeldt, C; Afrough, M; Agarwal, B; Agathos, M; Agatsuma, K; Aggarwal, N; Aguiar, O D; Aiello, L; Ain, A; Ajith, P; Allen, B; Allen, G; Allocca, A; Altin, P A; Amato, A; Ananyeva, A; Anderson, S B; Anderson, W G; Angelova, S V; Antier, S; Appert, S; Arai, K; Araya, M C; Areeda, J S; Arnaud, N; Ascenzi, S; Ashton, G; Ast, M; Aston, S M; Astone, P; Atallah, D V; Aufmuth, P; Aulbert, C; AultONeal, K; Austin, C; Avila-Alvarez, A; Babak, S; Bacon, P; Bader, M K M; Bae, S; Baker, P T; Baldaccini, F; Ballardin, G; Ballmer, S W; Banagiri, S; Barayoga, J C; Barclay, S E; Barish, B C; Barker, D; Barkett, K; Barone, F; Barr, B; Barsotti, L; Barsuglia, M; Barta, D; Bartlett, J; Bartos, I; Bassiri, R; Basti, A; Batch, J C; Bawaj, M; Bayley, J C; Bazzan, M; Bécsy, B; Beer, C; Bejger, M; Belahcene, I; Bell, A S; Berger, B K; Bergmann, G; Bero, J J; Berry, C P L; Bersanetti, D; Bertolini, A; Betzwieser, J; Bhagwat, S; Bhandare, R; Bilenko, I A; Billingsley, G; Billman, C R; Birch, J; Birney, R; Birnholtz, O; Biscans, S; Biscoveanu, S; Bisht, A; Bitossi, M; Biwer, C; Bizouard, M A; Blackburn, J K; Blackman, J; Blair, C D; Blair, D G; Blair, R M; Bloemen, S; Bock, O; Bode, N; Boer, M; Bogaert, G; Bohe, A; Bondu, F; Bonilla, E; Bonnand, R; Boom, B A; Bork, R; Boschi, V; Bose, S; Bossie, K; Bouffanais, Y; Bozzi, A; Bradaschia, C; Brady, P R; Branchesi, M; Brau, J E; Briant, T; Brillet, A; Brinkmann, M; Brisson, V; Brockill, P; Broida, J E; Brooks, A F; Brown, D A; Brown, D D; Brunett, S; Buchanan, C C; Buikema, A; Bulik, T; Bulten, H J; Buonanno, A; Buskulic, D; Buy, C; Byer, R L; Cabero, M; Cadonati, L; Cagnoli, G; Cahillane, C; Calderón Bustillo, J; Callister, T A; Calloni, E; Camp, J B; Canepa, M; Canizares, P; Cannon, K C; Cao, H; Cao, J; Capano, C D; Capocasa, E; Carbognani, F; Caride, S; Carney, M F; Diaz, J Casanueva; Casentini, C; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Cella, G; Cepeda, C B; Cerdá-Durán, P; Cerretani, G; Cesarini, E; Chamberlin, S J; Chan, M; Chao, S; Charlton, P; Chase, E; Chassande-Mottin, E; Chatterjee, D; Cheeseboro, B D; Chen, H Y; Chen, X; Chen, Y; Cheng, H-P; Chia, H; Chincarini, A; Chiummo, A; Chmiel, T; Cho, H S; Cho, M; Chow, J H; Christensen, N; Chu, Q; Chua, A J K; Chua, S; Chung, A K W; Chung, S; Ciani, G; Ciolfi, R; Cirelli, C E; Cirone, A; Clara, F; Clark, J A; Clearwater, P; Cleva, F; Cocchieri, C; Coccia, E; Cohadon, P-F; Cohen, D; Colla, A; Collette, C G; Cominsky, L R; Constancio, M; Conti, L; Cooper, S J; Corban, P; Corbitt, T R; Cordero-Carrión, I; Corley, K R; Cornish, N; Corsi, A; Cortese, S; Costa, C A; Coughlin, E; Coughlin, M W; Coughlin, S B; Coulon, J-P; Countryman, S T; Couvares, P; Covas, P B; Cowan, E E; Coward, D M; Cowart, M J; Coyne, D C; Coyne, R; Creighton, J D E; Creighton, T D; Cripe, J; Crowder, S G; Cullen, T J; Cumming, A; Cunningham, L; Cuoco, E; Canton, T Dal; Dálya, G; Danilishin, S L; D'Antonio, S; Danzmann, K; Dasgupta, A; Da Silva Costa, C F; Dattilo, V; Dave, I; Davier, M; Davis, D; Daw, E J; Day, B; De, S; DeBra, D; Degallaix, J; De Laurentis, M; Deléglise, S; Del Pozzo, W; Demos, N; Denker, T; Dent, T; De Pietri, R; Dergachev, V; De Rosa, R; DeRosa, R T; De Rossi, C; DeSalvo, R; de Varona, O; Devenson, J; Dhurandhar, S; Díaz, M C; Di Fiore, L; Di Giovanni, M; Di Girolamo, T; Di Lieto, A; Di Pace, S; Di Palma, I; Di Renzo, F; Doctor, Z; Dolique, V; Donovan, F; Dooley, K L; Doravari, S; Dorrington, I; Douglas, R; Dovale Álvarez, M; Downes, T P; Drago, M; Dreissigacker, C; Driggers, J C; Du, Z; Ducrot, M; Dupej, P; Dwyer, S E; Edo, T B; Edwards, M C; Effler, A; Eggenstein, H-B; Ehrens, P; Eichholz, J; Eikenberry, S S; Eisenstein, R A; Essick, R C; Estevez, D; Etienne, Z B; Etzel, T; Evans, M; Evans, T M; Factourovich, M; Fafone, V; Fair, H; Fairhurst, S; Fan, X; Farinon, S; Farr, B; Farr, W M; Fauchon-Jones, E J; Favata, M; Fays, M; Fee, C; Fehrmann, H; Feicht, J; Fejer, M M; Fernandez-Galiana, A; Ferrante, I; Ferreira, E C; Ferrini, F; Fidecaro, F; Finstad, D; Fiori, I; Fiorucci, D; Fishbach, M; Fisher, R P; Fitz-Axen, M; Flaminio, R; Fletcher, M; Fong, H; Font, J A; Forsyth, P W F; Forsyth, S S; Fournier, J-D; Frasca, S; Frasconi, F; Frei, Z; Freise, A; Frey, R; Frey, V; Fries, E M; Fritschel, P; Frolov, V V; Fulda, P; Fyffe, M; Gabbard, H; Gadre, B U; Gaebel, S M; Gair, J R; Gammaitoni, L; Ganija, M R; Gaonkar, S G; Garcia-Quiros, C; Garufi, F; Gateley, B; Gaudio, S; Gaur, G; Gayathri, V; Gehrels, N; Gemme, G; Genin, E; Gennai, A; George, D; George, J; Gergely, L; Germain, V; Ghonge, S; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S; Giaime, J A; Giardina, K D; Giazotto, A; Gill, K; Glover, L; Goetz, E; Goetz, R; Gomes, S; Goncharov, B; González, G; Gonzalez Castro, J M; Gopakumar, A; Gorodetsky, M L; Gossan, S E; Gosselin, M; Gouaty, R; Grado, A; Graef, C; Granata, M; Grant, A; Gras, S; Gray, C; Greco, G; Green, A C; Gretarsson, E M; Groot, P; Grote, H; Grunewald, S; Gruning, P; Guidi, G M; Guo, X; Gupta, A; Gupta, M K; Gushwa, K E; Gustafson, E K; Gustafson, R; Halim, O; Hall, B R; Hall, E D; Hamilton, E Z; Hammond, G; Haney, M; Hanke, M M; Hanks, J; Hanna, C; Hannam, M D; Hannuksela, O A; Hanson, J; Hardwick, T; Harms, J; Harry, G M; Harry, I W; Hart, M J; Haster, C-J; Haughian, K; Healy, J; Heidmann, A; Heintze, M C; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Hennig, J; Heptonstall, A W; Heurs, M; Hild, S; Hinderer, T; Hoak, D; Hofman, D; Holt, K; Holz, D E; Hopkins, P; Horst, C; Hough, J; Houston, E A; Howell, E J; Hreibi, A; Hu, Y M; Huerta, E A; Huet, D; Hughey, B; Husa, S; Huttner, S H; Huynh-Dinh, T; Indik, N; Inta, R; Intini, G; Isa, H N; Isac, J-M; Isi, M; Iyer, B R; Izumi, K; Jacqmin, T; Jani, K; Jaranowski, P; Jawahar, S; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; Junker, J; Kalaghatgi, C V; Kalogera, V; Kamai, B; Kandhasamy, S; Kang, G; Kanner, J B; Kapadia, S J; Karki, S; Karvinen, K S; Kasprzack, M; Katolik, M; Katsavounidis, E; Katzman, W; Kaufer, S; Kawabe, K; Kéfélian, F; Keitel, D; Kemball, A J; Kennedy, R; Kent, C; Key, J S; Khalili, F Y; Khan, I; Khan, S; Khan, Z; Khazanov, E A; Kijbunchoo, N; Kim, Chunglee; Kim, J C; Kim, K; Kim, W; Kim, W S; Kim, Y-M; Kimbrell, S J; King, E J; King, P J; Kinley-Hanlon, M; Kirchhoff, R; Kissel, J S; Kleybolte, L; Klimenko, S; Knowles, T D; Koch, P; Koehlenbeck, S M; Koley, S; Kondrashov, V; Kontos, A; Korobko, M; Korth, W Z; Kowalska, I; Kozak, D B; Krämer, C; Kringel, V; Królak, A; Kuehn, G; Kumar, P; Kumar, R; Kumar, S; Kuo, L; Kutynia, A; Kwang, S; Lackey, B D; Lai, K H; Landry, M; Lang, R N; Lange, J; Lantz, B; Lanza, R K; Lartaux-Vollard, A; Lasky, P D; Laxen, M; Lazzarini, A; Lazzaro, C; Leaci, P; Leavey, S; Lee, C H; Lee, H K; Lee, H M; Lee, H W; Lee, K; Lehmann, J; Lenon, A; Leonardi, M; Leroy, N; Letendre, N; Levin, Y; Li, T G F; Linker, S D; Littenberg, T B; Liu, J; Lo, R K L; Lockerbie, N A; London, L T; Lord, J E; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J D; Lousto, C O; Lovelace, G; Lück, H; Lumaca, D; Lundgren, A P; Lynch, R; Ma, Y; Macas, R; Macfoy, S; Machenschalk, B; MacInnis, M; Macleod, D M; Magaña Hernandez, I; Magaña-Sandoval, F; Magaña Zertuche, L; Magee, R M; Majorana, E; Maksimovic, I; Man, N; Mandic, V; Mangano, V; Mansell, G L; Manske, M; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markakis, C; Markosyan, A S; Markowitz, A; Maros, E; Marquina, A; Martelli, F; Martellini, L; Martin, I W; Martin, R M; Martynov, D V; Mason, K; Massera, E; Masserot, A; Massinger, T J; Masso-Reid, M; Mastrogiovanni, S; Matas, A; Matichard, F; Matone, L; Mavalvala, N; Mazumder, N; McCarthy, R; McClelland, D E; McCormick, S; McCuller, L; McGuire, S C; McIntyre, G; McIver, J; McManus, D J; McNeill, L; McRae, T; McWilliams, S T; Meacher, D; Meadors, G D; Mehmet, M; Meidam, J; Mejuto-Villa, E; Melatos, A; Mendell, G; Mercer, R A; Merilh, E L; Merzougui, M; Meshkov, S; Messenger, C; Messick, C; Metzdorff, R; Meyers, P M; Miao, H; Michel, C; Middleton, H; Mikhailov, E E; Milano, L; Miller, A L; Miller, B B; Miller, J; Millhouse, M; Milovich-Goff, M C; Minazzoli, O; Minenkov, Y; Ming, J; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moffa, D; Moggi, A; Mogushi, K; Mohan, M; Mohapatra, S R P; Montani, M; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mours, B; Mow-Lowry, C M; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Muñiz, E A; Muratore, M; Murray, P G; Napier, K; Nardecchia, I; Naticchioni, L; Nayak, R K; Neilson, J; Nelemans, G; Nelson, T J N; Nery, M; Neunzert, A; Nevin, L; Newport, J M; Newton, G; Ng, K K Y; Nguyen, T T; Nichols, D; Nielsen, A B; Nissanke, S; Nitz, A; Noack, A; Nocera, F; Nolting, D; North, C; Nuttall, L K; Oberling, J; O'Dea, G D; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Okada, M A; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; Ormiston, R; Ortega, L F; O'Shaughnessy, R; Ossokine, S; Ottaway, D J; Overmier, H; Owen, B J; Pace, A E; Page, J; Page, M A; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, Howard; Pan, Huang-Wei; Pang, B; Pang, P T H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Parida, A; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patil, M; Patricelli, B; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perez, C J; Perreca, A; Perri, L M; Pfeiffer, H P; Phelps, M; Piccinni, O J; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pirello, M; Pitkin, M; Poe, M; Poggiani, R; Popolizio, P; Porter, E K; Post, A; Powell, J; Prasad, J; Pratt, J W W; Pratten, G; Predoi, V; Prestegard, T; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L G; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rajan, C; Rajbhandari, B; Rakhmanov, M; Ramirez, K E; Ramos-Buades, A; Rapagnani, P; Raymond, V; Razzano, M; Read, J; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Ren, W; Reyes, S D; Ricci, F; Ricker, P M; Rieger, S; Riles, K; Rizzo, M; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romel, C L; Romie, J H; Rosińska, D; Ross, M P; Rowan, S; Rüdiger, A; Ruggi, P; Rutins, G; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Sakellariadou, M; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sampson, L M; Sanchez, E J; Sanchez, L E; Sanchis-Gual, N; Sandberg, V; Sanders, J R; Sassolas, B; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Scheel, M; Scheuer, J; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schulte, B W; Schutz, B F; Schwalbe, S G; Scott, J; Scott, S M; Seidel, E; Sellers, D; Sengupta, A S; Sentenac, D; Sequino, V; Sergeev, A; Shaddock, D A; Shaffer, T J; Shah, A A; Shahriar, M S; Shaner, M B; Shao, L; Shapiro, B; Shawhan, P; Sheperd, A; Shoemaker, D H; Shoemaker, D M; Siellez, K; Siemens, X; Sieniawska, M; Sigg, D; Silva, A D; Singer, L P; Singh, A; Singhal, A; Sintes, A M; Slagmolen, B J J; Smith, B; Smith, J R; Smith, R J E; Somala, S; Son, E J; Sonnenberg, J A; Sorazu, B; Sorrentino, F; Souradeep, T; Spencer, A P; Srivastava, A K; Staats, K; Staley, A; Steinke, M; Steinlechner, J; Steinlechner, S; Steinmeyer, D; Stevenson, S P; Stone, R; Stops, D J; Strain, K A; Stratta, G; Strigin, S E; Strunk, A; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, L; Sunil, S; Suresh, J; Sutton, P J; Swinkels, B L; Szczepańczyk, M J; Tacca, M; Tait, S C; Talbot, C; Talukder, D; Tanner, D B; Tao, D; Tápai, M; Taracchini, A; Tasson, J D; Taylor, J A; Taylor, R; Tewari, S V; Theeg, T; Thies, F; Thomas, E G; Thomas, M; Thomas, P; Thorne, K A; Thrane, E; Tiwari, S; Tiwari, V; Tokmakov, K V; Toland, K; Tonelli, M; Tornasi, Z; Torres-Forné, A; Torrie, C I; Töyrä, D; Travasso, F; Traylor, G; Trinastic, J; Tringali, M C; Trozzo, L; Tsang, K W; Tse, M; Tso, R; Tsukada, L; Tsuna, D; Tuyenbayev, D; Ueno, K; Ugolini, D; Unnikrishnan, C S; Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Varma, V; Vass, S; Vasúth, M; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Venugopalan, G; Verkindt, D; Vetrano, F; Viceré, A; Viets, A D; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walet, R; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, J Z; Wang, W H; Wang, Y F; Ward, R L; Warner, J; Was, M; Watchi, J; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Wessel, E K; Weßels, P; Westerweck, J; Westphal, T; Wette, K; Whelan, J T; Whiting, B F; Whittle, C; Wilken, D; Williams, D; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Woehler, J; Wofford, J; Wong, K W K; Worden, J; Wright, J L; Wu, D S; Wysocki, D M; Xiao, S; Yamamoto, H; Yancey, C C; Yang, L; Yap, M J; Yazback, M; Yu, Hang; Yu, Haocun; Yvert, M; Zadrożny, A; Zanolin, M; Zelenova, T; Zendri, J-P; Zevin, M; Zhang, L; Zhang, M; Zhang, T; Zhang, Y-H; Zhao, C; Zhou, M; Zhou, Z; Zhu, S J; Zhu, X J; Zucker, M E; Zweizig, J

2018-05-18

The detection of gravitational waves with Advanced LIGO and Advanced Virgo has enabled novel tests of general relativity, including direct study of the polarization of gravitational waves. While general relativity allows for only two tensor gravitational-wave polarizations, general metric theories can additionally predict two vector and two scalar polarizations. The polarization of gravitational waves is encoded in the spectral shape of the stochastic gravitational-wave background, formed by the superposition of cosmological and individually unresolved astrophysical sources. Using data recorded by Advanced LIGO during its first observing run, we search for a stochastic background of generically polarized gravitational waves. We find no evidence for a background of any polarization, and place the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background. Under log-uniform priors for the energy in each polarization, we limit the energy densities of tensor, vector, and scalar modes at 95% credibility to Ω_{0}^{T}<5.58×10^{-8}, Ω_{0}^{V}<6.35×10^{-8}, and Ω_{0}^{S}<1.08×10^{-7} at a reference frequency f_{0}=25  Hz.

Stochastic collective dynamics of charged-particle beams in the stability regime

NASA Astrophysics Data System (ADS)

Petroni, Nicola Cufaro; de Martino, Salvatore; de Siena, Silvio; Illuminati, Fabrizio

2001-01-01

We introduce a description of the collective transverse dynamics of charged (proton) beams in the stability regime by suitable classical stochastic fluctuations. In this scheme, the collective beam dynamics is described by time-reversal invariant diffusion processes deduced by stochastic variational principles (Nelson processes). By general arguments, we show that the diffusion coefficient, expressed in units of length, is given by λcN, where N is the number of particles in the beam and λc the Compton wavelength of a single constituent. This diffusion coefficient represents an effective unit of beam emittance. The hydrodynamic equations of the stochastic dynamics can be easily recast in the form of a Schrödinger equation, with the unit of emittance replacing the Planck action constant. This fact provides a natural connection to the so-called ``quantum-like approaches'' to beam dynamics. The transition probabilities associated to Nelson processes can be exploited to model evolutions suitable to control the transverse beam dynamics. In particular we show how to control, in the quadrupole approximation to the beam-field interaction, both the focusing and the transverse oscillations of the beam, either together or independently.

Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer.

PubMed

Roberts, James A; Friston, Karl J; Breakspear, Michael

2017-04-01

Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs). This article, Part I of a two-part series, offers a primer of SDMs and their application to large-scale neural systems in health and disease. The companion article, Part II, reviews the application of SDMs to brain disorders. SDMs generate a distribution of dynamic states, which (we argue) represent ideal candidates for modeling how the brain represents states of the world. When augmented with variational methods for model inversion, SDMs represent a powerful means of inferring neuronal dynamics from functional neuroimaging data in health and disease. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models.

PubMed

Daunizeau, J; Friston, K J; Kiebel, S J

2009-11-01

In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.

High-temperature morphological evolution of lithographically introduced cavities in silicon carbide

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

Narushima, Takayuki; Glaeser, Andreas M.

2000-12-01

Internal cavities of controlled geometry and crystallography were introduced in 6H silicon carbide single crystals by combining lithographic methods, ion beam etching, and solid-state diffusion bonding. The morphological evolution of these internal cavities (negative crystals) in response to anneals of up to 128 h duration at 1900 degrees C was examined using optical microscopy. Surface energy anisotropy and faceting have a strong influence on both the geometric and kinetic characteristics of evolution. Decomposition of 12{bar 1}0 cavity edges into 101{bar 0} facets was observed after 16 h anneals, indicating that 12{bar 1}0 faces are not components of the Wulff shape.more » The shape evolution kinetics of penny-shaped cavities were also investigated. Experimentally observed evolution rates decreased much more rapidly with those predicted by a model in which surface diffusion is assumed to be rate-limiting. This suggests that the development of facets, and the associated loss of ledges and terraces during the initial stages of evolution results in an evolution process limited by the nucleation rate of attachment/detachment sites (ledges) on the facets.« less

Image analysis methods for assessing levels of image plane nonuniformity and stochastic noise in a magnetic resonance image of a homogeneous phantom.

PubMed

Magnusson, P; Olsson, L E

2000-08-01

Magnetic response image plane nonuniformity and stochastic noise are properties that greatly influence the outcome of quantitative magnetic resonance imaging (MRI) evaluations such as gel dosimetry measurements using MRI. To study these properties, robust and accurate image analysis methods are required. New nonuniformity level assessment methods were designed, since previous methods were found to be insufficiently robust and accurate. The new and previously reported nonuniformity level assessment methods were analyzed with respect to, for example, insensitivity to stochastic noise; and previously reported stochastic noise level assessment methods with respect to insensitivity to nonuniformity. Using the same image data, different methods were found to assess significantly different levels of nonuniformity. Nonuniformity levels obtained using methods that count pixels in an intensity interval, and obtained using methods that use only intensity values, were found not to be comparable. The latter were found preferable, since they assess the quantity intrinsically sought. A new method which calculates a deviation image, with every pixel representing the deviation from a reference intensity, was least sensitive to stochastic noise. Furthermore, unlike any other analyzed method, it includes all intensity variations across the phantom area and allows for studies of nonuniformity shapes. This new method was designed for accurate studies of nonuniformities in gel dosimetry measurements, but could also be used with benefit in quality assurance and acceptance testing of MRI, scintillation camera, and computer tomography systems. The stochastic noise level was found to be greatly method dependent. Two methods were found to be insensitive to nonuniformity and also simple to use in practice. One method assesses the stochastic noise level as the average of the levels at five different positions within the phantom area, and the other assesses the stochastic noise in a region outside the phantom area.

Head shape evolution in Tropidurinae lizards: does locomotion constrain diet?

PubMed

Kohlsdorf, T; Grizante, M B; Navas, C A; Herrel, A

2008-05-01

Different components of complex integrated systems may be specialized for different functions, and thus the selective pressures acting on the system as a whole may be conflicting and can ultimately constrain organismal performance and evolution. The vertebrate cranial system is one of the most striking examples of a complex system with several possible functions, being associated to activities as different as locomotion, prey capture, display and defensive behaviours. Therefore, selective pressures on the cranial system as a whole are possibly complex and may be conflicting. The present study focuses on the influence of potentially conflicting selective pressures (diet vs. locomotion) on the evolution of head shape in Tropidurinae lizards. For example, the expected adaptations leading to flat heads and bodies in species living on vertical structures may conflict with the need for improved bite performance associated with the inclusion of hard or tough prey into the diet, a common phenomenon in Tropidurinae lizards. Body size and six variables describing head shape were quantified in preserved specimens of 23 species, and information on diet and substrate usage was obtained from the literature. No phylogenetic signal was observed in the morphological data at any branch length tested, suggesting adaptive evolution of head shape in Tropidurinae. This pattern was confirmed by both factor analysis and independent contrast analysis, which suggested adaptive co-variation between the head shape and the inclusion of hard prey into the diet. In contrast to our expectations, habitat use did not constrain or drive head shape evolution in the group.

Effects of Extrinsic Mortality on the Evolution of Aging: A Stochastic Modeling Approach

PubMed Central

Shokhirev, Maxim Nikolaievich; Johnson, Adiv Adam

2014-01-01

The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both classical and non-classical lifespan effects. PMID:24466165

Modeling the lake eutrophication stochastic ecosystem and the research of its stability.

PubMed

Wang, Bo; Qi, Qianqian

2018-06-01

In the reality, the lake system will be disturbed by stochastic factors including the external and internal factors. By adding the additive noise and the multiplicative noise to the right-hand sides of the model equation, the additive stochastic model and the multiplicative stochastic model are established respectively in order to reduce model errors induced by the absence of some physical processes. For both the two kinds of stochastic ecosystems, the authors studied the bifurcation characteristics with the FPK equation and the Lyapunov exponent method based on the Stratonovich-Khasminiskii stochastic average principle. Results show that, for the additive stochastic model, when control parameter (i.e., nutrient loading rate) falls into the interval [0.388644, 0.66003825], there exists bistability for the ecosystem and the additive noise intensities cannot make the bifurcation point drift. In the region of the bistability, the external stochastic disturbance which is one of the main triggers causing the lake eutrophication, may make the ecosystem unstable and induce a transition. When control parameter (nutrient loading rate) falls into the interval (0,  0.388644) and (0.66003825,  1.0), there only exists a stable equilibrium state and the additive noise intensity could not change it. For the multiplicative stochastic model, there exists more complex bifurcation performance and the multiplicative ecosystem will be broken by the multiplicative noise. Also, the multiplicative noise could reduce the extent of the bistable region, ultimately, the bistable region vanishes for sufficiently large noise. What's more, both the nutrient loading rate and the multiplicative noise will make the ecosystem have a regime shift. On the other hand, for the two kinds of stochastic ecosystems, the authors also discussed the evolution of the ecological variable in detail by using the Four-stage Runge-Kutta method of strong order γ=1.5. The numerical method was found to be capable of effectively explaining the regime shift theory and agreed with the realistic analyze. These conclusions also confirms the two paths for the system to move from one stable state to another proposed by Beisner et al. [3], which may help understand the occurrence mechanism related to the lake eutrophication from the view point of the stochastic model and mathematical analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES).

PubMed

Campos, Marcelino; Llorens, Carlos; Sempere, José M; Futami, Ricardo; Rodriguez, Irene; Carrasco, Purificación; Capilla, Rafael; Latorre, Amparo; Coque, Teresa M; Moya, Andres; Baquero, Fernando

2015-08-05

Antibiotic resistance is a major biomedical problem upon which public health systems demand solutions to construe the dynamics and epidemiological risk of resistant bacteria in anthropogenically-altered environments. The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances. Antibiotic resistance is not just the result of antibiotic-driven selection but more properly the consequence of a complex hierarchy of processes shaping the ecology and evolution of the distinct subcellular, cellular and supra-cellular vehicles involved in the dissemination of resistance genes. Such a complex background motivated us to explore the P-system standards of membrane computing an innovative natural computing formalism that abstracts the notion of movement across membranes to simulate antibiotic resistance evolution processes across nested levels of micro- and macro-environmental organization in a given ecosystem. In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis. The stochastic nature of the P-system model implemented in ARES explicitly links within and between host dynamics into a simulation, with feedback reciprocity among the different units of selection influenced by antibiotic exposure at various ecological levels. ARES offers the possibility of modeling predictive multilevel scenarios of antibiotic resistance evolution that can be interrogated, edited and re-simulated if necessary, with different parameters, until a correct model description of the process in the real world is convincingly approached. ARES can be accessed at http://gydb.org/ares.

Stochasticity, succession, and environmental perturbations in a fluidic ecosystem

PubMed Central

Zhou, Jizhong; Deng, Ye; Zhang, Ping; Xue, Kai; Liang, Yuting; Van Nostrand, Joy D.; Yang, Yunfeng; He, Zhili; Wu, Liyou; Stahl, David A.; Hazen, Terry C.; Tiedje, James M.; Arkin, Adam P.

2014-01-01

Unraveling the drivers of community structure and succession in response to environmental change is a central goal in ecology. Although the mechanisms shaping community structure have been intensively examined, those controlling ecological succession remain elusive. To understand the relative importance of stochastic and deterministic processes in mediating microbial community succession, a unique framework composed of four different cases was developed for fluidic and nonfluidic ecosystems. The framework was then tested for one fluidic ecosystem: a groundwater system perturbed by adding emulsified vegetable oil (EVO) for uranium immobilization. Our results revealed that groundwater microbial community diverged substantially away from the initial community after EVO amendment and eventually converged to a new community state, which was closely clustered with its initial state. However, their composition and structure were significantly different from each other. Null model analysis indicated that both deterministic and stochastic processes played important roles in controlling the assembly and succession of the groundwater microbial community, but their relative importance was time dependent. Additionally, consistent with the proposed conceptual framework but contradictory to conventional wisdom, the community succession responding to EVO amendment was primarily controlled by stochastic rather than deterministic processes. During the middle phase of the succession, the roles of stochastic processes in controlling community composition increased substantially, ranging from 81.3% to 92.0%. Finally, there are limited successional studies available to support different cases in the conceptual framework, but further well-replicated explicit time-series experiments are needed to understand the relative importance of deterministic and stochastic processes in controlling community succession. PMID:24550501

Etiology and treatment of hematological neoplasms: stochastic mathematical models.

PubMed

Radivoyevitch, Tomas; Li, Huamin; Sachs, Rainer K

2014-01-01

Leukemias are driven by stemlike cancer cells (SLCC), whose initiation, growth, response to treatment, and posttreatment behavior are often "stochastic", i.e., differ substantially even among very similar patients for reasons not observable with present techniques. We review the probabilistic mathematical methods used to analyze stochastics and give two specific examples. The first example concerns a treatment protocol, e.g., for acute myeloid leukemia (AML), where intermittent cytotoxic drug dosing (e.g., once each weekday) is used with intent to cure. We argue mathematically that, if independent SLCC are growing stochastically during prolonged treatment, then, other things being equal, front-loading doses are more effective for tumor eradication than back loading. We also argue that the interacting SLCC dynamics during treatment is often best modeled by considering SLCC in microenvironmental niches, with SLCC-SLCC interactions occurring only among SLCC within the same niche, and we present a stochastic dynamics formalism, involving "Poissonization," applicable in such situations. Interactions at a distance due to partial control of total cell numbers are also considered. The second half of this chapter concerns chromosomal aberrations, lesions known to cause some leukemias. A specific example is the induction of a Philadelphia chromosome by ionizing radiation, subsequent development of chronic myeloid leukemia (CML), CML treatment, and treatment outcome. This time evolution involves a coordinated sequence of > 10 steps, each stochastic in its own way, at the subatomic, molecular, macromolecular, cellular, tissue, and population scales, with corresponding time scales ranging from picoseconds to decades. We discuss models of these steps and progress in integrating models across scales.

Planetary Rings

NASA Astrophysics Data System (ADS)

Esposito, Larry

2014-03-01

Preface: a personal view of planetary rings; 1. Introduction: the allure of the ringed planets; 2. Studies of planetary rings 1610-2013; 3. Diversity of planetary rings; 4. Individual ring particles and their collisions; 5. Large-scale ring evolution; 6. Moons confine and sculpt rings; 7. Explaining ring phenomena; 8. N-body simulations; 9. Stochastic models; 10. Age and evolution of rings; 11. Saturn's mysterious F ring; 12. Uranus' rings and moons; 13. Neptune's partial rings; 14. Jupiter's ring-moon system after Galileo and New Horizons; 15. Ring photometry; 16. Dusty rings; 17. Concluding remarks; Afterword; Glossary; References; Index.

On spatial mutation-selection models

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

Kondratiev, Yuri, E-mail: kondrat@math.uni-bielefeld.de; Kutoviy, Oleksandr, E-mail: kutoviy@math.uni-bielefeld.de, E-mail: kutovyi@mit.edu; Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139

2013-11-15

We discuss the selection procedure in the framework of mutation models. We study the regulation for stochastically developing systems based on a transformation of the initial Markov process which includes a cost functional. The transformation of initial Markov process by cost functional has an analytic realization in terms of a Kimura-Maruyama type equation for the time evolution of states or in terms of the corresponding Feynman-Kac formula on the path space. The state evolution of the system including the limiting behavior is studied for two types of mutation-selection models.

Influence of stochastic geometric imperfections on the load-carrying behaviour of thin-walled structures using constrained random fields

NASA Astrophysics Data System (ADS)

Lauterbach, S.; Fina, M.; Wagner, W.

2018-04-01

Since structural engineering requires highly developed and optimized structures, the thickness dependency is one of the most controversially debated topics. This paper deals with stability analysis of lightweight thin structures combined with arbitrary geometrical imperfections. Generally known design guidelines only consider imperfections for simple shapes and loading, whereas for complex structures the lower-bound design philosophy still holds. Herein, uncertainties are considered with an empirical knockdown factor representing a lower bound of existing measurements. To fully understand and predict expected bearable loads, numerical investigations are essential, including geometrical imperfections. These are implemented into a stand-alone program code with a stochastic approach to compute random fields as geometric imperfections that are applied to nodes of the finite element mesh of selected structural examples. The stochastic approach uses the Karhunen-Loève expansion for the random field discretization. For this approach, the so-called correlation length l_c controls the random field in a powerful way. This parameter has a major influence on the buckling shape, and also on the stability load. First, the impact of the correlation length is studied for simple structures. Second, since most structures for engineering devices are more complex and combined structures, these are intensively discussed with the focus on constrained random fields for e.g. flange-web-intersections. Specific constraints for those random fields are pointed out with regard to the finite element model. Further, geometrical imperfections vanish where the structure is supported.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models.

PubMed

Oizumi, Ryo; Kuniya, Toshikazu; Enatsu, Yoichi

2016-01-01

Despite the fact that density effects and individual differences in life history are considered to be important for evolution, these factors lead to several difficulties in understanding the evolution of life history, especially when population sizes reach the carrying capacity. r/K selection theory explains what types of life strategies evolve in the presence of density effects and individual differences. However, the relationship between the life schedules of individuals and population size is still unclear, even if the theory can classify life strategies appropriately. To address this issue, we propose a few equations on adaptive life strategies in r/K selection where density effects are absent or present. The equations detail not only the adaptive life history but also the population dynamics. Furthermore, the equations can incorporate temporal individual differences, which are referred to as internal stochasticity. Our framework reveals that maximizing density effects is an evolutionarily stable strategy related to the carrying capacity. A significant consequence of our analysis is that adaptive strategies in both selections maximize an identical function, providing both population growth rate and carrying capacity. We apply our method to an optimal foraging problem in a semelparous species model and demonstrate that the adaptive strategy yields a lower intrinsic growth rate as well as a lower basic reproductive number than those obtained with other strategies. This study proposes that the diversity of life strategies arises due to the effects of density and internal stochasticity.

Has pollination mode shaped the evolution of ficus pollen?

PubMed

Wang, Gang; Chen, Jin; Li, Zong-Bo; Zhang, Feng-Ping; Yang, Da-Rong

2014-01-01

The extent to which co-evolutionary processes shape morphological traits is one of the most fascinating topics in evolutionary biology. Both passive and active pollination modes coexist in the fig tree (Ficus, Moraceae) and fig wasp (Agaonidae, Hymenoptera) mutualism. This classic obligate relationship that is about 75 million years old provides an ideal system to consider the role of pollination mode shifts on pollen evolution. Twenty-five fig species, which cover all six Ficus subgenera, and are native to the Xishuangbanna region of southwest China, were used to investigate pollen morphology with scanning electron microscope (SEM). Pollination mode was identified by the Anther/Ovule ratio in each species. Phylogenetic free regression and a correlated evolution test between binary traits were conducted based on a strong phylogenetic tree. Seventeen of the 25 fig species were actively pollinated and eight species were passively pollinated. Three pollen shape types and three kinds of exine ornamentation were recognized among these species. Pollen grains with ellipsoid shape and rugulate ornamentation were dominant. Ellipsoid pollen occurred in all 17 species of actively pollinated figs, while for the passively pollinated species, two obtuse end shapes were identified: cylinder and sphere shapes were identified in six of the eight species. All passively pollinated figs presented rugulate ornamentation, while for actively pollinated species, the smoother types - psilate and granulate-rugulate ornamentations - accounted for just five and two among the 17 species, respectively. The relationship between pollen shape and pollination mode was shown by both the phylogenetic free regression and the correlated evolution tests. Three pollen shape and ornamentation types were found in Ficus, which show characteristics related to passive or active pollination mode. Thus, the pollen shape is very likely shaped by pollination mode in this unique obligate mutualism.

Has Pollination Mode Shaped the Evolution of Ficus Pollen?

PubMed Central

Wang, Gang; Chen, Jin; Li, Zong-Bo; Zhang, Feng-Ping; Yang, Da-Rong

2014-01-01

Background The extent to which co-evolutionary processes shape morphological traits is one of the most fascinating topics in evolutionary biology. Both passive and active pollination modes coexist in the fig tree (Ficus, Moraceae) and fig wasp (Agaonidae, Hymenoptera) mutualism. This classic obligate relationship that is about 75 million years old provides an ideal system to consider the role of pollination mode shifts on pollen evolution. Methods and Main Findings Twenty-five fig species, which cover all six Ficus subgenera, and are native to the Xishuangbanna region of southwest China, were used to investigate pollen morphology with scanning electron microscope (SEM). Pollination mode was identified by the Anther/Ovule ratio in each species. Phylogenetic free regression and a correlated evolution test between binary traits were conducted based on a strong phylogenetic tree. Seventeen of the 25 fig species were actively pollinated and eight species were passively pollinated. Three pollen shape types and three kinds of exine ornamentation were recognized among these species. Pollen grains with ellipsoid shape and rugulate ornamentation were dominant. Ellipsoid pollen occurred in all 17 species of actively pollinated figs, while for the passively pollinated species, two obtuse end shapes were identified: cylinder and sphere shapes were identified in six of the eight species. All passively pollinated figs presented rugulate ornamentation, while for actively pollinated species, the smoother types - psilate and granulate-rugulate ornamentations - accounted for just five and two among the 17 species, respectively. The relationship between pollen shape and pollination mode was shown by both the phylogenetic free regression and the correlated evolution tests. Conclusions Three pollen shape and ornamentation types were found in Ficus, which show characteristics related to passive or active pollination mode. Thus, the pollen shape is very likely shaped by pollination mode in this unique obligate mutualism. PMID:24465976

External noise-induced transitions in a current-biased Josephson junction

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

Huang, Qiongwei; Xue, Changfeng, E-mail: cfxue@163.com; Tang, Jiashi

We investigate noise-induced transitions in a current-biased and weakly damped Josephson junction in the presence of multiplicative noise. By using the stochastic averaging procedure, the averaged amplitude equation describing dynamic evolution near a constant phase difference is derived. Numerical results show that a stochastic Hopf bifurcation between an absorbing and an oscillatory state occurs. This means the external controllable noise triggers a transition into the non-zero junction voltage state. With the increase of noise intensity, the stationary probability distribution peak shifts and is characterised by increased width and reduced height. And the different transition rates are shown for large andmore » small bias currents.« less

Shape Shifting Satellites in Binary Near-Earth Asteroids: Do Meteoroid Impacts Play a Role in BYORP Orbital Evolution?

NASA Technical Reports Server (NTRS)

Rubincam, David Parry

2012-01-01

Less than catastrophic meteoroid impacts over 10(exp 5) years may change the shape of small rubble-pile satellites in binary NEAs, lengthening the average BYORP (binary Yarkovsky-Radzievskii-Paddack) rate of orbital evolution. An estimate of shape-shifting meteoroid fluxes give numbers close enough to causing random walks in the semimajor axis of binary systems to warrant further investigation

A framework for longitudinal data analysis via shape regression

NASA Astrophysics Data System (ADS)

Fishbaugh, James; Durrleman, Stanley; Piven, Joseph; Gerig, Guido

2012-02-01

Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a polynomial of fixed degree. This type of analysis not only leads to separate models for each measurement, but there is no clear anatomical or biological interpretation to aid in the selection of the appropriate paradigm. In this paper, we propose a consistent framework for the analysis of longitudinal data by estimating the continuous evolution of shape over time as twice differentiable flows of deformations. In contrast to 1D regression models, one model is chosen to realistically capture the growth of anatomical structures. From the continuous evolution of shape, we can simply extract any clinical measurements of interest. We demonstrate on real anatomical surfaces that volume extracted from a continuous shape evolution is consistent with a 1D regression performed on the discrete measurements. We further show how the visualization of shape progression can aid in the search for significant measurements. Finally, we present an example on a shape complex of the brain (left hemisphere, right hemisphere, cerebellum) that demonstrates a potential clinical application for our framework.

Independent Axes of Genetic Variation and Parallel Evolutionary Divergence Of Opercle Bone Shape in Threespine Stickleback

PubMed Central

Kimmel, Charles B.; Cresko, William A.; Phillips, Patrick C.; Ullmann, Bonnie; Currey, Mark; von Hippel, Frank; Kristjánsson, Bjarni K.; Gelmond, Ofer; McGuigan, Katrina

2014-01-01

Evolution of similar phenotypes in independent populations is often taken as evidence of adaptation to the same fitness optimum. However, the genetic architecture of traits might cause evolution to proceed more often toward particular phenotypes, and less often toward others, independently of the adaptive value of the traits. Freshwater populations of Alaskan threespine stickleback have repeatedly evolved the same distinctive opercle shape after divergence from an oceanic ancestor. Here we demonstrate that this pattern of parallel evolution is widespread, distinguishing oceanic and freshwater populations across the Pacific Coast of North America and Iceland. We test whether this parallel evolution reflects genetic bias by estimating the additive genetic variance– covariance matrix (G) of opercle shape in an Alaskan oceanic (putative ancestral) population. We find significant additive genetic variance for opercle shape and that G has the potential to be biasing, because of the existence of regions of phenotypic space with low additive genetic variation. However, evolution did not occur along major eigenvectors of G, rather it occurred repeatedly in the same directions of high evolvability. We conclude that the parallel opercle evolution is most likely due to selection during adaptation to freshwater habitats, rather than due to biasing effects of opercle genetic architecture. PMID:22276538

Shape evolution of a melting nonspherical particle

NASA Astrophysics Data System (ADS)

Kintea, Daniel M.; Hauk, Tobias; Roisman, Ilia V.; Tropea, Cameron

2015-09-01

In this study melting of irregular ice crystals was observed in an acoustic levitator. The evolution of the particle shape is captured using a high-speed video system. Several typical phenomena have been discovered: change of the particle shape, appearance of a capillary flow of the melted liquid on the particle surface leading to liquid collection at the particle midsection (where the interface curvature is smallest), and appearance of sharp cusps at the particle tips. No such phenomena can be observed during melting of spherical particles. An approximate theoretical model is developed which accounts for the main physical phenomena associated with melting of an irregular particle. The agreement between the theoretical predictions for the melting time, for the evolution of the particle shape, and the corresponding experimental data is rather good.

Adaptive economic and ecological forest management under risk

Treesearch

Joseph Buongiorno; Mo Zhou

2015-01-01

Background: Forest managers must deal with inherently stochastic ecological and economic processes. The future growth of trees is uncertain, and so is their value. The randomness of low-impact, high frequency or rare catastrophic shocks in forest growth has significant implications in shaping the mix of tree species and the forest landscape...

Niche versus neutrality: a dynamical analysis

Treesearch

Michael Kalyuzhny; Efrat Seri; Rachel Chocron; Curtis H. Flather; Ronen Kadmon; Nadav M. Shnerb

2014-01-01

Understanding the forces shaping ecological communities is of crucial importance for basic science and conservation. After 50 years in which ecological theory has focused on either stable communities driven by niche-based forces or nonstable “neutral” communities driven by demographic stochasticity, contemporary theories suggest that ecological communities are driven...

Stochastic modelling of intermittent fluctuations in the scrape-off layer: Correlations, distributions, level crossings, and moment estimation

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

Garcia, O. E., E-mail: odd.erik.garcia@uit.no; Kube, R.; Theodorsen, A.

A stochastic model is presented for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas. The fluctuations in the plasma density are modeled by a super-position of uncorrelated pulses with fixed shape and duration, describing radial motion of blob-like structures. In the case of an exponential pulse shape and exponentially distributed pulse amplitudes, predictions are given for the lowest order moments, probability density function, auto-correlation function, level crossings, and average times for periods spent above and below a given threshold level. Also, the mean squared errors on estimators of sample mean and variance for realizations of the process bymore » finite time series are obtained. These results are discussed in the context of single-point measurements of fluctuations in the scrape-off layer, broad density profiles, and implications for plasma–wall interactions due to the transient transport events in fusion grade plasmas. The results may also have wide applications for modelling fluctuations in other magnetized plasmas such as basic laboratory experiments and ionospheric irregularities.« less

Programmable and coherent crystallization of semiconductors

PubMed Central

Yu, Liyang; Niazi, Muhammad R.; Ngongang Ndjawa, Guy O.; Li, Ruipeng; Kirmani, Ahmad R.; Munir, Rahim; Balawi, Ahmed H.; Laquai, Frédéric; Amassian, Aram

2017-01-01

The functional properties and technological utility of polycrystalline materials are largely determined by the structure, geometry, and spatial distribution of their multitude of crystals. However, crystallization is seeded through stochastic and incoherent nucleation events, limiting the ability to control or pattern the microstructure, texture, and functional properties of polycrystalline materials. We present a universal approach that can program the microstructure of materials through the coherent seeding of otherwise stochastic homogeneous nucleation events. The method relies on creating topographic variations to seed nucleation and growth at designated locations while delaying nucleation elsewhere. Each seed can thus produce a coherent growth front of crystallization with a geometry designated by the shape and arrangement of seeds. Periodic and aperiodic crystalline arrays of functional materials, such as semiconductors, can thus be created on demand and with unprecedented sophistication and ease by patterning the location and shape of the seeds. This approach is used to demonstrate printed arrays of organic thin-film transistors with remarkable performance and reproducibility owing to their demonstrated spatial control over the microstructure of organic and inorganic polycrystalline semiconductors. PMID:28275737

Stochastic Nonlinear Response of Woven CMCs

NASA Technical Reports Server (NTRS)

Kuang, C. Liu; Arnold, Steven M.

2013-01-01

It is well known that failure of a material is a locally driven event. In the case of ceramic matrix composites (CMCs), significant variations in the microstructure of the composite exist and their significance on both deformation and life response need to be assessed. Examples of these variations include changes in the fiber tow shape, tow shifting/nesting and voids within and between tows. In the present work, the influence of scale specific architectural features of woven ceramic composite are examined stochastically at both the macroscale (woven repeating unit cell (RUC)) and structural scale (idealized using multiple RUCs). The recently developed MultiScale Generalized Method of Cells methodology is used to determine the overall deformation response, proportional elastic limit (first matrix cracking), and failure under tensile loading conditions and associated probability distribution functions. Prior results showed that the most critical architectural parameter to account for is weave void shape and content with other parameters being less in severity. Current results show that statistically only the post-elastic limit region (secondary hardening modulus and ultimate tensile strength) is impacted by local uncertainties both at the macro and structural level.

Long-term strength and damage accumulation in laminates

NASA Astrophysics Data System (ADS)

Dzenis, Yuris A.; Joshi, Shiv P.

1993-04-01

A modified version of the probabilistic model developed by authors for damage evolution analysis of laminates subjected to random loading is utilized to predict long-term strength of laminates. The model assumes that each ply in a laminate consists of a large number of mesovolumes. Probabilistic variation functions for mesovolumes stiffnesses as well as strengths are used in the analysis. Stochastic strains are calculated using the lamination theory and random function theory. Deterioration of ply stiffnesses is calculated on the basis of the probabilities of mesovolumes failures using the theory of excursions of random process beyond the limits. Long-term strength and damage accumulation in a Kevlar/epoxy laminate under tension and complex in-plane loading are investigated. Effects of the mean level and stochastic deviation of loading on damage evolution and time-to-failure of laminate are discussed. Long-term cumulative damage at the time of the final failure at low loading levels is more than at high loading levels. The effect of the deviation in loading is more pronounced at lower mean loading levels.

Evolution of fairness and coalition formation in three-person ultimatum games.

PubMed

Nishimura, Takeshi; Okada, Akira; Shirata, Yasuhiro

2017-05-07

We consider the evolution of fairness and coalition formation in a three-person ultimatum game in which the coalition value depends on its size. Traditional game theory, which assumes selfish and rational players, predicts the largest and efficient coalition with a proposer exploiting most of the total value. In a stochastic evolutionary model (the frequency-dependent Moran process with mutations) where players make errors in estimating the payoffs and strategies of others, evolutionary selection favors the formation of a two-person subcoalition under weak selection and in the low mutation limit if and only if its coalition value exceeds a high proportion (0.7) of that of the largest coalition. Proposers offer 30-35% of the subcoalition value to a coalition member, excluding a non-member. Multilateral bargaining is critically different from the bilateral one. Coalition-forming behavior may cause economic inefficiency and social exclusion. Stochastic evolutionary game theory thus provides theoretical support to explain the behavior of human subjects in economic experiments of a three-person ultimatum game. Copyright © 2017 Elsevier Ltd. All rights reserved.

Single-shot quantum state estimation via a continuous measurement in the strong backaction regime

NASA Astrophysics Data System (ADS)

Cook, Robert L.; Riofrío, Carlos A.; Deutsch, Ivan H.

2014-09-01

We study quantum tomography based on a stochastic continuous-time measurement record obtained from a probe field collectively interacting with an ensemble of identically prepared systems. In comparison to previous studies, we consider here the case in which the measurement-induced backaction has a non-negligible effect on the dynamical evolution of the ensemble. We formulate a maximum likelihood estimate for the initial quantum state given only a single instance of the continuous diffusive measurement record. We apply our estimator to the simplest problem: state tomography of a single pure qubit, which, during the course of the measurement, is also subjected to dynamical control. We identify a regime where the many-body system is well approximated at all times by a separable pure spin coherent state, whose Bloch vector undergoes a conditional stochastic evolution. We simulate the results of our estimator and show that we can achieve close to the upper bound of fidelity set by the optimal generalized measurement. This estimate is compared to, and significantly outperforms, an equivalent estimator that ignores measurement backaction.

Evolution of Body Elongation in Gymnophthalmid Lizards: Relationships with Climate

PubMed Central

Grizante, Mariana B.; Brandt, Renata; Kohlsdorf, Tiana

2012-01-01

The evolution of elongated body shapes in vertebrates has intrigued biologists for decades and is particularly recurrent among squamates. Several aspects might explain how the environment influences the evolution of body elongation, but climate needs to be incorporated in this scenario to evaluate how it contributes to morphological evolution. Climatic parameters include temperature and precipitation, two variables that likely influence environmental characteristics, including soil texture and substrate coverage, which may define the selective pressures acting during the evolution of morphology. Due to development of geographic information system (GIS) techniques, these variables can now be included in evolutionary biology studies and were used in the present study to test for associations between variation in body shape and climate in the tropical lizard family Gymnophthalmidae. We first investigated how the morphological traits that define body shape are correlated in these lizards and then tested for associations between a descriptor of body elongation and climate. Our analyses revealed that the evolution of body elongation in Gymnophthalmidae involved concomitant changes in different morphological traits: trunk elongation was coupled with limb shortening and a reduction in body diameter, and the gradual variation along this axis was illustrated by less-elongated morphologies exhibiting shorter trunks and longer limbs. The variation identified in Gymnophthalmidae body shape was associated with climate, with the species from more arid environments usually being more elongated. Aridity is associated with high temperatures and low precipitation, which affect additional environmental features, including the habitat structure. This feature may influence the evolution of body shape because contrasting environments likely impose distinct demands for organismal performance in several activities, such as locomotion and thermoregulation. The present study establishes a connection between morphology and a broader natural component, climate, and introduces new questions about the spatial distribution of morphological variation among squamates. PMID:23166767

Model parameter estimations from residual gravity anomalies due to simple-shaped sources using Differential Evolution Algorithm

NASA Astrophysics Data System (ADS)

Ekinci, Yunus Levent; Balkaya, Çağlayan; Göktürkler, Gökhan; Turan, Seçil

2016-06-01

An efficient approach to estimate model parameters from residual gravity data based on differential evolution (DE), a stochastic vector-based metaheuristic algorithm, has been presented. We have showed the applicability and effectiveness of this algorithm on both synthetic and field anomalies. According to our knowledge, this is a first attempt of applying DE for the parameter estimations of residual gravity anomalies due to isolated causative sources embedded in the subsurface. The model parameters dealt with here are the amplitude coefficient (A), the depth and exact origin of causative source (zo and xo, respectively) and the shape factors (q and ƞ). The error energy maps generated for some parameter pairs have successfully revealed the nature of the parameter estimation problem under consideration. Noise-free and noisy synthetic single gravity anomalies have been evaluated with success via DE/best/1/bin, which is a widely used strategy in DE. Additionally some complicated gravity anomalies caused by multiple source bodies have been considered, and the results obtained have showed the efficiency of the algorithm. Then using the strategy applied in synthetic examples some field anomalies observed for various mineral explorations such as a chromite deposit (Camaguey district, Cuba), a manganese deposit (Nagpur, India) and a base metal sulphide deposit (Quebec, Canada) have been considered to estimate the model parameters of the ore bodies. Applications have exhibited that the obtained results such as the depths and shapes of the ore bodies are quite consistent with those published in the literature. Uncertainty in the solutions obtained from DE algorithm has been also investigated by Metropolis-Hastings (M-H) sampling algorithm based on simulated annealing without cooling schedule. Based on the resulting histogram reconstructions of both synthetic and field data examples the algorithm has provided reliable parameter estimations being within the sampling limits of M-H sampler. Although it is not a common inversion technique in geophysics, it can be stated that DE algorithm is worth to get more interest for parameter estimations from potential field data in geophysics considering its good accuracy, less computational cost (in the present problem) and the fact that a well-constructed initial guess is not required to reach the global minimum.

Superstatistical generalised Langevin equation: non-Gaussian viscoelastic anomalous diffusion

NASA Astrophysics Data System (ADS)

Ślęzak, Jakub; Metzler, Ralf; Magdziarz, Marcin

2018-02-01

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

NASA Astrophysics Data System (ADS)

Chen, Xianshun; Feng, Liang; Ong, Yew Soon

2012-07-01

In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

Time-Frequency Approach for Stochastic Signal Detection

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

Ghosh, Ripul; Akula, Aparna; Kumar, Satish

2011-10-20

The detection of events in a stochastic signal has been a subject of great interest. One of the oldest signal processing technique, Fourier Transform of a signal contains information regarding frequency content, but it cannot resolve the exact onset of changes in the frequency, all temporal information is contained in the phase of the transform. On the other hand, Spectrogram is better able to resolve temporal evolution of frequency content, but has a trade-off in time resolution versus frequency resolution in accordance with the uncertainty principle. Therefore, time-frequency representations are considered for energetic characterisation of the non-stationary signals. Wigner Villemore » Distribution (WVD) is the most prominent quadratic time-frequency signal representation and used for analysing frequency variations in signals.WVD allows for instantaneous frequency estimation at each data point, for a typical temporal resolution of fractions of a second. This paper through simulations describes the way time frequency models are applied for the detection of event in a stochastic signal.« less

Time-Frequency Approach for Stochastic Signal Detection

NASA Astrophysics Data System (ADS)

Ghosh, Ripul; Akula, Aparna; Kumar, Satish; Sardana, H. K.

2011-10-01

The detection of events in a stochastic signal has been a subject of great interest. One of the oldest signal processing technique, Fourier Transform of a signal contains information regarding frequency content, but it cannot resolve the exact onset of changes in the frequency, all temporal information is contained in the phase of the transform. On the other hand, Spectrogram is better able to resolve temporal evolution of frequency content, but has a trade-off in time resolution versus frequency resolution in accordance with the uncertainty principle. Therefore, time-frequency representations are considered for energetic characterisation of the non-stationary signals. Wigner Ville Distribution (WVD) is the most prominent quadratic time-frequency signal representation and used for analysing frequency variations in signals.WVD allows for instantaneous frequency estimation at each data point, for a typical temporal resolution of fractions of a second. This paper through simulations describes the way time frequency models are applied for the detection of event in a stochastic signal.

Rogue waves and entropy consumption

NASA Astrophysics Data System (ADS)

Hadjihoseini, Ali; Lind, Pedro G.; Mori, Nobuhito; Hoffmann, Norbert P.; Peinke, Joachim

2017-11-01

Based on data from the Sea of Japan and the North Sea the occurrence of rogue waves is analyzed by a scale-dependent stochastic approach, which interlinks fluctuations of waves for different spacings. With this approach we are able to determine a stochastic cascade process, which provides information of the general multipoint statistics. Furthermore the evolution of single trajectories in scale, which characterize wave height fluctuations in the surroundings of a chosen location, can be determined. The explicit knowledge of the stochastic process enables to assign entropy values to all wave events. We show that for these entropies the integral fluctuation theorem, a basic law of non-equilibrium thermodynamics, is valid. This implies that positive and negative entropy events must occur. Extreme events like rogue waves are characterized as negative entropy events. The statistics of these entropy fluctuations changes with the wave state, thus for the Sea of Japan the statistics of the entropies has a more pronounced tail for negative entropy values, indicating a higher probability of rogue waves.

Modified parton branching model for multi-particle production in hadronic collisions: Application to SUSY particle branching

NASA Astrophysics Data System (ADS)

Yuanyuan, Zhang

The stochastic branching model of multi-particle productions in high energy collision has theoretical basis in perturbative QCD, and also successfully describes the experimental data for a wide energy range. However, over the years, little attention has been put on the branching model for supersymmetric (SUSY) particles. In this thesis, a stochastic branching model has been built to describe the pure supersymmetric particle jets evolution. This model is a modified two-phase stochastic branching process, or more precisely a two phase Simple Birth Process plus Poisson Process. The general case that the jets contain both ordinary particle jets and supersymmetric particle jets has also been investigated. We get the multiplicity distribution of the general case, which contains a Hypergeometric function in its expression. We apply this new multiplicity distribution to the current experimental data of pp collision at center of mass energy √s = 0.9, 2.36, 7 TeV. The fitting shows the supersymmetric particles haven't participate branching at current collision energy.

Generalized stochastic resonance for a fractional harmonic oscillator with bias-signal-modulated trichotomous noise

NASA Astrophysics Data System (ADS)

Lin, Lifeng; Wang, Huiqi; Huang, Xipei; Wen, Yongxian

2018-03-01

For a fractional linear oscillator subjected to both parametric excitation of trichotomous noise and external excitation of bias-signal-modulated trichotomous noise, the generalized stochastic resonance (GSR) phenomena are investigated in this paper in case the noises are cross-correlative. First, the generalized Shapiro-Loginov formula and generalized fractional Shapiro-Loginov formula are derived. Then, by using the generalized (fractional) Shapiro-Loginov formula and the Laplace transformation technique, the exact expression of the first-order moment of the system’s steady response is obtained. The numerical results show that the evolution of the output amplitude amplification is nonmonotonic with the frequency of periodic signal, the noise parameters, and the fractional order. The GSR phenomena, including single-peak GSR, double-peak GSR and triple-peak GSR, are observed in this system. In addition, the interplay of the multiplicative trichotomous noise, bias-signal-modulated trichotomous noise and memory can induce and diversify the stochastic multi-resonance (SMR) phenomena, and the two kinds of trichotomous noises play opposite roles on the GSR.

Political model of social evolution

PubMed Central

Acemoglu, Daron; Egorov, Georgy; Sonin, Konstantin

2011-01-01

Almost all democratic societies evolved socially and politically out of authoritarian and nondemocratic regimes. These changes not only altered the allocation of economic resources in society but also the structure of political power. In this paper, we develop a framework for studying the dynamics of political and social change. The society consists of agents that care about current and future social arrangements and economic allocations; allocation of political power determines who has the capacity to implement changes in economic allocations and future allocations of power. The set of available social rules and allocations at any point in time is stochastic. We show that political and social change may happen without any stochastic shocks or as a result of a shock destabilizing an otherwise stable social arrangement. Crucially, the process of social change is contingent (and history-dependent): the timing and sequence of stochastic events determine the long-run equilibrium social arrangements. For example, the extent of democratization may depend on how early uncertainty about the set of feasible reforms in the future is resolved. PMID:22198760

Political model of social evolution.

PubMed

Acemoglu, Daron; Egorov, Georgy; Sonin, Konstantin

2011-12-27

Almost all democratic societies evolved socially and politically out of authoritarian and nondemocratic regimes. These changes not only altered the allocation of economic resources in society but also the structure of political power. In this paper, we develop a framework for studying the dynamics of political and social change. The society consists of agents that care about current and future social arrangements and economic allocations; allocation of political power determines who has the capacity to implement changes in economic allocations and future allocations of power. The set of available social rules and allocations at any point in time is stochastic. We show that political and social change may happen without any stochastic shocks or as a result of a shock destabilizing an otherwise stable social arrangement. Crucially, the process of social change is contingent (and history-dependent): the timing and sequence of stochastic events determine the long-run equilibrium social arrangements. For example, the extent of democratization may depend on how early uncertainty about the set of feasible reforms in the future is resolved.

Extinction time of a stochastic predator-prey model by the generalized cell mapping method

NASA Astrophysics Data System (ADS)

Han, Qun; Xu, Wei; Hu, Bing; Huang, Dongmei; Sun, Jian-Qiao

2018-03-01

The stochastic response and extinction time of a predator-prey model with Gaussian white noise excitations are studied by the generalized cell mapping (GCM) method based on the short-time Gaussian approximation (STGA). The methods for stochastic response probability density functions (PDFs) and extinction time statistics are developed. The Taylor expansion is used to deal with non-polynomial nonlinear terms of the model for deriving the moment equations with Gaussian closure, which are needed for the STGA in order to compute the one-step transition probabilities. The work is validated with direct Monte Carlo simulations. We have presented the transient responses showing the evolution from a Gaussian initial distribution to a non-Gaussian steady-state one. The effects of the model parameter and noise intensities on the steady-state PDFs are discussed. It is also found that the effects of noise intensities on the extinction time statistics are opposite to the effects on the limit probability distributions of the survival species.

An adaptive tau-leaping method for stochastic simulations of reaction-diffusion systems

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

Padgett, Jill M. A.; Ilie, Silvana, E-mail: silvana@ryerson.ca

2016-03-15

Stochastic modelling is critical for studying many biochemical processes in a cell, in particular when some reacting species have low population numbers. For many such cellular processes the spatial distribution of the molecular species plays a key role. The evolution of spatially heterogeneous biochemical systems with some species in low amounts is accurately described by the mesoscopic model of the Reaction-Diffusion Master Equation. The Inhomogeneous Stochastic Simulation Algorithm provides an exact strategy to numerically solve this model, but it is computationally very expensive on realistic applications. We propose a novel adaptive time-stepping scheme for the tau-leaping method for approximating themore » solution of the Reaction-Diffusion Master Equation. This technique combines effective strategies for variable time-stepping with path preservation to reduce the computational cost, while maintaining the desired accuracy. The numerical tests on various examples arising in applications show the improved efficiency achieved by the new adaptive method.« less

A unified model of the hierarchical and stochastic theories of gastric cancer

PubMed Central

Song, Yanjing; Wang, Yao; Tong, Chuan; Xi, Hongqing; Zhao, Xudong; Wang, Yi; Chen, Lin

2017-01-01

Gastric cancer (GC) is a life-threatening disease worldwide. Despite remarkable advances in treatments for GC, it is still fatal to many patients due to cancer progression, recurrence and metastasis. Regarding the development of novel therapeutic techniques, many studies have focused on the biological mechanisms that initiate tumours and cause treatment resistance. Tumours have traditionally been considered to result from somatic mutations, either via clonal evolution or through a stochastic model. However, emerging evidence has characterised tumours using a hierarchical organisational structure, with cancer stem cells (CSCs) at the apex. Both stochastic and hierarchical models are reasonable systems that have been hypothesised to describe tumour heterogeneity. Although each model alone inadequately explains tumour diversity, the two models can be integrated to provide a more comprehensive explanation. In this review, we discuss existing evidence supporting a unified model of gastric CSCs, including the regulatory mechanisms of this unified model in addition to the current status of stemness-related targeted therapy in GC patients. PMID:28301871

Biological signatures of dynamic river networks from a coupled landscape evolution and neutral community model

NASA Astrophysics Data System (ADS)

Stokes, M.; Perron, J. T.

2017-12-01

Freshwater systems host exceptionally species-rich communities whose spatial structure is dictated by the topology of the river networks they inhabit. Over geologic time, river networks are dynamic; drainage basins shrink and grow, and river capture establishes new connections between previously separated regions. It has been hypothesized that these changes in river network structure influence the evolution of life by exchanging and isolating species, perhaps boosting biodiversity in the process. However, no general model exists to predict the evolutionary consequences of landscape change. We couple a neutral community model of freshwater organisms to a landscape evolution model in which the river network undergoes drainage divide migration and repeated river capture. Neutral community models are macro-ecological models that include stochastic speciation and dispersal to produce realistic patterns of biodiversity. We explore the consequences of three modes of speciation - point mutation, time-protracted, and vicariant (geographic) speciation - by tracking patterns of diversity in time and comparing the final result to an equilibrium solution of the neutral model on the final landscape. Under point mutation, a simple model of stochastic and instantaneous speciation, the results are identical to the equilibrium solution and indicate the dominance of the species-area relationship in forming patterns of diversity. The number of species in a basin is proportional to its area, and regional species richness reaches its maximum when drainage area is evenly distributed among sub-basins. Time-protracted speciation is also modeled as a stochastic process, but in order to produce more realistic rates of diversification, speciation is not assumed to be instantaneous. Rather, each new species must persist for a certain amount of time before it is considered to be established. When vicariance (geographic speciation) is included, there is a transient signature of increased regional diversity after river capture. The results indicate that the mode of speciation and the rate of speciation relative to the rate of divide migration determine the evolutionary signature of river capture.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

PubMed

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.

Employing Eigenvalue Ratios to Generate Prior Fracture-like Features for Stochastic Hydrogeophysical Characterization of a Fractured Aquifer System

NASA Astrophysics Data System (ADS)

Brewster, J.; Oware, E. K.

2017-12-01

Groundwater hosted in fractured rocks constitutes almost 65% of the principal aquifers in the US. The exploitation and contaminant management of fractured aquifers require fracture flow and transport modeling, which in turn requires a detailed understanding of the structure of the aquifer. The widely used equivalent porous medium approach to modeling fractured aquifer systems is inadequate to accurately predict fracture transport processes due to the averaging of the sharp lithological contrast between the matrix and the fractures. The potential of geophysical imaging (GI) to estimate spatially continuous subsurface profiles in a minimally invasive fashion is well proven. Conventional deterministic GI strategies, however, produce geologically unrealistic, smoothed-out results due to commonly enforced smoothing constraints. Stochastic GI of fractured aquifers is becoming increasing appealing due to its ability to recover realistic fracture features while providing multiple likely realizations that enable uncertainty assessment. Generating prior spatial features consistent with the expected target structures is crucial in stochastic imaging. We propose to utilize eigenvalue ratios to resolve the elongated fracture features expected in a fractured aquifer system. Eigenvalues capture the major and minor directions of variability in a region, which can be employed to evaluate shape descriptors, such as eccentricity (elongation) and orientation of features in the region. Eccentricity ranges from zero to one, representing a circularly sharped to a line feature, respectively. Here, we apply eigenvalue ratios to define a joint objective parameter consisting of eccentricity (shape) and direction terms to guide the generation of prior fracture-like features in some predefined principal directions for stochastic GI. Preliminary unconditional, synthetic experiments reveal the potential of the algorithm to simulate prior fracture-like features. We illustrate the strategy with a 2D, cross-borehole electrical resistivity tomography (ERT) in a fractured aquifer at the UB Environmental Geophysics Imaging Site, with tomograms validated with gamma and caliper logs obtained from the two ERT wells.

Conditional Stochastic Models in Reduced Space: Towards Efficient Simulation of Tropical Cyclone Precipitation Patterns

NASA Astrophysics Data System (ADS)

Dodov, B.

2017-12-01

Stochastic simulation of realistic and statistically robust patterns of Tropical Cyclone (TC) induced precipitation is a challenging task. It is even more challenging in a catastrophe modeling context, where tens of thousands of typhoon seasons need to be simulated in order to provide a complete view of flood risk. Ultimately, one could run a coupled global climate model and regional Numerical Weather Prediction (NWP) model, but this approach is not feasible in the catastrophe modeling context and, most importantly, may not provide TC track patterns consistent with observations. Rather, we propose to leverage NWP output for the observed TC precipitation patterns (in terms of downscaled reanalysis 1979-2015) collected on a Lagrangian frame along the historical TC tracks and reduced to the leading spatial principal components of the data. The reduced data from all TCs is then grouped according to timing, storm evolution stage (developing, mature, dissipating, ETC transitioning) and central pressure and used to build a dictionary of stationary (within a group) and non-stationary (for transitions between groups) covariance models. Provided that the stochastic storm tracks with all the parameters describing the TC evolution are already simulated, a sequence of conditional samples from the covariance models chosen according to the TC characteristics at a given moment in time are concatenated, producing a continuous non-stationary precipitation pattern in a Lagrangian framework. The simulated precipitation for each event is finally distributed along the stochastic TC track and blended with a non-TC background precipitation using a data assimilation technique. The proposed framework provides means of efficient simulation (10000 seasons simulated in a couple of days) and robust typhoon precipitation patterns consistent with observed regional climate and visually undistinguishable from high resolution NWP output. The framework is used to simulate a catalog of 10000 typhoon seasons implemented in a flood risk model for Japan.

The Role of Breccia Lenses in Regolith Generation From the Formation of Small, Simple Craters: Application to the Apollo 15 Landing Site

NASA Astrophysics Data System (ADS)

Hirabayashi, M.; Howl, B. A.; Fassett, C. I.; Soderblom, J. M.; Minton, D. A.; Melosh, H. J.

2018-02-01

Impact cratering is likely a primary agent of regolith generation on airless bodies. Regolith production via impact cratering has long been a key topic of study since the Apollo era. The evolution of regolith due to impact cratering, however, is not well understood. A better formulation is needed to help quantify the formation mechanism and timescale of regolith evolution. Here we propose an analytically derived stochastic model that describes the evolution of regolith generated by small, simple craters. We account for ejecta blanketing as well as regolith infilling of the transient crater cavity. Our results show that the regolith infilling plays a key role in producing regolith. Our model demonstrates that because of the stochastic nature of impact cratering, the regolith thickness varies laterally, which is consistent with earlier work. We apply this analytical model to the regolith evolution at the Apollo 15 site. The regolith thickness is computed considering the observed crater size-frequency distribution of small, simple lunar craters (< 381 m in radius for ejecta blanketing and <100 m in radius for the regolith infilling). Allowing for some amount of regolith coming from the outside of the area, our result is consistent with an empirical result from the Apollo 15 seismic experiment. Finally, we find that the timescale of regolith growth is longer than that of crater equilibrium, implying that even if crater equilibrium is observed on a cratered surface, it is likely that the regolith thickness is still evolving due to additional impact craters.

Residual Viremia in Treated HIV+ Individuals

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

Conway, Jessica M.; Perelson, Alan S.

Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. However, some residual virus remains, below the level of detection, in HIV-infected patients on ART. Furthermore, the source of this viremia is an area of debate: does it derive primarily from activation of infected cells in the latent reservoir, or from ongoing viral replication? Our observations seem to be contradictory: there is evidence of short term evolution, implying that there must be ongoing viral replication, and viral strains should thus evolve. The phylogenetic analyses, and rare emergent drug resistance, suggest no long-term viral evolution, implying that virus derived frommore » activated latent cells must dominate. We use simple deterministic and stochastic models to gain insight into residual viremia dynamics in HIV-infected patients. Our modeling relies on two underlying assumptions for patients on suppressive ART: that latent cell activation drives viral dynamics and that the reproductive ratio of treated infection is less than 1. Nonetheless, the contribution of viral replication to residual viremia in patients on ART may be non-negligible. However, even if the portion of viremia attributable to viral replication is significant, our model predicts (1) that latent reservoir re-seeding remains negligible, and (2) some short-term viral evolution is permitted, but long-term evolution can still be limited: stochastic analysis of our model shows that de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia and, with relatively few parameters, recapitulates HIV viral dynamics observed in patients on suppressive therapy.« less

Residual Viremia in Treated HIV+ Individuals

DOE PAGES

Conway, Jessica M.; Perelson, Alan S.

2016-01-06

Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. However, some residual virus remains, below the level of detection, in HIV-infected patients on ART. Furthermore, the source of this viremia is an area of debate: does it derive primarily from activation of infected cells in the latent reservoir, or from ongoing viral replication? Our observations seem to be contradictory: there is evidence of short term evolution, implying that there must be ongoing viral replication, and viral strains should thus evolve. The phylogenetic analyses, and rare emergent drug resistance, suggest no long-term viral evolution, implying that virus derived frommore » activated latent cells must dominate. We use simple deterministic and stochastic models to gain insight into residual viremia dynamics in HIV-infected patients. Our modeling relies on two underlying assumptions for patients on suppressive ART: that latent cell activation drives viral dynamics and that the reproductive ratio of treated infection is less than 1. Nonetheless, the contribution of viral replication to residual viremia in patients on ART may be non-negligible. However, even if the portion of viremia attributable to viral replication is significant, our model predicts (1) that latent reservoir re-seeding remains negligible, and (2) some short-term viral evolution is permitted, but long-term evolution can still be limited: stochastic analysis of our model shows that de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia and, with relatively few parameters, recapitulates HIV viral dynamics observed in patients on suppressive therapy.« less

Evolution of Life and SETI (Evo-SETI)

NASA Astrophysics Data System (ADS)

Maccone, Claudio

When SETI scientists will be able to discover a signal or just some signs of an Extra-Terrestrial (ET) Civilization, those ETs should turn out to be technologically advanced at least as much as Humans, if not more, or much more so. Comparing the technological level of two different Civilizations is then a key issue in SETI. But at the moment we only know about the development of life on Earth over the last 3.5 billion years. We thus need to mathematically model the evolution of life on Earth (RNA to Humans) and then apply our results to other extra-solar planets to find out “where they stand” along their evolution of life. In a series of recent papers and in a book (refs. [1] through [4]) this author introduced a new statistical model embracing SETI, Darwinian Evolution and Human History into a unified statistical picture and concisely called Evo-SETI (Evolution & SETI). The relevant mathematical instruments are: 1) The statistical generalization of the Drake equation yielding the number N of communicating ET civilizations in the Galaxy. Assuming that each input variable in the Drake equation was a random variable, rather than just a pure number, N was shown to follow the lognormal probability distribution having as mean value the sum of the input mean values, and as variance the sum of the input variances (ref. [1]). 2) Geometric Brownian Motion (GBM), the stochastic process representing Evolution as the stochastic increase of the number of Species living on Earth over the last 3.5 billion years. This GBM is well-known in the mathematics of finances (Black-Sholes models). Its main features are that its probability density function (pdf) is a lognormal pdf, and its mean value is either an increasing, or, more rarely (as in the Mass Extinctions of the past) a decreasing exponential of the time. 3) The probability distributions known as b-lognormals, i.e. lognormals starting at a certain positive instant b>0 rather than at the origin. These b-lognormals were then forced by us to have their peak value located on the exponential mean-value curve of the GBM (this is the so-called “Peak-Locus Theorem”). In the framework of Darwinian Evolution, the resulting mathematical construction was shown to identify with Cladistics (refs. [2], [3], [4]). 4) The (Shannon) Entropy of such b-lognormals is then seen to represent the “degree of progress” reached by each living organism or by each big set of living organisms, like historic human civilizations. Having understood this fact, Human History may then be cast into the language of b-lognormals that are more and more organized in time (i.e. having smaller and smaller entropy, or smaller and smaller “chaos”), and have their peaks located on the increasing GBM exponential. This exponential is thus the “trend of progress” in Human History. 5) But our most striking new result is about the well-known “Molecular Clock of Evolution”, namely the “constant rate of Evolution at the molecular level” as shown by Kimura’s Neutral Theory of Molecular Evolution. We showed that that the Molecular Clock identifies with Entropy in our Evo-SETI model because they both grew linearly in time since the origin of life. 6) Furthermore, we applid our Evo-SETI model to lognormal stochastic processes other then the GBMs. For instance, we showed that the Markov-Korotayev (2007-2008, refs. [5], [6]) model for Darwinian Evolution identifies with an Evo-SETI model for which the mean value of the lognormal stochastic process is a cubic (third degree polynomial) function of the time. In conclusion: we have provided a vast mathematical model capable of embracing Molecular Evolution, SETI and Entropy into a simple set of statistical equations based upon b-lognormals pdfs and lognormal stochastic processes Keywords: Molecular Clock, Darwinian evolution, statistical Drake equation, lognormal probability densities, geometric Brownian motion, entropy. REFERENCES [1] Maccone, C. (2008), “The Statistical Drake Equation”, paper #IAC-08-A4.1.4 presented on October 1st, 2008, at the 59th International Astronautical Congress (IAC) held in Glasgow, Scotland, UK, September 29th thru October 3rd, 2008, later published in Acta Astronautica, Vol. 67 (2010), pages 1366-1383. [2] Maccone, C. (2011, b), “A Mathematical Model for Evolution and SETI”, Origins of Life and Evolutionary Biospheres (OLEB), Vol. 41, pages 609-619, available online December 3rd, 2011. [3] Maccone, C. (2012), “Mathematical SETI”, a 724-pages book published by Praxis-Springer in the fall of 2012. ISBN, ISBN-10: 3642274366 | ISBN-13: 978-3642274367 | Edition: 2012 [4] Maccone, C., (2013), “SETI, Evolution and Human History merged into a Mathematical Model”, International Journal of Astrobiology, Vol. 12, issue 3 (2013), pages 218-245. Available online since April 23, 2013. [5] Markov A., Korotayev A., “Phanerozoic marine biodiversity follows a hyperbolic trend”, Paleoworld, Volume 16, Issue 4, December 2007, Pages 311-318. [6] Markov A., Korotayev A., “Hyperbolic growth of marine and continental biodiversity through the Phanerozoic and community evolution”, Journal of General Biology. Volume 69, 2008, N. 3, pp. 175-194.

Steep Decay Phase Shaped by the Curvature Effect. II. Spectral Evolution

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

Lin, Da-Bin; Mu, Hui-Jun; Lu, Rui-Jing

We derive a simple analytical formula to describe the evolution of spectral index β in the steep decay phase shaped by the curvature effect with the assumption that the spectral parameters and Lorentz factor of the jet shell are the same for different latitudes. Here, the value of β is estimated in the 0.3−10 keV energy band. For a spherical thin shell with a cutoff power-law (CPL) intrinsic radiation spectrum, the spectral evolution can be read as a linear function of observer time. For the situation with the Band function intrinsic radiation spectrum, the spectral evolution may be complex. Ifmore » the observed break energy of the radiation spectrum is larger than 10 keV, the spectral evolution is the same as that shaped by jet shells with a CPL spectrum. If the observed break energy is less than 0.3 keV, the value of β would be a constant. For others, the spectral evolution can be approximated as a logarithmal function of the observer time in general.« less

Finite element formulation of fluctuating hydrodynamics for fluids filled with rigid particles using boundary fitted meshes

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

De Corato, M., E-mail: marco.decorato@unina.it; Slot, J.J.M., E-mail: j.j.m.slot@tue.nl; Hütter, M., E-mail: m.huetter@tue.nl

In this paper, we present a finite element implementation of fluctuating hydrodynamics with a moving boundary fitted mesh for treating the suspended particles. The thermal fluctuations are incorporated into the continuum equations using the Landau and Lifshitz approach [1]. The proposed implementation fulfills the fluctuation–dissipation theorem exactly at the discrete level. Since we restrict the equations to the creeping flow case, this takes the form of a relation between the diffusion coefficient matrix and friction matrix both at the particle and nodal level of the finite elements. Brownian motion of arbitrarily shaped particles in complex confinements can be considered withinmore » the present formulation. A multi-step time integration scheme is developed to correctly capture the drift term required in the stochastic differential equation (SDE) describing the evolution of the positions of the particles. The proposed approach is validated by simulating the Brownian motion of a sphere between two parallel plates and the motion of a spherical particle in a cylindrical cavity. The time integration algorithm and the fluctuating hydrodynamics implementation are then applied to study the diffusion and the equilibrium probability distribution of a confined circle under an external harmonic potential.« less

Bayesian model-emulation of stochastic gravitational-wave spectra for probes of the final-parsec problem with pulsar-timing arrays

NASA Astrophysics Data System (ADS)

Taylor, Stephen R.; Simon, Joseph; Sampson, Laura

2017-01-01

The final parsec of supermassive black-hole binary evolution is subject to the complex interplay of stellar loss-cone scattering, circumbinary disk accretion, and gravitational-wave emission, with binary eccentricity affected by all of these. The strain spectrum of gravitational-waves in the pulsar-timing band thus encodes rich information about the binary population's response to these various environmental mechanisms. Current spectral models have heretofore followed basic analytic prescriptions, and attempt to investigate these final-parsec mechanisms in an indirect fashion. Here we describe a new technique to directly probe the environmental properties of supermassive black-hole binaries through "Bayesian model-emulation". We perform black-hole binary population synthesis simulations at a restricted set of environmental parameter combinations, compute the strain spectra from these, then train a Gaussian process to learn the shape of the spectrum at any point in parameter space. We describe this technique, demonstrate its efficacy with a program of simulated datasets, then illustrate its power by directly constraining final-parsec physics in a Bayesian analysis of the NANOGrav 5-year dataset. The technique is fast, flexible, and robust.

Bayesian model-emulation of stochastic gravitational-wave spectra for probes of the final-parsec problem with pulsar-timing arrays

NASA Astrophysics Data System (ADS)

Taylor, Stephen; Simon, Joseph; Sampson, Laura

2017-01-01

The final parsec of supermassive black-hole binary evolution is subject to the complex interplay of stellar loss-cone scattering, circumbinary disk accretion, and gravitational-wave emission, with binary eccentricity affected by all of these. The strain spectrum of gravitational-waves in the pulsar-timing band thus encodes rich information about the binary population's response to these various environmental mechanisms. Current spectral models have heretofore followed basic analytic prescriptions, and attempt to investigate these final-parsec mechanisms in an indirect fashion. Here we describe a new technique to directly probe the environmental properties of supermassive black-hole binaries through ``Bayesian model-emulation''. We perform black-hole binary population synthesis simulations at a restricted set of environmental parameter combinations, compute the strain spectra from these, then train a Gaussian process to learn the shape of spectrum at any point in parameter space. We describe this technique, demonstrate its efficacy with a program of simulated datasets, then illustrate its power by directly constraining final-parsec physics in a Bayesian analysis of the NANOGrav 5-year dataset. The technique is fast, flexible, and robust.

The frequency dependence of the discharge properties in a capacitively coupled oxygen discharge

NASA Astrophysics Data System (ADS)

Gudmundsson, J. T.; Snorrason, D. I.; Hannesdottir, H.

2018-02-01

We use the one-dimensional object-oriented particle-in-cell Monte Carlo collision code oopd1 to explore the evolution of the charged particle density profiles, electron heating mechanism, the electron energy probability function (EEPF), and the ion energy distribution in a single frequency capacitively coupled oxygen discharge, with driving frequency in the range 12-100 MHz. At a low driving frequency and low pressure (5 and 10 mTorr), a combination of stochastic (α-mode) and drift ambipolar (DA) heating in the bulk plasma (the electronegative core) is observed and the DA-mode dominates the time averaged electron heating. As the driving frequency or pressure are increased, the heating mode transitions into a pure α-mode, where electron heating in the sheath region dominates. At low pressure (5 and 10 mTorr), this transition coincides with a sharp decrease in electronegativity. At low pressure and low driving frequency, the EEPF is concave. As the driving frequency is increased, the number of low energy electrons increases and the relative number of higher energy electrons (>10 eV) increases. At high driving frequency, the EEPF develops a convex shape or becomes bi-Maxwellian.

Orbital evolution and escape of Martian Trojans due to the Yarkovsky effect

NASA Astrophysics Data System (ADS)

Christou, Apostolos

2017-06-01

Recently it was shown that the Yarkovsky effect can lead to significant orbit change for Trojans of Mars [1,2] and that the orbital distribution of observed Trojans is consistent with a negative along-track acceleration of the same functional form as seasonal yarkovsky; this feature was used to constrain the age of the Eureka family of Mars Trojan asteroids [2]. In contrast, the Yarkovsky effect appears to have a negligible role in shaping observed families of Jupiter Trojans [3].To explore the evolution and end states of Trojans evolved by the Yarkosky effect, I have numerically integrated test particles under a model of the diurnal variant and for different values of the acceleration strength up to 10-2 AU/Myr for da/dt outside the resonance. I use as a starting point the orbits of the three largest Martian Trojans: 5261 Eureka, (101429) 1998 VF31 and (121514) 1999 UJ7.I find, as in [2], that the evolution of the inclination I and the libration amplitude L depends on the sign of the acceleration and is essentially deterministic. Considering the rate of change of the Tisserand constant [5,6] leads to a simple analytical expression that reproduces well the inclination evolution of the Trojans. The evolution of e is somewhat more stochastic, probably due to chaotic diffusion [4] and/or the influence of Mars’ eccentricity [2].Trojans escape upon reaching the boundaries of stability domains mapped out in [4], demarcated by resonances with principal secular modes and the Kozai resonance. The mechanism of escape is by increasing e and/or the libration amplitude to the point of allowing close encounters with Mars.During the presentation I will describe the ensemble evolution of Trojans under Yarkovsky, how it is related to the lifetime in the 1:1 resonance and discuss the implications for Trojan stability at Earth and Jupiter.[1] Christou, A.A., 2013, Icarus, 224, 144.[2] Ćuk, M., Christou, A.A., Hamilton, D.P., 2015, Icarus, 252, 339.[3] Milani, A., Knezević, Z., Spoto, F., Cellino, A., Novaković, B., Tsirvoulis, G., 2017, Icarus, 288, 240.[4] Scholl, H., Marzari, F., Tricarico, P., 2005, Icarus, 175, 397.[5] Hamilton, D.P., 1994, Icarus, 109, 221[6] Liou, J. C., Zook, H. A., 1997, Icarus, 128, 354.

Trait-specific processes of convergence and conservatism shape ecomorphological evolution in ground-dwelling squirrels.

PubMed

McLean, Bryan S; Helgen, Kristofer M; Goodwin, H Thomas; Cook, Joseph A

2018-03-01

Our understanding of mechanisms operating over deep timescales to shape phenotypic diversity often hinges on linking variation in one or few trait(s) to specific evolutionary processes. When distinct processes are capable of similar phenotypic signatures, however, identifying these drivers is difficult. We explored ecomorphological evolution across a radiation of ground-dwelling squirrels whose history includes convergence and constraint, two processes that can yield similar signatures of standing phenotypic diversity. Using four ecologically relevant trait datasets (body size, cranial, mandibular, and molariform tooth shape), we compared and contrasted variation, covariation, and disparity patterns in a new phylogenetic framework. Strong correlations existed between body size and two skull traits (allometry) and among skull traits themselves (integration). Inferred evolutionary modes were also concordant across traits (Ornstein-Uhlenbeck with two adaptive regimes). However, despite these broad similarities, we found divergent dynamics on the macroevolutionary landscape, with phenotypic disparity being differentially shaped by convergence and conservatism. Such among-trait heterogeneity in process (but not always pattern) reiterates the mosaic nature of morphological evolution, and suggests ground squirrel evolution is poorly captured by single process descriptors. Our results also highlight how use of single traits can bias macroevolutionary inference, affirming the importance of broader trait-bases in understanding phenotypic evolutionary dynamics. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Resources alter the structure and increase stochasticity in bromeliad microfauna communities.

PubMed

Petermann, Jana S; Kratina, Pavel; Marino, Nicholas A C; MacDonald, A Andrew M; Srivastava, Diane S

2015-01-01

Although stochastic and deterministic processes have been found to jointly shape structure of natural communities, the relative importance of both forces may vary across different environmental conditions and across levels of biological organization. We tested the effects of abiotic environmental conditions, altered trophic interactions and dispersal limitation on the structure of aquatic microfauna communities in Costa Rican tank bromeliads. Our approach combined natural gradients in environmental conditions with experimental manipulations of bottom-up interactions (resources), top-down interactions (predators) and dispersal at two spatial scales in the field. We found that resource addition strongly increased the abundance and reduced the richness of microfauna communities. Community composition shifted in a predictable way towards assemblages dominated by flagellates and ciliates but with lower abundance and richness of algae and amoebae. While all functional groups responded strongly and predictably to resource addition, similarity among communities at the species level decreased, suggesting a role of stochasticity in species-level assembly processes. Dispersal limitation did not affect the communities. Since our design excluded potential priority effects we can attribute the differences in community similarity to increased demographic stochasticity of resource-enriched communities related to erratic changes in population sizes of some species. In contrast to resources, predators and environmental conditions had negligible effects on community structure. Our results demonstrate that bromeliad microfauna communities are strongly controlled by bottom-up forces. They further suggest that the relative importance of stochasticity may change with productivity and with the organizational level at which communities are examined.

Resources Alter the Structure and Increase Stochasticity in Bromeliad Microfauna Communities

PubMed Central

Petermann, Jana S.; Kratina, Pavel; Marino, Nicholas A. C.; MacDonald, A. Andrew M.; Srivastava, Diane S.

2015-01-01

Although stochastic and deterministic processes have been found to jointly shape structure of natural communities, the relative importance of both forces may vary across different environmental conditions and across levels of biological organization. We tested the effects of abiotic environmental conditions, altered trophic interactions and dispersal limitation on the structure of aquatic microfauna communities in Costa Rican tank bromeliads. Our approach combined natural gradients in environmental conditions with experimental manipulations of bottom-up interactions (resources), top-down interactions (predators) and dispersal at two spatial scales in the field. We found that resource addition strongly increased the abundance and reduced the richness of microfauna communities. Community composition shifted in a predictable way towards assemblages dominated by flagellates and ciliates but with lower abundance and richness of algae and amoebae. While all functional groups responded strongly and predictably to resource addition, similarity among communities at the species level decreased, suggesting a role of stochasticity in species-level assembly processes. Dispersal limitation did not affect the communities. Since our design excluded potential priority effects we can attribute the differences in community similarity to increased demographic stochasticity of resource-enriched communities related to erratic changes in population sizes of some species. In contrast to resources, predators and environmental conditions had negligible effects on community structure. Our results demonstrate that bromeliad microfauna communities are strongly controlled by bottom-up forces. They further suggest that the relative importance of stochasticity may change with productivity and with the organizational level at which communities are examined. PMID:25775464

Optimization Testbed Cometboards Extended into Stochastic Domain

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.; Patnaik, Surya N.

2010-01-01

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

Stochastic tools hidden behind the empirical dielectric relaxation laws

NASA Astrophysics Data System (ADS)

Stanislavsky, Aleksander; Weron, Karina

2017-03-01

The paper is devoted to recent advances in stochastic modeling of anomalous kinetic processes observed in dielectric materials which are prominent examples of disordered (complex) systems. Theoretical studies of dynamical properties of ‘structures with variations’ (Goldenfield and Kadanoff 1999 Science 284 87-9) require application of such mathematical tools—by means of which their random nature can be analyzed and, independently of the details distinguishing various systems (dipolar materials, glasses, semiconductors, liquid crystals, polymers, etc), the empirical universal kinetic patterns can be derived. We begin with a brief survey of the historical background of the dielectric relaxation study. After a short outline of the theoretical ideas providing the random tools applicable to modeling of relaxation phenomena, we present probabilistic implications for the study of the relaxation-rate distribution models. In the framework of the probability distribution of relaxation rates we consider description of complex systems, in which relaxing entities form random clusters interacting with each other and single entities. Then we focus on stochastic mechanisms of the relaxation phenomenon. We discuss the diffusion approach and its usefulness for understanding of anomalous dynamics of relaxing systems. We also discuss extensions of the diffusive approach to systems under tempered random processes. Useful relationships among different stochastic approaches to the anomalous dynamics of complex systems allow us to get a fresh look at this subject. The paper closes with a final discussion on achievements of stochastic tools describing the anomalous time evolution of complex systems.

The Shape of Things to Come: The Computational Pictograph as a Bridge from Combinatorial Space to Outcome Distribution

ERIC Educational Resources Information Center

Abrahamson, Dor

2006-01-01

This snapshot introduces a computer-based representation and activity that enables students to simultaneously "see" the combinatorial space of a stochastic device (e.g., dice, spinner, coins) and its outcome distribution. The author argues that the "ambiguous" representation fosters student insight into probability. [Snapshots are subject to peer…

Soil pH mediates the balance between stochastic and deterministic assembly of bacteria

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

Tripathi, Binu M.; Stegen, James C.; Kim, Mincheol

Little is known about the factors affecting the relative influence of stochastic and deterministic processes that governs the assembly of microbial communities in successional soils. Here, we conducted a meta-analysis of bacterial communities using six different successional soils data sets, scattered across different regions, with different pH conditions in early and late successional soils. We found that soil pH was the best predictor of bacterial community assembly and the relative importance of stochastic and deterministic processes along successional soils. Extreme acidic or alkaline pH conditions lead to assembly of phylogenetically more clustered bacterial communities through deterministic processes, whereas pH conditionsmore » close to neutral lead to phylogenetically less clustered bacterial communities with more stochasticity. We suggest that the influence of pH, rather than successional age, is the main driving force in producing trends in phylogenetic assembly of bacteria, and that pH also influences the relative balance of stochastic and deterministic processes along successional soils. Given that pH had a much stronger association with community assembly than did successional age, we evaluated whether the inferred influence of pH was maintained when studying globally-distributed samples collected without regard for successional age. This dataset confirmed the strong influence of pH, suggesting that the influence of soil pH on community assembly processes occurs globally. Extreme pH conditions likely exert more stringent limits on survival and fitness, imposing strong selective pressures through ecological and evolutionary time. Taken together, these findings suggest that the degree to which stochastic vs. deterministic processes shape soil bacterial community assembly is a consequence of soil pH rather than successional age.« less

Transient ensemble dynamics in time-independent galactic potentials

NASA Astrophysics Data System (ADS)

Mahon, M. Elaine; Abernathy, Robert A.; Bradley, Brendan O.; Kandrup, Henry E.

1995-07-01

This paper summarizes a numerical investigation of the short-time, possibly transient, behaviour of ensembles of stochastic orbits evolving in fixed non-integrable potentials, with the aim of deriving insights into the structure and evolution of galaxies. The simulations involved three different two-dimensional potentials, quite different in appearance. However, despite these differences, ensembles in all three potentials exhibit similar behaviour. This suggests that the conclusions inferred from the simulations are robust, relying only on basic topological properties, e.g., the existence of KAM tori and cantori. Generic ensembles of initial conditions, corresponding to stochastic orbits, exhibit a rapid coarse-grained approach towards a near-invariant distribution on a time-scale <>t_H, although various irregularities associated with external and/or internal irregularities can drastically accelerate this process. A principal tool in the analysis is the notion of a local Liapounov exponent, which provides a statistical characterization of the overall instability of stochastic orbits over finite time intervals. In particular, there is a precise sense in which confined stochastic orbits are less unstable, with smaller local Liapounov exponents, than are unconfined stochastic orbits.

Mathematical Modeling of the Origins of Life

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The emergence of early metabolism - a network of catalyzed chemical reactions that supported self-maintenance, growth, reproduction and evolution of the ancestors of contemporary cells (protocells) was a critical, but still very poorly understood step on the path from inanimate to animate matter. Here, it is proposed and tested through mathematical modeling of biochemically plausible systems that the emergence of metabolism and its initial evolution towards higher complexity preceded the emergence of a genome. Even though the formation of protocellular metabolism was driven by non-genomic, highly stochastic processes the outcome was largely deterministic, strongly constrained by laws of chemistry. It is shown that such concepts as speciation and fitness to the environment, developed in the context of genomic evolution, also held in the absence of a genome.

Analytical approach to an integrate-and-fire model with spike-triggered adaptation

NASA Astrophysics Data System (ADS)

Schwalger, Tilo; Lindner, Benjamin

2015-12-01

The calculation of the steady-state probability density for multidimensional stochastic systems that do not obey detailed balance is a difficult problem. Here we present the analytical derivation of the stationary joint and various marginal probability densities for a stochastic neuron model with adaptation current. Our approach assumes weak noise but is valid for arbitrary adaptation strength and time scale. The theory predicts several effects of adaptation on the statistics of the membrane potential of a tonically firing neuron: (i) a membrane potential distribution with a convex shape, (ii) a strongly increased probability of hyperpolarized membrane potentials induced by strong and fast adaptation, and (iii) a maximized variability associated with the adaptation current at a finite adaptation time scale.

Introduction to Particle Acceleration in the Cosmos

NASA Technical Reports Server (NTRS)

Gallagher, D. L.; Horwitz, J. L.; Perez, J.; Quenby, J.

2005-01-01

Accelerated charged particles have been used on Earth since 1930 to explore the very essence of matter, for industrial applications, and for medical treatments. Throughout the universe nature employs a dizzying array of acceleration processes to produce particles spanning twenty orders of magnitude in energy range, while shaping our cosmic environment. Here, we introduce and review the basic physical processes causing particle acceleration, in astrophysical plasmas from geospace to the outer reaches of the cosmos. These processes are chiefly divided into four categories: adiabatic and other forms of non-stochastic acceleration, magnetic energy storage and stochastic acceleration, shock acceleration, and plasma wave and turbulent acceleration. The purpose of this introduction is to set the stage and context for the individual papers comprising this monograph.

The structure of red-infrared scattergrams of semivegetated landscapes

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Eagleson, Peter S.

1988-01-01

A physically based linear stochastic geometric canopy soil reflectance model is presented for characterizing spatial variability of semivegetated landscapes at subpixel and regional scales. Landscapes are conceptualized as stochastic geometric surfaces, incorporating not only the variability in geometric elements, but also the variability in vegetation and soil background reflectance which can be important in some scenes. The model is used to investigate several possible mechanisms which contribute to the often observed characteristic triangular shape of red-infrared scattergrams of semivegetated landscapes. Scattergrams of simulated and semivegetated scenes are analyzed with respect to the scales of the satellite pixel and subpixel components. Analysis of actual aerial radiometric data of a pecan orchard is presented in comparison with ground observations as preliminary confirmation of the theoretical results.

The structure of red-infrared scattergrams of semivegetated landscapes

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Eagleson, Peter S.

1989-01-01

A physically based linear stochastic geometric canopy soil reflectance model is presented for characterizing spatial variability of semivegetated landscapes at subpixel and regional scales. Landscapes are conceptualized as stochastic geometric surfaces, incorporating not only the variability in geometric elements, but also the variability in vegetation and soil background reflectance which can be important in some scenes. The model is used to investigate several possible mechanisms which contribute to the often observed characteristic triangular shape of red-infrared scattergrams of semivegetated landscapes. Scattergrams of simulated semivegetated scenes are analyzed with respect to the scales of the satellite pixel and subpixel components. Analysis of actual aerial radiometric data of a pecan orchard is presented in comparison with ground observations as preliminary confirmation of the theoretical results.

Quadratic resonance in the three-dimensional oscillations of inviscid drops with surface tension

NASA Technical Reports Server (NTRS)

Natarajan, R.; Brown, R. A.

1986-01-01

The moderate-amplitude, three-dimensional oscillations of an inviscid drop are described in terms of spherical harmonics. Specific oscillation modes are resonantly coupled by quadratic nonlinearities caused by inertia, capillarity, and drop deformation. The equations describing the interactions of these modes are derived from the variational principle for the appropriate Lagrangian by expressing the modal amplitudes to be functions of a slow time scale and by preaveraging the Lagrangian over the time scale of the primary oscillations. Stochastic motions are predicted for nonaxisymmetric deformations starting from most initial conditions, even those arbitrarily close to the axisymmetric shapes. The stochasticity is characterized by a redistribution of the energy contained in the initial deformation over all the degrees of freedom of the interacting modes.

Is dispersal neutral?

PubMed

Lowe, Winsor H; McPeek, Mark A

2014-08-01

Dispersal is difficult to quantify and often treated as purely stochastic and extrinsically controlled. Consequently, there remains uncertainty about how individual traits mediate dispersal and its ecological effects. Addressing this uncertainty is crucial for distinguishing neutral versus non-neutral drivers of community assembly. Neutral theory assumes that dispersal is stochastic and equivalent among species. This assumption can be rejected on principle, but common research approaches tacitly support the 'neutral dispersal' assumption. Theory and empirical evidence that dispersal traits are under selection should be broadly integrated in community-level research, stimulating greater scrutiny of this assumption. A tighter empirical connection between the ecological and evolutionary forces that shape dispersal will enable richer understanding of this fundamental process and its role in community assembly. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Ising Decision Maker: a binary stochastic network for choice response time.

PubMed

Verdonck, Stijn; Tuerlinckx, Francis

2014-07-01

The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (c) 2014 APA, all rights reserved.

Long-term influence of asteroids on planet longitudes and chaotic dynamics of the solar system

NASA Astrophysics Data System (ADS)

Woillez, E.; Bouchet, F.

2017-11-01

Over timescales much longer than an orbital period, the solar system exhibits large-scale chaotic behavior and can thus be viewed as a stochastic dynamical system. The aim of the present paper is to compare different sources of stochasticity in the solar system. More precisely we studied the importance of the long term influence of asteroids on the chaotic dynamics of the solar system. We show that the effects of asteroids on planets is similar to a white noise process, when those effects are considered on a timescale much larger than the correlation time τϕ ≃ 104 yr of asteroid trajectories. We computed the timescale τe after which the effects of the stochastic evolution of the asteroids lead to a loss of information for the initial conditions of the perturbed Laplace-Lagrange secular dynamics. The order of magnitude of this timescale is precisely determined by theoretical argument, and we find that τe ≃ 104 Myr. Although comparable to the full main-sequence lifetime of the sun, this timescale is considerably longer than the Lyapunov time τI ≃ 10 Myr of the solar system without asteroids. This shows that the external sources of chaos arise as a small perturbation in the stochastic secular behavior of the solar system, rather due to intrinsic chaos.

Coastal zone management with stochastic multi-criteria analysis.

PubMed

Félix, A; Baquerizo, A; Santiago, J M; Losada, M A

2012-12-15

The methodology for coastal management proposed in this study takes into account the physical processes of the coastal system and the stochastic nature of forcing agents. Simulation techniques are used to assess the uncertainty in the performance of a set of predefined management strategies based on different criteria representing the main concerns of interest groups. This statistical information as well as the distribution function that characterizes the uncertainty regarding the preferences of the decision makers is fed into a stochastic multi-criteria acceptability analysis that provides the probability of alternatives obtaining certain ranks and also calculates the preferences of a typical decision maker who supports an alternative. This methodology was applied as a management solution for Playa Granada in the Guadalfeo River Delta (Granada, Spain), where the construction of a dam in the river basin is causing severe erosion. The analysis of shoreline evolution took into account the coupled action of atmosphere, ocean, and land agents and their intrinsic stochastic character. This study considered five different management strategies. The criteria selected for the analysis were the economic benefits for three interest groups: (i) indirect beneficiaries of tourist activities; (ii) beach homeowners; and (iii) the administration. The strategies were ranked according to their effectiveness, and the relative importance given to each criterion was obtained. Copyright © 2012 Elsevier Ltd. All rights reserved.

Exact lower and upper bounds on stationary moments in stochastic biochemical systems

NASA Astrophysics Data System (ADS)

Ghusinga, Khem Raj; Vargas-Garcia, Cesar A.; Lamperski, Andrew; Singh, Abhyudai

2017-08-01

In the stochastic description of biochemical reaction systems, the time evolution of statistical moments for species population counts is described by a linear dynamical system. However, except for some ideal cases (such as zero- and first-order reaction kinetics), the moment dynamics is underdetermined as lower-order moments depend upon higher-order moments. Here, we propose a novel method to find exact lower and upper bounds on stationary moments for a given arbitrary system of biochemical reactions. The method exploits the fact that statistical moments of any positive-valued random variable must satisfy some constraints that are compactly represented through the positive semidefiniteness of moment matrices. Our analysis shows that solving moment equations at steady state in conjunction with constraints on moment matrices provides exact lower and upper bounds on the moments. These results are illustrated by three different examples—the commonly used logistic growth model, stochastic gene expression with auto-regulation and an activator-repressor gene network motif. Interestingly, in all cases the accuracy of the bounds is shown to improve as moment equations are expanded to include higher-order moments. Our results provide avenues for development of approximation methods that provide explicit bounds on moments for nonlinear stochastic systems that are otherwise analytically intractable.

Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae

DOE PAGES

Dar, R. D.; Karig, D. K.; Cooke, J. F.; ...

2010-09-01

Stochasticity is an inherent feature of complex systems with nanoscale structure. In such systems information is represented by small collections of elements (e.g. a few electrons on a quantum dot), and small variations in the populations of these elements may lead to big uncertainties in the information. Unfortunately, little is known about how to work within this inherently noisy environment to design robust functionality into complex nanoscale systems. Here, we look to the biological cell as an intriguing model system where evolution has mediated the trade-offs between fluctuations and function, and in particular we look at the relationships and trade-offsmore » between stochastic and deterministic responses in the gene expression of budding yeast (Saccharomyces cerevisiae). We find gene regulatory arrangements that control the stochastic and deterministic components of expression, and show that genes that have evolved to respond to stimuli (stress) in the most strongly deterministic way exhibit the most noise in the absence of the stimuli. We show that this relationship is consistent with a bursty 2-state model of gene expression, and demonstrate that this regulatory motif generates the most uncertainty in gene expression when there is the greatest uncertainty in the optimal level of gene expression.« less

Computing diffusivities from particle models out of equilibrium

NASA Astrophysics Data System (ADS)

Embacher, Peter; Dirr, Nicolas; Zimmer, Johannes; Reina, Celia

2018-04-01

A new method is proposed to numerically extract the diffusivity of a (typically nonlinear) diffusion equation from underlying stochastic particle systems. The proposed strategy requires the system to be in local equilibrium and have Gaussian fluctuations but it is otherwise allowed to undergo arbitrary out-of-equilibrium evolutions. This could be potentially relevant for particle data obtained from experimental applications. The key idea underlying the method is that finite, yet large, particle systems formally obey stochastic partial differential equations of gradient flow type satisfying a fluctuation-dissipation relation. The strategy is here applied to three classic particle models, namely independent random walkers, a zero-range process and a symmetric simple exclusion process in one space dimension, to allow the comparison with analytic solutions.

Cruising the rain forest floor: butterfly wing shape evolution and gliding in ground effect.

PubMed

Cespedes, Ann; Penz, Carla M; DeVries, Philip J

2015-05-01

Flight is a key innovation in the evolutionary success of insects and essential to dispersal, territoriality, courtship and oviposition. Wing shape influences flight performance and selection likely acts to maximize performance for conducting essential behaviours that in turn results in the evolution of wing shape. As wing shape also contributes to fitness, optimal shapes for particular flight behaviours can be assessed with aerodynamic predictions and placed in an ecomorphological context. Butterflies in the tribe Haeterini (Nymphalidae) are conspicuous members of understorey faunas in lowland Neotropical forests. Field observations indicate that the five genera in this clade differ in flight height and behaviour: four use gliding flight at the forest floor level, and one utilizes flapping flight above the forest floor. Nonetheless, the association of ground level gliding flight behaviour and wing shape has never been investigated in this or any other butterfly group. We used landmark-based geometric morphometrics to test whether wing shapes in Haeterini and their close relatives reflected observed flight behaviours. Four genera of Haeterini and some distantly related Satyrinae showed significant correspondence between wing shape and theoretical expectations in performance trade-offs that we attribute to selection for gliding in ground effect. Forewing shape differed between sexes for all taxa, and male wing shapes were aerodynamically more efficient for gliding flight than corresponding females. This suggests selection acts differentially on male and female wing shapes, reinforcing the idea that sex-specific flight behaviours contribute to the evolution of sexual dimorphism. Our study indicates that wing shapes in Haeterini butterflies evolved in response to habitat-specific flight behaviours, namely gliding in ground effect along the forest floor, resulting in ecomorphological partitions of taxa in morphospace. The convergent flight behaviour and wing morphology between tribes of Satyrinae suggest that the flight environment may offset phylogenetic constraints. Overall, this study provides a basis for exploring similar patterns of wing shape evolution in other taxa that glide in ground effect. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Expansion or extinction: deterministic and stochastic two-patch models with Allee effects.

PubMed

Kang, Yun; Lanchier, Nicolas

2011-06-01

We investigate the impact of Allee effect and dispersal on the long-term evolution of a population in a patchy environment. Our main focus is on whether a population already established in one patch either successfully invades an adjacent empty patch or undergoes a global extinction. Our study is based on the combination of analytical and numerical results for both a deterministic two-patch model and a stochastic counterpart. The deterministic model has either two, three or four attractors. The existence of a regime with exactly three attractors only appears when patches have distinct Allee thresholds. In the presence of weak dispersal, the analysis of the deterministic model shows that a high-density and a low-density populations can coexist at equilibrium in nearby patches, whereas the analysis of the stochastic model indicates that this equilibrium is metastable, thus leading after a large random time to either a global expansion or a global extinction. Up to some critical dispersal, increasing the intensity of the interactions leads to an increase of both the basin of attraction of the global extinction and the basin of attraction of the global expansion. Above this threshold, for both the deterministic and the stochastic models, the patches tend to synchronize as the intensity of the dispersal increases. This results in either a global expansion or a global extinction. For the deterministic model, there are only two attractors, while the stochastic model no longer exhibits a metastable behavior. In the presence of strong dispersal, the limiting behavior is entirely determined by the value of the Allee thresholds as the global population size in the deterministic and the stochastic models evolves as dictated by their single-patch counterparts. For all values of the dispersal parameter, Allee effects promote global extinction in terms of an expansion of the basin of attraction of the extinction equilibrium for the deterministic model and an increase of the probability of extinction for the stochastic model.

Mass fluctuation kinetics: Capturing stochastic effects in systems of chemical reactions through coupled mean-variance computations

NASA Astrophysics Data System (ADS)

Gómez-Uribe, Carlos A.; Verghese, George C.

2007-01-01

The intrinsic stochastic effects in chemical reactions, and particularly in biochemical networks, may result in behaviors significantly different from those predicted by deterministic mass action kinetics (MAK). Analyzing stochastic effects, however, is often computationally taxing and complex. The authors describe here the derivation and application of what they term the mass fluctuation kinetics (MFK), a set of deterministic equations to track the means, variances, and covariances of the concentrations of the chemical species in the system. These equations are obtained by approximating the dynamics of the first and second moments of the chemical master equation. Apart from needing knowledge of the system volume, the MFK description requires only the same information used to specify the MAK model, and is not significantly harder to write down or apply. When the effects of fluctuations are negligible, the MFK description typically reduces to MAK. The MFK equations are capable of describing the average behavior of the network substantially better than MAK, because they incorporate the effects of fluctuations on the evolution of the means. They also account for the effects of the means on the evolution of the variances and covariances, to produce quite accurate uncertainty bands around the average behavior. The MFK computations, although approximate, are significantly faster than Monte Carlo methods for computing first and second moments in systems of chemical reactions. They may therefore be used, perhaps along with a few Monte Carlo simulations of sample state trajectories, to efficiently provide a detailed picture of the behavior of a chemical system.

Topographic signatures of deep-seated landslides and a general landscape evolution model

NASA Astrophysics Data System (ADS)

Booth, A. M.; Roering, J. J.; Rempel, A. W.

2012-12-01

A fundamental goal of studying earth surface processes is to disentangle the complex web of interactions among baselevel, climate, and rock properties that generate characteristic landforms. Mechanistic geomorphic transport laws can quantitatively address this goal, but no widely accepted law for landslides exists. Here, we propose a transport law for deep-seated landslides and demonstrate its utility using a two-dimensional numerical landscape evolution model informed by study areas in the Waipaoa catchment, New Zealand and the Eel River catchment, California. We define a non-dimensional landslide number, which is the ratio of uplift to landslide flow time scales, that predicts three distinct landscape types. The first is dominated by stochastic landsliding, whereby discrete landslide events episodically erode material at rates far exceeding the long term uplift rate. The second is characterized by steady landsliding, in which the landslide flux at any location remains constant through time and is largest at the steepest locations in the catchment. The third is not significantly affected by landsliding. In both the "stochastic landsliding" and "steady landsliding" regimes, increases in the non-dimensional landslide number systematically reduce catchment relief and widen valley spacing, producing long, quasi-planar, low angle hillslopes despite high uplift rates. The stochastic landsliding regime best captures the frequent observation that deep-seated landslides produce a large sediment flux from a small aerial extent while being active only a fraction of the time. We suggest that this model is adaptable to a wide range of geologic settings and may be useful for interpreting climate-driven changes in landslide behavior.

Topographic signatures and a general transport law for deep-seated landslides in a landscape evolution model

NASA Astrophysics Data System (ADS)

Booth, Adam M.; Roering, Josh J.; Rempel, Alan W.

2013-06-01

A fundamental goal of studying earth surface processes is to disentangle the complex web of interactions among baselevel, tectonics, climate, and rock properties that generate characteristic landforms. Mechanistic geomorphic transport laws can quantitatively address this goal, but no widely accepted law for landslides exists. Here we propose a transport law for deep-seated landslides in weathered bedrock and demonstrate its utility using a two-dimensional numerical landscape evolution model informed by study areas in the Waipaoa catchment, New Zealand, and the Eel River catchment, California. We define a non-dimensional landslide number, which is the ratio of the horizontal landslide flux to the vertical tectonic flux, that characterizes three distinct landscape types. One is dominated by stochastic landsliding, whereby discrete landslide events episodically erode material at rates exceeding the long-term uplift rate. Another is characterized by steady landsliding, in which the landslide flux at any location remains constant through time and is greatest at the steepest locations in the catchment. The third is not significantly affected by landsliding. In both the "stochastic landsliding" and "steady landsliding" regimes, increases in the non-dimensional landslide number systematically reduce catchment relief and widen valley spacing, producing long, low angle hillslopes despite high uplift rates. The stochastic landsliding regime captures the frequent observation that deep-seated landslides produce large sediment fluxes from small areal extents while being active only a fraction of the time. We suggest that this model is adaptable to a wide range of geologic settings and is useful for interpreting climate-driven changes in landslide behavior.

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.

Pervasive genetic integration directs the evolution of human skull shape.

PubMed

Martínez-Abadías, Neus; Esparza, Mireia; Sjøvold, Torstein; González-José, Rolando; Santos, Mauro; Hernández, Miquel; Klingenberg, Christian Peter

2012-04-01

It has long been unclear whether the different derived cranial traits of modern humans evolved independently in response to separate selection pressures or whether they resulted from the inherent morphological integration throughout the skull. In a novel approach to this issue, we combine evolutionary quantitative genetics and geometric morphometrics to analyze genetic and phenotypic integration in human skull shape. We measured human skulls in the ossuary of Hallstatt (Austria), which offer a unique opportunity because they are associated with genealogical data. Our results indicate pronounced covariation of traits throughout the skull. Separate simulations of selection for localized shape changes corresponding to some of the principal derived characters of modern human skulls produced outcomes that were similar to each other and involved a joint response in all of these traits. The data for both genetic and phenotypic shape variation were not consistent with the hypothesis that the face, cranial base, and cranial vault are completely independent modules but relatively strongly integrated structures. These results indicate pervasive integration in the human skull and suggest a reinterpretation of the selective scenario for human evolution where the origin of any one of the derived characters may have facilitated the evolution of the others. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Dietary hardness, loading behavior, and the evolution of skull form in bats.

PubMed

Santana, Sharlene E; Grosse, Ian R; Dumont, Elizabeth R

2012-08-01

The morphology and biomechanics of the vertebrate skull reflect the physical properties of diet and behaviors used in food acquisition and processing. We use phyllostomid bats, the most diverse mammalian dietary radiation, to investigate if and how changes in dietary hardness and loading behaviors during feeding shaped the evolution of skull morphology and biomechanics. When selective regimes of food hardness are modeled, we found that species consuming harder foods have evolved skull shapes that allow for more efficient bite force production. These species have shorter skulls and a greater reliance on the temporalis muscle, both of which contribute to a higher mechanical advantage at an intermediate gape angle. The evolution of cranial morphology and biomechanics also appears to be related to loading behaviors. Evolutionary changes in skull shape and the relative role of the temporalis and masseter in generating bite force are correlated with changes in the use of torsional and bending loading behaviors. Functional equivalence appears to have evolved independently among three lineages of species that feed on liquids and are not obviously morphologically similar. These trends in cranial morphology and biomechanics provide insights into behavioral and ecological factors shaping the skull of a trophically diverse clade of mammals. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Asteroid Shapes Are Always Close To Fluid Equilibrium

NASA Astrophysics Data System (ADS)

Tanga, Paolo; Comito, C.; Hestroffer, D.; Richardson, D. C.

2010-10-01

The simple evidence that asteroid are composed by solid rocks suggests that their shape can be rather far from the theoretical equilibrium for rotating fluid bodies. The possible fragmented ("rubble-pile") nature of most of them has suggested interpretations based on elasto-plastic models (such as the Mohr-Coulomb theory) that take into account the static behavior of a granular structure. However, these approaches did not incorporate explicitly the possible evolution of shapes in time due to external factors such as crater forming impacts or tidal deformations. We revisited the theory of equilibrium shapes for fluids, quantitatively evaluating - by appropriate metrics - the distance of the observed shapes from fluid equilibrium. This distance turns out to be much smaller than previously expected. On the basis of this evidence, we simulated numerically the evolution of gravitational aggregates having a small degree of internal friction, consistent with the theoretical findings. Our results offer a global scenario for the evolution of asteroid shapes under the action of gradual stresses due to minor impacts, tidal forces and seismic shaking. We show that actual asteroid shapes are consistent with the evolution of aggregates tending towards minimum free energy states. We are able to explain the samples of observed shapes obtained by different techniques. Our findings strongly support a highly porous and fragmented nature for most asteroids, at least in an external layer. Reference: Tanga et al. 2009: ApJ Letters, 706, 1, L197-L202 Acknowledgments: PT and CC have been supported by the "Programme Nationale de Planetologie" of France; DCR acknowledges support by the NASA (grant no. NNX08AM39G issued through the Office of Space Science) and by the NSF (grant no. AST0708110).

Vertical distribution, flight behaviour and evolution of wing morphology in Morpho butterflies.

PubMed

Devries, P J; Penz, Carla M; Hill, Ryan I

2010-09-01

1. Flight is a key innovation in the evolution of insects that is crucial to their dispersal, migration, territoriality, courtship and predator avoidance. Male butterflies have characteristic territoriality and courtship flight behaviours, and females use a characteristic flight behaviour when searching for host plants. This implies that selection acts on wing morphology to maximize flight performance for conducting important behaviours among sexes. 2. Butterflies in the genus Morpho are obvious components of neotropical forests, and many observations indicate that they show two broad categories of flight behaviour and flight height. Although species can be categorized as using gliding or flapping flight, and flying at either canopy or understorey height, the association of flight behaviour and flight height with wing shape evolution has never been explored. 3. Two clades within Morpho differ in flight behaviour and height. Males and females of one clade inhabit the forest understorey and use flapping flight, whereas in the other clade, males use gliding flight at canopy level and females use flapping flight in both canopy and understorey. 4. We used independent contrasts to answer whether wing shape is associated with flight behaviour and height. Given a single switch to canopy habitation and gliding flight, we compared contrasts for the node at which the switch to canopy flight occurred with the distribution of values in the two focal clades. We found significant changes in wing shape at the transition to canopy flight only in males, and no change in size for either sex. A second node within the canopy clade suggests that other factors may also be involved in wing shape evolution. Our results reinforce the hypothesis that natural selection acts differently on male and female butterfly wing shape and indicate that the transition to canopy flight cannot explain all wing shape diversity in Morpho. 5. This study provides a starting point for characterizing evolution of wing morphology in forest butterflies in the contexts of habitat selection and flight behaviour. Further, these observations suggest that exploring wing shape evolution for canopy and understorey species in other insects may help understand the effects of habitat destruction on biological diversity.

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

USGS Publications Warehouse

Miller, David A.; Clark, W.R.; Arnold, S.J.; Bronikowski, A.M.

2011-01-01

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (??s) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on ?? s. The magnitude of variation in the proportion of gravid females and its effect on ??s was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on ??s was 4- 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution. ?? 2011 by the Ecological Society of America.

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories.

PubMed

Miller, David A; Clark, William R; Arnold, Stevan J; Bronikowski, Anne M

2011-08-01

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.

MONALISA for stochastic simulations of Petri net models of biochemical systems.

PubMed

Balazki, Pavel; Lindauer, Klaus; Einloft, Jens; Ackermann, Jörg; Koch, Ina

2015-07-10

The concept of Petri nets (PN) is widely used in systems biology and allows modeling of complex biochemical systems like metabolic systems, signal transduction pathways, and gene expression networks. In particular, PN allows the topological analysis based on structural properties, which is important and useful when quantitative (kinetic) data are incomplete or unknown. Knowing the kinetic parameters, the simulation of time evolution of such models can help to study the dynamic behavior of the underlying system. If the number of involved entities (molecules) is low, a stochastic simulation should be preferred against the classical deterministic approach of solving ordinary differential equations. The Stochastic Simulation Algorithm (SSA) is a common method for such simulations. The combination of the qualitative and semi-quantitative PN modeling and stochastic analysis techniques provides a valuable approach in the field of systems biology. Here, we describe the implementation of stochastic analysis in a PN environment. We extended MONALISA - an open-source software for creation, visualization and analysis of PN - by several stochastic simulation methods. The simulation module offers four simulation modes, among them the stochastic mode with constant firing rates and Gillespie's algorithm as exact and approximate versions. The simulator is operated by a user-friendly graphical interface and accepts input data such as concentrations and reaction rate constants that are common parameters in the biological context. The key features of the simulation module are visualization of simulation, interactive plotting, export of results into a text file, mathematical expressions for describing simulation parameters, and up to 500 parallel simulations of the same parameter sets. To illustrate the method we discuss a model for insulin receptor recycling as case study. We present a software that combines the modeling power of Petri nets with stochastic simulation of dynamic processes in a user-friendly environment supported by an intuitive graphical interface. The program offers a valuable alternative to modeling, using ordinary differential equations, especially when simulating single-cell experiments with low molecule counts. The ability to use mathematical expressions provides an additional flexibility in describing the simulation parameters. The open-source distribution allows further extensions by third-party developers. The software is cross-platform and is licensed under the Artistic License 2.0.

Trends in the sand: Directional evolution in the shell shape of recessing scallops (Bivalvia: Pectinidae).

PubMed

Sherratt, Emma; Alejandrino, Alvin; Kraemer, Andrew C; Serb, Jeanne M; Adams, Dean C

2016-09-01

Directional evolution is one of the most compelling evolutionary patterns observed in macroevolution. Yet, despite its importance, detecting such trends in multivariate data remains a challenge. In this study, we evaluate multivariate evolution of shell shape in 93 bivalved scallop species, combining geometric morphometrics and phylogenetic comparative methods. Phylomorphospace visualization described the history of morphological diversification in the group; revealing that taxa with a recessing life habit were the most distinctive in shell shape, and appeared to display a directional trend. To evaluate this hypothesis empirically, we extended existing methods by characterizing the mean directional evolution in phylomorphospace for recessing scallops. We then compared this pattern to what was expected under several alternative evolutionary scenarios using phylogenetic simulations. The observed pattern did not fall within the distribution obtained under multivariate Brownian motion, enabling us to reject this evolutionary scenario. By contrast, the observed pattern was more similar to, and fell within, the distribution obtained from simulations using Brownian motion combined with a directional trend. Thus, the observed data are consistent with a pattern of directional evolution for this lineage of recessing scallops. We discuss this putative directional evolutionary trend in terms of its potential adaptive role in exploiting novel habitats. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Malagasy cichlids differentially limit impacts of body shape evolution on oral jaw functional morphology.

PubMed

Martinez, Christopher M; Sparks, John S

2017-09-01

Patterns of trait covariation, such as integration and modularity, are vital factors that influence the evolution of vertebrate body plans. In functional systems, decoupling of morphological modules buffers functional change in one trait by reducing correlated variation with another. However, for complex morphologies with many-to-one mapping of form to function (MTOM), resistance to functional change may also be achieved by constraining morphological variation within a functionally stable region of morphospace. For this research, we used geometric morphometrics to evaluate the evolution of body shape and its relationship with jaw functional morphology in two independent radiations of endemic Malagasy cichlid (Teleostei: Cichlidae). Our results suggested that the two subfamilies used different strategies to mitigate impacts of body shape variation on a metric of jaw function, maxillary kinematic transmission (MKT): (1) modularity between cranial and postcranial morphologies, and (2) integration of body and jaw evolution, with jaw morphologies varying in a manner that limits change in MKT. This research shows that, unlike modularity, MTOM allows traits to retain strong evolutionary covariation while still reducing impacts on functionality. These results suggest that MTOM, and its influence on the evolution of correlated traits, is likely much more widespread than is currently understood. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Methods of Information Geometry to model complex shapes

NASA Astrophysics Data System (ADS)

De Sanctis, A.; Gattone, S. A.

2016-09-01

In this paper, a new statistical method to model patterns emerging in complex systems is proposed. A framework for shape analysis of 2- dimensional landmark data is introduced, in which each landmark is represented by a bivariate Gaussian distribution. From Information Geometry we know that Fisher-Rao metric endows the statistical manifold of parameters of a family of probability distributions with a Riemannian metric. Thus this approach allows to reconstruct the intermediate steps in the evolution between observed shapes by computing the geodesic, with respect to the Fisher-Rao metric, between the corresponding distributions. Furthermore, the geodesic path can be used for shape predictions. As application, we study the evolution of the rat skull shape. A future application in Ophthalmology is introduced.

Shape evolution of 72,74Kr with temperature in covariant density functional theory

NASA Astrophysics Data System (ADS)

Zhang, Wei; Niu, Yi-Fei

2017-09-01

The rich phenomena of deformations in neutron-deficient krypton isotopes, such as shape evolution with neutron number and shape coexistence, have attracted the interest of nuclear physicists for decades. It is interesting to study such shape phenomena using a novel way, e.g. by thermally exciting the nucleus. In this work, we develop the finite temperature covariant density functional theory for axially deformed nuclei with the treatment of pairing correlations by the BCS approach, and apply this approach for the study of shape evolution in 72,74Kr with increasing temperature. For 72Kr, with temperature increasing, the nucleus firstly experiences a relatively quick weakening in oblate deformation at temperature T ˜0.9 MeV, and then changes from oblate to spherical at T ˜2.1 MeV. For 74Kr, its global minimum is at quadrupole deformation β 2 ˜ -0.14 and abruptly changes to spherical at T˜ 1.7 MeV. The proton pairing transition occurs at critical temperature 0.6 MeV following the rule T c=0.6Δ p(0), where Δ p(0) is the proton pairing gap at zero temperature. The signatures of the above pairing transition and shape changes can be found in the specific heat curve. The single-particle level evolutions with temperature are presented. Supported by National Natural Science Foundation of China (11105042, 11305161, 11505157), Open Fund of Key Laboratory of Time and Frequency Primary Standards, CAS, and Support from Henan Administration of Foreign Experts Affairs

Adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope

NASA Astrophysics Data System (ADS)

Ma, Haotong; Hu, Haojun; Xie, Wenke; Zhao, Haichuan; Xu, Xiaojun; Chen, Jinbao

2013-08-01

We demonstrate the adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope based on the stochastic parallel gradient descent (SPGD) algorithm and dual phase only liquid crystal spatial light modulators (LC-SLMs). Adaptive pre-compensation the wavefront of projected laser beam at the transmitter telescope is chosen to improve the power coupling efficiency. One phase only LC-SLM adaptively optimizes phase distribution of the projected laser beam and the other generates turbulence phase screen. The intensity distributions of the dark hollow beam after passing through the turbulent atmosphere with and without adaptive beam shaping are analyzed in detail. The influence of propagation distance and aperture size of the Cassegrain-telescope on coupling efficiency are investigated theoretically and experimentally. These studies show that the power coupling can be significantly improved by adaptive beam shaping. The technique can be used in optical communication, deep space optical communication and relay mirror.

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

Manshour, Pouya; Ghasemi, Fatemeh; Sahimi, Muhammad

High-quality measurements of seismic activities around the world provide a wealth of data and information that are relevant to understanding of when earthquakes may occur. If viewed as complex stochastic time series, such data may be analyzed by methods that provide deeper insights into their nature, hence leading to better understanding of the data and their possible implications for earthquakes. In this paper, we provide further evidence for our recent proposal [P. Mansour et al., Phys. Rev. Lett. 102, 014101 (2009)] for the existence of a transition in the shape of the probability density function (PDF) of the successive detrendedmore » increments of the stochastic fluctuations of Earth's vertical velocity V{sub z}, collected by broadband stations before moderate and large earthquakes. To demonstrate the transition, we carried out extensive analysis of the data for V{sub z} for 12 earthquakes in several regions around the world, including the recent catasrophic one in Haiti. The analysis supports the hypothesis that before and near the time of an earthquake, the shape of the PDF undergoes significant and discernable changes, which can be characterized quantitatively. The typical time over which the PDF undergoes the transition is about 5-10 h prior to a moderate or large earthquake.« less

Studies of concentration and temperature dependences of precipitation kinetics in iron-copper alloys using kinetic Monte Carlo and stochastic statistical simulations

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

Khromov, K. Yu.; Vaks, V. G., E-mail: vaks@mbslab.kiae.ru; Zhuravlev, I. A.

2013-02-15

The previously developed ab initio model and the kinetic Monte Carlo method (KMCM) are used to simulate precipitation in a number of iron-copper alloys with different copper concentrations x and temperatures T. The same simulations are also made using an improved version of the previously suggested stochastic statistical method (SSM). The results obtained enable us to make a number of general conclusions about the dependences of the decomposition kinetics in Fe-Cu alloys on x and T. We also show that the SSM usually describes the precipitation kinetics in good agreement with the KMCM, and using the SSM in conjunction withmore » the KMCM allows extending the KMC simulations to the longer evolution times. The results of simulations seem to agree with available experimental data for Fe-Cu alloys within statistical errors of simulations and the scatter of experimental results. Comparison of simulation results with experiments for some multicomponent Fe-Cu-based alloys allows making certain conclusions about the influence of alloying elements in these alloys on the precipitation kinetics at different stages of evolution.« less

Modeling and optimization of the multiobjective stochastic joint replenishment and delivery problem under supply chain environment.

PubMed

Wang, Lin; Qu, Hui; Liu, Shan; Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted.

A novel procedure for the identification of chaos in complex biological systems

NASA Astrophysics Data System (ADS)

Bazeia, D.; Pereira, M. B. P. N.; Brito, A. V.; Oliveira, B. F. De; Ramos, J. G. G. S.

2017-03-01

We demonstrate the presence of chaos in stochastic simulations that are widely used to study biodiversity in nature. The investigation deals with a set of three distinct species that evolve according to the standard rules of mobility, reproduction and predation, with predation following the cyclic rules of the popular rock, paper and scissors game. The study uncovers the possibility to distinguish between time evolutions that start from slightly different initial states, guided by the Hamming distance which heuristically unveils the chaotic behavior. The finding opens up a quantitative approach that relates the correlation length to the average density of maxima of a typical species, and an ensemble of stochastic simulations is implemented to support the procedure. The main result of the work shows how a single and simple experimental realization that counts the density of maxima associated with the chaotic evolution of the species serves to infer its correlation length. We use the result to investigate others distinct complex systems, one dealing with a set of differential equations that can be used to model a diversity of natural and artificial chaotic systems, and another one, focusing on the ocean water level.

Study of selected phenotype switching strategies in time varying environment

NASA Astrophysics Data System (ADS)

Horvath, Denis; Brutovsky, Branislav

2016-03-01

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback-Leibler functional distances and the Hamming distance.

Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment

PubMed Central

Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted. PMID:24302880

Particle Swarm Optimization algorithms for geophysical inversion, practical hints

NASA Astrophysics Data System (ADS)

Garcia Gonzalo, E.; Fernandez Martinez, J.; Fernandez Alvarez, J.; Kuzma, H.; Menendez Perez, C.

2008-12-01

PSO is a stochastic optimization technique that has been successfully used in many different engineering fields. PSO algorithm can be physically interpreted as a stochastic damped mass-spring system (Fernandez Martinez and Garcia Gonzalo 2008). Based on this analogy we present a whole family of PSO algorithms and their respective first order and second order stability regions. Their performance is also checked using synthetic functions (Rosenbrock and Griewank) showing a degree of ill-posedness similar to that found in many geophysical inverse problems. Finally, we present the application of these algorithms to the analysis of a Vertical Electrical Sounding inverse problem associated to a seawater intrusion in a coastal aquifer in South Spain. We analyze the role of PSO parameters (inertia, local and global accelerations and discretization step), both in convergence curves and in the a posteriori sampling of the depth of an intrusion. Comparison is made with binary genetic algorithms and simulated annealing. As result of this analysis, practical hints are given to select the correct algorithm and to tune the corresponding PSO parameters. Fernandez Martinez, J.L., Garcia Gonzalo, E., 2008a. The generalized PSO: a new door to PSO evolution. Journal of Artificial Evolution and Applications. DOI:10.1155/2008/861275.

Exploring Quantum Dynamics of Continuous Measurement with a Superconducting Qubit

NASA Astrophysics Data System (ADS)

Jadbabaie, Arian; Forouzani, Neda; Tan, Dian; Murch, Kater

Weak measurements obtain partial information about a quantum state with minimal backaction. This enables state tracking without immediate collapse to eigenstates, of interest to both experimental and theoretical physics. State tomography and continuous weak measurements may be used to reconstruct the evolution of a single system, known as a quantum trajectory. We examine experimental trajectories of a two-level system at varied measurement strengths with constant unitary drive. Our analysis is applied to a transmon qubit dispersively coupled to a 3D microwave cavity in the circuit QED architecture. The weakly coupled cavity acts as pointer system for QND measurements in the qubit's energy basis. Our results indicate a marked difference in state purity between two approaches for trajectory reconstruction: the Bayesian and Stochastic Master Equation (SME) formalisms. Further, we observe the transition from diffusive to jump-like trajectories, state purity evolution, and a novel, tilted form of the Quantum Zeno effect. This work provides new insight into quantum behavior and prompts further comparison of SME and Bayesian formalisms to understand the nature of quantum systems. Our results are applicable to a variety of fields, from stochastic thermodynamics to quantum control.

Continuously growing rodent molars result from a predictable quantitative evolutionary change over 50 million years

PubMed Central

Mushegyan, Vagan; Eronen, Jussi T.; Lawing, A. Michelle; Sharir, Amnon; Janis, Christine; Jernvall, Jukka; Klein, Ophir D.

2015-01-01

Summary The fossil record is widely informative about evolution, but fossils are not systematically used to study the evolution of stem cell-driven renewal. Here, we examined evolution of the continuous growth (hypselodonty) of rodent molar teeth, which is fuelled by the presence of dental stem cells. We studied occurrences of 3500 North American rodent fossils, ranging from 50 million years ago (mya) to 2 mya. We examined changes in molar height to determine if evolution of hypselodonty shows distinct patterns in the fossil record, and we found that hypselodont taxa emerged through intermediate forms of increasing crown height. Next, we designed a Markov simulation model, which replicated molar height increases throughout the Cenozoic, and, moreover, evolution of hypselodonty. Thus, by extension, the retention of the adult stem-cell niche appears to be a predictable quantitative rather than a stochastic qualitative process. Our analyses predict that hypselodonty will eventually become the dominant phenotype. PMID:25921530

Unexpectedly rapid evolution of mandibular shape in hominins.

PubMed

Raia, P; Boggioni, M; Carotenuto, F; Castiglione, S; Di Febbraro, M; Di Vincenzo, F; Melchionna, M; Mondanaro, A; Papini, A; Profico, A; Serio, C; Veneziano, A; Vero, V A; Rook, L; Meloro, C; Manzi, G

2018-05-09

Members of the hominins - namely the so-called 'australopiths' and the species of the genus Homo - are known to possess short and deep mandibles and relatively small incisors and canines. It is commonly assumed that this suite of traits evolved in early members of the clade in response to changing environmental conditions and increased consumption of though food items. With the emergence of Homo, the functional meaning of mandible shape variation is thought to have been weakened by technological advancements and (later) by the control over fire. In contrast to this expectation, we found that mandible shape evolution in hominins is exceptionally rapid as compared to any other primate clade, and that the direction and rate of shape change (from the ape ancestor) are no different between the australopiths and Homo. We deem several factors including the loss of honing complex, canine reduction, and the acquisition of different diets may have concurred in producing such surprisingly high evolutionary rates. This study reveals the evolution of mandibular shape in hominins has strong morpho-functional and ecological significance attached.

Head shape evolution in Gymnophthalmidae: does habitat use constrain the evolution of cranial design in fossorial lizards?

PubMed

Barros, F C; Herrel, A; Kohlsdorf, T

2011-11-01

Habitat usage comprises interactions between ecological parameters and organismal capacities, and the selective pressures that ultimately determine the outcome of such processes in an evolutionary scale may be conflicting when the same morphological structure is recruited for different activities. Here, we investigate the roles of diet and locomotion in the evolution of cranial design in gymnophthalmid lizards and test the hypothesis that microhabitat use drives head shape evolution, particularly in head-first burrowers. Morphological factors were analysed in relation to continuous ecological indexes (prey hardness and substrate compactness) using conventional and phylogenetic approaches. Results suggest that the evolution of head morphology in Gymnophthalmidae was shaped under the influence of microhabitat use rather than diet: burrowers have shorter heads with lower rostral angulation, independently of the prey consumed. Food preferences appear to be relatively conserved throughout the phylogeny of the group, which may have permitted the extensive radiation of gymnophthalmids into fossorial microhabitats. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Stochastic subspace identification for operational modal analysis of an arch bridge

NASA Astrophysics Data System (ADS)

Loh, Chin-Hsiung; Chen, Ming-Che; Chao, Shu-Hsien

2012-04-01

In this paer the application of output-only system identification technique, known as Stochastic Subspace Identification (SSI) algorithms, for civil infrastructures is carried out. The ability of covariance driven stochastic subspace identification (SSI-COV) was proved through the analysis of the ambient data of an arch bridge under operational condition. A newly developed signal processing technique, Singular Spectrum analysis (SSA), capable to smooth noisy signals, is adopted for pre-processing the recorded data before the SSI. The conjunction of SSA and SSICOV provides a useful criterion for the system order determination. With the aim of estimating accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data Hankel matrix. Identification task of a real structure, Guandu Bridge, is carried out to identify the system natural frequencies and mode shapes. The uncertainty of the identified model parameters from output-only measurement of the bridge under operation condition, such as temperature and traffic loading conditions, is discussed.

An uncertainty model of acoustic metamaterials with random parameters

NASA Astrophysics Data System (ADS)

He, Z. C.; Hu, J. Y.; Li, Eric

2018-01-01

Acoustic metamaterials (AMs) are man-made composite materials. However, the random uncertainties are unavoidable in the application of AMs due to manufacturing and material errors which lead to the variance of the physical responses of AMs. In this paper, an uncertainty model based on the change of variable perturbation stochastic finite element method (CVPS-FEM) is formulated to predict the probability density functions of physical responses of AMs with random parameters. Three types of physical responses including the band structure, mode shapes and frequency response function of AMs are studied in the uncertainty model, which is of great interest in the design of AMs. In this computation, the physical responses of stochastic AMs are expressed as linear functions of the pre-defined random parameters by using the first-order Taylor series expansion and perturbation technique. Then, based on the linear function relationships of parameters and responses, the probability density functions of the responses can be calculated by the change-of-variable technique. Three numerical examples are employed to demonstrate the effectiveness of the CVPS-FEM for stochastic AMs, and the results are validated by Monte Carlo method successfully.

Exact event-driven implementation for recurrent networks of stochastic perfect integrate-and-fire neurons.

PubMed

Taillefumier, Thibaud; Touboul, Jonathan; Magnasco, Marcelo

2012-12-01

In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks' dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like interactions. In addition to being exact from the mathematical standpoint, our proposed method is highly efficient numerically. We envision that our algorithm is especially indicated for studying the emergence of polychronized motifs in networks evolving under spike-timing-dependent plasticity with intrinsic noise.

The role of phase dynamics in a stochastic model of a passively advected scalar

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan

2016-05-01

Collective synchronous motion of the phases is introduced in a model for the stochastic passive advection-diffusion of a scalar with external forcing. The model for the phase coupling dynamics follows the well known Kuramoto model paradigm of limit-cycle oscillators. The natural frequencies in the Kuramoto model are assumed to obey a given scale dependence through a dispersion relation of the drift-wave form -βk/1 +k2 , where β is a constant representing the typical strength of the gradient. The present aim is to study the importance of collective phase dynamics on the characteristic time evolution of the fluctuation energy and the formation of coherent structures. Our results show that the assumption of a fully stochastic phase state of turbulence is more relevant for high values of β, where we find that the energy spectrum follows a k-7 /2 scaling. Whereas for lower β there is a significant difference between a-synchronised and synchronised phase states, one could expect the formation of coherent modulations in the latter case.

Modelling stock order flows with non-homogeneous intensities from high-frequency data

NASA Astrophysics Data System (ADS)

Gorshenin, Andrey K.; Korolev, Victor Yu.; Zeifman, Alexander I.; Shorgin, Sergey Ya.; Chertok, Andrey V.; Evstafyev, Artem I.; Korchagin, Alexander Yu.

2013-10-01

A micro-scale model is proposed for the evolution of such information system as the limit order book in financial markets. Within this model, the flows of orders (claims) are described by doubly stochastic Poisson processes taking account of the stochastic character of intensities of buy and sell orders that determine the price discovery mechanism. The proposed multiplicative model of stochastic intensities makes it possible to analyze the characteristics of the order flows as well as the instantaneous proportion of the forces of buyers and sellers, that is, the imbalance process, without modelling the external information background. The proposed model gives the opportunity to link the micro-scale (high-frequency) dynamics of the limit order book with the macro-scale models of stock price processes of the form of subordinated Wiener processes by means of limit theorems of probability theory and hence, to use the normal variance-mean mixture models of the corresponding heavy-tailed distributions. The approach can be useful in different areas with similar properties (e.g., in plasma physics).

A computational framework for prime implicants identification in noncoherent dynamic systems.

PubMed

Di Maio, Francesco; Baronchelli, Samuele; Zio, Enrico

2015-01-01

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time-dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple-valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases. © 2014 Society for Risk Analysis.

Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics

NASA Astrophysics Data System (ADS)

Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.

Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.

Computational Modeling of Fluctuations in Energy and Metabolic Pathways of Methanogenic Archaea

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

Luthey-Schulten, Zaida

The methanogenic archaea, anaerobic microbes that convert CO2 and H2 and/or other small organic fermentation products into methane, play an unusually large role in the global carbon cycle. As they perform the final step in the anaerobic breakdown of biomass, methanogens are a biogenic source of an estimated one billion tons methane each year. Depending on the location, produced methane can be considered as either a greenhouse gas (agricultural byproduct), sequestered carbon storage (methane hydrate deposits), or a potential energy source (organic wastewater treatment). These microbes therefore represent an important target for biotechnology applications. Computational models of methanogens with predictivemore » power are useful aids in the adaptation of methanogenic systems, but need to connect processes of wide-ranging time and length scales. In this project, we developed several computational methodologies for modeling the dynamic behavior of entire cells that connects stochastic reaction-diffusion dynamics of individual biochemical pathways with genome-scale modeling of metabolic networks. While each of these techniques were in the realm of well-defined computational methods, here we integrated them to develop several entirely new approaches to systems biology. The first scientific aim of the project was to model how noise in a biochemical pathway propagates into cellular phenotypes. Genetic circuits have been optimized by evolution to regulate molecular processes despite stochastic noise, but the effect of such noise on a cellular biochemical networks is currently unknown. An integrated stochastic/systems model of Escherichia coli species was created to analyze how noise in protein expression gives—and therefore noise in metabolic fluxes—gives rise to multiple cellular phenotype in isogenic population. After the initial work developing and validating methods that allow characterization of the heterogeneity in the model organism E. coli, the project shifted toward investigations of the methanogen Methanosarcina acetivorans. By integrating an unprecedented transcriptomics dataset for growth of the methanogen on many substrates with an in silico model, heterogeneity in metabolic pathway usage and methane production were examined. This lent insight into the physiological requirements of the organism under different environmental conditions and uncovered the unique regulatory role that mRNA half-life has in shaping metabolic flux distributions in this organism.« less

Cranial ontogenetic variation in early saurischians and the role of heterochrony in the diversification of predatory dinosaurs.

PubMed

Foth, Christian; Hedrick, Brandon P; Ezcurra, Martin D

2016-01-01

Non-avian saurischian skulls underwent at least 165 million years of evolution and shapes varied from elongated skulls, such as in the theropod Coelophysis, to short and box-shaped skulls, such as in the sauropod Camarasaurus. A number of factors have long been considered to drive skull shape, including phylogeny, dietary preferences and functional constraints. However, heterochrony is increasingly being recognized as an important factor in dinosaur evolution. In order to quantitatively analyse the impact of heterochrony on saurischian skull shape, we analysed five ontogenetic trajectories using two-dimensional geometric morphometrics in a phylogenetic framework. This allowed for the comparative investigation of main ontogenetic shape changes and the evaluation of how heterochrony affected skull shape through both ontogenetic and phylogenetic trajectories. Using principal component analyses and multivariate regressions, it was possible to quantify different ontogenetic trajectories and evaluate them for evidence of heterochronic events allowing testing of previous hypotheses on cranial heterochrony in saurischians. We found that the skull shape of the hypothetical ancestor of Saurischia likely led to basal Sauropodomorpha through paedomorphosis, and to basal Theropoda mainly through peramorphosis. Paedomorphosis then led from Orionides to Avetheropoda, indicating that the paedomorphic trend found by previous authors in advanced coelurosaurs may extend back into the early evolution of Avetheropoda. Not only are changes in saurischian skull shape complex due to the large number of factors that affected it, but heterochrony itself is complex, with a number of possible reversals throughout non-avian saurischian evolution. In general, the sampling of complete ontogenetic trajectories including early juveniles is considerably lower than the sampling of single adult or subadult individuals, which is a major impediment to the study of heterochrony on non-avian dinosaurs. Thus, the current work represents an exploratory analysis. To better understand the cranial ontogeny and the impact of heterochrony on skull evolution in saurischians, the data set that we present here must be expanded and complemented with further sampling from future fossil discoveries, especially of juvenile individuals.

Most Colorful Example of Genetic Assimilation? Exploring the Evolutionary Destiny of Recurrent Phenotypic Accommodation.

PubMed

Badyaev, Alexander V; Potticary, Ahva L; Morrison, Erin S

2017-08-01

Evolution of adaptation requires both generation of novel phenotypic variation and retention of a locally beneficial subset of this variation. Such retention can be facilitated by genetic assimilation, the accumulation of genetic and molecular mechanisms that stabilize induced phenotypes and assume progressively greater control over their reliable production. A particularly strong inference into genetic assimilation as an evolutionary process requires a system where it is possible to directly evaluate the extent to which an induced phenotype is progressively incorporated into preexisting developmental pathways. Evolution of diet-dependent pigmentation in birds-where external carotenoids are coopted into internal metabolism to a variable degree before being integrated with a feather's developmental processes-provides such an opportunity. Here we combine a metabolic network view of carotenoid evolution with detailed empirical study of feather modifications to show that the effect of physical properties of carotenoids on feather structure depends on their metabolic modification, their environmental recurrence, and biochemical redundancy, as predicted by the genetic assimilation hypothesis. Metabolized carotenoids caused less stochastic variation in feather structure and were more closely integrated with feather growth than were dietary carotenoids of the same molecular weight. These patterns were driven by the recurrence of organism-carotenoid associations: commonly used dietary carotenoids and biochemically redundant derived carotenoids caused less stochastic variation in feather structure than did rarely used or biochemically unique compounds. We discuss implications of genetic assimilation processes for the evolutionary diversification of diet-dependent animal coloration.

Stochastic, adaptive sampling of information by microvilli in fly photoreceptors.

PubMed

Song, Zhuoyi; Postma, Marten; Billings, Stephen A; Coca, Daniel; Hardie, Roger C; Juusola, Mikko

2012-08-07

In fly photoreceptors, light is focused onto a photosensitive waveguide, the rhabdomere, consisting of tens of thousands of microvilli. Each microvillus is capable of generating elementary responses, quantum bumps, in response to single photons using a stochastically operating phototransduction cascade. Whereas much is known about the cascade reactions, less is known about how the concerted action of the microvilli population encodes light changes into neural information and how the ultrastructure and biochemical machinery of photoreceptors of flies and other insects evolved in relation to the information sampling and processing they perform. We generated biophysically realistic fly photoreceptor models, which accurately simulate the encoding of visual information. By comparing stochastic simulations with single cell recordings from Drosophila photoreceptors, we show how adaptive sampling by 30,000 microvilli captures the temporal structure of natural contrast changes. Following each bump, individual microvilli are rendered briefly (~100-200 ms) refractory, thereby reducing quantum efficiency with increasing intensity. The refractory period opposes saturation, dynamically and stochastically adjusting availability of microvilli (bump production rate: sample rate), whereas intracellular calcium and voltage adapt bump amplitude and waveform (sample size). These adapting sampling principles result in robust encoding of natural light changes, which both approximates perceptual contrast constancy and enhances novel events under different light conditions, and predict information processing across a range of species with different visual ecologies. These results clarify why fly photoreceptors are structured the way they are and function as they do, linking sensory information to sensory evolution and revealing benefits of stochasticity for neural information processing. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stochastic, Adaptive Sampling of Information by Microvilli in Fly Photoreceptors

PubMed Central

Song, Zhuoyi; Postma, Marten; Billings, Stephen A.; Coca, Daniel; Hardie, Roger C.; Juusola, Mikko

2012-01-01

Summary Background In fly photoreceptors, light is focused onto a photosensitive waveguide, the rhabdomere, consisting of tens of thousands of microvilli. Each microvillus is capable of generating elementary responses, quantum bumps, in response to single photons using a stochastically operating phototransduction cascade. Whereas much is known about the cascade reactions, less is known about how the concerted action of the microvilli population encodes light changes into neural information and how the ultrastructure and biochemical machinery of photoreceptors of flies and other insects evolved in relation to the information sampling and processing they perform. Results We generated biophysically realistic fly photoreceptor models, which accurately simulate the encoding of visual information. By comparing stochastic simulations with single cell recordings from Drosophila photoreceptors, we show how adaptive sampling by 30,000 microvilli captures the temporal structure of natural contrast changes. Following each bump, individual microvilli are rendered briefly (∼100–200 ms) refractory, thereby reducing quantum efficiency with increasing intensity. The refractory period opposes saturation, dynamically and stochastically adjusting availability of microvilli (bump production rate: sample rate), whereas intracellular calcium and voltage adapt bump amplitude and waveform (sample size). These adapting sampling principles result in robust encoding of natural light changes, which both approximates perceptual contrast constancy and enhances novel events under different light conditions, and predict information processing across a range of species with different visual ecologies. Conclusions These results clarify why fly photoreceptors are structured the way they are and function as they do, linking sensory information to sensory evolution and revealing benefits of stochasticity for neural information processing. PMID:22704990

Emergence, reductionism and landscape response to climate change

NASA Astrophysics Data System (ADS)

Harrison, Stephan; Mighall, Tim

2010-05-01

Predicting landscape response to external forcing is hampered by the non-linear, stochastic and contingent (ie dominated by historical accidents) forcings inherent in landscape evolution. Using examples from research carried out in southwest Ireland we suggest that non-linearity in landform evolution is likely to be a strong control making regional predictions of landscape response to climate change very difficult. While uncertainties in GCM projections have been widely explored in climate science much less attention has been directed by geomorphologists to the uncertainties in landform evolution under conditions of climate change and this problem may be viewed within the context of philosophical approaches to reductionsim and emergence. Understanding the present and future trajectory of landform change may also guide us to provide an enhanced appreciation of how landforms evolved in the past.

Does aquatic foraging impact head shape evolution in snakes?

PubMed Central

Cornette, Raphaël; Fabre, Anne-Claire; Godoy-Diana, Ramiro; Herrel, Anthony

2016-01-01

Evolutionary trajectories are often biased by developmental and historical factors. However, environmental factors can also impose constraints on the evolutionary trajectories of organisms leading to convergence of morphology in similar ecological contexts. The physical properties of water impose strong constraints on aquatic feeding animals by generating pressure waves that can alert prey and potentially push them away from the mouth. These hydrodynamic constraints have resulted in the independent evolution of suction feeding in most groups of secondarily aquatic tetrapods. Despite the fact that snakes cannot use suction, they have invaded the aquatic milieu many times independently. Here, we test whether the aquatic environment has constrained head shape evolution in snakes and whether shape converges on that predicted by biomechanical models. To do so, we used three-dimensional geometric morphometrics and comparative, phylogenetically informed analyses on a large sample of aquatic snake species. Our results show that aquatic snakes partially conform to our predictions and have a narrower anterior part of the head and dorsally positioned eyes and nostrils. This morphology is observed, irrespective of the phylogenetic relationships among species, suggesting that the aquatic environment does indeed drive the evolution of head shape in snakes, thus biasing the evolutionary trajectory of this group of animals. PMID:27581887

Irregular synchronous activity in stochastically-coupled networks of integrate-and-fire neurons.

PubMed

Lin, J K; Pawelzik, K; Ernst, U; Sejnowski, T J

1998-08-01

We investigate the spatial and temporal aspects of firing patterns in a network of integrate-and-fire neurons arranged in a one-dimensional ring topology. The coupling is stochastic and shaped like a Mexican hat with local excitation and lateral inhibition. With perfect precision in the couplings, the attractors of activity in the network occur at every position in the ring. Inhomogeneities in the coupling break the translational invariance of localized attractors and lead to synchronization within highly active as well as weakly active clusters. The interspike interval variability is high, consistent with recent observations of spike time distributions in visual cortex. The robustness of our results is demonstrated with more realistic simulations on a network of McGregor neurons which model conductance changes and after-hyperpolarization potassium currents.

Conservation laws shape dissipation

NASA Astrophysics Data System (ADS)

Rao, Riccardo; Esposito, Massimiliano

2018-02-01

Starting from the most general formulation of stochastic thermodynamics—i.e. a thermodynamically consistent nonautonomous stochastic dynamics describing systems in contact with several reservoirs—we define a procedure to identify the conservative and the minimal set of nonconservative contributions in the entropy production. The former is expressed as the difference between changes caused by time-dependent drivings and a generalized potential difference. The latter is a sum over the minimal set of flux-force contributions controlling the dissipative flows across the system. When the system is initially prepared at equilibrium (e.g. by turning off drivings and forces), a finite-time detailed fluctuation theorem holds for the different contributions. Our approach relies on identifying the complete set of conserved quantities and can be viewed as the extension of the theory of generalized Gibbs ensembles to nonequilibrium situations.

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

Pan, Yu, E-mail: yu.pan@anu.edu.au, E-mail: zibo.miao@anu.edu.au; Miao, Zibo, E-mail: yu.pan@anu.edu.au, E-mail: zibo.miao@anu.edu.au; Amini, Hadis, E-mail: nhamini@stanford.edu

Quantum Markovian systems, modeled as unitary dilations in the quantum stochastic calculus of Hudson and Parthasarathy, have become standard in current quantum technological applications. This paper investigates the stability theory of such systems. Lyapunov-type conditions in the Heisenberg picture are derived in order to stabilize the evolution of system operators as well as the underlying dynamics of the quantum states. In particular, using the quantum Markov semigroup associated with this quantum stochastic differential equation, we derive sufficient conditions for the existence and stability of a unique and faithful invariant quantum state. Furthermore, this paper proves the quantum invariance principle, whichmore » extends the LaSalle invariance principle to quantum systems in the Heisenberg picture. These results are formulated in terms of algebraic constraints suitable for engineering quantum systems that are used in coherent feedback networks.« less

Emergent Lévy behavior in single-cell stochastic gene expression

NASA Astrophysics Data System (ADS)

Jia, Chen; Zhang, Michael Q.; Qian, Hong

2017-10-01

Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the Lévy limit provides a theoretical foundation for an empirical equation proposed in N. Friedman et al., Phys. Rev. Lett. 97, 168302 (2006), 10.1103/PhysRevLett.97.168302. Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.

Weighted Flow Algorithms (WFA) for stochastic particle coagulation

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

DeVille, R.E.L., E-mail: rdeville@illinois.edu; Riemer, N., E-mail: nriemer@illinois.edu; West, M., E-mail: mwest@illinois.edu

2011-09-20

Stochastic particle-resolved methods are a useful way to compute the time evolution of the multi-dimensional size distribution of atmospheric aerosol particles. An effective approach to improve the efficiency of such models is the use of weighted computational particles. Here we introduce particle weighting functions that are power laws in particle size to the recently-developed particle-resolved model PartMC-MOSAIC and present the mathematical formalism of these Weighted Flow Algorithms (WFA) for particle coagulation and growth. We apply this to an urban plume scenario that simulates a particle population undergoing emission of different particle types, dilution, coagulation and aerosol chemistry along a Lagrangianmore » trajectory. We quantify the performance of the Weighted Flow Algorithm for number and mass-based quantities of relevance for atmospheric sciences applications.« less

Stochastic thermodynamics of fluctuating density fields: Non-equilibrium free energy differences under coarse-graining

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

Leonard, T.; Lander, B.; Seifert, U.

2013-11-28

We discuss the stochastic thermodynamics of systems that are described by a time-dependent density field, for example, simple liquids and colloidal suspensions. For a time-dependent change of external parameters, we show that the Jarzynski relation connecting work with the change of free energy holds if the time evolution of the density follows the Kawasaki-Dean equation. Specifically, we study the work distributions for the compression and expansion of a two-dimensional colloidal model suspension implementing a practical coarse-graining scheme of the microscopic particle positions. We demonstrate that even if coarse-grained dynamics and density functional do not match, the fluctuation relations for themore » work still hold albeit for a different, apparent, change of free energy.« less

Inversion method based on stochastic optimization for particle sizing.

PubMed

Sánchez-Escobar, Juan Jaime; Barbosa-Santillán, Liliana Ibeth; Vargas-Ubera, Javier; Aguilar-Valdés, Félix

2016-08-01

A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.

Weighted Flow Algorithms (WFA) for stochastic particle coagulation

NASA Astrophysics Data System (ADS)

DeVille, R. E. L.; Riemer, N.; West, M.

2011-09-01

Stochastic particle-resolved methods are a useful way to compute the time evolution of the multi-dimensional size distribution of atmospheric aerosol particles. An effective approach to improve the efficiency of such models is the use of weighted computational particles. Here we introduce particle weighting functions that are power laws in particle size to the recently-developed particle-resolved model PartMC-MOSAIC and present the mathematical formalism of these Weighted Flow Algorithms (WFA) for particle coagulation and growth. We apply this to an urban plume scenario that simulates a particle population undergoing emission of different particle types, dilution, coagulation and aerosol chemistry along a Lagrangian trajectory. We quantify the performance of the Weighted Flow Algorithm for number and mass-based quantities of relevance for atmospheric sciences applications.

Historical and contingent factors affect re-evolution of a complex feature lost during mass extinction in communities of digital organisms.

PubMed

Yedid, G; Ofria, C A; Lenski, R E

2008-09-01

Re-evolution of complex biological features following the extinction of taxa bearing them remains one of evolution's most interesting phenomena, but is not amenable to study in fossil taxa. We used communities of digital organisms (computer programs that self-replicate, mutate and evolve), subjected to periods of low resource availability, to study the evolution, loss and re-evolution of a complex computational trait, the function EQU (bit-wise logical equals). We focused our analysis on cases where the pre-extinction EQU clade had surviving descendents at the end of the extinction episode. To see if these clades retained the capacity to re-evolve EQU, we seeded one set of multiple subreplicate 'replay' populations using the most abundant survivor of the pre-extinction EQU clade, and another set with the actual end-extinction ancestor of the organism in which EQU re-evolved following the extinction episode. Our results demonstrate that stochastic, historical, genomic and ecological factors can lead to constraints on further adaptation, and facilitate or hinder re-evolution of a complex feature.

New insights into time series analysis. II - Non-correlated observations

NASA Astrophysics Data System (ADS)

Ferreira Lopes, C. E.; Cross, N. J. G.

2017-08-01

Context. Statistical parameters are used to draw conclusions in a vast number of fields such as finance, weather, industrial, and science. These parameters are also used to identify variability patterns on photometric data to select non-stochastic variations that are indicative of astrophysical effects. New, more efficient, selection methods are mandatory to analyze the huge amount of astronomical data. Aims: We seek to improve the current methods used to select non-stochastic variations on non-correlated data. Methods: We used standard and new data-mining parameters to analyze non-correlated data to find the best way to discriminate between stochastic and non-stochastic variations. A new approach that includes a modified Strateva function was performed to select non-stochastic variations. Monte Carlo simulations and public time-domain data were used to estimate its accuracy and performance. Results: We introduce 16 modified statistical parameters covering different features of statistical distribution such as average, dispersion, and shape parameters. Many dispersion and shape parameters are unbound parameters, I.e. equations that do not require the calculation of average. Unbound parameters are computed with single loop and hence decreasing running time. Moreover, the majority of these parameters have lower errors than previous parameters, which is mainly observed for distributions with few measurements. A set of non-correlated variability indices, sample size corrections, and a new noise model along with tests of different apertures and cut-offs on the data (BAS approach) are introduced. The number of mis-selections are reduced by about 520% using a single waveband and 1200% combining all wavebands. On the other hand, the even-mean also improves the correlated indices introduced in Paper I. The mis-selection rate is reduced by about 18% if the even-mean is used instead of the mean to compute the correlated indices in the WFCAM database. Even-statistics allows us to improve the effectiveness of both correlated and non-correlated indices. Conclusions: The selection of non-stochastic variations is improved by non-correlated indices. The even-averages provide a better estimation of mean and median for almost all statistical distributions analyzed. The correlated variability indices, which are proposed in the first paper of this series, are also improved if the even-mean is used. The even-parameters will also be useful for classifying light curves in the last step of this project. We consider that the first step of this project, where we set new techniques and methods that provide a huge improvement on the efficiency of selection of variable stars, is now complete. Many of these techniques may be useful for a large number of fields. Next, we will commence a new step of this project regarding the analysis of period search methods.

Stochastic Lotka-Volterra equations: A model of lagged diffusion of technology in an interconnected world

NASA Astrophysics Data System (ADS)

Chakrabarti, Anindya S.

2016-01-01

We present a model of technological evolution due to interaction between multiple countries and the resultant effects on the corresponding macro variables. The world consists of a set of economies where some countries are leaders and some are followers in the technology ladder. All of them potentially gain from technological breakthroughs. Applying Lotka-Volterra (LV) equations to model evolution of the technology frontier, we show that the way technology diffuses creates repercussions in the partner economies. This process captures the spill-over effects on major macro variables seen in the current highly globalized world due to trickle-down effects of technology.

Intrinsic periodic and aperiodic stochastic resonance in an electrochemical cell

NASA Astrophysics Data System (ADS)

Tiwari, Ishant; Phogat, Richa; Parmananda, P.; Ocampo-Espindola, J. L.; Rivera, M.

2016-08-01

In this paper we show the interaction of a composite of a periodic or aperiodic signal and intrinsic electrochemical noise with the nonlinear dynamics of an electrochemical cell configured to study the corrosion of iron in an acidic media. The anodic voltage setpoint (V0) in the cell is chosen such that the anodic current (I ) exhibits excitable fixed point behavior in the absence of noise. The subthreshold periodic (aperiodic) signal consists of a train of rectangular pulses with a fixed amplitude and width, separated by regular (irregular) time intervals. The irregular time intervals chosen are of deterministic and stochastic origins. The amplitude of the intrinsic internal noise, regulated by the concentration of chloride ions, is then monotonically increased, and the provoked dynamics are analyzed. The signal to noise ratio and the cross-correlation coefficient versus the chloride ions' concentration curves have a unimodal shape indicating the emergence of an intrinsic periodic or aperiodic stochastic resonance. The abscissa for the maxima of these unimodal curves correspond to the optimum value of intrinsic noise where maximum regularity of the invoked dynamics is observed. In the particular case of the intrinsic periodic stochastic resonance, the scanning electron microscope images for the electrode metal surfaces are shown for certain values of chloride ions' concentrations. These images, qualitatively, corroborate the emergence of order as a result of the interaction between the nonlinear dynamics and the composite signal.

Morphological Evolution of Pit-Patterned Si(001) Substrates Driven by Surface-Energy Reduction

NASA Astrophysics Data System (ADS)

Salvalaglio, Marco; Backofen, Rainer; Voigt, Axel; Montalenti, Francesco

2017-09-01

Lateral ordering of heteroepitaxial islands can be conveniently achieved by suitable pit-patterning of the substrate prior to deposition. Controlling shape, orientation, and size of the pits is not trivial as, being metastable, they can significantly evolve during deposition/annealing. In this paper, we exploit a continuum model to explore the typical metastable pit morphologies that can be expected on Si(001), depending on the initial depth/shape. Evolution is predicted using a surface-diffusion model, formulated in a phase-field framework, and tackling surface-energy anisotropy. Results are shown to nicely reproduce typical metastable shapes reported in the literature. Moreover, long time scale evolutions of pit profiles with different depths are found to follow a similar kinetic pathway. The model is also exploited to treat the case of heteroepitaxial growth involving two materials characterized by different facets in their equilibrium Wulff's shape. This can lead to significant changes in morphologies, such as a rotation of the pit during deposition as evidenced in Ge/Si experiments.

Morphological Evolution of Pit-Patterned Si(001) Substrates Driven by Surface-Energy Reduction.

PubMed

Salvalaglio, Marco; Backofen, Rainer; Voigt, Axel; Montalenti, Francesco

2017-09-29

Lateral ordering of heteroepitaxial islands can be conveniently achieved by suitable pit-patterning of the substrate prior to deposition. Controlling shape, orientation, and size of the pits is not trivial as, being metastable, they can significantly evolve during deposition/annealing. In this paper, we exploit a continuum model to explore the typical metastable pit morphologies that can be expected on Si(001), depending on the initial depth/shape. Evolution is predicted using a surface-diffusion model, formulated in a phase-field framework, and tackling surface-energy anisotropy. Results are shown to nicely reproduce typical metastable shapes reported in the literature. Moreover, long time scale evolutions of pit profiles with different depths are found to follow a similar kinetic pathway. The model is also exploited to treat the case of heteroepitaxial growth involving two materials characterized by different facets in their equilibrium Wulff's shape. This can lead to significant changes in morphologies, such as a rotation of the pit during deposition as evidenced in Ge/Si experiments.

Stochastic Coastal/Regional Uncertainty Modelling: a Copernicus marine research project in the framework of Service Evolution

NASA Astrophysics Data System (ADS)

Vervatis, Vassilios; De Mey, Pierre; Ayoub, Nadia; Kailas, Marios; Sofianos, Sarantis

2017-04-01

The project entitled Stochastic Coastal/Regional Uncertainty Modelling (SCRUM) aims at strengthening CMEMS in the areas of ocean uncertainty quantification, ensemble consistency verification and ensemble data assimilation. The project has been initiated by the University of Athens and LEGOS/CNRS research teams, in the framework of CMEMS Service Evolution. The work is based on stochastic modelling of ocean physics and biogeochemistry in the Bay of Biscay, on an identical sub-grid configuration of the IBI-MFC system in its latest CMEMS operational version V2. In a first step, we use a perturbed tendencies scheme to generate ensembles describing uncertainties in open ocean and on the shelf, focusing on upper ocean processes. In a second step, we introduce two methodologies (i.e. rank histograms and array modes) aimed at checking the consistency of the above ensembles with respect to TAC data and arrays. Preliminary results highlight that wind uncertainties dominate all other atmosphere-ocean sources of model errors. The ensemble spread in medium-range ensembles is approximately 0.01 m for SSH and 0.15 °C for SST, though these values vary depending on season and cross shelf regions. Ecosystem model uncertainties emerging from perturbations in physics appear to be moderately larger than those perturbing the concentration of the biogeochemical compartments, resulting in total chlorophyll spread at about 0.01 mg.m-3. First consistency results show that the model ensemble and the pseudo-ensemble of OSTIA (L4) observation SSTs appear to exhibit nonzero joint probabilities with each other since error vicinities overlap. Rank histograms show that the model ensemble is initially under-dispersive, though results improve in the context of seasonal-range ensembles.

Convergent evolution of sexual shape dimorphism in Diptera.

PubMed

Bonduriansky, Russell

2006-05-01

Several patterns of sexual shape dimorphism, such as male body elongation, eye stalks, or extensions of the exoskeleton, have evolved repeatedly in the true flies (Diptera). Although these dimorphisms may have evolved in response to sexual selection on male body shape, conserved genetic factors may have contributed to this convergent evolution, resulting in stronger phenotypic convergence than might be expected from functional requirements alone. I compared phenotypic variation in body shape in two distantly related species exhibiting sexually dimorphic body elongation: Prochyliza xanthostoma (Piophilidae) and Telostylinus angusticollis (Neriidae). Although sexual selection appears to act differently on male body shape in these species, they exhibited strikingly similar patterns of sexual dimorphism. Likewise, patterns of within-sex shape variation were similar in the two species, particularly in males: relative elongation of the male head capsule, antenna, and legs was associated with reduced head capsule width and wing length, but was nearly independent of variation in thorax length. However, the two species presented contrasting patterns of static allometry: male sexual traits exhibited elevated allometric slopes in T. angusticollis, but not in P. xanthostoma. These results suggest that a shared pattern of covariation among traits may have channeled the evolution of sexually dimorphic body elongation in these species. Nonetheless, static allometries may have been shaped by species-specific selection pressures or genetic architectures. Copyright 2006 Wiley-Liss, Inc.

Global Topology Optimisation

DTIC Science & Technology

2016-10-31

statistical physics. Sec. IV includes several examples of the application of the stochastic method, including matching of a shape to a fixed design, and...an important part of any future application of this method. Second, re-initialization of the level set can lead to small but significant movements of...of engineering design problems [6, 17]. However, many of the relevant applications involve non-convex optimisation problems with multiple locally

On the modeling of epidemics under the influence of risk perception

NASA Astrophysics Data System (ADS)

de Lillo, S.; Fioriti, G.; Prioriello, M. L.

An epidemic spreading model is presented in the framework of the kinetic theory of active particles. The model is characterized by the influence of risk perception which can reduce the diffusion of infection. The evolution of the system is modeled through nonlinear interactions, whose output is described by stochastic games. The results of numerical simulations are discussed for different initial conditions.

Dynamics of Markets

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2009-09-01

Preface; 1. Econophysics: why and what; 2. Neo-classical economic theory; 3. Probability and stochastic processes; 4. Introduction to financial economics; 5. Introduction to portfolio selection theory; 6. Scaling, pair correlations, and conditional densities; 7. Statistical ensembles: deducing dynamics from time series; 8. Martingale option pricing; 9. FX market globalization: evolution of the dollar to worldwide reserve currency; 10. Macroeconomics and econometrics: regression models vs. empirically based modeling; 11. Complexity; Index.

Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach

PubMed Central

Appia, Vikram; Ganapathy, Balaji; Yezzi, Anthony; Faber, Tracy

2014-01-01

We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divisions) in an image and then combines these locally accurate segmentation curves to obtain a global segmentation. The training data for our approach consists of training shapes and associated auxiliary (target) masks. The masks indicate the various regions of the shape exhibiting highly correlated variations locally which may be rather independent of the variations in the distant parts of the global shape. Thus, in a sense, we are clustering the variations exhibited in the training data set. We then use a parametric model to implicitly represent each localized segmentation curve as a combination of the local shape priors obtained by representing the training shapes and the masks as a collection of signed distance functions. We also propose a parametric model to combine the locally evolved segmentation curves into a single hybrid (global) segmentation. Finally, we combine the evolution of these semilocal and global parameters to minimize an objective energy function. The resulting algorithm thus provides a globally accurate solution, which retains the local variations in shape. We present some results to illustrate how our approach performs better than the traditional approach with fully global PCA. PMID:25520901

Body shape transformation along a shared axis of anatomical evolution in labyrinth fishes (Anabantoidei).

PubMed

Collar, David C; Quintero, Michelle; Buttler, Bernardo; Ward, Andrea B; Mehta, Rita S

2016-03-01

Major morphological transformations, such as the evolution of elongate body shape in vertebrates, punctuate evolutionary history. A fundamental step in understanding the processes that give rise to such transformations is identification of the underlying anatomical changes. But as we demonstrate in this study, important insights can also be gained by comparing these changes to those that occur in ancestral and closely related lineages. In labyrinth fishes (Anabantoidei), rapid evolution of a highly derived torpedo-shaped body in the common ancestor of the pikehead (Luciocephalus aura and L. pulcher) occurred primarily through exceptional elongation of the head, with secondary contributions involving reduction in body depth and lengthening of the precaudal vertebral region. This combination of changes aligns closely with the primary axis of anatomical diversification in other anabantoids, revealing that pikehead evolution involved extraordinarily rapid change in structures that were ancestrally labile. Finer-scale examination of the anatomical components that determine head elongation also shows alignment between the pikehead evolutionary trajectory and the primary axis of cranial diversification in anabantoids, with much higher evolutionary rates leading to the pikehead. Altogether, our results show major morphological transformation stemming from extreme change along a shared morphological axis in labyrinth fishes. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Early bursts of body size and shape evolution are rare in comparative data.

PubMed

Harmon, Luke J; Losos, Jonathan B; Jonathan Davies, T; Gillespie, Rosemary G; Gittleman, John L; Bryan Jennings, W; Kozak, Kenneth H; McPeek, Mark A; Moreno-Roark, Franck; Near, Thomas J; Purvis, Andy; Ricklefs, Robert E; Schluter, Dolph; Schulte Ii, James A; Seehausen, Ole; Sidlauskas, Brian L; Torres-Carvajal, Omar; Weir, Jason T; Mooers, Arne Ø

2010-08-01

George Gaylord Simpson famously postulated that much of life's diversity originated as adaptive radiations-more or less simultaneous divergences of numerous lines from a single ancestral adaptive type. However, identifying adaptive radiations has proven difficult due to a lack of broad-scale comparative datasets. Here, we use phylogenetic comparative data on body size and shape in a diversity of animal clades to test a key model of adaptive radiation, in which initially rapid morphological evolution is followed by relative stasis. We compared the fit of this model to both single selective peak and random walk models. We found little support for the early-burst model of adaptive radiation, whereas both other models, particularly that of selective peaks, were commonly supported. In addition, we found that the net rate of morphological evolution varied inversely with clade age. The youngest clades appear to evolve most rapidly because long-term change typically does not attain the amount of divergence predicted from rates measured over short time scales. Across our entire analysis, the dominant pattern was one of constraints shaping evolution continually through time rather than rapid evolution followed by stasis. We suggest that the classical model of adaptive radiation, where morphological evolution is initially rapid and slows through time, may be rare in comparative data.

Understanding Galaxy Shapes Across Cosmic Time Using The IllustrisTNG Simulation

NASA Astrophysics Data System (ADS)

Genel, Shy

2017-08-01

Legacy HST observations have enabled groundbreaking measurements of galaxy structure over cosmic time, measurements that still require theoretical interpretation in the context of a comprehensive galaxy evolution model. This proposed research aims at significantly promoting our understanding of the shapes of galaxies as quantified by their principal axes ratios. The main tool we propose to use is IllustrisTNG, a suite consisting of two of the largest cosmological hydrodynamical simulations run to date, which contain resolved galaxy populations (thousands of L* galaxies) that represent a state-of-the-art match to observed galaxies. In Part I of the program, we will use the simulations to create mock images and study the dependence of projected shape measurements on various factors: shape estimator, observed band, the presence of dust, radial and surface brightness cuts, and noise. We will then perform apples-to-apples comparison with observations (including HST), and provide predictions for archival as well as future observations. Further, we will quantify the intrinsic, three-dimensional, shape distribution of galaxies as a function of various galaxy parameters: redshift, mass, color, and size. In Part II of the program, we will develop theoretical insights into the physical mechanisms driving these results. We will study how galaxy shapes relate to angular momentum and merger history, and will follow the shape evolution of individual galaxies over time, looking for correlations to the evolution of other galaxy properties, e.g. size and SFR. We will also study galaxy shape relations to dark matter halo shape, thereby providing input for high-precision cosmic shear models.

Scaling of Ln(Permeability) in Sediments and Velocity Distributions in Turbulence: The Possibility of an Analogy.

NASA Astrophysics Data System (ADS)

Molz, F. J.; Kozubowski, T. J.; Miller, R. S.; Podgorski, K.

2005-12-01

The theory of non-stationary stochastic processes with stationary increments gives rise to stochastic fractals. When such fractals are used to represent measurements of (assumed stationary) physical properties, such as ln(k) increments in sediments or velocity increments "delta(v)" in turbulent flows, the resulting measurements exhibit scaling, either spatial, temporal or both. (In the present context, such scaling refers to systematic changes in the statistical properties of the increment distributions, such as variance, with the lag size over which the increments are determined.) Depending on the class of probability density functions (PDFs) that describe the increment distributions, the resulting stochastic fractals will display different properties. Until recently, the stationary increment process was represented using mainly Gaussian, Gamma or Levy PDFs. However, measurements in both sediments and fluid turbulence indicate that these PDFs are not commonly observed. Based on recent data and previous studies referenced and discussed in Meerschaert et al. (2004) and Molz et al. (2005), the measured increment PDFs display an approximate double exponential (Laplace) shape at smaller lags, and this shape evolves towards Gaussian at larger lags. A model for this behavior based on the Generalized Laplace PDF family called fractional Laplace motion, in analogy with its Gaussian counterpart - fractional Brownian motion, has been suggested (Meerschaert et al., 2004) and the necessary mathematics elaborated (Kozubowski et al., 2005). The resulting stochastic fractal is not a typical self-affine monofractal, but it does exhibit monofractal-like scaling in certain lag size ranges. To date, it has been shown that the Generalized Laplace family fits ln(k) increment distributions and reproduces the original 1941 theory of Kolmogorov when applied to Eulerian turbulent velocity increments. However, to make a physically self-consistent application to turbulence, one must adopt a Lagrangian viewpoint, and the details of this approach are still being developed. The potential analogy between turbulent delta(v) and sediment delta[ln(k)] is intriguing, and perhaps offers insight into the underlying chaotic processes that constitute turbulence and may result also in the pervasive heterogeneity observed in most natural sediments. Properties of the new Laplace fractal are presented, and potential applications to both sediments and fluid turbulence are discussed.

Tangent map intermittency as an approximate analysis of intermittency in a high dimensional fully stochastic dynamical system: The Tangled Nature model.

PubMed

Diaz-Ruelas, Alvaro; Jeldtoft Jensen, Henrik; Piovani, Duccio; Robledo, Alberto

2016-12-01

It is well known that low-dimensional nonlinear deterministic maps close to a tangent bifurcation exhibit intermittency and this circumstance has been exploited, e.g., by Procaccia and Schuster [Phys. Rev. A 28, 1210 (1983)], to develop a general theory of 1/f spectra. This suggests it is interesting to study the extent to which the behavior of a high-dimensional stochastic system can be described by such tangent maps. The Tangled Nature (TaNa) Model of evolutionary ecology is an ideal candidate for such a study, a significant model as it is capable of reproducing a broad range of the phenomenology of macroevolution and ecosystems. The TaNa model exhibits strong intermittency reminiscent of punctuated equilibrium and, like the fossil record of mass extinction, the intermittency in the model is found to be non-stationary, a feature typical of many complex systems. We derive a mean-field version for the evolution of the likelihood function controlling the reproduction of species and find a local map close to tangency. This mean-field map, by our own local approximation, is able to describe qualitatively only one episode of the intermittent dynamics of the full TaNa model. To complement this result, we construct a complete nonlinear dynamical system model consisting of successive tangent bifurcations that generates time evolution patterns resembling those of the full TaNa model in macroscopic scales. The switch from one tangent bifurcation to the next in the sequences produced in this model is stochastic in nature, based on criteria obtained from the local mean-field approximation, and capable of imitating the changing set of types of species and total population in the TaNa model. The model combines full deterministic dynamics with instantaneous parameter random jumps at stochastically drawn times. In spite of the limitations of our approach, which entails a drastic collapse of degrees of freedom, the description of a high-dimensional model system in terms of a low-dimensional one appears to be illuminating.

A continuum dislocation dynamics framework for plasticity of polycrystalline materials

NASA Astrophysics Data System (ADS)

Askari, Hesam Aldin

The objective of this research is to investigate the mechanical response of polycrystals in different settings to identify the mechanisms that give rise to specific response observed in the deformation process. Particularly the large deformation of magnesium alloys and yield properties of copper in small scales are investigated. We develop a continuum dislocation dynamics framework based on dislocation mechanisms and interaction laws and implement this formulation in a viscoplastic self-consistent scheme to obtain the mechanical response in a polycrystalline system. The versatility of this method allows various applications in the study of problems involving large deformation, study of microstructure and its evolution, superplasticity, study of size effect in polycrystals and stochastic plasticity. The findings from the numerical solution are compared to the experimental results to validate the simulation results. We apply this framework to study the deformation mechanisms in magnesium alloys at moderate to fast strain rates and room temperature to 450 °C. Experiments for the same range of strain rates and temperatures were carried out to obtain the mechanical and material properties, and to compare with the numerical results. The numerical approach for magnesium is divided into four main steps; 1) room temperature unidirectional loading 2) high temperature deformation without grain boundary sliding 3) high temperature with grain boundary sliding mechanism 4) room temperature cyclic loading. We demonstrate the capability of our modeling approach in prediction of mechanical properties and texture evolution and discuss the improvement obtained by using the continuum dislocation dynamics method. The framework was also applied to nano-sized copper polycrystals to study the yield properties at small scales and address the observed yield scatter. By combining our developed method with a Monte Carlo simulation approach, the stochastic plasticity at small length scales was studied and the sources of the uncertainty in the polycrystalline structure are discussed. Our results suggest that the stochastic response is mainly because of a) stochastic plasticity due to dislocation substructure inside crystals and b) the microstructure of the polycrystalline material. The extent of the uncertainty is correlated to the "effective cell length" in the sampling procedure whether using simulations and experimental approach.

The Star-Forming Main Sequence as a Natural Consequence of the Central Limit Theorem

NASA Astrophysics Data System (ADS)

Kelson, Daniel David

2015-08-01

Star-formation rates (SFR) of disk galaxies correlate with stellar mass, with a small dispersion in SSFR at fixed mass, sigma~0.3 dex. With such scatter this star-formation main sequence (SFMS) has been interpreted as deterministic and fundamental. Here I demonstrate that such a correlation arises naturally from the central limit theorem. The derivation begins by approximating in situ stellar mass growth as a stochastic process, much like a random walk, where the expectation of SFR at any time is equal to the SFR at the previous time. The SFRs of real galaxies, however, do not experience wholly random stochastic changes over time, but change in a highly correlated fashion due to the long reach of gravity and the correlation of structure in the universe. We therefore generalize the results for star-formation as a stochastic process that has random correlations over random and potentially infinite timescales. For unbiased samples of (disk) galaxies we derive expectation values for SSFR and its scatter, such that =2/T, and Sig[SFR/M]=. Note that this relative scatter is independent of mass and time. This derived correlation between SFR and stellar mass, and its evolution, matches published data to z=10 with sufficient accuracy to constrain cosmological parameters from the data. This statistical approach to the diversity of star-formation histories reproduces several important observables, including: the scatter in SSFR at fixed mass; the forms of SFHs of nearby dwarf galaxies and the Milky Way. At least one additional process beyond a single one responsible for in situ stellar mass growth will be required to match the evolution of the stellar mass function, and we discuss ways to generalize the framework. The implied dispersion in SFHs, and the SFMS's insensitivity to timescales of stochasticity, thus substantially limits the ability to connect massive galaxies to their progenitors over long cosmic baselines. Such analytical work shows promise for statisically modeling distributions of galaxies over cosmic time, in a manner particularly indpendent of the thorny uncertainties in sub-grid astrophysics of modern cosmological simulations.

Slowly switching between environments facilitates reverse evolution in small populations.

PubMed

Tan, Longzhi; Gore, Jeff

2012-10-01

Natural populations must constantly adapt to ever-changing environmental conditions. A particularly interesting question is whether such adaptations can be reversed by returning the population to an ancestral environment. Such evolutionary reversals have been observed in both natural and laboratory populations. However, the factors that determine the reversibility of evolution are still under debate. The time scales of environmental change vary over a wide range, but little is known about how the rate of environmental change influences the reversibility of evolution. Here, we demonstrate computationally that slowly switching between environments increases the reversibility of evolution for small populations that are subject to only modest clonal interference. For small populations, slow switching reduces the mean number of mutations acquired in a new environment and also increases the probability of reverse evolution at each of these "genetic distances." As the population size increases, slow switching no longer reduces the genetic distance, thus decreasing the evolutionary reversibility. We confirm this effect using both a phenomenological model of clonal interference and also a Wright-Fisher stochastic simulation that incorporates genetic diversity. Our results suggest that the rate of environmental change is a key determinant of the reversibility of evolution, and provides testable hypotheses for experimental evolution. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Chromosome Evolution in Connection with Repetitive Sequences and Epigenetics in Plants.

PubMed

Li, Shu-Fen; Su, Ting; Cheng, Guang-Qian; Wang, Bing-Xiao; Li, Xu; Deng, Chuan-Liang; Gao, Wu-Jun

2017-10-24

Chromosome evolution is a fundamental aspect of evolutionary biology. The evolution of chromosome size, structure and shape, number, and the change in DNA composition suggest the high plasticity of nuclear genomes at the chromosomal level. Repetitive DNA sequences, which represent a conspicuous fraction of every eukaryotic genome, particularly in plants, are found to be tightly linked with plant chromosome evolution. Different classes of repetitive sequences have distinct distribution patterns on the chromosomes. Mounting evidence shows that repetitive sequences may play multiple generative roles in shaping the chromosome karyotypes in plants. Furthermore, recent development in our understanding of the repetitive sequences and plant chromosome evolution has elucidated the involvement of a spectrum of epigenetic modification. In this review, we focused on the recent evidence relating to the distribution pattern of repetitive sequences in plant chromosomes and highlighted their potential relevance to chromosome evolution in plants. We also discussed the possible connections between evolution and epigenetic alterations in chromosome structure and repatterning, such as heterochromatin formation, centromere function, and epigenetic-associated transposable element inactivation.

Brain shape convergence in the adaptive radiation of New World monkeys

PubMed Central

Aristide, Leandro; dos Reis, Sergio Furtado; Machado, Alessandra C.; Lima, Inaya; Lopes, Ricardo T.; Perez, S. Ivan

2016-01-01

Primates constitute one of the most diverse mammalian clades, and a notable feature of their diversification is the evolution of brain morphology. However, the evolutionary processes and ecological factors behind these changes are largely unknown. In this work, we investigate brain shape diversification of New World monkeys during their adaptive radiation in relation to different ecological dimensions. Our results reveal that brain diversification in this clade can be explained by invoking a model of adaptive peak shifts to unique and shared optima, defined by a multidimensional ecological niche hypothesis. Particularly, we show that the evolution of convergent brain phenotypes may be related to ecological factors associated with group size (e.g., social complexity). Together, our results highlight the complexity of brain evolution and the ecological significance of brain shape changes during the evolutionary diversification of a primate clade. PMID:26858427