FW-CADIS Method for Global and Semi-Global Variance Reduction of Monte Carlo Radiation Transport Calculations

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

Wagner, John C; Peplow, Douglas E.; Mosher, Scott W

2014-01-01

This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development ofmore » an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC sequence of SCALE and the ADVANTG/MCNP framework. Application of the method to representative, real-world problems, including calculation of dose rate and energy dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.« less

Deterministic modelling and stochastic simulation of biochemical pathways using MATLAB.

PubMed

Ullah, M; Schmidt, H; Cho, K H; Wolkenhauer, O

2006-03-01

The analysis of complex biochemical networks is conducted in two popular conceptual frameworks for modelling. The deterministic approach requires the solution of ordinary differential equations (ODEs, reaction rate equations) with concentrations as continuous state variables. The stochastic approach involves the simulation of differential-difference equations (chemical master equations, CMEs) with probabilities as variables. This is to generate counts of molecules for chemical species as realisations of random variables drawn from the probability distribution described by the CMEs. Although there are numerous tools available, many of them free, the modelling and simulation environment MATLAB is widely used in the physical and engineering sciences. We describe a collection of MATLAB functions to construct and solve ODEs for deterministic simulation and to implement realisations of CMEs for stochastic simulation using advanced MATLAB coding (Release 14). The program was successfully applied to pathway models from the literature for both cases. The results were compared to implementations using alternative tools for dynamic modelling and simulation of biochemical networks. The aim is to provide a concise set of MATLAB functions that encourage the experimentation with systems biology models. All the script files are available from www.sbi.uni-rostock.de/ publications_matlab-paper.html.

Exact and approximate stochastic simulation of intracellular calcium dynamics.

PubMed

Wieder, Nicolas; Fink, Rainer H A; Wegner, Frederic von

2011-01-01

In simulations of chemical systems, the main task is to find an exact or approximate solution of the chemical master equation (CME) that satisfies certain constraints with respect to computation time and accuracy. While Brownian motion simulations of single molecules are often too time consuming to represent the mesoscopic level, the classical Gillespie algorithm is a stochastically exact algorithm that provides satisfying results in the representation of calcium microdomains. Gillespie's algorithm can be approximated via the tau-leap method and the chemical Langevin equation (CLE). Both methods lead to a substantial acceleration in computation time and a relatively small decrease in accuracy. Elimination of the noise terms leads to the classical, deterministic reaction rate equations (RRE). For complex multiscale systems, hybrid simulations are increasingly proposed to combine the advantages of stochastic and deterministic algorithms. An often used exemplary cell type in this context are striated muscle cells (e.g., cardiac and skeletal muscle cells). The properties of these cells are well described and they express many common calcium-dependent signaling pathways. The purpose of the present paper is to provide an overview of the aforementioned simulation approaches and their mutual relationships in the spectrum ranging from stochastic to deterministic algorithms.

Chemical reactions induced by oscillating external fields in weak thermal environments

NASA Astrophysics Data System (ADS)

Craven, Galen T.; Bartsch, Thomas; Hernandez, Rigoberto

2015-02-01

Chemical reaction rates must increasingly be determined in systems that evolve under the control of external stimuli. In these systems, when a reactant population is induced to cross an energy barrier through forcing from a temporally varying external field, the transition state that the reaction must pass through during the transformation from reactant to product is no longer a fixed geometric structure, but is instead time-dependent. For a periodically forced model reaction, we develop a recrossing-free dividing surface that is attached to a transition state trajectory [T. Bartsch, R. Hernandez, and T. Uzer, Phys. Rev. Lett. 95, 058301 (2005)]. We have previously shown that for single-mode sinusoidal driving, the stability of the time-varying transition state directly determines the reaction rate [G. T. Craven, T. Bartsch, and R. Hernandez, J. Chem. Phys. 141, 041106 (2014)]. Here, we extend our previous work to the case of multi-mode driving waveforms. Excellent agreement is observed between the rates predicted by stability analysis and rates obtained through numerical calculation of the reactive flux. We also show that the optimal dividing surface and the resulting reaction rate for a reactive system driven by weak thermal noise can be approximated well using the transition state geometry of the underlying deterministic system. This agreement persists as long as the thermal driving strength is less than the order of that of the periodic driving. The power of this result is its simplicity. The surprising accuracy of the time-dependent noise-free geometry for obtaining transition state theory rates in chemical reactions driven by periodic fields reveals the dynamics without requiring the cost of brute-force calculations.

Copper benchmark experiment for the testing of JEFF-3.2 nuclear data for fusion applications

NASA Astrophysics Data System (ADS)

Angelone, M.; Flammini, D.; Loreti, S.; Moro, F.; Pillon, M.; Villar, R.; Klix, A.; Fischer, U.; Kodeli, I.; Perel, R. L.; Pohorecky, W.

2017-09-01

A neutronics benchmark experiment on a pure Copper block (dimensions 60 × 70 × 70 cm3) aimed at testing and validating the recent nuclear data libraries for fusion applications was performed in the frame of the European Fusion Program at the 14 MeV ENEA Frascati Neutron Generator (FNG). Reaction rates, neutron flux spectra and doses were measured using different experimental techniques (e.g. activation foils techniques, NE213 scintillator and thermoluminescent detectors). This paper first summarizes the analyses of the experiment carried-out using the MCNP5 Monte Carlo code and the European JEFF-3.2 library. Large discrepancies between calculation (C) and experiment (E) were found for the reaction rates both in the high and low neutron energy range. The analysis was complemented by sensitivity/uncertainty analyses (S/U) using the deterministic and Monte Carlo SUSD3D and MCSEN codes, respectively. The S/U analyses enabled to identify the cross sections and energy ranges which are mostly affecting the calculated responses. The largest discrepancy among the C/E values was observed for the thermal (capture) reactions indicating severe deficiencies in the 63,65Cu capture and elastic cross sections at lower rather than at high energy. Deterministic and MC codes produced similar results. The 14 MeV copper experiment and its analysis thus calls for a revision of the JEFF-3.2 copper cross section and covariance data evaluation. A new analysis of the experiment was performed with the MCNP5 code using the revised JEFF-3.3-T2 library released by NEA and a new, not yet distributed, revised JEFF-3.2 Cu evaluation produced by KIT. A noticeable improvement of the C/E results was obtained with both new libraries.

Simulated maximum likelihood method for estimating kinetic rates in gene expression.

PubMed

Tian, Tianhai; Xu, Songlin; Gao, Junbin; Burrage, Kevin

2007-01-01

Kinetic rate in gene expression is a key measurement of the stability of gene products and gives important information for the reconstruction of genetic regulatory networks. Recent developments in experimental technologies have made it possible to measure the numbers of transcripts and protein molecules in single cells. Although estimation methods based on deterministic models have been proposed aimed at evaluating kinetic rates from experimental observations, these methods cannot tackle noise in gene expression that may arise from discrete processes of gene expression, small numbers of mRNA transcript, fluctuations in the activity of transcriptional factors and variability in the experimental environment. In this paper, we develop effective methods for estimating kinetic rates in genetic regulatory networks. The simulated maximum likelihood method is used to evaluate parameters in stochastic models described by either stochastic differential equations or discrete biochemical reactions. Different types of non-parametric density functions are used to measure the transitional probability of experimental observations. For stochastic models described by biochemical reactions, we propose to use the simulated frequency distribution to evaluate the transitional density based on the discrete nature of stochastic simulations. The genetic optimization algorithm is used as an efficient tool to search for optimal reaction rates. Numerical results indicate that the proposed methods can give robust estimations of kinetic rates with good accuracy.

Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.

PubMed

Horne, Gregory P; Donoclift, Thomas A; Sims, Howard E; Orr, Robin M; Pimblott, Simon M

2016-11-17

A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.

Simulation of unsteady flows by the DSMC macroscopic chemistry method

NASA Astrophysics Data System (ADS)

Goldsworthy, Mark; Macrossan, Michael; Abdel-jawad, Madhat

2009-03-01

In the Direct Simulation Monte-Carlo (DSMC) method, a combination of statistical and deterministic procedures applied to a finite number of 'simulator' particles are used to model rarefied gas-kinetic processes. In the macroscopic chemistry method (MCM) for DSMC, chemical reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell, not just those selected for collisions, is used to determine a reaction rate coefficient for that cell. Unlike collision-based methods, MCM can be used with any viscosity or non-reacting collision models and any non-reacting energy exchange models. It can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies. MCM has been previously validated for steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation. Close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature, density and species mole fractions, as well as for the accumulated number of net reactions per cell.

Stochastic flux analysis of chemical reaction networks

PubMed Central

2013-01-01

Background Chemical reaction networks provide an abstraction scheme for a broad range of models in biology and ecology. The two common means for simulating these networks are the deterministic and the stochastic approaches. The traditional deterministic approach, based on differential equations, enjoys a rich set of analysis techniques, including a treatment of reaction fluxes. However, the discrete stochastic simulations, which provide advantages in some cases, lack a quantitative treatment of network fluxes. Results We describe a method for flux analysis of chemical reaction networks, where flux is given by the flow of species between reactions in stochastic simulations of the network. Extending discrete event simulation algorithms, our method constructs several data structures, and thereby reveals a variety of statistics about resource creation and consumption during the simulation. We use these structures to quantify the causal interdependence and relative importance of the reactions at arbitrary time intervals with respect to the network fluxes. This allows us to construct reduced networks that have the same flux-behavior, and compare these networks, also with respect to their time series. We demonstrate our approach on an extended example based on a published ODE model of the same network, that is, Rho GTP-binding proteins, and on other models from biology and ecology. Conclusions We provide a fully stochastic treatment of flux analysis. As in deterministic analysis, our method delivers the network behavior in terms of species transformations. Moreover, our stochastic analysis can be applied, not only at steady state, but at arbitrary time intervals, and used to identify the flow of specific species between specific reactions. Our cases study of Rho GTP-binding proteins reveals the role played by the cyclic reverse fluxes in tuning the behavior of this network. PMID:24314153

Stochastic flux analysis of chemical reaction networks.

PubMed

Kahramanoğulları, Ozan; Lynch, James F

2013-12-07

Chemical reaction networks provide an abstraction scheme for a broad range of models in biology and ecology. The two common means for simulating these networks are the deterministic and the stochastic approaches. The traditional deterministic approach, based on differential equations, enjoys a rich set of analysis techniques, including a treatment of reaction fluxes. However, the discrete stochastic simulations, which provide advantages in some cases, lack a quantitative treatment of network fluxes. We describe a method for flux analysis of chemical reaction networks, where flux is given by the flow of species between reactions in stochastic simulations of the network. Extending discrete event simulation algorithms, our method constructs several data structures, and thereby reveals a variety of statistics about resource creation and consumption during the simulation. We use these structures to quantify the causal interdependence and relative importance of the reactions at arbitrary time intervals with respect to the network fluxes. This allows us to construct reduced networks that have the same flux-behavior, and compare these networks, also with respect to their time series. We demonstrate our approach on an extended example based on a published ODE model of the same network, that is, Rho GTP-binding proteins, and on other models from biology and ecology. We provide a fully stochastic treatment of flux analysis. As in deterministic analysis, our method delivers the network behavior in terms of species transformations. Moreover, our stochastic analysis can be applied, not only at steady state, but at arbitrary time intervals, and used to identify the flow of specific species between specific reactions. Our cases study of Rho GTP-binding proteins reveals the role played by the cyclic reverse fluxes in tuning the behavior of this network.

Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.

PubMed

Schaff, James C; Gao, Fei; Li, Ye; Novak, Igor L; Slepchenko, Boris M

2016-12-01

Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell.

The Poisson distribution and beyond: methods for microfluidic droplet production and single cell encapsulation.

PubMed

Collins, David J; Neild, Adrian; deMello, Andrew; Liu, Ai-Qun; Ai, Ye

2015-09-07

There is a recognized and growing need for rapid and efficient cell assays, where the size of microfluidic devices lend themselves to the manipulation of cellular populations down to the single cell level. An exceptional way to analyze cells independently is to encapsulate them within aqueous droplets surrounded by an immiscible fluid, so that reagents and reaction products are contained within a controlled microenvironment. Most cell encapsulation work has focused on the development and use of passive methods, where droplets are produced continuously at high rates by pumping fluids from external pressure-driven reservoirs through defined microfluidic geometries. With limited exceptions, the number of cells encapsulated per droplet in these systems is dictated by Poisson statistics, reducing the proportion of droplets that contain the desired number of cells and thus the effective rate at which single cells can be encapsulated. Nevertheless, a number of recently developed actively-controlled droplet production methods present an alternative route to the production of droplets at similar rates and with the potential to improve the efficiency of single-cell encapsulation. In this critical review, we examine both passive and active methods for droplet production and explore how these can be used to deterministically and non-deterministically encapsulate cells.

Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems.

PubMed

Winkelmann, Stefanie; Schütte, Christof

2017-09-21

Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems

NASA Astrophysics Data System (ADS)

Winkelmann, Stefanie; Schütte, Christof

2017-09-01

Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

PubMed

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology

PubMed Central

Gao, Fei; Li, Ye; Novak, Igor L.; Slepchenko, Boris M.

2016-01-01

Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium ‘sparks’ as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell. PMID:27959915

Heart rate variability as determinism with jump stochastic parameters.

PubMed

Zheng, Jiongxuan; Skufca, Joseph D; Bollt, Erik M

2013-08-01

We use measured heart rate information (RR intervals) to develop a one-dimensional nonlinear map that describes short term deterministic behavior in the data. Our study suggests that there is a stochastic parameter with persistence which causes the heart rate and rhythm system to wander about a bifurcation point. We propose a modified circle map with a jump process noise term as a model which can qualitatively capture such this behavior of low dimensional transient determinism with occasional (stochastically defined) jumps from one deterministic system to another within a one parameter family of deterministic systems.

Transient Macroscopic Chemistry in the DSMC Method

NASA Astrophysics Data System (ADS)

Goldsworthy, M. J.; Macrossan, M. N.; Abdel-Jawad, M.

2008-12-01

In the Direct Simulation Monte Carlo method, a combination of statistical and deterministic procedures applied to a finite number of `simulator' particles are used to model rarefied gas-kinetic processes. Traditionally, chemical reactions are modelled using information from specific colliding particle pairs. In the Macroscopic Chemistry Method (MCM), the reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell is used to determine a reaction rate coefficient for that cell. MCM has previously been applied to steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation and during the unsteady development of 2-D flow through a cavity. For the shock tube simulation, close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature and species mole fractions. For the cavity flow, a high degree of thermal non-equilibrium is present and non-equilibrium reaction rate correction factors are employed in MCM. Very close agreement is demonstrated for ensemble averaged mole fraction contours predicted by the particle and macroscopic methods at three different flow-times. A comparison of the accumulated number of net reactions per cell shows that both methods compute identical numbers of reaction events. For the 2-D flow, MCM required similar CPU and memory resources to the particle chemistry method. The Macroscopic Chemistry Method is applicable to any general DSMC code using any viscosity or non-reacting collision models and any non-reacting energy exchange models. MCM can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies.

Spatiotemporal pattern formation in a prey-predator model under environmental driving forces

NASA Astrophysics Data System (ADS)

Sirohi, Anuj Kumar; Banerjee, Malay; Chakraborti, Anirban

2015-09-01

Many existing studies on pattern formation in the reaction-diffusion systems rely on deterministic models. However, environmental noise is often a major factor which leads to significant changes in the spatiotemporal dynamics. In this paper, we focus on the spatiotemporal patterns produced by the predator-prey model with ratio-dependent functional response and density dependent death rate of predator. We get the reaction-diffusion equations incorporating the self-diffusion terms, corresponding to random movement of the individuals within two dimensional habitats, into the growth equations for the prey and predator population. In order to have the noise added model, small amplitude heterogeneous perturbations to the linear intrinsic growth rates are introduced using uncorrelated Gaussian white noise terms. For the noise added system, we then observe spatial patterns for the parameter values lying outside the Turing instability region. With thorough numerical simulations we characterize the patterns corresponding to Turing and Turing-Hopf domain and study their dependence on different system parameters like noise-intensity, etc.

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.

Bootstrapping Least Squares Estimates in Biochemical Reaction Networks

PubMed Central

Linder, Daniel F.

2015-01-01

The paper proposes new computational methods of computing confidence bounds for the least squares estimates (LSEs) of rate constants in mass-action biochemical reaction network and stochastic epidemic models. Such LSEs are obtained by fitting the set of deterministic ordinary differential equations (ODEs), corresponding to the large volume limit of a reaction network, to network’s partially observed trajectory treated as a continuous-time, pure jump Markov process. In the large volume limit the LSEs are asymptotically Gaussian, but their limiting covariance structure is complicated since it is described by a set of nonlinear ODEs which are often ill-conditioned and numerically unstable. The current paper considers two bootstrap Monte-Carlo procedures, based on the diffusion and linear noise approximations for pure jump processes, which allow one to avoid solving the limiting covariance ODEs. The results are illustrated with both in-silico and real data examples from the LINE 1 gene retrotranscription model and compared with those obtained using other methods. PMID:25898769

Stability analysis of multi-group deterministic and stochastic epidemic models with vaccination rate

NASA Astrophysics Data System (ADS)

Wang, Zhi-Gang; Gao, Rui-Mei; Fan, Xiao-Ming; Han, Qi-Xing

2014-09-01

We discuss in this paper a deterministic multi-group MSIR epidemic model with a vaccination rate, the basic reproduction number ℛ0, a key parameter in epidemiology, is a threshold which determines the persistence or extinction of the disease. By using Lyapunov function techniques, we show if ℛ0 is greater than 1 and the deterministic model obeys some conditions, then the disease will prevail, the infective persists and the endemic state is asymptotically stable in a feasible region. If ℛ0 is less than or equal to 1, then the infective disappear so the disease dies out. In addition, stochastic noises around the endemic equilibrium will be added to the deterministic MSIR model in order that the deterministic model is extended to a system of stochastic ordinary differential equations. In the stochastic version, we carry out a detailed analysis on the asymptotic behavior of the stochastic model. In addition, regarding the value of ℛ0, when the stochastic system obeys some conditions and ℛ0 is greater than 1, we deduce the stochastic system is stochastically asymptotically stable. Finally, the deterministic and stochastic model dynamics are illustrated through computer simulations.

Noise-induced modulation of the relaxation kinetics around a non-equilibrium steady state of non-linear chemical reaction networks.

PubMed

Ramaswamy, Rajesh; Sbalzarini, Ivo F; González-Segredo, Nélido

2011-01-28

Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF) of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker-Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM) or fluorescence-correlation spectroscopy (FCS) to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates.

An effective rate equation approach to reaction kinetics in small volumes: theory and application to biochemical reactions in nonequilibrium steady-state conditions.

PubMed

Grima, R

2010-07-21

Chemical master equations provide a mathematical description of stochastic reaction kinetics in well-mixed conditions. They are a valid description over length scales that are larger than the reactive mean free path and thus describe kinetics in compartments of mesoscopic and macroscopic dimensions. The trajectories of the stochastic chemical processes described by the master equation can be ensemble-averaged to obtain the average number density of chemical species, i.e., the true concentration, at any spatial scale of interest. For macroscopic volumes, the true concentration is very well approximated by the solution of the corresponding deterministic and macroscopic rate equations, i.e., the macroscopic concentration. However, this equivalence breaks down for mesoscopic volumes. These deviations are particularly significant for open systems and cannot be calculated via the Fokker-Planck or linear-noise approximations of the master equation. We utilize the system-size expansion including terms of the order of Omega(-1/2) to derive a set of differential equations whose solution approximates the true concentration as given by the master equation. These equations are valid in any open or closed chemical reaction network and at both the mesoscopic and macroscopic scales. In the limit of large volumes, the effective mesoscopic rate equations become precisely equal to the conventional macroscopic rate equations. We compare the three formalisms of effective mesoscopic rate equations, conventional rate equations, and chemical master equations by applying them to several biochemical reaction systems (homodimeric and heterodimeric protein-protein interactions, series of sequential enzyme reactions, and positive feedback loops) in nonequilibrium steady-state conditions. In all cases, we find that the effective mesoscopic rate equations can predict very well the true concentration of a chemical species. This provides a useful method by which one can quickly determine the regions of parameter space in which there are maximum differences between the solutions of the master equation and the corresponding rate equations. We show that these differences depend sensitively on the Fano factors and on the inherent structure and topology of the chemical network. The theory of effective mesoscopic rate equations generalizes the conventional rate equations of physical chemistry to describe kinetics in systems of mesoscopic size such as biological cells.

Deterministic Computer-Controlled Polishing Process for High-Energy X-Ray Optics

NASA Technical Reports Server (NTRS)

Khan, Gufran S.; Gubarev, Mikhail; Speegle, Chet; Ramsey, Brian

2010-01-01

A deterministic computer-controlled polishing process for large X-ray mirror mandrels is presented. Using tool s influence function and material removal rate extracted from polishing experiments, design considerations of polishing laps and optimized operating parameters are discussed

Deterministic bead-in-droplet ejection utilizing an integrated plug-in bead dispenser for single bead-based applications

NASA Astrophysics Data System (ADS)

Kim, Hojin; Choi, In Ho; Lee, Sanghyun; Won, Dong-Joon; Oh, Yong Suk; Kwon, Donghoon; Sung, Hyung Jin; Jeon, Sangmin; Kim, Joonwon

2017-04-01

This paper presents a deterministic bead-in-droplet ejection (BIDE) technique that regulates the precise distribution of microbeads in an ejected droplet. The deterministic BIDE was realized through the effective integration of a microfluidic single-particle handling technique with a liquid dispensing system. The integrated bead dispenser facilitates the transfer of the desired number of beads into a dispensing volume and the on-demand ejection of bead-encapsulated droplets. Single bead-encapsulated droplets were ejected every 3 s without any failure. Multiple-bead dispensing with deterministic control of the number of beads was demonstrated to emphasize the originality and quality of the proposed dispensing technique. The dispenser was mounted using a plug-socket type connection, and the dispensing process was completely automated using a programmed sequence without any microscopic observation. To demonstrate a potential application of the technique, bead-based streptavidin-biotin binding assay in an evaporating droplet was conducted using ultralow numbers of beads. The results evidenced the number of beads in the droplet crucially influences the reliability of the assay. Therefore, the proposed deterministic bead-in-droplet technology can be utilized to deliver desired beads onto a reaction site, particularly to reliably and efficiently enrich and detect target biomolecules.

Deterministic bead-in-droplet ejection utilizing an integrated plug-in bead dispenser for single bead-based applications.

PubMed

Kim, Hojin; Choi, In Ho; Lee, Sanghyun; Won, Dong-Joon; Oh, Yong Suk; Kwon, Donghoon; Sung, Hyung Jin; Jeon, Sangmin; Kim, Joonwon

2017-04-10

This paper presents a deterministic bead-in-droplet ejection (BIDE) technique that regulates the precise distribution of microbeads in an ejected droplet. The deterministic BIDE was realized through the effective integration of a microfluidic single-particle handling technique with a liquid dispensing system. The integrated bead dispenser facilitates the transfer of the desired number of beads into a dispensing volume and the on-demand ejection of bead-encapsulated droplets. Single bead-encapsulated droplets were ejected every 3 s without any failure. Multiple-bead dispensing with deterministic control of the number of beads was demonstrated to emphasize the originality and quality of the proposed dispensing technique. The dispenser was mounted using a plug-socket type connection, and the dispensing process was completely automated using a programmed sequence without any microscopic observation. To demonstrate a potential application of the technique, bead-based streptavidin-biotin binding assay in an evaporating droplet was conducted using ultralow numbers of beads. The results evidenced the number of beads in the droplet crucially influences the reliability of the assay. Therefore, the proposed deterministic bead-in-droplet technology can be utilized to deliver desired beads onto a reaction site, particularly to reliably and efficiently enrich and detect target biomolecules.

Deterministic bead-in-droplet ejection utilizing an integrated plug-in bead dispenser for single bead–based applications

PubMed Central

Kim, Hojin; Choi, In Ho; Lee, Sanghyun; Won, Dong-Joon; Oh, Yong Suk; Kwon, Donghoon; Sung, Hyung Jin; Jeon, Sangmin; Kim, Joonwon

2017-01-01

This paper presents a deterministic bead-in-droplet ejection (BIDE) technique that regulates the precise distribution of microbeads in an ejected droplet. The deterministic BIDE was realized through the effective integration of a microfluidic single-particle handling technique with a liquid dispensing system. The integrated bead dispenser facilitates the transfer of the desired number of beads into a dispensing volume and the on-demand ejection of bead-encapsulated droplets. Single bead–encapsulated droplets were ejected every 3 s without any failure. Multiple-bead dispensing with deterministic control of the number of beads was demonstrated to emphasize the originality and quality of the proposed dispensing technique. The dispenser was mounted using a plug-socket type connection, and the dispensing process was completely automated using a programmed sequence without any microscopic observation. To demonstrate a potential application of the technique, bead-based streptavidin–biotin binding assay in an evaporating droplet was conducted using ultralow numbers of beads. The results evidenced the number of beads in the droplet crucially influences the reliability of the assay. Therefore, the proposed deterministic bead-in-droplet technology can be utilized to deliver desired beads onto a reaction site, particularly to reliably and efficiently enrich and detect target biomolecules. PMID:28393911

Enzyme efficiency: An open reaction system perspective

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

Banerjee, Kinshuk, E-mail: kb36@rice.edu; Bhattacharyya, Kamal, E-mail: pchemkb@gmail.com

2015-12-21

A measure of enzyme efficiency is proposed for an open reaction network that, in suitable form, applies to closed systems as well. The idea originates from the description of classical enzyme kinetics in terms of cycles. We derive analytical expressions for the efficiency measure by treating the network not only deterministically but also stochastically. The latter accounts for any significant amount of noise that can be present in biological systems and hence reveals its impact on efficiency. Numerical verification of the results is also performed. It is found that the deterministic equation overestimates the efficiency, the more so for verymore » small system sizes. Roles of various kinetics parameters and system sizes on the efficiency are thoroughly explored and compared with the standard definition k{sub 2}/K{sub M}. Study of substrate fluctuation also indicates an interesting efficiency-accuracy balance.« less

Necessary conditions for the emergence of homochirality via autocatalytic self-replication

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

Stich, Michael; Ribó, Josep M.; Blackmond, Donna G., E-mail: blackmond@scripps.edu

We analyze a recent proposal for spontaneous mirror symmetry breaking based on the coupling of first-order enantioselective autocatalysis and direct production of the enantiomers that invokes a critical role for intrinsic reaction noise. For isolated systems, the racemic state is the unique stable outcome for both stochastic and deterministic dynamics when the system is in compliance with the constraints dictated by the thermodynamics of chemical reaction processes. In open systems, the racemic outcome also results for both stochastic and deterministic dynamics when driving the autocatalysis unidirectionally by external reagents. Nonracemic states can result in the latter only if the reversemore » reactions are strictly zero: these are kinetically controlled outcomes for small populations and volumes, and can be simulated by stochastic dynamics. However, the stability of the thermodynamic limit proves that the racemic outcome is the unique stable state for strictly irreversible externally driven autocatalysis. These findings contradict the suggestion that the inhibition requirement of the Frank autocatalytic model for the emergence of homochirality may be relaxed in a noise-induced mechanism.« less

Dynamic partitioning for hybrid simulation of the bistable HIV-1 transactivation network.

PubMed

Griffith, Mark; Courtney, Tod; Peccoud, Jean; Sanders, William H

2006-11-15

The stochastic kinetics of a well-mixed chemical system, governed by the chemical Master equation, can be simulated using the exact methods of Gillespie. However, these methods do not scale well as systems become more complex and larger models are built to include reactions with widely varying rates, since the computational burden of simulation increases with the number of reaction events. Continuous models may provide an approximate solution and are computationally less costly, but they fail to capture the stochastic behavior of small populations of macromolecules. In this article we present a hybrid simulation algorithm that dynamically partitions the system into subsets of continuous and discrete reactions, approximates the continuous reactions deterministically as a system of ordinary differential equations (ODE) and uses a Monte Carlo method for generating discrete reaction events according to a time-dependent propensity. Our approach to partitioning is improved such that we dynamically partition the system of reactions, based on a threshold relative to the distribution of propensities in the discrete subset. We have implemented the hybrid algorithm in an extensible framework, utilizing two rigorous ODE solvers to approximate the continuous reactions, and use an example model to illustrate the accuracy and potential speedup of the algorithm when compared with exact stochastic simulation. Software and benchmark models used for this publication can be made available upon request from the authors.

Automatic mesh adaptivity for hybrid Monte Carlo/deterministic neutronics modeling of difficult shielding problems

DOE PAGES

Ibrahim, Ahmad M.; Wilson, Paul P.H.; Sawan, Mohamed E.; ...

2015-06-30

The CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been limited by the large number of processors and memory requirements for their preliminary deterministic calculations and final Monte Carlo calculation. Three mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as muchmore » geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility. Using these algorithms resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled this difficult calculation to be accurately solved using an FW-CADIS simulation on a regular computer cluster, eliminating the need for a world-class super computer.« less

Use of reduction rate as a quantitative knob for controlling the twin structure and shape of palladium nanocrystals.

PubMed

Wang, Yi; Peng, Hsin-Chieh; Liu, Jingyue; Huang, Cheng Zhi; Xia, Younan

2015-02-11

Kinetic control is a powerful means for maneuvering the twin structure and shape of metal nanocrystals and thus optimizing their performance in a variety of applications. However, there is only a vague understanding of the explicit roles played by reaction kinetics due to the lack of quantitative information about the kinetic parameters. With Pd as an example, here we demonstrate that kinetic parameters, including rate constant and activation energy, can be derived from spectroscopic measurements and then used to calculate the initial reduction rate and further have this parameter quantitatively correlated with the twin structure of a seed and nanocrystal. On a quantitative basis, we were able to determine the ranges of initial reduction rates required for the formation of nanocrystals with a specific twin structure, including single-crystal, multiply twinned, and stacking fault-lined. This work represents a major step forward toward the deterministic syntheses of colloidal noble-metal nanocrystals with specific twin structures and shapes.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

PubMed

Kalantzis, Georgios

2009-06-01

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

Langevin approach to a chemical wave front: Selection of the propagation velocity in the presence of internal noise

NASA Astrophysics Data System (ADS)

Lemarchand, A.; Lesne, A.; Mareschal, M.

1995-05-01

The reaction-diffusion equation associated with the Fisher chemical model A+B-->2A admits wave-front solutions by replacing an unstable stationary state with a stable one. The deterministic analysis concludes that their propagation velocity is not prescribed by the dynamics. For a large class of initial conditions the velocity which is spontaneously selected is equal to the minimum allowed velocity vmin, as predicted by the marginal stability criterion. In order to test the relevance of this deterministic description we investigate the macroscopic consequences, on the velocity and the width of the front, of the intrinsic stochasticity due to the underlying microscopic dynamics. We solve numerically the Langevin equations, deduced analytically from the master equation within a system size expansion procedure. We show that the mean profile associated with the stochastic solution propagates faster than the deterministic solution at a velocity up to 25% greater than vmin.

Hybrid stochastic and deterministic simulations of calcium blips.

PubMed

Rüdiger, S; Shuai, J W; Huisinga, W; Nagaiah, C; Warnecke, G; Parker, I; Falcke, M

2007-09-15

Intracellular calcium release is a prime example for the role of stochastic effects in cellular systems. Recent models consist of deterministic reaction-diffusion equations coupled to stochastic transitions of calcium channels. The resulting dynamics is of multiple time and spatial scales, which complicates far-reaching computer simulations. In this article, we introduce a novel hybrid scheme that is especially tailored to accurately trace events with essential stochastic variations, while deterministic concentration variables are efficiently and accurately traced at the same time. We use finite elements to efficiently resolve the extreme spatial gradients of concentration variables close to a channel. We describe the algorithmic approach and we demonstrate its efficiency compared to conventional methods. Our single-channel model matches experimental data and results in intriguing dynamics if calcium is used as charge carrier. Random openings of the channel accumulate in bursts of calcium blips that may be central for the understanding of cellular calcium dynamics.

Magnified gradient function with deterministic weight modification in adaptive learning.

PubMed

Ng, Sin-Chun; Cheung, Chi-Chung; Leung, Shu-Hung

2004-11-01

This paper presents two novel approaches, backpropagation (BP) with magnified gradient function (MGFPROP) and deterministic weight modification (DWM), to speed up the convergence rate and improve the global convergence capability of the standard BP learning algorithm. The purpose of MGFPROP is to increase the convergence rate by magnifying the gradient function of the activation function, while the main objective of DWM is to reduce the system error by changing the weights of a multilayered feedforward neural network in a deterministic way. Simulation results show that the performance of the above two approaches is better than BP and other modified BP algorithms for a number of learning problems. Moreover, the integration of the above two approaches forming a new algorithm called MDPROP, can further improve the performance of MGFPROP and DWM. From our simulation results, the MDPROP algorithm always outperforms BP and other modified BP algorithms in terms of convergence rate and global convergence capability.

Effects of magnetometer calibration and maneuvers on accuracies of magnetometer-only attitude-and-rate determination

NASA Technical Reports Server (NTRS)

Challa, M.; Natanson, G.

1998-01-01

Two different algorithms - a deterministic magnetic-field-only algorithm and a Kalman filter for gyroless spacecraft - are used to estimate the attitude and rates of the Rossi X-Ray Timing Explorer (RXTE) using only measurements from a three-axis magnetometer. The performance of these algorithms is examined using in-flight data from various scenarios. In particular, significant enhancements in accuracies are observed when' the telemetered magnetometer data are accurately calibrated using a recently developed calibration algorithm. Interesting features observed in these studies of the inertial-pointing RXTE include a remarkable sensitivity of the filter to the numerical values of the noise parameters and relatively long convergence time spans. By analogy, the accuracy of the deterministic scheme is noticeably lower as a result of reduced rates of change of the body-fixed geomagnetic field. Preliminary results show the filter-per-axis attitude accuracies ranging between 0.1 and 0.5 deg and rate accuracies between 0.001 deg/sec and 0.005 deg./sec, whereas the deterministic method needs a more sophisticated techniques for smoothing time derivatives of the measured geomagnetic field to clearly distinguish both attitude and rate solutions from the numerical noise. Also included is a new theoretical development in the deterministic algorithm: the transformation of a transcendental equation in the original theory into an 8th-order polynomial equation. It is shown that this 8th-order polynomial reduces to quadratic equations in the two limiting cases-infinitely high wheel momentum, and constant rates-discussed in previous publications.

Optimizing Chemical Reactions with Deep Reinforcement Learning.

PubMed

Zhou, Zhenpeng; Li, Xiaocheng; Zare, Richard N

2017-12-27

Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient exploration strategy by drawing the reaction conditions from certain probability distributions, which resulted in an improvement on regret from 0.062 to 0.039 compared with a deterministic policy. Combining the efficient exploration policy with accelerated microdroplet reactions, optimal reaction conditions were determined in 30 min for the four reactions considered, and a better understanding of the factors that control microdroplet reactions was reached. Moreover, our model showed a better performance after training on reactions with similar or even dissimilar underlying mechanisms, which demonstrates its learning ability.

Stochastic dynamics and non-equilibrium thermodynamics of a bistable chemical system: the Schlögl model revisited.

PubMed

Vellela, Melissa; Qian, Hong

2009-10-06

Schlögl's model is the canonical example of a chemical reaction system that exhibits bistability. Because the biological examples of bistability and switching behaviour are increasingly numerous, this paper presents an integrated deterministic, stochastic and thermodynamic analysis of the model. After a brief review of the deterministic and stochastic modelling frameworks, the concepts of chemical and mathematical detailed balances are discussed and non-equilibrium conditions are shown to be necessary for bistability. Thermodynamic quantities such as the flux, chemical potential and entropy production rate are defined and compared across the two models. In the bistable region, the stochastic model exhibits an exchange of the global stability between the two stable states under changes in the pump parameters and volume size. The stochastic entropy production rate shows a sharp transition that mirrors this exchange. A new hybrid model that includes continuous diffusion and discrete jumps is suggested to deal with the multiscale dynamics of the bistable system. Accurate approximations of the exponentially small eigenvalue associated with the time scale of this switching and the full time-dependent solution are calculated using Matlab. A breakdown of previously known asymptotic approximations on small volume scales is observed through comparison with these and Monte Carlo results. Finally, in the appendix section is an illustration of how the diffusion approximation of the chemical master equation can fail to represent correctly the mesoscopically interesting steady-state behaviour of the system.

Investigation of HZETRN 2010 as a Tool for Single Event Effect Qualification of Avionics Systems - Part II

NASA Technical Reports Server (NTRS)

Rojdev, Kristina; Koontz, Steve; Reddell, Brandon; Atwell, William; Boeder, Paul

2015-01-01

An accurate prediction of spacecraft avionics single event effect (SEE) radiation susceptibility is key to ensuring a safe and reliable vehicle. This is particularly important for long-duration deep space missions for human exploration where there is little or no chance for a quick emergency return to Earth. Monte Carlo nuclear reaction and transport codes such as FLUKA can be used to generate very accurate models of the expected in-flight radiation environment for SEE analyses. A major downside to using a Monte Carlo-based code is that the run times can be very long (on the order of days). A more popular choice for SEE calculations is the CREME96 deterministic code, which offers significantly shorter run times (on the order of seconds). However, CREME96, though fast and easy to use, has not been updated in several years and underestimates secondary particle shower effects in spacecraft structural shielding mass. Another modeling option to consider is the deterministic code HZETRN 20104, which includes updates to address secondary particle shower effects more accurately. This paper builds on previous work by Rojdev, et al. to compare the use of HZETRN 2010 against CREME96 as a tool to verify spacecraft avionics system reliability in a space flight SEE environment. This paper will discuss modifications made to HZETRN 2010 to improve its performance for calculating SEE rates and compare results with both in-flight SEE rates and other calculation methods.

Motor selection dynamics in FEF explain the reaction time variance of saccades to single targets

PubMed Central

Hauser, Christopher K; Zhu, Dantong; Stanford, Terrence R

2018-01-01

In studies of voluntary movement, a most elemental quantity is the reaction time (RT) between the onset of a visual stimulus and a saccade toward it. However, this RT demonstrates extremely high variability which, in spite of extensive research, remains unexplained. It is well established that, when a visual target appears, oculomotor activity gradually builds up until a critical level is reached, at which point a saccade is triggered. Here, based on computational work and single-neuron recordings from monkey frontal eye field (FEF), we show that this rise-to-threshold process starts from a dynamic initial state that already contains other incipient, internally driven motor plans, which compete with the target-driven activity to varying degrees. The ensuing conflict resolution process, which manifests in subtle covariations between baseline activity, build-up rate, and threshold, consists of fundamentally deterministic interactions, and explains the observed RT distributions while invoking only a small amount of intrinsic randomness. PMID:29652247

Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

PubMed

Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

2017-10-03

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Non-Deterministic Dynamic Instability of Composite Shells

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2004-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics, and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties, in that order.

Relation Between the Cell Volume and the Cell Cycle Dynamics in Mammalian cell

NASA Astrophysics Data System (ADS)

Magno, A. C. G.; Oliveira, I. L.; Hauck, J. V. S.

2016-08-01

The main goal of this work is to add and analyze an equation that represents the volume in a dynamical model of the mammalian cell cycle proposed by Gérard and Goldbeter (2011) [1]. The cell division occurs when the cyclinB/Cdkl complex is totally degraded (Tyson and Novak, 2011)[2] and it reaches a minimum value. At this point, the cell is divided into two newborn daughter cells and each one will contain the half of the cytoplasmic content of the mother cell. The equations of our base model are only valid if the cell volume, where the reactions occur, is constant. Whether the cell volume is not constant, that is, the rate of change of its volume with respect to time is explicitly taken into account in the mathematical model, then the equations of the original model are no longer valid. Therefore, every equations were modified from the mass conservation principle for considering a volume that changes with time. Through this approach, the cell volume affects all model variables. Two different dynamic simulation methods were accomplished: deterministic and stochastic. In the stochastic simulation, the volume affects every model's parameters which have molar unit, whereas in the deterministic one, it is incorporated into the differential equations. In deterministic simulation, the biochemical species may be in concentration units, while in stochastic simulation such species must be converted to number of molecules which are directly proportional to the cell volume. In an effort to understand the influence of the new equation a stability analysis was performed. This elucidates how the growth factor impacts the stability of the model's limit cycles. In conclusion, a more precise model, in comparison to the base model, was created for the cell cycle as it now takes into consideration the cell volume variation

Optimizing Chemical Reactions with Deep Reinforcement Learning

PubMed Central

2017-01-01

Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient exploration strategy by drawing the reaction conditions from certain probability distributions, which resulted in an improvement on regret from 0.062 to 0.039 compared with a deterministic policy. Combining the efficient exploration policy with accelerated microdroplet reactions, optimal reaction conditions were determined in 30 min for the four reactions considered, and a better understanding of the factors that control microdroplet reactions was reached. Moreover, our model showed a better performance after training on reactions with similar or even dissimilar underlying mechanisms, which demonstrates its learning ability. PMID:29296675

Extending atomistic scale chemistry to mesoscale model of condensed-phase deflagration

NASA Astrophysics Data System (ADS)

Joshi, Kaushik; Chaudhuri, Santanu

2017-01-01

Predictive simulations connecting chemistry that follow the shock or thermal initiation of energetic materials to subsequent deflagration or detonation events is currently outside the realm of possibilities. Molecular dynamics and first-principles based dynamics have made progress in understanding reactions in picosecond to nanosecond time scale. Results from thermal ignition of different phases of RDX show a complex reaction network and emergence of a deterministic behavior for critical temperature before ignition and hot spot growth rates. The kinetics observed is dependent on the hot spot temperature, system size and thermal conductivity. For cases where ignition is observed, the incubation period is dominated by intermolecular and intramolecular hydrogen transfer reactions. The gradual temperature and pressure increase in the incubation period is accompanied by accumulation of heavier polyradicals. The challenge of connecting such chemistry in mesoscale simulations remain in reducing the complexity of chemistry. The hot spot growth kinetics in RDX grains and interfaces is an important challenge for reactive simulations aiming to fill in the gaps in our knowledge in the nanoseconds to microseconds time scale. The results discussed indicate that the mesoscale chemistry may include large polyradical molecules in dense reactive mix reaching an instability point at certain temperatures and pressures.

Amplification of intrinsic fluctuations by the Lorenz equations

NASA Astrophysics Data System (ADS)

Fox, Ronald F.; Elston, T. C.

1993-07-01

Macroscopic systems (e.g., hydrodynamics, chemical reactions, electrical circuits, etc.) manifest intrinsic fluctuations of molecular and thermal origin. When the macroscopic dynamics is deterministically chaotic, the intrinsic fluctuations may become amplified by several orders of magnitude. Numerical studies of this phenomenon are presented in detail for the Lorenz model. Amplification to macroscopic scales is exhibited, and quantitative methods (binning and a difference-norm) are presented for measuring macroscopically subliminal amplification effects. In order to test the quality of the numerical results, noise induced chaos is studied around a deterministically nonchaotic state, where the scaling law relating the Lyapunov exponent to noise strength obtained for maps is confirmed for the Lorenz model, a system of ordinary differential equations.

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

Shielding Calculations on Waste Packages - The Limits and Possibilities of different Calculation Methods by the example of homogeneous and inhomogeneous Waste Packages

NASA Astrophysics Data System (ADS)

Adams, Mike; Smalian, Silva

2017-09-01

For nuclear waste packages the expected dose rates and nuclide inventory are beforehand calculated. Depending on the package of the nuclear waste deterministic programs like MicroShield® provide a range of results for each type of packaging. Stochastic programs like "Monte-Carlo N-Particle Transport Code System" (MCNP®) on the other hand provide reliable results for complex geometries. However this type of program requires a fully trained operator and calculations are time consuming. The problem here is to choose an appropriate program for a specific geometry. Therefore we compared the results of deterministic programs like MicroShield® and stochastic programs like MCNP®. These comparisons enable us to make a statement about the applicability of the various programs for chosen types of containers. As a conclusion we found that for thin-walled geometries deterministic programs like MicroShield® are well suited to calculate the dose rate. For cylindrical containers with inner shielding however, deterministic programs hit their limits. Furthermore we investigate the effect of an inhomogeneous material and activity distribution on the results. The calculations are still ongoing. Results will be presented in the final abstract.

A Scalable Computational Framework for Establishing Long-Term Behavior of Stochastic Reaction Networks

PubMed Central

Khammash, Mustafa

2014-01-01

Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed. PMID:24968191

Reflector and Protections in a Sodium-cooled Fast Reactor: Modelling and Optimization

NASA Astrophysics Data System (ADS)

Blanchet, David; Fontaine, Bruno

2017-09-01

The ASTRID project (Advanced Sodium Technological Reactor for Industrial Demonstration) is a Generation IV nuclear reactor concept under development in France [1]. In this frame, studies are underway to optimize radial reflectors and protections. Considering radial protections made in natural boron carbide, this study is conducted to assess the neutronic performances of the MgO as the reference choice for reflector material, in comparison with other possible materials including a more conventional stainless steel. The analysis is based upon a simplified 1-D and 2-D deterministic modelling of the reactor, providing simplified interfaces between core, reflector and protections. Such models allow examining detailed reaction rate distributions; they also provide physical insights into local spectral effects occurring at the Core-Reflector and at the Reflector-Protection interfaces.

Stochastic von Bertalanffy models, with applications to fish recruitment.

PubMed

Lv, Qiming; Pitchford, Jonathan W

2007-02-21

We consider three individual-based models describing growth in stochastic environments. Stochastic differential equations (SDEs) with identical von Bertalanffy deterministic parts are formulated, with a stochastic term which decreases, remains constant, or increases with organism size, respectively. Probability density functions for hitting times are evaluated in the context of fish growth and mortality. Solving the hitting time problem analytically or numerically shows that stochasticity can have a large positive impact on fish recruitment probability. It is also demonstrated that the observed mean growth rate of surviving individuals always exceeds the mean population growth rate, which itself exceeds the growth rate of the equivalent deterministic model. The consequences of these results in more general biological situations are discussed.

The Simplest Complete Model of Choice Response Time: Linear Ballistic Accumulation

ERIC Educational Resources Information Center

Brown, Scott D.; Heathcote, Andrew

2008-01-01

We propose a linear ballistic accumulator (LBA) model of decision making and reaction time. The LBA is simpler than other models of choice response time, with independent accumulators that race towards a common response threshold. Activity in the accumulators increases in a linear and deterministic manner. The simplicity of the model allows…

Controlling transient chaos in deterministic flows with applications to electrical power systems and ecology

NASA Astrophysics Data System (ADS)

Dhamala, Mukeshwar; Lai, Ying-Cheng

1999-02-01

Transient chaos is a common phenomenon in nonlinear dynamics of many physical, biological, and engineering systems. In applications it is often desirable to maintain sustained chaos even in parameter regimes of transient chaos. We address how to sustain transient chaos in deterministic flows. We utilize a simple and practical method, based on extracting the fundamental dynamics from time series, to maintain chaos. The method can result in control of trajectories from almost all initial conditions in the original basin of the chaotic attractor from which transient chaos is created. We apply our method to three problems: (1) voltage collapse in electrical power systems, (2) species preservation in ecology, and (3) elimination of undesirable bursting behavior in a chemical reaction system.

A high repetition deterministic single ion source

NASA Astrophysics Data System (ADS)

Sahin, C.; Geppert, P.; Müllers, A.; Ott, H.

2017-12-01

We report on a deterministic single ion source with high repetition rate and high fidelity. The source employs a magneto-optical trap, where ultracold rubidium atoms are photoionized. The electrons herald the creation of a corresponding ion, whose timing information is used to manipulate its trajectory in flight. We demonstrate an ion rate of up to 4× {10}4 {{{s}}}-1 and achieve a fidelity for single ion operation of 98%. The technique can be used for all atomic species, which can be laser-cooled, and opens up new applications in ion microscopy, ion implantation and surface spectroscopy.

The origin of life is a spatially localized stochastic transition

PubMed Central

2012-01-01

Background Life depends on biopolymer sequences as catalysts and as genetic material. A key step in the Origin of Life is the emergence of an autocatalytic system of biopolymers. Here we study computational models that address the way a living autocatalytic system could have emerged from a non-living chemical system, as envisaged in the RNA World hypothesis. Results We consider (i) a chemical reaction system describing RNA polymerization, and (ii) a simple model of catalytic replicators that we call the Two’s Company model. Both systems have two stable states: a non-living state, characterized by a slow spontaneous rate of RNA synthesis, and a living state, characterized by rapid autocatalytic RNA synthesis. The origin of life is a transition between these two stable states. The transition is driven by stochastic concentration fluctuations involving relatively small numbers of molecules in a localized region of space. These models are simulated on a two-dimensional lattice in which reactions occur locally on single sites and diffusion occurs by hopping of molecules to neighbouring sites. Conclusions If diffusion is very rapid, the system is well-mixed. The transition to life becomes increasingly difficult as the lattice size is increased because the concentration fluctuations that drive the transition become relatively smaller when larger numbers of molecules are involved. In contrast, when diffusion occurs at a finite rate, concentration fluctuations are local. The transition to life occurs in one local region and then spreads across the rest of the surface. The transition becomes easier with larger lattice sizes because there are more independent regions in which it could occur. The key observations that apply to our models and to the real world are that the origin of life is a rare stochastic event that is localized in one region of space due to the limited rate of diffusion of the molecules involved and that the subsequent spread across the surface is deterministic. It is likely that the time required for the deterministic spread is much shorter than the waiting time for the origin, in which case life evolves only once on a planet, and then rapidly occupies the whole surface. Reviewers Reviewed by Omer Markovitch (nominated by Doron Lancet), Claus Wilke, and Nobuto Takeuchi (nominated by Eugene Koonin). PMID:23176307

Classification of radiation effects for dose limitation purposes: history, current situation and future prospects

PubMed Central

Hamada, Nobuyuki; Fujimichi, Yuki

2014-01-01

Radiation exposure causes cancer and non-cancer health effects, each of which differs greatly in the shape of the dose–response curve, latency, persistency, recurrence, curability, fatality and impact on quality of life. In recent decades, for dose limitation purposes, the International Commission on Radiological Protection has divided such diverse effects into tissue reactions (formerly termed non-stochastic and deterministic effects) and stochastic effects. On the one hand, effective dose limits aim to reduce the risks of stochastic effects (cancer/heritable effects) and are based on the detriment-adjusted nominal risk coefficients, assuming a linear-non-threshold dose response and a dose and dose rate effectiveness factor of 2. On the other hand, equivalent dose limits aim to avoid tissue reactions (vision-impairing cataracts and cosmetically unacceptable non-cancer skin changes) and are based on a threshold dose. However, the boundary between these two categories is becoming vague. Thus, we review the changes in radiation effect classification, dose limitation concepts, and the definition of detriment and threshold. Then, the current situation is overviewed focusing on (i) stochastic effects with a threshold, (ii) tissue reactions without a threshold, (iii) target organs/tissues for circulatory disease, (iv) dose levels for limitation of cancer risks vs prevention of non-life-threatening tissue reactions vs prevention of life-threatening tissue reactions, (v) mortality or incidence of thyroid cancer, and (vi) the detriment for tissue reactions. For future discussion, one approach is suggested that classifies radiation effects according to whether effects are life threatening, and radiobiological research needs are also briefly discussed. PMID:24794798

Stochastic models for regulatory networks of the genetic toggle switch.

PubMed

Tian, Tianhai; Burrage, Kevin

2006-05-30

Bistability arises within a wide range of biological systems from the lambda phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Stochastic models for regulatory networks of the genetic toggle switch

PubMed Central

Tian, Tianhai; Burrage, Kevin

2006-01-01

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks. PMID:16714385

Jitter and phase noise of ADPLL due to PSN with deterministic frequency

NASA Astrophysics Data System (ADS)

Deng, Xiaoying; Yang, Jun; Wu, Jianhui

2011-09-01

In this article, jitter and phase noise of all-digital phase-locked loop due to power supply noise (PSN) with deterministic frequency are analysed. It leads to the conclusion that jitter and phase noise heavily depend on the noise frequency. Compared with jitter, phase noise is much less affected by the deterministic PSN. Our method is utilised to study a CMOS ADPLL designed and simulated in SMIC 0.13 µm standard CMOS process. A comparison between the results obtained by our method and those obtained by simulation and measurement proves the accuracy of the predicted model. When the digital controlled oscillator was corrupted by PSN with 100 mVpk-pk, the measured jitters were 33.9 ps at the rate of fG = 192 MHz and 148.5 ps at the rate of fG = 40 MHz. However, the measured phase noise was exactly the same except for two impulses appearing at 192 and 40 MHz, respectively.

How the growth rate of host cells affects cancer risk in a deterministic way

NASA Astrophysics Data System (ADS)

Draghi, Clément; Viger, Louise; Denis, Fabrice; Letellier, Christophe

2017-09-01

It is well known that cancers are significantly more often encountered in some tissues than in other ones. In this paper, by using a deterministic model describing the interactions between host, effector immune and tumor cells at the tissue level, we show that this can be explained by the dependency of tumor growth on parameter values characterizing the type as well as the state of the tissue considered due to the "way of life" (environmental factors, food consumption, drinking or smoking habits, etc.). Our approach is purely deterministic and, consequently, the strong correlation (r = 0.99) between the number of detectable growing tumors and the growth rate of cells from the nesting tissue can be explained without evoking random mutation arising during DNA replications in nonmalignant cells or "bad luck". Strategies to limit the mortality induced by cancer could therefore be well based on improving the way of life, that is, by better preserving the tissue where mutant cells randomly arise.

Deterministic delivery of remote entanglement on a quantum network.

PubMed

Humphreys, Peter C; Kalb, Norbert; Morits, Jaco P J; Schouten, Raymond N; Vermeulen, Raymond F L; Twitchen, Daniel J; Markham, Matthew; Hanson, Ronald

2018-06-01

Large-scale quantum networks promise to enable secure communication, distributed quantum computing, enhanced sensing and fundamental tests of quantum mechanics through the distribution of entanglement across nodes 1-7 . Moving beyond current two-node networks 8-13 requires the rate of entanglement generation between nodes to exceed the decoherence (loss) rate of the entanglement. If this criterion is met, intrinsically probabilistic entangling protocols can be used to provide deterministic remote entanglement at pre-specified times. Here we demonstrate this using diamond spin qubit nodes separated by two metres. We realize a fully heralded single-photon entanglement protocol that achieves entangling rates of up to 39 hertz, three orders of magnitude higher than previously demonstrated two-photon protocols on this platform 14 . At the same time, we suppress the decoherence rate of remote-entangled states to five hertz through dynamical decoupling. By combining these results with efficient charge-state control and mitigation of spectral diffusion, we deterministically deliver a fresh remote state with an average entanglement fidelity of more than 0.5 at every clock cycle of about 100 milliseconds without any pre- or post-selection. These results demonstrate a key building block for extended quantum networks and open the door to entanglement distribution across multiple remote nodes.

Implicit Sequence Learning in Dyslexia: A Within-Sequence Comparison of First- and Higher-Order Information

ERIC Educational Resources Information Center

Du, Wenchong; Kelly, Steve W.

2013-01-01

The present study examines implicit sequence learning in adult dyslexics with a focus on comparing sequence transitions with different statistical complexities. Learning of a 12-item deterministic sequence was assessed in 12 dyslexic and 12 non-dyslexic university students. Both groups showed equivalent standard reaction time increments when the…

Study of secondary neutron interactions with 232Th, 129I, and 127I nuclei with the uranium assembly “QUINTA” at 2, 4, and 8GeV deuteron beams of the JINR Nuclotron accelerator

DOE PAGES

Adam, J.; Chilap, V. V.; Furman, V. I.; ...

2015-11-04

The natural uranium assembly, “QUINTA”, was irradiated with 2, 4, and 8 GeV deuterons. The 232Th, 127I, and 129I samples have been exposed to secondary neutrons produced in the assembly at a 20-cm radial distance from the deuteron beam axis. The spectra of gamma rays emitted by the activated 232Th, 127I, and 129I samples have been analyzed and several tens of product nuclei have been identified. For each of those products, neutron-induced reaction rates have been determined. The transmutation power for the 129I samples is estimated. Furthermore, experimental results were compared to those calculated with well-known stochastic and deterministic codes.

Dynamics and thermodynamics of open chemical networks

NASA Astrophysics Data System (ADS)

Esposito, Massimiliano

Open chemical networks (OCN) are large sets of coupled chemical reactions where some of the species are chemostated (i.e. continuously restored from the environment). Cell metabolism is a notable example of OCN. Two results will be presented. First, dissipation in OCN operating in nonequilibrium steady-states strongly depends on the network topology (algebraic properties of the stoichiometric matrix). An application to oligosaccharides exchange dynamics performed by so-called D-enzymes will be provided. Second, at low concentration the dissipation of OCN is in general inaccurately predicted by deterministic dynamics (i.e. nonlinear rate equations for the species concentrations). In this case a description in terms of the chemical master equation is necessary. A notable exception is provided by so-called deficiency zero networks, i.e. chemical networks with no hidden cycles present in the graph of reactant complexes.

Review of Hybrid (Deterministic/Monte Carlo) Radiation Transport Methods, Codes, and Applications at Oak Ridge National Laboratory

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

Wagner, John C; Peplow, Douglas E.; Mosher, Scott W

2011-01-01

This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or moremore » localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(102-4), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.« less

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

NASA Astrophysics Data System (ADS)

Kim, Changho; Nonaka, Andy; Bell, John B.; Garcia, Alejandro L.; Donev, Aleksandar

2017-03-01

We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules, to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. By comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

DOE PAGES

Kim, Changho; Nonaka, Andy; Bell, John B.; ...

2017-03-24

Here, we develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules,more » to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. Furthermore, by comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.« less

Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses.

PubMed

Zhang, Wenbing; Tang, Yang; Huang, Tingwen; Kurths, Jurgen

In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.

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.

Hemopoietic Response to Low Dose-Rates of Ionizing Radiation Shows Stem Cell Tolerance and Adaptation

PubMed Central

Fliedner, Theodor M.; Graessle, Dieter H.; Meineke, Viktor; Feinendegen, Ludwig E.

2012-01-01

Chronic exposure of mammals to low dose-rates of ionizing radiation affects proliferating cell systems as a function of both dose-rate and the total dose accumulated. The lower the dose-rate the higher needs to be the total dose for a deterministic effect, i.e., tissue reaction to appear. Stem cells provide for proliferating, maturing and functional cells. Stem cells usually are particularly radiosensitive and damage to them may propagate to cause failure of functional cells. The paper revisits 1) medical histories with emphasis on the hemopoietic system of the victims of ten accidental chronic radiation exposures, 2) published hematological findings of long-term chronically gamma-irradiated rodents, and 3) such findings in dogs chronically exposed in large life-span studies. The data are consistent with the hypothesis that hemopoietic stem and early progenitor cells have the capacity to tolerate and adapt to being repetitively hit by energy deposition events. The data are compatible with the “injured stem cell hypothesis”, stating that radiation–injured stem cells, depending on dose-rate, may continue to deliver clones of functional cells that maintain homeostasis of hemopoiesis throughout life. Further studies perhaps on separated hemopoietic stem cells may unravel the molecular-biology mechanisms causing radiation tolerance and adaptation. PMID:23304110

Synchronization of random bit generators based on coupled chaotic lasers and application to cryptography.

PubMed

Kanter, Ido; Butkovski, Maria; Peleg, Yitzhak; Zigzag, Meital; Aviad, Yaara; Reidler, Igor; Rosenbluh, Michael; Kinzel, Wolfgang

2010-08-16

Random bit generators (RBGs) constitute an important tool in cryptography, stochastic simulations and secure communications. The later in particular has some difficult requirements: high generation rate of unpredictable bit strings and secure key-exchange protocols over public channels. Deterministic algorithms generate pseudo-random number sequences at high rates, however, their unpredictability is limited by the very nature of their deterministic origin. Recently, physical RBGs based on chaotic semiconductor lasers were shown to exceed Gbit/s rates. Whether secure synchronization of two high rate physical RBGs is possible remains an open question. Here we propose a method, whereby two fast RBGs based on mutually coupled chaotic lasers, are synchronized. Using information theoretic analysis we demonstrate security against a powerful computational eavesdropper, capable of noiseless amplification, where all parameters are publicly known. The method is also extended to secure synchronization of a small network of three RBGs.

The multinomial simulation algorithm for discrete stochastic simulation of reaction-diffusion systems.

PubMed

Lampoudi, Sotiria; Gillespie, Dan T; Petzold, Linda R

2009-03-07

The Inhomogeneous Stochastic Simulation Algorithm (ISSA) is a variant of the stochastic simulation algorithm in which the spatially inhomogeneous volume of the system is divided into homogeneous subvolumes, and the chemical reactions in those subvolumes are augmented by diffusive transfers of molecules between adjacent subvolumes. The ISSA can be prohibitively slow when the system is such that diffusive transfers occur much more frequently than chemical reactions. In this paper we present the Multinomial Simulation Algorithm (MSA), which is designed to, on the one hand, outperform the ISSA when diffusive transfer events outnumber reaction events, and on the other, to handle small reactant populations with greater accuracy than deterministic-stochastic hybrid algorithms. The MSA treats reactions in the usual ISSA fashion, but uses appropriately conditioned binomial random variables for representing the net numbers of molecules diffusing from any given subvolume to a neighbor within a prescribed distance. Simulation results illustrate the benefits of the algorithm.

Effects of Noise on Ecological Invasion Processes: Bacteriophage-mediated Competition in Bacteria

NASA Astrophysics Data System (ADS)

Joo, Jaewook; Eric, Harvill; Albert, Reka

2007-03-01

Pathogen-mediated competition, through which an invasive species carrying and transmitting a pathogen can be a superior competitor to a more vulnerable resident species, is one of the principle driving forces influencing biodiversity in nature. Using an experimental system of bacteriophage-mediated competition in bacterial populations and a deterministic model, we have shown in [Joo et al 2005] that the competitive advantage conferred by the phage depends only on the relative phage pathology and is independent of the initial phage concentration and other phage and host parameters such as the infection-causing contact rate, the spontaneous and infection-induced lysis rates, and the phage burst size. Here we investigate the effects of stochastic fluctuations on bacterial invasion facilitated by bacteriophage, and examine the validity of the deterministic approach. We use both numerical and analytical methods of stochastic processes to identify the source of noise and assess its magnitude. We show that the conclusions obtained from the deterministic model are robust against stochastic fluctuations, yet deviations become prominently large when the phage are more pathological to the invading bacterial strain.

A MODEL OF ESTUARY RESPONSE TO NITROGEN LOADING AND FRESHWATER RESIDENCE TIME

EPA Science Inventory

We have developed a deterministic model that relates average annual nitrogen loading rate and water residence time in an estuary to in-estuary nitrogen concentrations and loss rates (e.g. denitrification and incorporation in sediments), and to rates of nitrogen export across the ...

Study of secondary neutron interactions with ²³²Th, ¹²⁹I, and ¹²⁷I nuclei with the uranium assembly "QUINTA" at 2, 4, and 8 GeV deuteron beams of the JINR Nuclotron accelerator.

PubMed

Adam, J; Chilap, V V; Furman, V I; Kadykov, M G; Khushvaktov, J; Pronskikh, V S; Solnyshkin, A A; Stegailov, V I; Suchopar, M; Tsoupko-Sitnikov, V M; Tyutyunnikov, S I; Vrzalova, J; Wagner, V; Zavorka, L

2016-01-01

The natural uranium assembly, "QUINTA", was irradiated with 2, 4, and 8GeV deuterons. The (232)Th, (127)I, and (129)I samples have been exposed to secondary neutrons produced in the assembly at a 20-cm radial distance from the deuteron beam axis. The spectra of gamma rays emitted by the activated (232)Th, (127)I, and (129)I samples have been analyzed and several tens of product nuclei have been identified. For each of those products, neutron-induced reaction rates have been determined. The transmutation power for the (129)I samples is estimated. Experimental results were compared to those calculated with well-known stochastic and deterministic codes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A PC-based magnetometer-only attitude and rate determination system for gyroless spacecraft

NASA Technical Reports Server (NTRS)

Challa, M.; Natanson, G.; Deutschmann, J.; Galal, K.

1995-01-01

This paper describes a prototype PC-based system that uses measurements from a three-axis magnetometer (TAM) to estimate the state (three-axis attitude and rates) of a spacecraft given no a priori information other than the mass properties. The system uses two algorithms that estimate the spacecraft's state - a deterministic magnetic-field only algorithm and a Kalman filter for gyroless spacecraft. The algorithms are combined by invoking the deterministic algorithm to generate the spacecraft state at epoch using a small batch of data and then using this deterministic epoch solution as the initial condition for the Kalman filter during the production run. System input comprises processed data that includes TAM and reference magnetic field data. Additional information, such as control system data and measurements from line-of-sight sensors, can be input to the system if available. Test results are presented using in-flight data from two three-axis stabilized spacecraft: Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) (gyroless, Sun-pointing) and Earth Radiation Budget Satellite (ERBS) (gyro-based, Earth-pointing). The results show that, using as little as 700 s of data, the system is capable of accuracies of 1.5 deg in attitude and 0.01 deg/s in rates; i.e., within SAMPEX mission requirements.

Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations

NASA Astrophysics Data System (ADS)

Samoilov, Michael; Plyasunov, Sergey; Arkin, Adam P.

2005-02-01

Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics. network motif | signal transduction | chemical reaction | synthetic biology | systems biology

On the precision of quasi steady state assumptions in stochastic dynamics

NASA Astrophysics Data System (ADS)

Agarwal, Animesh; Adams, Rhys; Castellani, Gastone C.; Shouval, Harel Z.

2012-07-01

Many biochemical networks have complex multidimensional dynamics and there is a long history of methods that have been used for dimensionality reduction for such reaction networks. Usually a deterministic mass action approach is used; however, in small volumes, there are significant fluctuations from the mean which the mass action approach cannot capture. In such cases stochastic simulation methods should be used. In this paper, we evaluate the applicability of one such dimensionality reduction method, the quasi-steady state approximation (QSSA) [L. Menten and M. Michaelis, "Die kinetik der invertinwirkung," Biochem. Z 49, 333369 (1913)] for dimensionality reduction in case of stochastic dynamics. First, the applicability of QSSA approach is evaluated for a canonical system of enzyme reactions. Application of QSSA to such a reaction system in a deterministic setting leads to Michaelis-Menten reduced kinetics which can be used to derive the equilibrium concentrations of the reaction species. In the case of stochastic simulations, however, the steady state is characterized by fluctuations around the mean equilibrium concentration. Our analysis shows that a QSSA based approach for dimensionality reduction captures well the mean of the distribution as obtained from a full dimensional simulation but fails to accurately capture the distribution around that mean. Moreover, the QSSA approximation is not unique. We have then extended the analysis to a simple bistable biochemical network model proposed to account for the stability of synaptic efficacies; the substrate of learning and memory [J. E. Lisman, "A mechanism of memory storage insensitive to molecular turnover: A bistable autophosphorylating kinase," Proc. Natl. Acad. Sci. U.S.A. 82, 3055-3057 (1985)], 10.1073/pnas.82.9.3055. Our analysis shows that a QSSA based dimensionality reduction method results in errors as big as two orders of magnitude in predicting the residence times in the two stable states.

GOBF-ARMA based model predictive control for an ideal reactive distillation column.

PubMed

Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K

2015-11-01

This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. Copyright © 2015 Elsevier Inc. All rights reserved.

Discrete-Time Deterministic $Q$ -Learning: A Novel Convergence Analysis.

PubMed

Wei, Qinglai; Lewis, Frank L; Sun, Qiuye; Yan, Pengfei; Song, Ruizhuo

2017-05-01

In this paper, a novel discrete-time deterministic Q -learning algorithm is developed. In each iteration of the developed Q -learning algorithm, the iterative Q function is updated for all the state and control spaces, instead of updating for a single state and a single control in traditional Q -learning algorithm. A new convergence criterion is established to guarantee that the iterative Q function converges to the optimum, where the convergence criterion of the learning rates for traditional Q -learning algorithms is simplified. During the convergence analysis, the upper and lower bounds of the iterative Q function are analyzed to obtain the convergence criterion, instead of analyzing the iterative Q function itself. For convenience of analysis, the convergence properties for undiscounted case of the deterministic Q -learning algorithm are first developed. Then, considering the discounted factor, the convergence criterion for the discounted case is established. Neural networks are used to approximate the iterative Q function and compute the iterative control law, respectively, for facilitating the implementation of the deterministic Q -learning algorithm. Finally, simulation results and comparisons are given to illustrate the performance of the developed algorithm.

Deterministic error correction for nonlocal spatial-polarization hyperentanglement

PubMed Central

Li, Tao; Wang, Guan-Yu; Deng, Fu-Guo; Long, Gui-Lu

2016-01-01

Hyperentanglement is an effective quantum source for quantum communication network due to its high capacity, low loss rate, and its unusual character in teleportation of quantum particle fully. Here we present a deterministic error-correction scheme for nonlocal spatial-polarization hyperentangled photon pairs over collective-noise channels. In our scheme, the spatial-polarization hyperentanglement is first encoded into a spatial-defined time-bin entanglement with identical polarization before it is transmitted over collective-noise channels, which leads to the error rejection of the spatial entanglement during the transmission. The polarization noise affecting the polarization entanglement can be corrected with a proper one-step decoding procedure. The two parties in quantum communication can, in principle, obtain a nonlocal maximally entangled spatial-polarization hyperentanglement in a deterministic way, which makes our protocol more convenient than others in long-distance quantum communication. PMID:26861681

Deterministic error correction for nonlocal spatial-polarization hyperentanglement.

PubMed

Li, Tao; Wang, Guan-Yu; Deng, Fu-Guo; Long, Gui-Lu

2016-02-10

Hyperentanglement is an effective quantum source for quantum communication network due to its high capacity, low loss rate, and its unusual character in teleportation of quantum particle fully. Here we present a deterministic error-correction scheme for nonlocal spatial-polarization hyperentangled photon pairs over collective-noise channels. In our scheme, the spatial-polarization hyperentanglement is first encoded into a spatial-defined time-bin entanglement with identical polarization before it is transmitted over collective-noise channels, which leads to the error rejection of the spatial entanglement during the transmission. The polarization noise affecting the polarization entanglement can be corrected with a proper one-step decoding procedure. The two parties in quantum communication can, in principle, obtain a nonlocal maximally entangled spatial-polarization hyperentanglement in a deterministic way, which makes our protocol more convenient than others in long-distance quantum communication.

Deterministic mechanisms define the long-term anaerobic digestion microbiome and its functionality regardless of the initial microbial community.

PubMed

Peces, M; Astals, S; Jensen, P D; Clarke, W P

2018-05-17

The impact of the starting inoculum on long-term anaerobic digestion performance, process functionality and microbial community composition remains unclear. To understand the impact of starting inoculum, active microbial communities from four different full-scale anaerobic digesters were each used to inoculate four continuous lab-scale anaerobic digesters, which were operated identically for 295 days. Digesters were operated at 15 days solid retention time, an organic loading rate of 1 g COD L r -1 d -1 (75:25 - cellulose:casein) and 37 °C. Results showed that long-term process performance, metabolic rates (hydrolytic, acetogenic, and methanogenic) and microbial community are independent of the inoculum source. Digesters process performance converged after 80 days, while metabolic rates and microbial communities converged after 120-145 days. The convergence of the different microbial communities towards a core-community proves that the deterministic factors (process operational conditions) were a stronger driver than the initial microbial community composition. Indeed, the core-community represented 72% of the relative abundance among the four digesters. Moreover, a number of positive correlations were observed between higher metabolic rates and the relative abundance of specific microbial groups. These correlations showed that both substrate consumers and suppliers trigger higher metabolic rates, expanding the knowledge of the nexus between microorganisms and functionality. Overall, these results support that deterministic factors control microbial communities in bioreactors independently of the inoculum source. Hence, it seems plausible that a desired microbial composition and functionality can be achieved by tuning process operational conditions. Copyright © 2018. Published by Elsevier Ltd.

Amygdala and Ventral Striatum Make Distinct Contributions to Reinforcement Learning.

PubMed

Costa, Vincent D; Dal Monte, Olga; Lucas, Daniel R; Murray, Elisabeth A; Averbeck, Bruno B

2016-10-19

Reinforcement learning (RL) theories posit that dopaminergic signals are integrated within the striatum to associate choices with outcomes. Often overlooked is that the amygdala also receives dopaminergic input and is involved in Pavlovian processes that influence choice behavior. To determine the relative contributions of the ventral striatum (VS) and amygdala to appetitive RL, we tested rhesus macaques with VS or amygdala lesions on deterministic and stochastic versions of a two-arm bandit reversal learning task. When learning was characterized with an RL model relative to controls, amygdala lesions caused general decreases in learning from positive feedback and choice consistency. By comparison, VS lesions only affected learning in the stochastic task. Moreover, the VS lesions hastened the monkeys' choice reaction times, which emphasized a speed-accuracy trade-off that accounted for errors in deterministic learning. These results update standard accounts of RL by emphasizing distinct contributions of the amygdala and VS to RL. Published by Elsevier Inc.

Amygdala and ventral striatum make distinct contributions to reinforcement learning

PubMed Central

Costa, Vincent D.; Monte, Olga Dal; Lucas, Daniel R.; Murray, Elisabeth A.; Averbeck, Bruno B.

2016-01-01

Summary Reinforcement learning (RL) theories posit that dopaminergic signals are integrated within the striatum to associate choices with outcomes. Often overlooked is that the amygdala also receives dopaminergic input and is involved in Pavlovian processes that influence choice behavior. To determine the relative contributions of the ventral striatum (VS) and amygdala to appetitive RL we tested rhesus macaques with VS or amygdala lesions on deterministic and stochastic versions of a two-arm bandit reversal learning task. When learning was characterized with a RL model relative to controls, amygdala lesions caused general decreases in learning from positive feedback and choice consistency. By comparison, VS lesions only affected learning in the stochastic task. Moreover, the VS lesions hastened the monkeys’ choice reaction times, which emphasized a speed-accuracy tradeoff that accounted for errors in deterministic learning. These results update standard accounts of RL by emphasizing distinct contributions of the amygdala and VS to RL. PMID:27720488

Spatial modeling of cell signaling networks.

PubMed

Cowan, Ann E; Moraru, Ion I; Schaff, James C; Slepchenko, Boris M; Loew, Leslie M

2012-01-01

The shape of a cell, the sizes of subcellular compartments, and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic versus stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions, and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities, and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling. Copyright © 2012 Elsevier Inc. All rights reserved.

Deterministic and storable single-photon source based on a quantum memory.

PubMed

Chen, Shuai; Chen, Yu-Ao; Strassel, Thorsten; Yuan, Zhen-Sheng; Zhao, Bo; Schmiedmayer, Jörg; Pan, Jian-Wei

2006-10-27

A single-photon source is realized with a cold atomic ensemble (87Rb atoms). A single excitation, written in an atomic quantum memory by Raman scattering of a laser pulse, is retrieved deterministically as a single photon at a predetermined time. It is shown that the production rate of single photons can be enhanced considerably by a feedback circuit while the single-photon quality is conserved. Such a single-photon source is well suited for future large-scale realization of quantum communication and linear optical quantum computation.

Modelling and simulating reaction-diffusion systems using coloured Petri nets.

PubMed

Liu, Fei; Blätke, Mary-Ann; Heiner, Monika; Yang, Ming

2014-10-01

Reaction-diffusion systems often play an important role in systems biology when developmental processes are involved. Traditional methods of modelling and simulating such systems require substantial prior knowledge of mathematics and/or simulation algorithms. Such skills may impose a challenge for biologists, when they are not equally well-trained in mathematics and computer science. Coloured Petri nets as a high-level and graphical language offer an attractive alternative, which is easily approachable. In this paper, we investigate a coloured Petri net framework integrating deterministic, stochastic and hybrid modelling formalisms and corresponding simulation algorithms for the modelling and simulation of reaction-diffusion processes that may be closely coupled with signalling pathways, metabolic reactions and/or gene expression. Such systems often manifest multiscaleness in time, space and/or concentration. We introduce our approach by means of some basic diffusion scenarios, and test it against an established case study, the Brusselator model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Computational singular perturbation analysis of stochastic chemical systems with stiffness

NASA Astrophysics Data System (ADS)

Wang, Lijin; Han, Xiaoying; Cao, Yanzhao; Najm, Habib N.

2017-04-01

Computational singular perturbation (CSP) is a useful method for analysis, reduction, and time integration of stiff ordinary differential equation systems. It has found dominant utility, in particular, in chemical reaction systems with a large range of time scales at continuum and deterministic level. On the other hand, CSP is not directly applicable to chemical reaction systems at micro or meso-scale, where stochasticity plays an non-negligible role and thus has to be taken into account. In this work we develop a novel stochastic computational singular perturbation (SCSP) analysis and time integration framework, and associated algorithm, that can be used to not only construct accurately and efficiently the numerical solutions to stiff stochastic chemical reaction systems, but also analyze the dynamics of the reduced stochastic reaction systems. The algorithm is illustrated by an application to a benchmark stochastic differential equation model, and numerical experiments are carried out to demonstrate the effectiveness of the construction.

Immersion freezing of internally and externally mixed mineral dust species analyzed by stochastic and deterministic models

NASA Astrophysics Data System (ADS)

Wong, B.; Kilthau, W.; Knopf, D. A.

2017-12-01

Immersion freezing is recognized as the most important ice crystal formation process in mixed-phase cloud environments. It is well established that mineral dust species can act as efficient ice nucleating particles. Previous research has focused on determination of the ice nucleation propensity of individual mineral dust species. In this study, the focus is placed on how different mineral dust species such as illite, kaolinite and feldspar, initiate freezing of water droplets when present in internal and external mixtures. The frozen fraction data for single and multicomponent mineral dust droplet mixtures are recorded under identical cooling rates. Additionally, the time dependence of freezing is explored. Externally and internally mixed mineral dust droplet samples are exposed to constant temperatures (isothermal freezing experiments) and frozen fraction data is recorded based on time intervals. Analyses of single and multicomponent mineral dust droplet samples include different stochastic and deterministic models such as the derivation of the heterogeneous ice nucleation rate coefficient (J­­het), the single contact angle (α) description, the α-PDF model, active sites representation, and the deterministic model. Parameter sets derived from freezing data of single component mineral dust samples are evaluated for prediction of cooling rate dependent and isothermal freezing of multicomponent externally or internally mixed mineral dust samples. The atmospheric implications of our findings are discussed.

Computing rates of Markov models of voltage-gated ion channels by inverting partial differential equations governing the probability density functions of the conducting and non-conducting states.

PubMed

Tveito, Aslak; Lines, Glenn T; Edwards, Andrew G; McCulloch, Andrew

2016-07-01

Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Dual Roles for Spike Signaling in Cortical Neural Populations

PubMed Central

Ballard, Dana H.; Jehee, Janneke F. M.

2011-01-01

A prominent feature of signaling in cortical neurons is that of randomness in the action potential. The output of a typical pyramidal cell can be well fit with a Poisson model, and variations in the Poisson rate repeatedly have been shown to be correlated with stimuli. However while the rate provides a very useful characterization of neural spike data, it may not be the most fundamental description of the signaling code. Recent data showing γ frequency range multi-cell action potential correlations, together with spike timing dependent plasticity, are spurring a re-examination of the classical model, since precise timing codes imply that the generation of spikes is essentially deterministic. Could the observed Poisson randomness and timing determinism reflect two separate modes of communication, or do they somehow derive from a single process? We investigate in a timing-based model whether the apparent incompatibility between these probabilistic and deterministic observations may be resolved by examining how spikes could be used in the underlying neural circuits. The crucial component of this model draws on dual roles for spike signaling. In learning receptive fields from ensembles of inputs, spikes need to behave probabilistically, whereas for fast signaling of individual stimuli, the spikes need to behave deterministically. Our simulations show that this combination is possible if deterministic signals using γ latency coding are probabilistically routed through different members of a cortical cell population at different times. This model exhibits standard features characteristic of Poisson models such as orientation tuning and exponential interval histograms. In addition, it makes testable predictions that follow from the γ latency coding. PMID:21687798

Deterministic quantum state transfer and remote entanglement using microwave photons.

PubMed

Kurpiers, P; Magnard, P; Walter, T; Royer, B; Pechal, M; Heinsoo, J; Salathé, Y; Akin, A; Storz, S; Besse, J-C; Gasparinetti, S; Blais, A; Wallraff, A

2018-06-01

Sharing information coherently between nodes of a quantum network is fundamental to distributed quantum information processing. In this scheme, the computation is divided into subroutines and performed on several smaller quantum registers that are connected by classical and quantum channels 1 . A direct quantum channel, which connects nodes deterministically rather than probabilistically, achieves larger entanglement rates between nodes and is advantageous for distributed fault-tolerant quantum computation 2 . Here we implement deterministic state-transfer and entanglement protocols between two superconducting qubits fabricated on separate chips. Superconducting circuits 3 constitute a universal quantum node 4 that is capable of sending, receiving, storing and processing quantum information 5-8 . Our implementation is based on an all-microwave cavity-assisted Raman process 9 , which entangles or transfers the qubit state of a transmon-type artificial atom 10 with a time-symmetric itinerant single photon. We transfer qubit states by absorbing these itinerant photons at the receiving node, with a probability of 98.1 ± 0.1 per cent, achieving a transfer-process fidelity of 80.02 ± 0.07 per cent for a protocol duration of only 180 nanoseconds. We also prepare remote entanglement on demand with a fidelity as high as 78.9 ± 0.1 per cent at a rate of 50 kilohertz. Our results are in excellent agreement with numerical simulations based on a master-equation description of the system. This deterministic protocol has the potential to be used for quantum computing distributed across different nodes of a cryogenic network.

The experience of linking Victorian emergency medical service trauma data

PubMed Central

Boyle, Malcolm J

2008-01-01

Background The linking of a large Emergency Medical Service (EMS) dataset with the Victorian Department of Human Services (DHS) hospital datasets and Victorian State Trauma Outcome Registry and Monitoring (VSTORM) dataset to determine patient outcomes has not previously been undertaken in Victoria. The objective of this study was to identify the linkage rate of a large EMS trauma dataset with the Department of Human Services hospital datasets and VSTORM dataset. Methods The linking of an EMS trauma dataset to the hospital datasets utilised deterministic and probabilistic matching. The linking of three EMS trauma datasets to the VSTORM dataset utilised deterministic, probabilistic and manual matching. Results There were 66.7% of patients from the EMS dataset located in the VEMD. There were 96% of patients located in the VAED who were defined in the VEMD as being admitted to hospital. 3.7% of patients located in the VAED could not be found in the VEMD due to hospitals not reporting to the VEMD. For the EMS datasets, there was a 146% increase in successful links with the trauma profile dataset, a 221% increase in successful links with the mechanism of injury only dataset, and a 46% increase with sudden deterioration dataset, to VSTORM when using manual compared to deterministic matching. Conclusion This study has demonstrated that EMS data can be successfully linked to other health related datasets using deterministic and probabilistic matching with varying levels of success. The quality of EMS data needs to be improved to ensure better linkage success rates with other health related datasets. PMID:19014622

Evolution with Stochastic Fitness and Stochastic Migration

PubMed Central

Rice, Sean H.; Papadopoulos, Anthony

2009-01-01

Background Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration. Methodology/Principal Findings We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter. Conclusions/Significance As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory. PMID:19816580

Dispersal-Based Microbial Community Assembly Decreases Biogeochemical Function

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

Graham, Emily B.; Stegen, James C.

Ecological mechanisms influence relationships among microbial communities, which in turn impact biogeochemistry. In particular, microbial communities are assembled by deterministic (e.g., selection) and stochastic (e.g., dispersal) processes, and the relative balance of these two process types is hypothesized to alter the influence of microbial communities over biogeochemical function. We used an ecological simulation model to evaluate this hypothesis, defining biogeochemical function generically to represent any biogeochemical reaction of interest. We assembled receiving communities under different levels of dispersal from a source community that was assembled purely by selection. The dispersal scenarios ranged from no dispersal (i.e., selection-only) to dispersal ratesmore » high enough to overwhelm selection (i.e., homogenizing dispersal). We used an aggregate measure of community fitness to infer a given community’s biogeochemical function relative to other communities. We also used ecological null models to further link the relative influence of deterministic assembly to function. We found that increasing rates of dispersal decrease biogeochemical function by increasing the proportion of maladapted taxa in a local community. Niche breadth was also a key determinant of biogeochemical function, suggesting a tradeoff between the function of generalist and specialist species. Finally, we show that microbial assembly processes exert greater influence over biogeochemical function when there is variation in the relative contributions of dispersal and selection among communities. Taken together, our results highlight the influence of spatial processes on biogeochemical function and indicate the need to account for such effects in models that aim to predict biogeochemical function under future environmental scenarios.« less

Dispersal-Based Microbial Community Assembly Decreases Biogeochemical Function

DOE PAGES

Graham, Emily B.; Stegen, James C.

2017-11-01

Ecological mechanisms influence relationships among microbial communities, which in turn impact biogeochemistry. In particular, microbial communities are assembled by deterministic (e.g., selection) and stochastic (e.g., dispersal) processes, and the relative balance of these two process types is hypothesized to alter the influence of microbial communities over biogeochemical function. We used an ecological simulation model to evaluate this hypothesis, defining biogeochemical function generically to represent any biogeochemical reaction of interest. We assembled receiving communities under different levels of dispersal from a source community that was assembled purely by selection. The dispersal scenarios ranged from no dispersal (i.e., selection-only) to dispersal ratesmore » high enough to overwhelm selection (i.e., homogenizing dispersal). We used an aggregate measure of community fitness to infer a given community’s biogeochemical function relative to other communities. We also used ecological null models to further link the relative influence of deterministic assembly to function. We found that increasing rates of dispersal decrease biogeochemical function by increasing the proportion of maladapted taxa in a local community. Niche breadth was also a key determinant of biogeochemical function, suggesting a tradeoff between the function of generalist and specialist species. Finally, we show that microbial assembly processes exert greater influence over biogeochemical function when there is variation in the relative contributions of dispersal and selection among communities. Taken together, our results highlight the influence of spatial processes on biogeochemical function and indicate the need to account for such effects in models that aim to predict biogeochemical function under future environmental scenarios.« less

Review of Hybrid (Deterministic/Monte Carlo) Radiation Transport Methods, Codes, and Applications at Oak Ridge National Laboratory

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

Wagner, John C; Peplow, Douglas E.; Mosher, Scott W

2010-01-01

This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or moremore » localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(10{sup 2-4}), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.« less

Signal separation by nonlinear projections: The fetal electrocardiogram

NASA Astrophysics Data System (ADS)

Schreiber, Thomas; Kaplan, Daniel T.

1996-05-01

We apply a locally linear projection technique which has been developed for noise reduction in deterministically chaotic signals to extract the fetal component from scalar maternal electrocardiographic (ECG) recordings. Although we do not expect the maternal ECG to be deterministic chaotic, typical signals are effectively confined to a lower-dimensional manifold when embedded in delay space. The method is capable of extracting fetal heart rate even when the fetal component and the noise are of comparable amplitude. If the noise is small, more details of the fetal ECG, like P and T waves, can be recovered.

Selective sweeps in growing microbial colonies

NASA Astrophysics Data System (ADS)

Korolev, Kirill S.; Müller, Melanie J. I.; Karahan, Nilay; Murray, Andrew W.; Hallatschek, Oskar; Nelson, David R.

2012-04-01

Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.

Deterministic separation of cancer cells from blood at 10 mL/min

NASA Astrophysics Data System (ADS)

Loutherback, Kevin; D'Silva, Joseph; Liu, Liyu; Wu, Amy; Austin, Robert H.; Sturm, James C.

2012-12-01

Circulating tumor cells (CTCs) and circulating clusters of cancer and stromal cells have been identified in the blood of patients with malignant cancer and can be used as a diagnostic for disease severity, assess the efficacy of different treatment strategies and possibly determine the eventual location of metastatic invasions for possible treatment. There is thus a critical need to isolate, propagate and characterize viable CTCs and clusters of cancer cells with their associated stroma cells. Here, we present a microfluidic device for mL/min flow rate, continuous-flow capture of viable CTCs from blood using deterministic lateral displacement (DLD) arrays. We show here that a DLD array device can isolate CTCs from blood with capture efficiency greater than 85% CTCs at volumetric flow rates of up to 10 mL/min with no effect on cell viability.

Current fluctuations in periodically driven systems

NASA Astrophysics Data System (ADS)

Barato, Andre C.; Chetrite, Raphael

2018-05-01

Small nonequelibrium systems driven by an external periodic protocol can be described by Markov processes with time-periodic transition rates. In general, current fluctuations in such small systems are large and may play a crucial role. We develop a theoretical formalism to evaluate the rate of such large deviations in periodically driven systems. We show that the scaled cumulant generating function that characterizes current fluctuations is given by a maximal Floquet exponent. Comparing deterministic protocols with stochastic protocols, we show that, with respect to large deviations, systems driven by a stochastic protocol with an infinitely large number of jumps are equivalent to systems driven by deterministic protocols. Our results are illustrated with three case studies: a two-state model for a heat engine, a three-state model for a molecular pump, and a biased random walk with a time-periodic affinity.

A split-step method to include electron–electron collisions via Monte Carlo in multiple rate equation simulations

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

Huthmacher, Klaus; Molberg, Andreas K.; Rethfeld, Bärbel

2016-10-01

A split-step numerical method for calculating ultrafast free-electron dynamics in dielectrics is introduced. The two split steps, independently programmed in C++11 and FORTRAN 2003, are interfaced via the presented open source wrapper. The first step solves a deterministic extended multi-rate equation for the ionization, electron–phonon collisions, and single photon absorption by free-carriers. The second step is stochastic and models electron–electron collisions using Monte-Carlo techniques. This combination of deterministic and stochastic approaches is a unique and efficient method of calculating the nonlinear dynamics of 3D materials exposed to high intensity ultrashort pulses. Results from simulations solving the proposed model demonstrate howmore » electron–electron scattering relaxes the non-equilibrium electron distribution on the femtosecond time scale.« less

Investigation of HZETRN 2010 as a Tool for Single Event Effect Qualification of Avionics Systems

NASA Technical Reports Server (NTRS)

Rojdev, Kristina; Koontz, Steve; Atwell, William; Boeder, Paul

2014-01-01

NASA's future missions are focused on long-duration deep space missions for human exploration which offers no options for a quick emergency return to Earth. The combination of long mission duration with no quick emergency return option leads to unprecedented spacecraft system safety and reliability requirements. It is important that spacecraft avionics systems for human deep space missions are not susceptible to Single Event Effect (SEE) failures caused by space radiation (primarily the continuous galactic cosmic ray background and the occasional solar particle event) interactions with electronic components and systems. SEE effects are typically managed during the design, development, and test (DD&T) phase of spacecraft development by using heritage hardware (if possible) and through extensive component level testing, followed by system level failure analysis tasks that are both time consuming and costly. The ultimate product of the SEE DD&T program is a prediction of spacecraft avionics reliability in the flight environment produced using various nuclear reaction and transport codes in combination with the component and subsystem level radiation test data. Previous work by Koontz, et al.1 utilized FLUKA, a Monte Carlo nuclear reaction and transport code, to calculate SEE and single event upset (SEU) rates. This code was then validated against in-flight data for a variety of spacecraft and space flight environments. However, FLUKA has a long run-time (on the order of days). CREME962, an easy to use deterministic code offering short run times, was also compared with FLUKA predictions and in-flight data. CREME96, though fast and easy to use, has not been updated in several years and underestimates secondary particle shower effects in spacecraft structural shielding mass. Thus, this paper will investigate the use of HZETRN 20103, a fast and easy to use deterministic transport code, similar to CREME96, that was developed at NASA Langley Research Center primarily for flight crew ionizing radiation dose assessments. HZETRN 2010 includes updates to address secondary particle shower effects more accurately, and might be used as another tool to verify spacecraft avionics system reliability in space flight SEE environments.

Ion pump as Brownian motor: theory of electroconformational coupling and proof of ratchet mechanism for Na,K-ATPase action

NASA Astrophysics Data System (ADS)

Tsong, Tian Yow; Chang, Cheng-Hung

2003-04-01

This article reviews some concepts of the Brownian Ratchet which are relevant to our discussion of mechanisms of action of Na,K-ATPase, a universal ion pump and an elemental motor protein of the biological cell. Under wide ranges of ionic compositions it can hydrolyze an ATP and use the γ-phosphorous bond energy of ATP to pump 3 Na + out of, and 2 K + into the cell, both being uphill transport. During the ATP-dependent pump cycle, the enzyme oscillates between E1 and E2 states. Our experiment replaces ATP with externally applied electric field of various waveforms, amplitudes, and frequencies. The field enforced-oscillation, or fluctuation of E1 and E2 states enables the enzyme to harvest energy from the applied field and convert it to the chemical gradient energy of cations. A theory of electroconformational coupling (TEC), which embodies all the essential features of the Brownian Ratchet, successfully simulates these experimental results. Our analysis based on a four-state TEC model indicates that the equilibrium and the rate constants of the transport system define the frequency and the amplitude of the field for the optimal activation. Waveform, frequency, and amplitude are three elements of signal. Thus, electric signal of the ion pump is found by TEC analysis of the experimental data. Electric noise (white) superimposed on an electric signal changes the pump efficiency and produces effects similar to the stochastic resonance reported in other biological systems. The TEC concept is compared with the most commonly used Michaelis-Menten enzyme mechanism (MME) for similarities and differences. Both MME and TEC are catalytic wheels, which recycle the catalyst in each turnover. However, a MME can only catalyze reaction of descending free energy while a TEC enzyme can catalyze reaction of ascending free energy by harvesting needed energy from an off-equilibrium electric noise. The TEC mechanism is shown to be applicable to other biological motors and engines, as well. Deterministic and non-deterministic noise is examined in reference to future extension of the TEC model for biological transduction of free energy.

Refinement and evaluation of helicopter real-time self-adaptive active vibration controller algorithms

NASA Technical Reports Server (NTRS)

Davis, M. W.

1984-01-01

A Real-Time Self-Adaptive (RTSA) active vibration controller was used as the framework in developing a computer program for a generic controller that can be used to alleviate helicopter vibration. Based upon on-line identification of system parameters, the generic controller minimizes vibration in the fuselage by closed-loop implementation of higher harmonic control in the main rotor system. The new generic controller incorporates a set of improved algorithms that gives the capability to readily define many different configurations by selecting one of three different controller types (deterministic, cautious, and dual), one of two linear system models (local and global), and one or more of several methods of applying limits on control inputs (external and/or internal limits on higher harmonic pitch amplitude and rate). A helicopter rotor simulation analysis was used to evaluate the algorithms associated with the alternative controller types as applied to the four-bladed H-34 rotor mounted on the NASA Ames Rotor Test Apparatus (RTA) which represents the fuselage. After proper tuning all three controllers provide more effective vibration reduction and converge more quickly and smoothly with smaller control inputs than the initial RTSA controller (deterministic with external pitch-rate limiting). It is demonstrated that internal limiting of the control inputs a significantly improves the overall performance of the deterministic controller.

Effects of intrinsic stochasticity on delayed reaction-diffusion patterning systems.

PubMed

Woolley, Thomas E; Baker, Ruth E; Gaffney, Eamonn A; Maini, Philip K; Seirin-Lee, Sungrim

2012-05-01

Cellular gene expression is a complex process involving many steps, including the transcription of DNA and translation of mRNA; hence the synthesis of proteins requires a considerable amount of time, from ten minutes to several hours. Since diffusion-driven instability has been observed to be sensitive to perturbations in kinetic delays, the application of Turing patterning mechanisms to the problem of producing spatially heterogeneous differential gene expression has been questioned. In deterministic systems a small delay in the reactions can cause a large increase in the time it takes a system to pattern. Recently, it has been observed that in undelayed systems intrinsic stochasticity can cause pattern initiation to occur earlier than in the analogous deterministic simulations. Here we are interested in adding both stochasticity and delays to Turing systems in order to assess whether stochasticity can reduce the patterning time scale in delayed Turing systems. As analytical insights to this problem are difficult to attain and often limited in their use, we focus on stochastically simulating delayed systems. We consider four different Turing systems and two different forms of delay. Our results are mixed and lead to the conclusion that, although the sensitivity to delays in the Turing mechanism is not completely removed by the addition of intrinsic noise, the effects of the delays are clearly ameliorated in certain specific cases.

Balanced branching in transcription termination.

PubMed

Harrington, K J; Laughlin, R B; Liang, S

2001-04-24

The theory of stochastic transcription termination based on free-energy competition [von Hippel, P. H. & Yager, T. D. (1992) Science 255, 809-812 and von Hippel, P. H. & Yager, T. D. (1991) Proc. Natl. Acad. Sci. USA 88, 2307-2311] requires two or more reaction rates to be delicately balanced over a wide range of physical conditions. A large body of work on glasses and large molecules suggests that this balancing should be impossible in such a large system in the absence of a new organizing principle of matter. We review the experimental literature of termination and find no evidence for such a principle, but do find many troubling inconsistencies, most notably, anomalous memory effects. These effects suggest that termination has a deterministic component and may conceivably not be stochastic at all. We find that a key experiment by Wilson and von Hippel [Wilson, K. S. & von Hippel, P. H. (1994) J. Mol. Biol. 244, 36-51] thought to demonstrate stochastic termination was an incorrectly analyzed regulatory effect of Mg(2+) binding.

Trade-off study and computer simulation for assessing spacecraft pointing accuracy and stability capabilities

NASA Astrophysics Data System (ADS)

Algrain, Marcelo C.; Powers, Richard M.

1997-05-01

A case study, written in a tutorial manner, is presented where a comprehensive computer simulation is developed to determine the driving factors contributing to spacecraft pointing accuracy and stability. Models for major system components are described. Among them are spacecraft bus, attitude controller, reaction wheel assembly, star-tracker unit, inertial reference unit, and gyro drift estimators (Kalman filter). The predicted spacecraft performance is analyzed for a variety of input commands and system disturbances. The primary deterministic inputs are the desired attitude angles and rate set points. The stochastic inputs include random torque disturbances acting on the spacecraft, random gyro bias noise, gyro random walk, and star-tracker noise. These inputs are varied over a wide range to determine their effects on pointing accuracy and stability. The results are presented in the form of trade- off curves designed to facilitate the proper selection of subsystems so that overall spacecraft pointing accuracy and stability requirements are met.

Deterministic analysis of processes at corroding metal surfaces and the study of electrochemical noise in these systems

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

Latanision, R.M.

1990-12-01

Electrochemical corrosion is pervasive in virtually all engineering systems and in virtually all industrial circumstances. Although engineers now understand how to design systems to minimize corrosion in many instances, many fundamental questions remain poorly understood and, therefore, the development of corrosion control strategies is based more on empiricism than on a deep understanding of the processes by which metals corrode in electrolytes. Fluctuations in potential, or current, in electrochemical systems have been observed for many years. To date, all investigations of this phenomenon have utilized non-deterministic analyses. In this work it is proposed to study electrochemical noise from a deterministicmore » viewpoint by comparison of experimental parameters, such as first and second order moments (non-deterministic), with computer simulation of corrosion at metal surfaces. In this way it is proposed to analyze the origins of these fluctuations and to elucidate the relationship between these fluctuations and kinetic parameters associated with metal dissolution and cathodic reduction reactions. This research program addresses in essence two areas of interest: (a) computer modeling of corrosion processes in order to study the electrochemical processes on an atomistic scale, and (b) experimental investigations of fluctuations in electrochemical systems and correlation of experimental results with computer modeling. In effect, the noise generated by mathematical modeling will be analyzed and compared to experimental noise in electrochemical systems. 1 fig.« less

Dynamic Probabilistic Instability of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2009-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

Noise-induced symmetry breaking far from equilibrium and the emergence of biological homochirality

NASA Astrophysics Data System (ADS)

Jafarpour, Farshid; Biancalani, Tommaso; Goldenfeld, Nigel

2017-03-01

The origin of homochirality, the observed single-handedness of biological amino acids and sugars, has long been attributed to autocatalysis, a frequently assumed precursor for early life self-replication. However, the stability of homochiral states in deterministic autocatalytic systems relies on cross-inhibition of the two chiral states, an unlikely scenario for early life self-replicators. Here we present a theory for a stochastic individual-level model of autocatalytic prebiotic self-replicators that are maintained out of thermal equilibrium. Without chiral inhibition, the racemic state is the global attractor of the deterministic dynamics, but intrinsic multiplicative noise stabilizes the homochiral states. Moreover, we show that this noise-induced bistability is robust with respect to diffusion of molecules of opposite chirality, and systems of diffusively coupled autocatalytic chemical reactions synchronize their final homochiral states when the self-replication is the dominant production mechanism for the chiral molecules. We conclude that nonequilibrium autocatalysis is a viable mechanism for homochirality, without imposing additional nonlinearities such as chiral inhibition.

Nuclear and radiological terrorism: continuing education article.

PubMed

Anderson, Peter D; Bokor, Gyula

2013-06-01

Terrorism involving radioactive materials includes improvised nuclear devices, radiation exposure devices, contamination of food sources, radiation dispersal devices, or an attack on a nuclear power plant or a facility/vehicle that houses radioactive materials. Ionizing radiation removes electrons from atoms and changes the valence of the electrons enabling chemical reactions with elements that normally do not occur. Ionizing radiation includes alpha rays, beta rays, gamma rays, and neutron radiation. The effects of radiation consist of stochastic and deterministic effects. Cancer is the typical example of a stochastic effect of radiation. Deterministic effects include acute radiation syndrome (ARS). The hallmarks of ARS are damage to the skin, gastrointestinal tract, hematopoietic tissue, and in severe cases the neurovascular structures. Radiation produces psychological effects in addition to physiological effects. Radioisotopes relevant to terrorism include titrium, americium 241, cesium 137, cobalt 60, iodine 131, plutonium 238, califormium 252, iridium 192, uranium 235, and strontium 90. Medications used for treating a radiation exposure include antiemetics, colony-stimulating factors, antibiotics, electrolytes, potassium iodine, and chelating agents.

Noise induced phenomena in combustion

NASA Astrophysics Data System (ADS)

Liu, Hongliang

Quantitative models of combustion usually consist of systems of deterministic differential equations. However, there are reasons to suspect that noise may have a significant influence. In this thesis, our primary objective is to study the effect of noise on measurable quantities in the combustion process. Our first study involves combustion in a homogeneous gas. With a one step reaction model, we analytically estimate the requirements under which noise is important to create significant differences. Our simulation shows that a bi-modality phenomenon appears when appropriate parameters are applied, which agrees with our analytical result. Our second study involves steady planar flames. We use a relatively complete chemical model of the H2/air reaction system, which contains all eight reactive species (H2, O2, H, O, OH, H2O, HO2, H2O2) and N2. Our mathematical model for this system is a reacting flow model. We derive noise terms related to transport processes by a method advocated by Landau & Lifshitz, and we also derive noise terms related to chemical reactions. We develop a code to simulate this system. The numerical implementation relies on a good Riemann solver, suitable initial and boundary conditions, and so on. We also implement a code on a continuation method, which not only can be used to study approximate properties of laminar flames under deterministic governing equations, but also eliminates the difficulty of providing a suitable initial condition for governing equations with noise. With numerical experiments, we find the difference of flame speed exist when the noise is turned on or off although it is small when compared with the influence of other parameters, for example, the equivalence ratio. It will be a starting point for further studies to include noise in combustion.

General solution of the chemical master equation and modality of marginal distributions for hierarchic first-order reaction networks.

PubMed

Reis, Matthias; Kromer, Justus A; Klipp, Edda

2018-01-20

Multimodality is a phenomenon which complicates the analysis of statistical data based exclusively on mean and variance. Here, we present criteria for multimodality in hierarchic first-order reaction networks, consisting of catalytic and splitting reactions. Those networks are characterized by independent and dependent subnetworks. First, we prove the general solvability of the Chemical Master Equation (CME) for this type of reaction network and thereby extend the class of solvable CME's. Our general solution is analytical in the sense that it allows for a detailed analysis of its statistical properties. Given Poisson/deterministic initial conditions, we then prove the independent species to be Poisson/binomially distributed, while the dependent species exhibit generalized Poisson/Khatri Type B distributions. Generalized Poisson/Khatri Type B distributions are multimodal for an appropriate choice of parameters. We illustrate our criteria for multimodality by several basic models, as well as the well-known two-stage transcription-translation network and Bateman's model from nuclear physics. For both examples, multimodality was previously not reported.

Computational singular perturbation analysis of stochastic chemical systems with stiffness

DOE PAGES

Wang, Lijin; Han, Xiaoying; Cao, Yanzhao; ...

2017-01-25

Computational singular perturbation (CSP) is a useful method for analysis, reduction, and time integration of stiff ordinary differential equation systems. It has found dominant utility, in particular, in chemical reaction systems with a large range of time scales at continuum and deterministic level. On the other hand, CSP is not directly applicable to chemical reaction systems at micro or meso-scale, where stochasticity plays an non-negligible role and thus has to be taken into account. In this work we develop a novel stochastic computational singular perturbation (SCSP) analysis and time integration framework, and associated algorithm, that can be used to notmore » only construct accurately and efficiently the numerical solutions to stiff stochastic chemical reaction systems, but also analyze the dynamics of the reduced stochastic reaction systems. Furthermore, the algorithm is illustrated by an application to a benchmark stochastic differential equation model, and numerical experiments are carried out to demonstrate the effectiveness of the construction.« less

A Radiation Shielding Code for Spacecraft and Its Validation

NASA Technical Reports Server (NTRS)

Shinn, J. L.; Cucinotta, F. A.; Singleterry, R. C.; Wilson, J. W.; Badavi, F. F.; Badhwar, G. D.; Miller, J.; Zeitlin, C.; Heilbronn, L.; Tripathi, R. K.

2000-01-01

The HZETRN code, which uses a deterministic approach pioneered at NASA Langley Research Center, has been developed over the past decade to evaluate the local radiation fields within sensitive materials (electronic devices and human tissue) on spacecraft in the space environment. The code describes the interactions of shield materials with the incident galactic cosmic rays, trapped protons, or energetic protons from solar particle events in free space and low Earth orbit. The content of incident radiations is modified by atomic and nuclear reactions with the spacecraft and radiation shield materials. High-energy heavy ions are fragmented into less massive reaction products, and reaction products are produced by direct knockout of shield constituents or from de-excitation products. An overview of the computational procedures and database which describe these interactions is given. Validation of the code with recent Monte Carlo benchmarks, and laboratory and flight measurement is also included.

Multi-Algorithm Particle Simulations with Spatiocyte.

PubMed

Arjunan, Satya N V; Takahashi, Koichi

2017-01-01

As quantitative biologists get more measurements of spatially regulated systems such as cell division and polarization, simulation of reaction and diffusion of proteins using the data is becoming increasingly relevant to uncover the mechanisms underlying the systems. Spatiocyte is a lattice-based stochastic particle simulator for biochemical reaction and diffusion processes. Simulations can be performed at single molecule and compartment spatial scales simultaneously. Molecules can diffuse and react in 1D (filament), 2D (membrane), and 3D (cytosol) compartments. The implications of crowded regions in the cell can be investigated because each diffusing molecule has spatial dimensions. Spatiocyte adopts multi-algorithm and multi-timescale frameworks to simulate models that simultaneously employ deterministic, stochastic, and particle reaction-diffusion algorithms. Comparison of light microscopy images to simulation snapshots is supported by Spatiocyte microscopy visualization and molecule tagging features. Spatiocyte is open-source software and is freely available at http://spatiocyte.org .

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

NASA Astrophysics Data System (ADS)

Vijaykumar, Adithya; Ouldridge, Thomas E.; ten Wolde, Pieter Rein; Bolhuis, Peter G.

2017-03-01

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.

Mutual Information Rate and Bounds for It

PubMed Central

Baptista, Murilo S.; Rubinger, Rero M.; Viana, Emilson R.; Sartorelli, José C.; Parlitz, Ulrich; Grebogi, Celso

2012-01-01

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators. PMID:23112809

Forbidden patterns in financial time series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano

2008-03-01

The existence of forbidden patterns, i.e., certain missing sequences in a given time series, is a recently proposed instrument of potential application in the study of time series. Forbidden patterns are related to the permutation entropy, which has the basic properties of classic chaos indicators, such as Lyapunov exponent or Kolmogorov entropy, thus allowing to separate deterministic (usually chaotic) from random series; however, it requires fewer values of the series to be calculated, and it is suitable for using with small datasets. In this paper, the appearance of forbidden patterns is studied in different economical indicators such as stock indices (Dow Jones Industrial Average and Nasdaq Composite), NYSE stocks (IBM and Boeing), and others (ten year Bond interest rate), to find evidence of deterministic behavior in their evolutions. Moreover, the rate of appearance of the forbidden patterns is calculated, and some considerations about the underlying dynamics are suggested.

Converting differential-equation models of biological systems to membrane computing.

PubMed

Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

2013-12-01

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Stochastic and Deterministic Approaches to Gas-grain Modeling of Interstellar Sources

NASA Astrophysics Data System (ADS)

Vasyunin, Anton; Herbst, Eric; Caselli, Paola

During the last decade, our understanding of the chemistry on surfaces of interstellar grains has been significantly enchanced. Extensive laboratory studies have revealed complex structure and dynamics in interstellar ice analogues, thus making our knowledge much more detailed. In addition, the first qualitative investigations of new processes were made, such as non-thermal chemical desorption of species from dust grains into the gas. Not surprisingly, the rapid growth of knowledge about the physics and chemistry of interstellar ices led to the development of a new generation of astrochemical models. The models are typically characterized by more detailed treatments of the ice physics and chemistry than previously. The utilized numerical approaches vary greatly from microscopic models, in which every single molecule is traced, to ``mean field'' macroscopic models, which simulate the evolution of averaged characteristics of interstellar ices, such as overall bulk composition. While microscopic models based on a stochastic Monte Carlo approach are potentially able to simulate the evolution of interstellar ices with an account of most subtle effects found in a laboratory, their use is often impractical due to limited knowledge about star-forming regions and huge computational demands. On the other hand, deterministic macroscopic models that often utilize kinetic rate equations are computationally efficient but experience difficulties in incorporation of such potentially important effects as ice segregation or discreteness of surface chemical reactions. In my talk, I will review the state of the art in the development of gas-grain astrochemical models. I will discuss how to incorporate key features of ice chemistry and dynamics in the gas-grain astrochemical models, and how the incorporation of recent laboratory findings into gas-grain models helps to better match observations.

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

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

Biondo, Elliott D.; Wilson, Paul P. H.

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation ofmore » an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 104 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.« less

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

DOE PAGES

Biondo, Elliott D.; Wilson, Paul P. H.

2017-05-08

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation ofmore » an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 104 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.« less

The importance of environmental variability and management control error to optimal harvest policies

USGS Publications Warehouse

Hunter, C.M.; Runge, M.C.

2004-01-01

State-dependent strategies (SDSs) are the most general form of harvest policy because they allow the harvest rate to depend, without constraint, on the state of the system. State-dependent strategies that provide an optimal harvest rate for any system state can be calculated, and stochasticity can be appropriately accommodated in this optimization. Stochasticity poses 2 challenges to harvest policies: (1) the population will never be at the equilibrium state; and (2) stochasticity induces uncertainty about future states. We investigated the effects of 2 types of stochasticity, environmental variability and management control error, on SDS harvest policies for a white-tailed deer (Odocoileus virginianus) model, and contrasted these with a harvest policy based on maximum sustainable yield (MSY). Increasing stochasticity resulted in more conservative SDSs; that is, higher population densities were required to support the same harvest rate, but these effects were generally small. As stochastic effects increased, SDSs performed much better than MSY. Both deterministic and stochastic SDSs maintained maximum mean annual harvest yield (AHY) and optimal equilibrium population size (Neq) in a stochastic environment, whereas an MSY policy could not. We suggest 3 rules of thumb for harvest management of long-lived vertebrates in stochastic systems: (1) an SDS is advantageous over an MSY policy, (2) using an SDS rather than an MSY is more important than whether a deterministic or stochastic SDS is used, and (3) for SDSs, rankings of the variability in management outcomes (e.g., harvest yield) resulting from parameter stochasticity can be predicted by rankings of the deterministic elasticities.

Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes

PubMed Central

Shimo, Hanae; Arjunan, Satya Nanda Vel; Machiyama, Hiroaki; Nishino, Taiko; Suematsu, Makoto; Fujita, Hideaki; Tomita, Masaru; Takahashi, Koichi

2015-01-01

Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs. PMID:26046580

Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes.

PubMed

Shimo, Hanae; Arjunan, Satya Nanda Vel; Machiyama, Hiroaki; Nishino, Taiko; Suematsu, Makoto; Fujita, Hideaki; Tomita, Masaru; Takahashi, Koichi

2015-06-01

Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

Probabilistic short-term forecasting of eruption rate at Kīlauea Volcano using a physics-based model

NASA Astrophysics Data System (ADS)

Anderson, K. R.

2016-12-01

Deterministic models of volcanic eruptions yield predictions of future activity conditioned on uncertainty in the current state of the system. Physics-based eruption models are well-suited for deterministic forecasting as they can relate magma physics with a wide range of observations. Yet, physics-based eruption forecasting is strongly limited by an inadequate understanding of volcanic systems, and the need for eruption models to be computationally tractable. At Kīlauea Volcano, Hawaii, episodic depressurization-pressurization cycles of the magma system generate correlated, quasi-exponential variations in ground deformation and surface height of the active summit lava lake. Deflations are associated with reductions in eruption rate, or even brief eruptive pauses, and thus partly control lava flow advance rates and associated hazard. Because of the relatively well-understood nature of Kīlauea's shallow magma plumbing system, and because more than 600 of these events have been recorded to date, they offer a unique opportunity to refine a physics-based effusive eruption forecasting approach and apply it to lava eruption rates over short (hours to days) time periods. A simple physical model of the volcano ascribes observed data to temporary reductions in magma supply to an elastic reservoir filled with compressible magma. This model can be used to predict the evolution of an ongoing event, but because the mechanism that triggers events is unknown, event durations are modeled stochastically from previous observations. A Bayesian approach incorporates diverse data sets and prior information to simultaneously estimate uncertain model parameters and future states of the system. Forecasts take the form of probability distributions for eruption rate or cumulative erupted volume at some future time. Results demonstrate the significant uncertainties that still remain even for short-term eruption forecasting at a well-monitored volcano - but also the value of a physics-based, mixed deterministic-probabilistic eruption forecasting approach in reducing and quantifying these uncertainties.

Filling of a Poisson trap by a population of random intermittent searchers.

PubMed

Bressloff, Paul C; Newby, Jay M

2012-03-01

We extend the continuum theory of random intermittent search processes to the case of N independent searchers looking to deliver cargo to a single hidden target located somewhere on a semi-infinite track. Each searcher randomly switches between a stationary state and either a leftward or rightward constant velocity state. We assume that all of the particles start at one end of the track and realize sample trajectories independently generated from the same underlying stochastic process. The hidden target is treated as a partially absorbing trap in which a particle can only detect the target and deliver its cargo if it is stationary and within range of the target; the particle is removed from the system after delivering its cargo. As a further generalization of previous models, we assume that up to n successive particles can find the target and deliver its cargo. Assuming that the rate of target detection scales as 1/N, we show that there exists a well-defined mean-field limit N→∞, in which the stochastic model reduces to a deterministic system of linear reaction-hyperbolic equations for the concentrations of particles in each of the internal states. These equations decouple from the stochastic process associated with filling the target with cargo. The latter can be modeled as a Poisson process in which the time-dependent rate of filling λ(t) depends on the concentration of stationary particles within the target domain. Hence, we refer to the target as a Poisson trap. We analyze the efficiency of filling the Poisson trap with n particles in terms of the waiting time density f(n)(t). The latter is determined by the integrated Poisson rate μ(t)=∫(0)(t)λ(s)ds, which in turn depends on the solution to the reaction-hyperbolic equations. We obtain an approximate solution for the particle concentrations by reducing the system of reaction-hyperbolic equations to a scalar advection-diffusion equation using a quasisteady-state analysis. We compare our analytical results for the mean-field model with Monte Carlo simulations for finite N. We thus determine how the mean first passage time (MFPT) for filling the target depends on N and n.

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths.

PubMed

Olariu, Victor; Manesso, Erica; Peterson, Carsten

2017-06-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis-Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming.

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths

PubMed Central

Olariu, Victor; Manesso, Erica

2017-01-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis–Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming. PMID:28680655

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA

PubMed Central

Currin, Andrew; Korovin, Konstantin; Ababi, Maria; Roper, Katherine; Kell, Douglas B.; Day, Philip J.

2017-01-01

The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first physical design of an NUTM. This design is based on Thue string rewriting systems, and thereby avoids the limitations of most previous DNA computing schemes: all the computation is local (simple edits to strings) so there is no need for communication, and there is no need to order operations. The design exploits DNA's ability to replicate to execute an exponential number of computational paths in P time. Each Thue rewriting step is embodied in a DNA edit implemented using a novel combination of polymerase chain reactions and site-directed mutagenesis. We demonstrate that the design works using both computational modelling and in vitro molecular biology experimentation: the design is thermodynamically favourable, microprogramming can be used to encode arbitrary Thue rules, all classes of Thue rule can be implemented, and non-deterministic rule implementation. In an NUTM, the resource limitation is space, which contrasts with classical UTMs and QUTMs where it is time. This fundamental difference enables an NUTM to trade space for time, which is significant for both theoretical computer science and physics. It is also of practical importance, for to quote Richard Feynman ‘there's plenty of room at the bottom’. This means that a desktop DNA NUTM could potentially utilize more processors than all the electronic computers in the world combined, and thereby outperform the world's current fastest supercomputer, while consuming a tiny fraction of its energy. PMID:28250099

Aboveground and belowground arthropods experience different relative influences of stochastic versus deterministic community assembly processes following disturbance

PubMed Central

Martinez, Alexander S.; Faist, Akasha M.

2016-01-01

Background Understanding patterns of biodiversity is a longstanding challenge in ecology. Similar to other biotic groups, arthropod community structure can be shaped by deterministic and stochastic processes, with limited understanding of what moderates the relative influence of these processes. Disturbances have been noted to alter the relative influence of deterministic and stochastic processes on community assembly in various study systems, implicating ecological disturbances as a potential moderator of these forces. Methods Using a disturbance gradient along a 5-year chronosequence of insect-induced tree mortality in a subalpine forest of the southern Rocky Mountains, Colorado, USA, we examined changes in community structure and relative influences of deterministic and stochastic processes in the assembly of aboveground (surface and litter-active species) and belowground (species active in organic and mineral soil layers) arthropod communities. Arthropods were sampled for all years of the chronosequence via pitfall traps (aboveground community) and modified Winkler funnels (belowground community) and sorted to morphospecies. Community structure of both communities were assessed via comparisons of morphospecies abundance, diversity, and composition. Assembly processes were inferred from a mixture of linear models and matrix correlations testing for community associations with environmental properties, and from null-deviation models comparing observed vs. expected levels of species turnover (Beta diversity) among samples. Results Tree mortality altered community structure in both aboveground and belowground arthropod communities, but null models suggested that aboveground communities experienced greater relative influences of deterministic processes, while the relative influence of stochastic processes increased for belowground communities. Additionally, Mantel tests and linear regression models revealed significant associations between the aboveground arthropod communities and vegetation and soil properties, but no significant association among belowground arthropod communities and environmental factors. Discussion Our results suggest context-dependent influences of stochastic and deterministic community assembly processes across different fractions of a spatially co-occurring ground-dwelling arthropod community following disturbance. This variation in assembly may be linked to contrasting ecological strategies and dispersal rates within above- and below-ground communities. Our findings add to a growing body of evidence indicating concurrent influences of stochastic and deterministic processes in community assembly, and highlight the need to consider potential variation across different fractions of biotic communities when testing community ecology theory and considering conservation strategies. PMID:27761333

A variational method for analyzing limit cycle oscillations in stochastic hybrid systems

NASA Astrophysics Data System (ADS)

Bressloff, Paul C.; MacLaurin, James

2018-06-01

Many systems in biology can be modeled through ordinary differential equations, which are piece-wise continuous, and switch between different states according to a Markov jump process known as a stochastic hybrid system or piecewise deterministic Markov process (PDMP). In the fast switching limit, the dynamics converges to a deterministic ODE. In this paper, we develop a phase reduction method for stochastic hybrid systems that support a stable limit cycle in the deterministic limit. A classic example is the Morris-Lecar model of a neuron, where the switching Markov process is the number of open ion channels and the continuous process is the membrane voltage. We outline a variational principle for the phase reduction, yielding an exact analytic expression for the resulting phase dynamics. We demonstrate that this decomposition is accurate over timescales that are exponential in the switching rate ɛ-1 . That is, we show that for a constant C, the probability that the expected time to leave an O(a) neighborhood of the limit cycle is less than T scales as T exp (-C a /ɛ ) .

A computation study on the interplay between surface morphology and electrochemical performance of patterned thin film electrodes for Li-ion batteries

NASA Astrophysics Data System (ADS)

Gur, Sourav; Frantziskonis, George N.; Aifantis, Katerina E.

2017-08-01

Recent experiments illustrate that the morphology of the electrode surface impacts the voltage - capacity curves and long term cycling performance of Li-ion batteries. The present study systematically explores the role of the electrode surface morphology and uncertainties in the reactions that occur during electrochemical cycling, by performing kinetic Monte Carlo (kMC) simulations using the lattice Boltzmann method (LBM). This allows encoding of the inherent stochasticity at discrete microscale reaction events over the deterministic mean field reaction dynamics that occur in Li-ion cells. The electrodes are taken to be dense thin films whose surfaces are patterned with conical, trapezoidal, dome-shaped, or pillar-shaped structures. It is shown that the inherent perturbations in the reactions together with the characteristics of the electrode surface configuration can significantly improve battery performance, mainly because patterned surfaces, as opposed to flat surfaces, result in a smaller voltage drop. The most efficient pattern was the trapezoidal, which is consistent with experimental evidence on Si patterned electrodes.

Chaotic behavior in the locomotion of Amoeba proteus.

PubMed

Miyoshi, H; Kagawa, Y; Tsuchiya, Y

2001-01-01

The locomotion of Amoeba proteus has been investigated by algorithms evaluating correlation dimension and Lyapunov spectrum developed in the field of nonlinear science. It is presumed by these parameters whether the random behavior of the system is stochastic or deterministic. For the analysis of the nonlinear parameters, n-dimensional time-delayed vectors have been reconstructed from a time series of periphery and area of A. proteus images captured with a charge-coupled-device camera, which characterize its random motion. The correlation dimension analyzed has shown the random motion of A. proteus is subjected only to 3-4 macrovariables, though the system is a complex system composed of many degrees of freedom. Furthermore, the analysis of the Lyapunov spectrum has shown its largest exponent takes positive values. These results indicate the random behavior of A. proteus is chaotic and deterministic motion on an attractor with low dimension. It may be important for the elucidation of the cell locomotion to take account of nonlinear interactions among a small number of dynamics such as the sol-gel transformation, the cytoplasmic streaming, and the relating chemical reaction occurring in the cell.

Deterministic chaotic dynamics of Raba River flow (Polish Carpathian Mountains)

NASA Astrophysics Data System (ADS)

Kędra, Mariola

2014-02-01

Is the underlying dynamics of river flow random or deterministic? If it is deterministic, is it deterministic chaotic? This issue is still controversial. The application of several independent methods, techniques and tools for studying daily river flow data gives consistent, reliable and clear-cut results to the question. The outcomes point out that the investigated discharge dynamics is not random but deterministic. Moreover, the results completely confirm the nonlinear deterministic chaotic nature of the studied process. The research was conducted on daily discharge from two selected gauging stations of the mountain river in southern Poland, the Raba River.

Noiseless amplification of weak coherent fields exploiting energy fluctuations of the field

NASA Astrophysics Data System (ADS)

Partanen, Mikko; Häyrynen, Teppo; Oksanen, Jani; Tulkki, Jukka

2012-12-01

Quantum optics dictates that amplification of a pure state by any linear deterministic amplifier always introduces noise in the signal and results in a mixed output state. However, it has recently been shown that noiseless amplification becomes possible if the requirement of a deterministic operation is relaxed. Here we propose and analyze a noiseless amplification scheme where the energy required to amplify the signal originates from the stochastic fluctuations in the field itself. In contrast to previous amplification setups, our setup shows that a signal can be amplified even if no energy is added to the signal from external sources. We investigate the relation between the amplification and its success rate as well as the statistics of the output states after successful and failed amplification processes. Furthermore, we also optimize the setup to find the maximum success rates in terms of the reflectivities of the beam splitters used in the setup and discuss the relation of our setup with the previous setups.

Advances in the computation of the Sjöstrand, Rossi, and Feynman distributions

DOE PAGES

Talamo, A.; Gohar, Y.; Gabrielli, F.; ...

2017-02-01

This study illustrates recent computational advances in the application of the Sjöstrand (area), Rossi, and Feynman methods to estimate the effective multiplication factor of a subcritical system driven by an external neutron source. The methodologies introduced in this study have been validated with the experimental results from the KUKA facility of Japan by Monte Carlo (MCNP6 and MCNPX) and deterministic (ERANOS, VARIANT, and PARTISN) codes. When the assembly is driven by a pulsed neutron source generated by a particle accelerator and delayed neutrons are at equilibrium, the Sjöstrand method becomes extremely fast if the integral of the reaction rate frommore » a single pulse is split into two parts. These two integrals distinguish between the neutron counts during and after the pulse period. To conclude, when the facility is driven by a spontaneous fission neutron source, the timestamps of the detector neutron counts can be obtained up to the nanosecond precision using MCNP6, which allows obtaining the Rossi and Feynman distributions.« less

Line-of-sight pointing accuracy/stability analysis and computer simulation for small spacecraft

NASA Astrophysics Data System (ADS)

Algrain, Marcelo C.; Powers, Richard M.

1996-06-01

This paper presents a case study where a comprehensive computer simulation is developed to determine the driving factors contributing to spacecraft pointing accuracy and stability. The simulation is implemented using XMATH/SystemBuild software from Integrated Systems, Inc. The paper is written in a tutorial manner and models for major system components are described. Among them are spacecraft bus, attitude controller, reaction wheel assembly, star-tracker unit, inertial reference unit, and gyro drift estimators (Kalman filter). THe predicted spacecraft performance is analyzed for a variety of input commands and system disturbances. The primary deterministic inputs are desired attitude angles and rate setpoints. The stochastic inputs include random torque disturbances acting on the spacecraft, random gyro bias noise, gyro random walk, and star-tracker noise. These inputs are varied over a wide range to determine their effects on pointing accuracy and stability. The results are presented in the form of trade-off curves designed to facilitate the proper selection of subsystems so that overall spacecraft pointing accuracy and stability requirements are met.

Numerical approaches to combustion modeling. Progress in Astronautics and Aeronautics. Vol. 135

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

Oran, E.S.; Boris, J.P.

1991-01-01

Various papers on numerical approaches to combustion modeling are presented. The topics addressed include; ab initio quantum chemistry for combustion; rate coefficient calculations for combustion modeling; numerical modeling of combustion of complex hydrocarbons; combustion kinetics and sensitivity analysis computations; reduction of chemical reaction models; length scales in laminar and turbulent flames; numerical modeling of laminar diffusion flames; laminar flames in premixed gases; spectral simulations of turbulent reacting flows; vortex simulation of reacting shear flow; combustion modeling using PDF methods. Also considered are: supersonic reacting internal flow fields; studies of detonation initiation, propagation, and quenching; numerical modeling of heterogeneous detonations, deflagration-to-detonationmore » transition to reactive granular materials; toward a microscopic theory of detonations in energetic crystals; overview of spray modeling; liquid drop behavior in dense and dilute clusters; spray combustion in idealized configurations: parallel drop streams; comparisons of deterministic and stochastic computations of drop collisions in dense sprays; ignition and flame spread across solid fuels; numerical study of pulse combustor dynamics; mathematical modeling of enclosure fires; nuclear systems.« less

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy.

PubMed

Zelyak, O; Fallone, B G; St-Aubin, J

2017-12-14

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation.

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy

NASA Astrophysics Data System (ADS)

Zelyak, O.; Fallone, B. G.; St-Aubin, J.

2018-01-01

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation.

Corrigendum to "Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy".

PubMed

Zelyak, Oleksandr; Fallone, B Gino; St-Aubin, Joel

2018-03-12

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation. © 2018 Institute of Physics and Engineering in Medicine.

Critical velocities for deflagration and detonation triggered by voids in a REBO high explosive

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

Herring, Stuart Davis; Germann, Timothy C; Jensen, Niels G

2010-01-01

The effects of circular voids on the shock sensitivity of a two-dimensional model high explosive crystal are considered. We simulate a piston impact using molecular dynamics simulations with a Reactive Empirical Bond Order (REBO) model potential for a sub-micron, sub-ns exothermic reaction in a diatomic molecular solid. The probability of initiating chemical reactions is found to rise more suddenly with increasing piston velocity for larger voids that collapse more deterministically. A void with radius as small as 10 nm reduces the minimum initiating velocity by a factor of 4. The transition at larger velocities to detonation is studied in amore » micron-long sample with a single void (and its periodic images). The reaction yield during the shock traversal increases rapidly with velocity, then becomes a prompt, reliable detonation. A void of radius 2.5 nm reduces the critical velocity by 10% from the perfect crystal. A Pop plot of the time-to-detonation at higher velocities shows a characteristic pressure dependence.« less

Model reduction of multiscale chemical langevin equations: a numerical case study.

PubMed

Sotiropoulos, Vassilios; Contou-Carrere, Marie-Nathalie; Daoutidis, Prodromos; Kaznessis, Yiannis N

2009-01-01

Two very important characteristics of biological reaction networks need to be considered carefully when modeling these systems. First, models must account for the inherent probabilistic nature of systems far from the thermodynamic limit. Often, biological systems cannot be modeled with traditional continuous-deterministic models. Second, models must take into consideration the disparate spectrum of time scales observed in biological phenomena, such as slow transcription events and fast dimerization reactions. In the last decade, significant efforts have been expended on the development of stochastic chemical kinetics models to capture the dynamics of biomolecular systems, and on the development of robust multiscale algorithms, able to handle stiffness. In this paper, the focus is on the dynamics of reaction sets governed by stiff chemical Langevin equations, i.e., stiff stochastic differential equations. These are particularly challenging systems to model, requiring prohibitively small integration step sizes. We describe and illustrate the application of a semianalytical reduction framework for chemical Langevin equations that results in significant gains in computational cost.

Magnetometer-only attitude and rate determination for a gyro-less spacecraft

NASA Technical Reports Server (NTRS)

Natanson, G. A.; Challa, M. S.; Deutschmann, J.; Baker, D. F.

1994-01-01

Attitude determination algorithms that requires only the earth's magnetic field will be useful for contingency conditions. One way to determine attitude is to use the time derivative of the magnetic field as the second vector in the attitude determination process. When no gyros are available, however, attitude determination becomes difficult because the rates must be propagated via integration of Euler's equation, which in turn requires knowledge of the initial rates. The spacecraft state to be determined must then include not only the attitude but also rates. This paper describes a magnetometer-only attitude determination scheme with no a priori knowledge of the spacecraft state, which uses a deterministic algorithm to initialize an extended Kalman filter. The deterministic algorithm uses Euler's equation to relate the time derivatives of the magnetic field in the reference and body frames and solves the resultant transcendental equations for the coarse attitude and rates. An important feature of the filter is that its state vector also includes corrections to the propagated rates, thus enabling it to generate highly accurate solutions. The method was tested using in-flight data from the Solar, Anomalous, and Magnetospheric Particles Explorer (SAMPEX), a Small Explorer spacecraft. SAMPEX data using several eclipse periods were used to simulate conditions that may exist during the failure of the on-board digital sun sensor. The combined algorithm has been found effective, yielding accuracies of 1.5 deg in attitude (within even nominal mission requirements) and 0.01 degree per second (deg/sec) in the rates.

Phenotypic switching of populations of cells in a stochastic environment

NASA Astrophysics Data System (ADS)

Hufton, Peter G.; Lin, Yen Ting; Galla, Tobias

2018-02-01

In biology phenotypic switching is a common bet-hedging strategy in the face of uncertain environmental conditions. Existing mathematical models often focus on periodically changing environments to determine the optimal phenotypic response. We focus on the case in which the environment switches randomly between discrete states. Starting from an individual-based model we derive stochastic differential equations to describe the dynamics, and obtain analytical expressions for the mean instantaneous growth rates based on the theory of piecewise-deterministic Markov processes. We show that optimal phenotypic responses are non-trivial for slow and intermediate environmental processes, and systematically compare the cases of periodic and random environments. The best response to random switching is more likely to be heterogeneity than in the case of deterministic periodic environments, net growth rates tend to be higher under stochastic environmental dynamics. The combined system of environment and population of cells can be interpreted as host-pathogen interaction, in which the host tries to choose environmental switching so as to minimise growth of the pathogen, and in which the pathogen employs a phenotypic switching optimised to increase its growth rate. We discuss the existence of Nash-like mutual best-response scenarios for such host-pathogen games.

About influence of input rate random part of nonstationary queue system on statistical estimates of its macroscopic indicators

NASA Astrophysics Data System (ADS)

Korelin, Ivan A.; Porshnev, Sergey V.

2018-05-01

A model of the non-stationary queuing system (NQS) is described. The input of this model receives a flow of requests with input rate λ = λdet (t) + λrnd (t), where λdet (t) is a deterministic function depending on time; λrnd (t) is a random function. The parameters of functions λdet (t), λrnd (t) were identified on the basis of statistical information on visitor flows collected from various Russian football stadiums. The statistical modeling of NQS is carried out and the average statistical dependences are obtained: the length of the queue of requests waiting for service, the average wait time for the service, the number of visitors entered to the stadium on the time. It is shown that these dependencies can be characterized by the following parameters: the number of visitors who entered at the time of the match; time required to service all incoming visitors; the maximum value; the argument value when the studied dependence reaches its maximum value. The dependences of these parameters on the energy ratio of the deterministic and random component of the input rate are investigated.

Modeling a SI epidemic with stochastic transmission: hyperbolic incidence rate.

PubMed

Christen, Alejandra; Maulén-Yañez, M Angélica; González-Olivares, Eduardo; Curé, Michel

2018-03-01

In this paper a stochastic susceptible-infectious (SI) epidemic model is analysed, which is based on the model proposed by Roberts and Saha (Appl Math Lett 12: 37-41, 1999), considering a hyperbolic type nonlinear incidence rate. Assuming the proportion of infected population varies with time, our new model is described by an ordinary differential equation, which is analogous to the equation that describes the double Allee effect. The limit of the solution of this equation (deterministic model) is found when time tends to infinity. Then, the asymptotic behaviour of a stochastic fluctuation due to the environmental variation in the coefficient of disease transmission is studied. Thus a stochastic differential equation (SDE) is obtained and the existence of a unique solution is proved. Moreover, the SDE is analysed through the associated Fokker-Planck equation to obtain the invariant measure when the proportion of the infected population reaches steady state. An explicit expression for invariant measure is found and we study some of its properties. The long time behaviour of deterministic and stochastic models are compared by simulations. According to our knowledge this incidence rate has not been previously used for this type of epidemic models.

Stochastic integrated assessment of climate tipping points indicates the need for strict climate policy

NASA Astrophysics Data System (ADS)

Lontzek, Thomas S.; Cai, Yongyang; Judd, Kenneth L.; Lenton, Timothy M.

2015-05-01

Perhaps the most `dangerous’ aspect of future climate change is the possibility that human activities will push parts of the climate system past tipping points, leading to irreversible impacts. The likelihood of such large-scale singular events is expected to increase with global warming, but is fundamentally uncertain. A key question is how should the uncertainty surrounding tipping events affect climate policy? We address this using a stochastic integrated assessment model, based on the widely used deterministic DICE model. The temperature-dependent likelihood of tipping is calibrated using expert opinions, which we find to be internally consistent. The irreversible impacts of tipping events are assumed to accumulate steadily over time (rather than instantaneously), consistent with scientific understanding. Even with conservative assumptions about the rate and impacts of a stochastic tipping event, today’s optimal carbon tax is increased by ~50%. For a plausibly rapid, high-impact tipping event, today’s optimal carbon tax is increased by >200%. The additional carbon tax to delay climate tipping grows at only about half the rate of the baseline carbon tax. This implies that the effective discount rate for the costs of stochastic climate tipping is much lower than the discount rate for deterministic climate damages. Our results support recent suggestions that the costs of carbon emission used to inform policy are being underestimated, and that uncertain future climate damages should be discounted at a low rate.

Describing the linkages of the immigration, refugees and citizenship Canada permanent resident data and vital statistics death registry to Ontario's administrative health database.

PubMed

Chiu, Maria; Lebenbaum, Michael; Lam, Kelvin; Chong, Nelson; Azimaee, Mahmoud; Iron, Karey; Manuel, Doug; Guttmann, Astrid

2016-10-21

Ontario, the most populous province in Canada, has a universal healthcare system that routinely collects health administrative data on its 13 million legal residents that is used for health research. Record linkage has become a vital tool for this research by enriching this data with the Immigration, Refugees and Citizenship Canada Permanent Resident (IRCC-PR) database and the Office of the Registrar General's Vital Statistics-Death (ORG-VSD) registry. Our objectives were to estimate linkage rates and compare characteristics of individuals in the linked versus unlinked files. We used both deterministic and probabilistic linkage methods to link the IRCC-PR database (1985-2012) and ORG-VSD registry (1990-2012) to the Ontario's Registered Persons Database. Linkage rates were estimated and standardized differences were used to assess differences in socio-demographic and other characteristics between the linked and unlinked records. The overall linkage rates for the IRCC-PR database and ORG-VSD registry were 86.4 and 96.2 %, respectively. The majority (68.2 %) of the record linkages in IRCC-PR were achieved after three deterministic passes, 18.2 % were linked probabilistically, and 13.6 % were unlinked. Similarly the majority (79.8 %) of the record linkages in the ORG-VSD were linked using deterministic record linkage, 16.3 % were linked after probabilistic and manual review, and 3.9 % were unlinked. Unlinked and linked files were similar for most characteristics, such as age and marital status for IRCC-PR and sex and most causes of death for ORG-VSD. However, lower linkage rates were observed among people born in East Asia (78 %) in the IRCC-PR database and certain causes of death in the ORG-VSD registry, namely perinatal conditions (61.3 %) and congenital anomalies (81.3 %). The linkages of immigration and vital statistics data to existing population-based healthcare data in Ontario, Canada will enable many novel cross-sectional and longitudinal studies to be conducted. Analytic techniques to account for sub-optimal linkage rates may be required in studies of certain ethnic groups or certain causes of death among children and infants.

PROJECTED POPULATION-LEVEL EFFECTS OF THIOBENCARB EXPOSURE ON THE MYSID, AMERICAMYSIS BAHIA, AND EXTINCTION PROBABILITY IN A CONCENTRATION-DECAY EXPOSURE SYSTEM

EPA Science Inventory

Population-level effects of the mysid, Americamysis bahia, exposed to varying thiobencarb concentrations were estimated using stage-structured matrix models. A deterministic density-independent matrix model estimated the decrease in population growth rate, l, with increas...

An Equilibrium Flow Model of a University Campus.

ERIC Educational Resources Information Center

Oliver, Robert M.; Hopkins, David S. P.

This paper develops a simple deterministic model that relates student admissions and enrollments to the final demand for educated students. It includes the effects of dropout rates and student-teacher ratios on student enrollments and faculty staffing levels. Certain technological requirements are assumed known and given. These, as well as the…

First principles pulse pile-up balance equation and fast deterministic solution

NASA Astrophysics Data System (ADS)

Sabbatucci, Lorenzo; Fernández, Jorge E.

2017-08-01

Pulse pile-up (PPU) is an always present effect which introduces a distortion into the spectrum measured with radiation detectors and that worsen with the increasing emission rate of the radiation source. It is fully ascribable to the pulse handling circuitry of the detector and it is not comprised in the detector response function which is well explained by a physical model. The PPU changes both the number and the height of the recorded pulses, which are related, respectively, with the number of detected particles and their energy. In the present work, it is derived a first principles balance equation for second order PPU to obtain a post-processing correction to apply to X-ray measurements. The balance equation is solved for the particular case of rectangular pulse shape using a deterministic iterative procedure for which it will be shown the convergence. The proposed method, deterministic rectangular PPU (DRPPU), requires minimum amount of information and, as example, it is applied to a solid state Si detector with active or off-line PPU suppression circuitry. A comparison shows that the results obtained with this fast and simple approach are comparable to those from the more sophisticated procedure using precise detector pulse shapes.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 2

NASA Technical Reports Server (NTRS)

Onwubiko, Chin-Yere; Onyebueke, Landon

1996-01-01

The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.

Deterministic direct reprogramming of somatic cells to pluripotency.

PubMed

Rais, Yoach; Zviran, Asaf; Geula, Shay; Gafni, Ohad; Chomsky, Elad; Viukov, Sergey; Mansour, Abed AlFatah; Caspi, Inbal; Krupalnik, Vladislav; Zerbib, Mirie; Maza, Itay; Mor, Nofar; Baran, Dror; Weinberger, Leehee; Jaitin, Diego A; Lara-Astiaso, David; Blecher-Gonen, Ronnie; Shipony, Zohar; Mukamel, Zohar; Hagai, Tzachi; Gilad, Shlomit; Amann-Zalcenstein, Daniela; Tanay, Amos; Amit, Ido; Novershtern, Noa; Hanna, Jacob H

2013-10-03

Somatic cells can be inefficiently and stochastically reprogrammed into induced pluripotent stem (iPS) cells by exogenous expression of Oct4 (also called Pou5f1), Sox2, Klf4 and Myc (hereafter referred to as OSKM). The nature of the predominant rate-limiting barrier(s) preventing the majority of cells to successfully and synchronously reprogram remains to be defined. Here we show that depleting Mbd3, a core member of the Mbd3/NuRD (nucleosome remodelling and deacetylation) repressor complex, together with OSKM transduction and reprogramming in naive pluripotency promoting conditions, result in deterministic and synchronized iPS cell reprogramming (near 100% efficiency within seven days from mouse and human cells). Our findings uncover a dichotomous molecular function for the reprogramming factors, serving to reactivate endogenous pluripotency networks while simultaneously directly recruiting the Mbd3/NuRD repressor complex that potently restrains the reactivation of OSKM downstream target genes. Subsequently, the latter interactions, which are largely depleted during early pre-implantation development in vivo, lead to a stochastic and protracted reprogramming trajectory towards pluripotency in vitro. The deterministic reprogramming approach devised here offers a novel platform for the dissection of molecular dynamics leading to establishing pluripotency at unprecedented flexibility and resolution.

Sensitivity analysis in a Lassa fever deterministic mathematical model

NASA Astrophysics Data System (ADS)

Abdullahi, Mohammed Baba; Doko, Umar Chado; Mamuda, Mamman

2015-05-01

Lassa virus that causes the Lassa fever is on the list of potential bio-weapons agents. It was recently imported into Germany, the Netherlands, the United Kingdom and the United States as a consequence of the rapid growth of international traffic. A model with five mutually exclusive compartments related to Lassa fever is presented and the basic reproduction number analyzed. A sensitivity analysis of the deterministic model is performed. This is done in order to determine the relative importance of the model parameters to the disease transmission. The result of the sensitivity analysis shows that the most sensitive parameter is the human immigration, followed by human recovery rate, then person to person contact. This suggests that control strategies should target human immigration, effective drugs for treatment and education to reduced person to person contact.

Maxwell Demon Dynamics: Deterministic Chaos, the Szilard Map, and the Intelligence of Thermodynamic Systems

NASA Astrophysics Data System (ADS)

Boyd, Alexander B.; Crutchfield, James P.

2016-05-01

We introduce a deterministic chaotic system—the Szilard map—that encapsulates the measurement, control, and erasure protocol by which Maxwellian demons extract work from a heat reservoir. Implementing the demon's control function in a dynamical embodiment, our construction symmetrizes the demon and the thermodynamic system, allowing one to explore their functionality and recover the fundamental trade-off between the thermodynamic costs of dissipation due to measurement and those due to erasure. The map's degree of chaos—captured by the Kolmogorov-Sinai entropy—is the rate of energy extraction from the heat bath. Moreover, an engine's statistical complexity quantifies the minimum necessary system memory for it to function. In this way, dynamical instability in the control protocol plays an essential and constructive role in intelligent thermodynamic systems.

Deterministic Secure Quantum Communication and Authentication Protocol based on Extended GHZ-W State and Quantum One-time Pad

NASA Astrophysics Data System (ADS)

Li, Na; Li, Jian; Li, Lei-Lei; Wang, Zheng; Wang, Tao

2016-08-01

A deterministic secure quantum communication and authentication protocol based on extended GHZ-W state and quantum one-time pad is proposed. In the protocol, state | φ -> is used as the carrier. One photon of | φ -> state is sent to Alice, and Alice obtains a random key by measuring photons with bases determined by ID. The information of bases is secret to others except Alice and Bob. Extended GHZ-W states are used as decoy photons, the positions of which in information sequence are encoded with identity string ID of the legal user, and the eavesdropping detection rate reaches 81%. The eavesdropping detection based on extended GHZ-W state combines with authentication and the secret ID ensures the security of the protocol.

A Deterministic Interfacial Cyclic Oxidation Spalling Model. Part 1; Model Development and Parametric Response

NASA Technical Reports Server (NTRS)

Smialek, James L.

2002-01-01

An equation has been developed to model the iterative scale growth and spalling process that occurs during cyclic oxidation of high temperature materials. Parabolic scale growth and spalling of a constant surface area fraction have been assumed. Interfacial spallation of the only the thickest segments was also postulated. This simplicity allowed for representation by a simple deterministic summation series. Inputs are the parabolic growth rate constant, the spall area fraction, oxide stoichiometry, and cycle duration. Outputs include the net weight change behavior, as well as the total amount of oxygen and metal consumed, the total amount of oxide spalled, and the mass fraction of oxide spalled. The outputs all follow typical well-behaved trends with the inputs and are in good agreement with previous interfacial models.

Structural Deterministic Safety Factors Selection Criteria and Verification

NASA Technical Reports Server (NTRS)

Verderaime, V.

1992-01-01

Though current deterministic safety factors are arbitrarily and unaccountably specified, its ratio is rooted in resistive and applied stress probability distributions. This study approached the deterministic method from a probabilistic concept leading to a more systematic and coherent philosophy and criterion for designing more uniform and reliable high-performance structures. The deterministic method was noted to consist of three safety factors: a standard deviation multiplier of the applied stress distribution; a K-factor for the A- or B-basis material ultimate stress; and the conventional safety factor to ensure that the applied stress does not operate in the inelastic zone of metallic materials. The conventional safety factor is specifically defined as the ratio of ultimate-to-yield stresses. A deterministic safety index of the combined safety factors was derived from which the corresponding reliability proved the deterministic method is not reliability sensitive. The bases for selecting safety factors are presented and verification requirements are discussed. The suggested deterministic approach is applicable to all NASA, DOD, and commercial high-performance structures under static stresses.

Modeling metabolic networks in C. glutamicum: a comparison of rate laws in combination with various parameter optimization strategies

PubMed Central

Dräger, Andreas; Kronfeld, Marcel; Ziller, Michael J; Supper, Jochen; Planatscher, Hannes; Magnus, Jørgen B; Oldiges, Marco; Kohlbacher, Oliver; Zell, Andreas

2009-01-01

Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1) experimental measurement of participating molecules, (2) assignment of rate laws to each reaction, and (3) parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem. Results We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1) coarse-grained comparison of the algorithms on all models and (2) fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis. Conclusion A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics model. A Langevin model is advisable to take stochastic effects into account. To estimate the model parameters, three algorithms are particularly useful: For first attempts the settings-free Tribes algorithm yields valuable results. Particle swarm optimization and differential evolution provide significantly better results with appropriate settings. PMID:19144170

The Diffusion Model Is Not a Deterministic Growth Model: Comment on Jones and Dzhafarov (2014)

PubMed Central

Smith, Philip L.; Ratcliff, Roger; McKoon, Gail

2015-01-01

Jones and Dzhafarov (2014) claim that several current models of speeded decision making in cognitive tasks, including the diffusion model, can be viewed as special cases of other general models or model classes. The general models can be made to match any set of response time (RT) distribution and accuracy data exactly by a suitable choice of parameters and so are unfalsifiable. The implication of their claim is that models like the diffusion model are empirically testable only by artificially restricting them to exclude unfalsifiable instances of the general model. We show that Jones and Dzhafarov’s argument depends on enlarging the class of “diffusion” models to include models in which there is little or no diffusion. The unfalsifiable models are deterministic or near-deterministic growth models, from which the effects of within-trial variability have been removed or in which they are constrained to be negligible. These models attribute most or all of the variability in RT and accuracy to across-trial variability in the rate of evidence growth, which is permitted to be distributed arbitrarily and to vary freely across experimental conditions. In contrast, in the standard diffusion model, within-trial variability in evidence is the primary determinant of variability in RT. Across-trial variability, which determines the relative speed of correct responses and errors, is theoretically and empirically constrained. Jones and Dzhafarov’s attempt to include the diffusion model in a class of models that also includes deterministic growth models misrepresents and trivializes it and conveys a misleading picture of cognitive decision-making research. PMID:25347314

ACCELERATING FUSION REACTOR NEUTRONICS MODELING BY AUTOMATIC COUPLING OF HYBRID MONTE CARLO/DETERMINISTIC TRANSPORT ON CAD GEOMETRY

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

Biondo, Elliott D; Ibrahim, Ahmad M; Mosher, Scott W

2015-01-01

Detailed radiation transport calculations are necessary for many aspects of the design of fusion energy systems (FES) such as ensuring occupational safety, assessing the activation of system components for waste disposal, and maintaining cryogenic temperatures within superconducting magnets. Hybrid Monte Carlo (MC)/deterministic techniques are necessary for this analysis because FES are large, heavily shielded, and contain streaming paths that can only be resolved with MC. The tremendous complexity of FES necessitates the use of CAD geometry for design and analysis. Previous ITER analysis has required the translation of CAD geometry to MCNP5 form in order to use the AutomateD VAriaNcemore » reducTion Generator (ADVANTG) for hybrid MC/deterministic transport. In this work, ADVANTG was modified to support CAD geometry, allowing hybrid (MC)/deterministic transport to be done automatically and eliminating the need for this translation step. This was done by adding a new ray tracing routine to ADVANTG for CAD geometries using the Direct Accelerated Geometry Monte Carlo (DAGMC) software library. This new capability is demonstrated with a prompt dose rate calculation for an ITER computational benchmark problem using both the Consistent Adjoint Driven Importance Sampling (CADIS) method an the Forward Weighted (FW)-CADIS method. The variance reduction parameters produced by ADVANTG are shown to be the same using CAD geometry and standard MCNP5 geometry. Significant speedups were observed for both neutrons (as high as a factor of 7.1) and photons (as high as a factor of 59.6).« less

Reaction-diffusion controlled growth of complex structures

NASA Astrophysics Data System (ADS)

Noorduin, Willem; Mahadevan, L.; Aizenberg, Joanna

2013-03-01

Understanding how the emergence of complex forms and shapes in biominerals came about is both of fundamental and practical interest. Although biomineralization processes and organization strategies to give higher order architectures have been studied extensively, synthetic approaches to mimic these self-assembled structures are highly complex and have been difficult to emulate, let alone replicate. The emergence of solution patterns has been found in reaction-diffusion systems such as Turing patterns and the BZ reaction. Intrigued by this spontaneous formation of complexity we explored if similar processes can lead to patterns in the solid state. We here identify a reaction-diffusion system in which the shape of the solidified products is a direct readout of the environmental conditions. Based on insights in the underlying mechanism, we developed a toolbox of engineering strategies to deterministically sculpt patterns and shapes, and combine different morphologies to create a landscape of hierarchical multi scale-complex tectonic architectures with unprecedented levels of complexity. These findings may hold profound implications for understanding, mimicking and ultimately expanding upon nature's morphogenesis strategies, allowing the synthesis of advanced highly complex microscale materials and devices. WLN acknowledges the Netherlands Organization for Scientific Research for financial support

Probabilistic vs. deterministic fiber tracking and the influence of different seed regions to delineate cerebellar-thalamic fibers in deep brain stimulation.

PubMed

Schlaier, Juergen R; Beer, Anton L; Faltermeier, Rupert; Fellner, Claudia; Steib, Kathrin; Lange, Max; Greenlee, Mark W; Brawanski, Alexander T; Anthofer, Judith M

2017-06-01

This study compared tractography approaches for identifying cerebellar-thalamic fiber bundles relevant to planning target sites for deep brain stimulation (DBS). In particular, probabilistic and deterministic tracking of the dentate-rubro-thalamic tract (DRTT) and differences between the spatial courses of the DRTT and the cerebello-thalamo-cortical (CTC) tract were compared. Six patients with movement disorders were examined by magnetic resonance imaging (MRI), including two sets of diffusion-weighted images (12 and 64 directions). Probabilistic and deterministic tractography was applied on each diffusion-weighted dataset to delineate the DRTT. Results were compared with regard to their sensitivity in revealing the DRTT and additional fiber tracts and processing time. Two sets of regions-of-interests (ROIs) guided deterministic tractography of the DRTT or the CTC, respectively. Tract distances to an atlas-based reference target were compared. Probabilistic fiber tracking with 64 orientations detected the DRTT in all twelve hemispheres. Deterministic tracking detected the DRTT in nine (12 directions) and in only two (64 directions) hemispheres. Probabilistic tracking was more sensitive in detecting additional fibers (e.g. ansa lenticularis and medial forebrain bundle) than deterministic tracking. Probabilistic tracking lasted substantially longer than deterministic. Deterministic tracking was more sensitive in detecting the CTC than the DRTT. CTC tracts were located adjacent but consistently more posterior to DRTT tracts. These results suggest that probabilistic tracking is more sensitive and robust in detecting the DRTT but harder to implement than deterministic approaches. Although sensitivity of deterministic tracking is higher for the CTC than the DRTT, targets for DBS based on these tracts likely differ. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Structuring evolution: biochemical networks and metabolic diversification in birds.

PubMed

Morrison, Erin S; Badyaev, Alexander V

2016-08-25

Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a "global" carotenoid network - comprising of all known enzymatic reactions among naturally occurring carotenoids - with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds. We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network - compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution. The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.

Cultural Predictors of Academic Motivation and Achievement: A Self-Deterministic Approach

ERIC Educational Resources Information Center

Young, Adena; Johnson, Gail; Hawthorne, Melissa; Pugh, Jeremy

2011-01-01

College retention and graduation rates are significantly lower for African American and Hispanic American students. Limited research has been conducted on the relationship between academic motivation and perceived social support. The purpose of this study was to determine the importance of social support as a predictor of academic motivation and…

Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series

NASA Astrophysics Data System (ADS)

Chen, Wei-Shing

2011-04-01

The aim of the article is to answer the question if the Taiwan unemployment rate dynamics is generated by a non-linear deterministic dynamic process. This paper applies a recurrence plot and recurrence quantification approach based on the analysis of non-stationary hidden transition patterns of the unemployment rate of Taiwan. The case study uses the time series data of the Taiwan’s unemployment rate during the period from 1978/01 to 2010/06. The results show that recurrence techniques are able to identify various phases in the evolution of unemployment transition in Taiwan.

A nonlinear dynamic age-structured model of e-commerce in spain: Stability analysis of the equilibrium by delay and stochastic perturbations

NASA Astrophysics Data System (ADS)

Burgos, C.; Cortés, J.-C.; Shaikhet, L.; Villanueva, R.-J.

2018-11-01

First, we propose a deterministic age-structured epidemiological model to study the diffusion of e-commerce in Spain. Afterwards, we determine the parameters (death, birth and growth rates) of the underlying demographic model as well as the parameters (transmission of the use of e-commerce rates) of the proposed epidemiological model that best fit real data retrieved from the Spanish National Statistical Institute. Motivated by the two following facts: first the dynamics of acquiring the use of a new technology as e-commerce is mainly driven by the feedback after interacting with our peers (family, friends, mates, mass media, etc.), hence having a certain delay, and second the inherent uncertainty of sampled real data and the social complexity of the phenomena under analysis, we introduce aftereffect and stochastic perturbations in the initial deterministic model. This leads to a delayed stochastic model for e-commerce. We then investigate sufficient conditions in order to guarantee the stability in probability of the equilibrium point of the dynamic e-commerce delayed stochastic model. Our theoretical findings are numerically illustrated using real data.

Magnetometer-Only Attitude and Rate Estimates for Spinning Spacecraft

NASA Technical Reports Server (NTRS)

Challa, M.; Natanson, G.; Ottenstein, N.

2000-01-01

A deterministic algorithm and a Kalman filter for gyroless spacecraft are used independently to estimate the three-axis attitude and rates of rapidly spinning spacecraft using only magnetometer data. In-flight data from the Wide-Field Infrared Explorer (WIRE) during its tumble, and the Fast Auroral Snapshot Explorer (FAST) during its nominal mission mode are used to show that the algorithms can successfully estimate the above in spite of the high rates. Results using simulated data are used to illustrate the importance of accurate and frequent data.

RAINIER: A simulation tool for distributions of excited nuclear states and cascade fluctuations

NASA Astrophysics Data System (ADS)

Kirsch, L. E.; Bernstein, L. A.

2018-06-01

A new code has been developed named RAINIER that simulates the γ-ray decay of discrete and quasi-continuum nuclear levels for a user-specified range of energy, angular momentum, and parity including a realistic treatment of level spacing and transition width fluctuations. A similar program, DICEBOX, uses the Monte Carlo method to simulate level and width fluctuations but is restricted in its initial level population algorithm. On the other hand, modern reaction codes such as TALYS and EMPIRE populate a wide range of states in the residual nucleus prior to γ-ray decay, but do not go beyond the use of deterministic functions and therefore neglect cascade fluctuations. This combination of capabilities allows RAINIER to be used to determine quasi-continuum properties through comparison with experimental data. Several examples are given that demonstrate how cascade fluctuations influence experimental high-resolution γ-ray spectra from reactions that populate a wide range of initial states.

Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth

PubMed Central

Sanga, Sandeep; Frieboes, Hermann B.; Zheng, Xiaoming; Gatenby, Robert; Bearer, Elaine L.; Cristini, Vittorio

2007-01-01

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically review advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we propose and discuss a multi-scale, i.e., from the molecular to the gross tumor scale, mathematical and computational “first-principle” approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We demonstrate that this methodology, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as phenotype-diagnostic tool and thus to predict collective and individual tumor cell invasion of surrounding host. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior. PMID:17629503

Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.

PubMed

Salis, Howard; Kaznessis, Yiannis

2005-02-01

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.

Self-Assembly through Noncovalent Preorganization of Reactants: Explaining the Formation of a Polyfluoroxometalate.

PubMed

Schreiber, Roy E; Avram, Liat; Neumann, Ronny

2018-01-09

High-order elementary reactions in homogeneous solutions involving more than two molecules are statistically improbable and very slow to proceed. They are not generally considered in classical transition-state or collision theories. Yet, rather selective, high-yield product formation is common in self-assembly processes that require many reaction steps. On the basis of recent observations of crystallization as well as reactions in dense phases, it is shown that self-assembly can occur by preorganization of reactants in a noncovalent supramolecular assembly, whereby directing forces can lead to an apparent one-step transformation of multiple reactants. A simple and general kinetic model for multiple reactant transformation in a dense phase that can account for many-bodied transformations was developed. Furthermore, the self-assembly of polyfluoroxometalate anion [H 2 F 6 NaW 18 O 56 ] 7- from simple tungstate Na 2 WO 2 F 4 was demonstrated by using 2D 19 F- 19 F NOESY, 2D 19 F- 19 F COSY NMR spectroscopy, a new 2D 19 F{ 183 W} NMR technique, as well as ESI-MS and diffusion NMR spectroscopy, and the crucial involvement of a supramolecular assembly was found. The deterministic kinetic reaction model explains the reaction in a dense phase and supports the suggested self-assembly mechanism. Reactions in dense phases may be of general importance in understanding other self-assembly reactions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Immersion freezing of supermicron mineral dust particles: freezing results, testing different schemes for describing ice nucleation, and ice nucleation active site densities.

PubMed

Wheeler, M J; Mason, R H; Steunenberg, K; Wagstaff, M; Chou, C; Bertram, A K

2015-05-14

Ice nucleation on mineral dust particles is known to be an important process in the atmosphere. To accurately implement ice nucleation on mineral dust particles in atmospheric simulations, a suitable theory or scheme is desirable to describe laboratory freezing data in atmospheric models. In the following, we investigated ice nucleation by supermicron mineral dust particles [kaolinite and Arizona Test Dust (ATD)] in the immersion mode. The median freezing temperature for ATD was measured to be approximately -30 °C compared with approximately -36 °C for kaolinite. The freezing results were then used to test four different schemes previously used to describe ice nucleation in atmospheric models. In terms of ability to fit the data (quantified by calculating the reduced chi-squared values), the following order was found for ATD (from best to worst): active site, pdf-α, deterministic, single-α. For kaolinite, the following order was found (from best to worst): active site, deterministic, pdf-α, single-α. The variation in the predicted median freezing temperature per decade change in the cooling rate for each of the schemes was also compared with experimental results from other studies. The deterministic model predicts the median freezing temperature to be independent of cooling rate, while experimental results show a weak dependence on cooling rate. The single-α, pdf-α, and active site schemes all agree with the experimental results within roughly a factor of 2. On the basis of our results and previous results where different schemes were tested, the active site scheme is recommended for describing the freezing of ATD and kaolinite particles. We also used our ice nucleation results to determine the ice nucleation active site (INAS) density for the supermicron dust particles tested. Using the data, we show that the INAS densities of supermicron kaolinite and ATD particles studied here are smaller than the INAS densities of submicron kaolinite and ATD particles previously reported in the literature.

Deterministic quantum dense coding networks

NASA Astrophysics Data System (ADS)

Roy, Saptarshi; Chanda, Titas; Das, Tamoghna; Sen(De), Aditi; Sen, Ujjwal

2018-07-01

We consider the scenario of deterministic classical information transmission between multiple senders and a single receiver, when they a priori share a multipartite quantum state - an attempt towards building a deterministic dense coding network. Specifically, we prove that in the case of two or three senders and a single receiver, generalized Greenberger-Horne-Zeilinger (gGHZ) states are not beneficial for sending classical information deterministically beyond the classical limit, except when the shared state is the GHZ state itself. On the other hand, three- and four-qubit generalized W (gW) states with specific parameters as well as the four-qubit Dicke states can provide a quantum advantage of sending the information in deterministic dense coding. Interestingly however, numerical simulations in the three-qubit scenario reveal that the percentage of states from the GHZ-class that are deterministic dense codeable is higher than that of states from the W-class.

Call Admission Control on Single Node Networks under Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) Scheduler

NASA Astrophysics Data System (ADS)

Hanada, Masaki; Nakazato, Hidenori; Watanabe, Hitoshi

Multimedia applications such as music or video streaming, video teleconferencing and IP telephony are flourishing in packet-switched networks. Applications that generate such real-time data can have very diverse quality-of-service (QoS) requirements. In order to guarantee diverse QoS requirements, the combined use of a packet scheduling algorithm based on Generalized Processor Sharing (GPS) and leaky bucket traffic regulator is the most successful QoS mechanism. GPS can provide a minimum guaranteed service rate for each session and tight delay bounds for leaky bucket constrained sessions. However, the delay bounds for leaky bucket constrained sessions under GPS are unnecessarily large because each session is served according to its associated constant weight until the session buffer is empty. In order to solve this problem, a scheduling policy called Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) was proposed in [17]. ORC-GPS is a rate-based scheduling like GPS, and controls the service rate in order to lower the delay bounds for leaky bucket constrained sessions. In this paper, we propose a call admission control (CAC) algorithm for ORC-GPS, for leaky-bucket constrained sessions with deterministic delay requirements. This CAC algorithm for ORC-GPS determines the optimal values of parameters of ORC-GPS from the deterministic delay requirements of the sessions. In numerical experiments, we compare the CAC algorithm for ORC-GPS with one for GPS in terms of schedulable region and computational complexity.

Deterministic Function Computation with Chemical Reaction Networks*

PubMed Central

Chen, Ho-Lin; Doty, David; Soloveichik, David

2013-01-01

Chemical reaction networks (CRNs) formally model chemistry in a well-mixed solution. CRNs are widely used to describe information processing occurring in natural cellular regulatory networks, and with upcoming advances in synthetic biology, CRNs are a promising language for the design of artificial molecular control circuitry. Nonetheless, despite the widespread use of CRNs in the natural sciences, the range of computational behaviors exhibited by CRNs is not well understood. CRNs have been shown to be efficiently Turing-universal (i.e., able to simulate arbitrary algorithms) when allowing for a small probability of error. CRNs that are guaranteed to converge on a correct answer, on the other hand, have been shown to decide only the semilinear predicates (a multi-dimensional generalization of “eventually periodic” sets). We introduce the notion of function, rather than predicate, computation by representing the output of a function f : ℕk → ℕl by a count of some molecular species, i.e., if the CRN starts with x1, …, xk molecules of some “input” species X1, …, Xk, the CRN is guaranteed to converge to having f(x1, …, xk) molecules of the “output” species Y1, …, Yl. We show that a function f : ℕk → ℕl is deterministically computed by a CRN if and only if its graph {(x, y) ∈ ℕk × ℕl ∣ f(x) = y} is a semilinear set. Finally, we show that each semilinear function f (a function whose graph is a semilinear set) can be computed by a CRN on input x in expected time O(polylog ∥x∥1). PMID:25383068

Soil erosion assessment - Mind the gap

NASA Astrophysics Data System (ADS)

Kim, Jongho; Ivanov, Valeriy Y.; Fatichi, Simone

2016-12-01

Accurate assessment of erosion rates remains an elusive problem because soil loss is strongly nonunique with respect to the main drivers. In addressing the mechanistic causes of erosion responses, we discriminate between macroscale effects of external factors - long studied and referred to as "geomorphic external variability", and microscale effects, introduced as "geomorphic internal variability." The latter source of erosion variations represents the knowledge gap, an overlooked but vital element of geomorphic response, significantly impacting the low predictability skill of deterministic models at field-catchment scales. This is corroborated with experiments using a comprehensive physical model that dynamically updates the soil mass and particle composition. As complete knowledge of microscale conditions for arbitrary location and time is infeasible, we propose that new predictive frameworks of soil erosion should embed stochastic components in deterministic assessments of external and internal types of geomorphic variability.

Deterministic Coupling of Quantum Emitters in 2D Materials to Plasmonic Nanocavity Arrays.

PubMed

Tran, Toan Trong; Wang, Danqing; Xu, Zai-Quan; Yang, Ankun; Toth, Milos; Odom, Teri W; Aharonovich, Igor

2017-04-12

Quantum emitters in two-dimensional materials are promising candidates for studies of light-matter interaction and next generation, integrated on-chip quantum nanophotonics. However, the realization of integrated nanophotonic systems requires the coupling of emitters to optical cavities and resonators. In this work, we demonstrate hybrid systems in which quantum emitters in 2D hexagonal boron nitride (hBN) are deterministically coupled to high-quality plasmonic nanocavity arrays. The plasmonic nanoparticle arrays offer a high-quality, low-loss cavity in the same spectral range as the quantum emitters in hBN. The coupled emitters exhibit enhanced emission rates and reduced fluorescence lifetimes, consistent with Purcell enhancement in the weak coupling regime. Our results provide the foundation for a versatile approach for achieving scalable, integrated hybrid systems based on low-loss plasmonic nanoparticle arrays and 2D materials.

The Stochastic Modelling of Endemic Diseases

NASA Astrophysics Data System (ADS)

Susvitasari, Kurnia; Siswantining, Titin

2017-01-01

A study about epidemic has been conducted since a long time ago, but genuine progress was hardly forthcoming until the end of the 19th century (Bailey, 1975). Both deterministic and stochastic models were used to describe these. Then, from 1927 to 1939 Kermack and McKendrick introduced a generality of this model, including some variables to consider such as rate of infection and recovery. The purpose of this project is to investigate the behaviour of the models when we set the basic reproduction number, R0. This quantity is defined as the expected number of contacts made by a typical infective to susceptibles in the population. According to the epidemic threshold theory, when R0 ≤ 1, minor epidemic occurs with probability one in both approaches, but when R0 > 1, the deterministic and stochastic models have different interpretation. In the deterministic approach, major epidemic occurs with probability one when R0 > 1 and predicts that the disease will settle down to an endemic equilibrium. Stochastic models, on the other hand, identify that the minor epidemic can possibly occur. If it does, then the epidemic will die out quickly. Moreover, if we let the population size be large and the major epidemic occurs, then it will take off and then reach the endemic level and move randomly around the deterministic’s equilibrium.

Stochastic calculus of protein filament formation under spatial confinement

NASA Astrophysics Data System (ADS)

Michaels, Thomas C. T.; Dear, Alexander J.; Knowles, Tuomas P. J.

2018-05-01

The growth of filamentous aggregates from precursor proteins is a process of central importance to both normal and aberrant biology, for instance as the driver of devastating human disorders such as Alzheimer's and Parkinson's diseases. The conventional theoretical framework for describing this class of phenomena in bulk is based upon the mean-field limit of the law of mass action, which implicitly assumes deterministic dynamics. However, protein filament formation processes under spatial confinement, such as in microdroplets or in the cellular environment, show intrinsic variability due to the molecular noise associated with small-volume effects. To account for this effect, in this paper we introduce a stochastic differential equation approach for investigating protein filament formation processes under spatial confinement. Using this framework, we study the statistical properties of stochastic aggregation curves, as well as the distribution of reaction lag-times. Moreover, we establish the gradual breakdown of the correlation between lag-time and normalized growth rate under spatial confinement. Our results establish the key role of spatial confinement in determining the onset of stochasticity in protein filament formation and offer a formalism for studying protein aggregation kinetics in small volumes in terms of the kinetic parameters describing the aggregation dynamics in bulk.

Ergodicity of Truncated Stochastic Navier Stokes with Deterministic Forcing and Dispersion

NASA Astrophysics Data System (ADS)

Majda, Andrew J.; Tong, Xin T.

2016-10-01

Turbulence in idealized geophysical flows is a very rich and important topic. The anisotropic effects of explicit deterministic forcing, dispersive effects from rotation due to the β -plane and F-plane, and topography together with random forcing all combine to produce a remarkable number of realistic phenomena. These effects have been studied through careful numerical experiments in the truncated geophysical models. These important results include transitions between coherent jets and vortices, and direct and inverse turbulence cascades as parameters are varied, and it is a contemporary challenge to explain these diverse statistical predictions. Here we contribute to these issues by proving with full mathematical rigor that for any values of the deterministic forcing, the β - and F-plane effects and topography, with minimal stochastic forcing, there is geometric ergodicity for any finite Galerkin truncation. This means that there is a unique smooth invariant measure which attracts all statistical initial data at an exponential rate. In particular, this rigorous statistical theory guarantees that there are no bifurcations to multiple stable and unstable statistical steady states as geophysical parameters are varied in contrast to claims in the applied literature. The proof utilizes a new statistical Lyapunov function to account for enstrophy exchanges between the statistical mean and the variance fluctuations due to the deterministic forcing. It also requires careful proofs of hypoellipticity with geophysical effects and uses geometric control theory to establish reachability. To illustrate the necessity of these conditions, a two-dimensional example is developed which has the square of the Euclidean norm as the Lyapunov function and is hypoelliptic with nonzero noise forcing, yet fails to be reachable or ergodic.

Probability versus Representativeness in Infancy: Can Infants Use Naïve Physics to Adjust Population Base Rates in Probabilistic Inference?

ERIC Educational Resources Information Center

Denison, Stephanie; Trikutam, Pallavi; Xu, Fei

2014-01-01

A rich tradition in developmental psychology explores physical reasoning in infancy. However, no research to date has investigated whether infants can reason about physical objects that behave probabilistically, rather than deterministically. Physical events are often quite variable, in that similar-looking objects can be placed in similar…

Creating a stage-based deterministic PVA model - the western prairie fringed orchid [Exercise 12

Treesearch

Carolyn Hull Sieg; Rudy M. King; Fred Van Dyke

2003-01-01

Contemporary efforts to conserve populations and species often employ population viability analysis (PVA), a specific application of population modeling that estimates the effects of environmental and demographic processes on population growth rates. These models can also be used to estimate probabilities that a population will fall below a certain level. This...

Assessing Potential Climate Change Effects on Loblolly Pine Growth: A Probabilistic Regional Modeling Approach

Treesearch

Peter B. Woodbury; James E. Smith; David A. Weinstein; John A. Laurence

1998-01-01

Most models of the potential effects of climate change on forest growth have produced deterministic predictions. However, there are large uncertainties in data on regional forest condition, estimates of future climate, and quantitative relationships between environmental conditions and forest growth rate. We constructed a new model to analyze these uncertainties...

Treatment of uncertainties in atmospheric chemical systems: A combined modeling and experimental approach

NASA Astrophysics Data System (ADS)

Pun, Betty Kong-Ling

1998-12-01

Uncertainty is endemic in modeling. This thesis is a two- phase program to understand the uncertainties in urban air pollution model predictions and in field data used to validate them. Part I demonstrates how to improve atmospheric models by analyzing the uncertainties in these models and using the results to guide new experimentation endeavors. Part II presents an experiment designed to characterize atmospheric fluctuations, which have significant implications towards the model validation process. A systematic study was undertaken to investigate the effects of uncertainties in the SAPRC mechanism for gas- phase chemistry in polluted atmospheres. The uncertainties of more than 500 parameters were compiled, including reaction rate constants, product coefficients, organic composition, and initial conditions. Uncertainty propagation using the Deterministic Equivalent Modeling Method (DEMM) revealed that the uncertainties in ozone predictions can be up to 45% based on these parametric uncertainties. The key parameters found to dominate the uncertainties of the predictions include photolysis rates of NO2, O3, and formaldehyde; the rate constant for nitric acid formation; and initial amounts of NOx and VOC. Similar uncertainty analysis procedures applied to two other mechanisms used in regional air quality models led to the conclusion that in the presence of parametric uncertainties, the mechanisms cannot be discriminated. Research efforts should focus on reducing parametric uncertainties in photolysis rates, reaction rate constants, and source terms. A new tunable diode laser (TDL) infrared spectrometer was designed and constructed to measure multiple pollutants simultaneously in the same ambient air parcels. The sensitivities of the one hertz measurements were 2 ppb for ozone, 1 ppb for NO, and 0.5 ppb for NO2. Meteorological data were also collected for wind, temperature, and UV intensity. The field data showed clear correlations between ozone, NO, and NO2 in the one-second time scale. Fluctuations in pollutant concentrations were found to be extremely dependent on meteorological conditions. Deposition fluxes calculated using the Eddy Correlation technique were found to be small on concrete surfaces. These high time-resolution measurements were used to develop an understanding of the variability in atmospheric measurements, which would be useful in determining the acceptable discrepancy of model and observations. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Correlation structures in short-term variabilities of stock indices and exchange rates

NASA Astrophysics Data System (ADS)

Nakamura, Tomomichi; Small, Michael

2007-09-01

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.

Development of a flood early warning system and communication with end-users: the Vipava/Vipacco case study in the KULTURisk FP7 project

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Caronna, Paolo; Ranzi, Roberto

2014-05-01

Within the framework of risk communication, the goal of an early warning system is to support the interaction between technicians and authorities (and subsequently population) as a prevention measure. The methodology proposed in the KULTURisk FP7 project aimed to build a closer collaboration between these actors, in the perspective of promoting pro-active actions to mitigate the effects of flood hazards. The transnational (Slovenia/ Italy) Soča/Isonzo case study focused on this concept of cooperation between stakeholders and hydrological forecasters. The DIMOSHONG_VIP hydrological model was calibrated for the Vipava/Vipacco River (650 km2), a tributary of the Soča/Isonzo River, on the basis of flood events occurred between 1998 and 2012. The European Centre for Medium-Range Weather Forecasts (ECMWF) provided the past meteorological forecasts, both deterministic (1 forecast) and probabilistic (51 ensemble members). The resolution of the ECMWF grid is currently about 15 km (Deterministic-DET) and 30 km (Ensemble Prediction System-EPS). A verification was conducted to validate the flood-forecast outputs of the DIMOSHONG_VIP+ECMWF early warning system. Basic descriptive statistics, like event probability, probability of a forecast occurrence and frequency bias were determined. Some performance measures were calculated, such as hit rate (probability of detection) and false alarm rate (probability of false detection). Relative Opening Characteristic (ROC) curves were generated both for deterministic and probabilistic forecasts. These analysis showed a good performance of the early warning system, in respect of the small size of the sample. A particular attention was spent to the design of flood-forecasting output charts, involving and inquiring stakeholders (Alto Adriatico River Basin Authority), hydrology specialists in the field, and common people. Graph types for both forecasted precipitation and discharge were set. Three different risk thresholds were identified ("attention", "pre-alarm" or "alert", "alarm"), with an "icon-style" representation, suitable for communication to civil protection stakeholders or the public. Aiming at showing probabilistic representations in a "user-friendly" way, we opted for the visualization of the single deterministic forecasted hydrograph together with the 5%, 25%, 50%, 75% and 95% percentiles bands of the Hydrological Ensemble Prediction System (HEPS). HEPS is generally used for 3-5 days hydrological forecasts, while the error due to incorrect initial data is comparable to the error due to the lower resolution with respect to the deterministic forecast. In the short term forecasting (12-48 hours) the HEPS-members show obviously a similar tendency; in this case, considering its higher resolution, the deterministic forecast is expected to be more effective. The plot of different forecasts in the same chart allows the use of model outputs from 4/5 days to few hours before a potential flood event. This framework was built to help a stakeholder, like a mayor, a civil protection authority, etc, in the flood control and management operations, and was designed to be included in a wider decision support system.

Low technology systems for wastewater treatment: perspectives.

PubMed

Brissaud, F

2007-01-01

Low technology systems for the treatment of wastewater are sometimes presented as remnants of the past, nowadays supposedly only meant to serve developing countries and remote rural areas. However, considering their advantages and disadvantages together with enhanced treatment requirements and recent research and technological developments, the future of these systems still appears promising. Successful applications of low technology systems require that more care is taken of their design and operation than often observed. Correlatively, more efforts should be made to decipher the treatment mechanisms and determine the related reaction parameters, so as to provide more deterministic approaches of the natural wastewater treatment systems and better predict their performance.

Mathematical biomarkers for the autonomic regulation of cardiovascular system.

PubMed

Campos, Luciana A; Pereira, Valter L; Muralikrishna, Amita; Albarwani, Sulayma; Brás, Susana; Gouveia, Sónia

2013-10-07

Heart rate and blood pressure are the most important vital signs in diagnosing disease. Both heart rate and blood pressure are characterized by a high degree of short term variability from moment to moment, medium term over the normal day and night as well as in the very long term over months to years. The study of new mathematical algorithms to evaluate the variability of these cardiovascular parameters has a high potential in the development of new methods for early detection of cardiovascular disease, to establish differential diagnosis with possible therapeutic consequences. The autonomic nervous system is a major player in the general adaptive reaction to stress and disease. The quantitative prediction of the autonomic interactions in multiple control loops pathways of cardiovascular system is directly applicable to clinical situations. Exploration of new multimodal analytical techniques for the variability of cardiovascular system may detect new approaches for deterministic parameter identification. A multimodal analysis of cardiovascular signals can be studied by evaluating their amplitudes, phases, time domain patterns, and sensitivity to imposed stimuli, i.e., drugs blocking the autonomic system. The causal effects, gains, and dynamic relationships may be studied through dynamical fuzzy logic models, such as the discrete-time model and discrete-event model. We expect an increase in accuracy of modeling and a better estimation of the heart rate and blood pressure time series, which could be of benefit for intelligent patient monitoring. We foresee that identifying quantitative mathematical biomarkers for autonomic nervous system will allow individual therapy adjustments to aim at the most favorable sympathetic-parasympathetic balance.

Mathematical biomarkers for the autonomic regulation of cardiovascular system

PubMed Central

Campos, Luciana A.; Pereira, Valter L.; Muralikrishna, Amita; Albarwani, Sulayma; Brás, Susana; Gouveia, Sónia

2013-01-01

Heart rate and blood pressure are the most important vital signs in diagnosing disease. Both heart rate and blood pressure are characterized by a high degree of short term variability from moment to moment, medium term over the normal day and night as well as in the very long term over months to years. The study of new mathematical algorithms to evaluate the variability of these cardiovascular parameters has a high potential in the development of new methods for early detection of cardiovascular disease, to establish differential diagnosis with possible therapeutic consequences. The autonomic nervous system is a major player in the general adaptive reaction to stress and disease. The quantitative prediction of the autonomic interactions in multiple control loops pathways of cardiovascular system is directly applicable to clinical situations. Exploration of new multimodal analytical techniques for the variability of cardiovascular system may detect new approaches for deterministic parameter identification. A multimodal analysis of cardiovascular signals can be studied by evaluating their amplitudes, phases, time domain patterns, and sensitivity to imposed stimuli, i.e., drugs blocking the autonomic system. The causal effects, gains, and dynamic relationships may be studied through dynamical fuzzy logic models, such as the discrete-time model and discrete-event model. We expect an increase in accuracy of modeling and a better estimation of the heart rate and blood pressure time series, which could be of benefit for intelligent patient monitoring. We foresee that identifying quantitative mathematical biomarkers for autonomic nervous system will allow individual therapy adjustments to aim at the most favorable sympathetic-parasympathetic balance. PMID:24109456

Deterministic Walks with Choice

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

Beeler, Katy E.; Berenhaut, Kenneth S.; Cooper, Joshua N.

2014-01-10

This paper studies deterministic movement over toroidal grids, integrating local information, bounded memory and choice at individual nodes. The research is motivated by recent work on deterministic random walks, and applications in multi-agent systems. Several results regarding passing tokens through toroidal grids are discussed, as well as some open questions.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

PubMed Central

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Multi-Dimensional, Mesoscopic Monte Carlo Simulations of Inhomogeneous Reaction-Drift-Diffusion Systems on Graphics-Processing Units

PubMed Central

Vigelius, Matthias; Meyer, Bernd

2012-01-01

For many biological applications, a macroscopic (deterministic) treatment of reaction-drift-diffusion systems is insufficient. Instead, one has to properly handle the stochastic nature of the problem and generate true sample paths of the underlying probability distribution. Unfortunately, stochastic algorithms are computationally expensive and, in most cases, the large number of participating particles renders the relevant parameter regimes inaccessible. In an attempt to address this problem we present a genuine stochastic, multi-dimensional algorithm that solves the inhomogeneous, non-linear, drift-diffusion problem on a mesoscopic level. Our method improves on existing implementations in being multi-dimensional and handling inhomogeneous drift and diffusion. The algorithm is well suited for an implementation on data-parallel hardware architectures such as general-purpose graphics processing units (GPUs). We integrate the method into an operator-splitting approach that decouples chemical reactions from the spatial evolution. We demonstrate the validity and applicability of our algorithm with a comprehensive suite of standard test problems that also serve to quantify the numerical accuracy of the method. We provide a freely available, fully functional GPU implementation. Integration into Inchman, a user-friendly web service, that allows researchers to perform parallel simulations of reaction-drift-diffusion systems on GPU clusters is underway. PMID:22506001

Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regression.

PubMed

Horst, Fabian; Eekhoff, Alexander; Newell, Karl M; Schöllhorn, Wolfgang I

2017-01-01

Traditionally, gait analysis has been centered on the idea of average behavior and normality. On one hand, clinical diagnoses and therapeutic interventions typically assume that average gait patterns remain constant over time. On the other hand, it is well known that all our movements are accompanied by a certain amount of variability, which does not allow us to make two identical steps. The purpose of this study was to examine changes in the intra-individual gait patterns across different time-scales (i.e., tens-of-mins, tens-of-hours). Nine healthy subjects performed 15 gait trials at a self-selected speed on 6 sessions within one day (duration between two subsequent sessions from 10 to 90 mins). For each trial, time-continuous ground reaction forces and lower body joint angles were measured. A supervised learning model using a kernel-based discriminant regression was applied for classifying sessions within individual gait patterns. Discernable characteristics of intra-individual gait patterns could be distinguished between repeated sessions by classification rates of 67.8 ± 8.8% and 86.3 ± 7.9% for the six-session-classification of ground reaction forces and lower body joint angles, respectively. Furthermore, the one-on-one-classification showed that increasing classification rates go along with increasing time durations between two sessions and indicate that changes of gait patterns appear at different time-scales. Discernable characteristics between repeated sessions indicate continuous intrinsic changes in intra-individual gait patterns and suggest a predominant role of deterministic processes in human motor control and learning. Natural changes of gait patterns without any externally induced injury or intervention may reflect continuous adaptations of the motor system over several time-scales. Accordingly, the modelling of walking by means of average gait patterns that are assumed to be near constant over time needs to be reconsidered in the context of these findings, especially towards more individualized and situational diagnoses and therapy.

Particle-based simulations of polarity establishment reveal stochastic promotion of Turing pattern formation

PubMed Central

Ramirez, Samuel A.; Elston, Timothy C.

2018-01-01

Polarity establishment, the spontaneous generation of asymmetric molecular distributions, is a crucial component of many cellular functions. Saccharomyces cerevisiae (yeast) undergoes directed growth during budding and mating, and is an ideal model organism for studying polarization. In yeast and many other cell types, the Rho GTPase Cdc42 is the key molecular player in polarity establishment. During yeast polarization, multiple patches of Cdc42 initially form, then resolve into a single front. Because polarization relies on strong positive feedback, it is likely that the amplification of molecular-level fluctuations underlies the generation of multiple nascent patches. In the absence of spatial cues, these fluctuations may be key to driving polarization. Here we used particle-based simulations to investigate the role of stochastic effects in a Turing-type model of yeast polarity establishment. In the model, reactions take place either between two molecules on the membrane, or between a cytosolic and a membrane-bound molecule. Thus, we developed a computational platform that explicitly simulates molecules at and near the cell membrane, and implicitly handles molecules away from the membrane. To evaluate stochastic effects, we compared particle simulations to deterministic reaction-diffusion equation simulations. Defining macroscopic rate constants that are consistent with the microscopic parameters for this system is challenging, because diffusion occurs in two dimensions and particles exchange between the membrane and cytoplasm. We address this problem by empirically estimating macroscopic rate constants from appropriately designed particle-based simulations. Ultimately, we find that stochastic fluctuations speed polarity establishment and permit polarization in parameter regions predicted to be Turing stable. These effects can operate at Cdc42 abundances expected of yeast cells, and promote polarization on timescales consistent with experimental results. To our knowledge, our work represents the first particle-based simulations of a model for yeast polarization that is based on a Turing mechanism. PMID:29529021

Comparison of three controllers applied to helicopter vibration

NASA Technical Reports Server (NTRS)

Leyland, Jane A.

1992-01-01

A comparison was made of the applicability and suitability of the deterministic controller, the cautious controller, and the dual controller for the reduction of helicopter vibration by using higher harmonic blade pitch control. A randomly generated linear plant model was assumed and the performance index was defined to be a quadratic output metric of this linear plant. A computer code, designed to check out and evaluate these controllers, was implemented and used to accomplish this comparison. The effects of random measurement noise, the initial estimate of the plant matrix, and the plant matrix propagation rate were determined for each of the controllers. With few exceptions, the deterministic controller yielded the greatest vibration reduction (as characterized by the quadratic output metric) and operated with the greatest reliability. Theoretical limitations of these controllers were defined and appropriate candidate alternative methods, including one method particularly suitable to the cockpit, were identified.

On Transform Domain Communication Systems under Spectrum Sensing Mismatch: A Deterministic Analysis.

PubMed

Jin, Chuanxue; Hu, Su; Huang, Yixuan; Luo, Qu; Huang, Dan; Li, Yi; Gao, Yuan; Cheng, Shaochi

2017-07-08

Towards the era of mobile Internet and the Internet of Things (IoT), numerous sensors and devices are being introduced and interconnected. To support such an amount of data traffic, traditional wireless communication technologies are facing challenges both in terms of the increasing shortage of spectrum resources and massive multiple access. The transform-domain communication system (TDCS) is considered as an alternative multiple access system, where 5G and mobile IoT are mainly focused. However, previous studies about TDCS are under the assumption that the transceiver has the global spectrum information, without the consideration of spectrum sensing mismatch (SSM). In this paper, we present the deterministic analysis of TDCS systems under arbitrary given spectrum sensing scenarios, especially the influence of the SSM pattern to the signal to noise ratio (SNR) performance. Simulation results show that arbitrary SSM pattern can lead to inferior bit error rate (BER) performance.

High-throughput deterministic single-cell encapsulation and droplet pairing, fusion, and shrinkage in a single microfluidic device.

PubMed

Schoeman, Rogier M; Kemna, Evelien W M; Wolbers, Floor; van den Berg, Albert

2014-02-01

In this article, we present a microfluidic device capable of successive high-yield single-cell encapsulation in droplets, with additional droplet pairing, fusion, and shrinkage. Deterministic single-cell encapsulation is realized using Dean-coupled inertial ordering of cells in a Yin-Yang-shaped curved microchannel using a double T-junction, with a frequency over 2000 Hz, followed by controlled droplet pairing with a 100% success rate. Subsequently, droplet fusion is realized using electrical actuation resulting in electro-coalescence of two droplets, each containing a single HL60 cell, with 95% efficiency. Finally, volume reduction of the fused droplet up to 75% is achieved by a triple pitchfork structure. This droplet volume reduction is necessary to obtain close cell-cell membrane contact necessary for final cell electrofusion, leading to hybridoma formation, which is the ultimate aim of this research. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Real-time flood forecasting

USGS Publications Warehouse

Lai, C.; Tsay, T.-K.; Chien, C.-H.; Wu, I.-L.

2009-01-01

Researchers at the Hydroinformatic Research and Development Team (HIRDT) of the National Taiwan University undertook a project to create a real time flood forecasting model, with an aim to predict the current in the Tamsui River Basin. The model was designed based on deterministic approach with mathematic modeling of complex phenomenon, and specific parameter values operated to produce a discrete result. The project also devised a rainfall-stage model that relates the rate of rainfall upland directly to the change of the state of river, and is further related to another typhoon-rainfall model. The geographic information system (GIS) data, based on precise contour model of the terrain, estimate the regions that were perilous to flooding. The HIRDT, in response to the project's progress, also devoted their application of a deterministic model to unsteady flow of thermodynamics to help predict river authorities issue timely warnings and take other emergency measures.

Detection of "noisy" chaos in a time series

NASA Technical Reports Server (NTRS)

Chon, K. H.; Kanters, J. K.; Cohen, R. J.; Holstein-Rathlou, N. H.

1997-01-01

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Phonon arithmetic in a trapped ion system

NASA Astrophysics Data System (ADS)

Um, Mark; Zhang, Junhua; Lv, Dingshun; Lu, Yao; An, Shuoming; Zhang, Jing-Ning; Nha, Hyunchul; Kim, M. S.; Kim, Kihwan

2016-04-01

Single-quantum level operations are important tools to manipulate a quantum state. Annihilation or creation of single particles translates a quantum state to another by adding or subtracting a particle, depending on how many are already in the given state. The operations are probabilistic and the success rate has yet been low in their experimental realization. Here we experimentally demonstrate (near) deterministic addition and subtraction of a bosonic particle, in particular a phonon of ionic motion in a harmonic potential. We realize the operations by coupling phonons to an auxiliary two-level system and applying transitionless adiabatic passage. We show handy repetition of the operations on various initial states and demonstrate by the reconstruction of the density matrices that the operations preserve coherences. We observe the transformation of a classical state to a highly non-classical one and a Gaussian state to a non-Gaussian one by applying a sequence of operations deterministically.

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

Pest persistence and eradication conditions in a deterministic model for sterile insect release.

PubMed

Gordillo, Luis F

2015-01-01

The release of sterile insects is an environment friendly pest control method used in integrated pest management programmes. Difference or differential equations based on Knipling's model often provide satisfactory qualitative descriptions of pest populations subject to sterile release at relatively high densities with large mating encounter rates, but fail otherwise. In this paper, I derive and explore numerically deterministic population models that include sterile release together with scarce mating encounters in the particular case of species with long lifespan and multiple matings. The differential equations account separately the effects of mating failure due to sterile male release and the frequency of mating encounters. When insects spatial spread is incorporated through diffusion terms, computations reveal the possibility of steady pest persistence in finite size patches. In the presence of density dependence regulation, it is observed that sterile release might contribute to induce sudden suppression of the pest population.

Quantum key distribution with delayed privacy amplification and its application to the security proof of a two-way deterministic protocol

NASA Astrophysics Data System (ADS)

Fung, Chi-Hang Fred; Ma, Xiongfeng; Chau, H. F.; Cai, Qing-Yu

2012-03-01

Privacy amplification (PA) is an essential postprocessing step in quantum key distribution (QKD) for removing any information an eavesdropper may have on the final secret key. In this paper, we consider delaying PA of the final key after its use in one-time pad encryption and prove its security. We prove that the security and the key generation rate are not affected by delaying PA. Delaying PA has two applications: it serves as a tool for significantly simplifying the security proof of QKD with a two-way quantum channel, and also it is useful in QKD networks with trusted relays. To illustrate the power of the delayed PA idea, we use it to prove the security of a qubit-based two-way deterministic QKD protocol which uses four states and four encoding operations.

Deterministic secure quantum communication using a single d-level system.

PubMed

Jiang, Dong; Chen, Yuanyuan; Gu, Xuemei; Xie, Ling; Chen, Lijun

2017-03-22

Deterministic secure quantum communication (DSQC) can transmit secret messages between two parties without first generating a shared secret key. Compared with quantum key distribution (QKD), DSQC avoids the waste of qubits arising from basis reconciliation and thus reaches higher efficiency. In this paper, based on data block transmission and order rearrangement technologies, we propose a DSQC protocol. It utilizes a set of single d-level systems as message carriers, which are used to directly encode the secret message in one communication process. Theoretical analysis shows that these employed technologies guarantee the security, and the use of a higher dimensional quantum system makes our protocol achieve higher security and efficiency. Since only quantum memory is required for implementation, our protocol is feasible with current technologies. Furthermore, Trojan horse attack (THA) is taken into account in our protocol. We give a THA model and show that THA significantly increases the multi-photon rate and can thus be detected.

Tapered fiber coupling of single photons emitted by a deterministically positioned single nitrogen vacancy center

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

Liebermeister, Lars, E-mail: lars.liebermeister@physik.uni-muenchen.de; Petersen, Fabian; Münchow, Asmus v.

2014-01-20

A diamond nano-crystal hosting a single nitrogen vacancy (NV) center is optically selected with a confocal scanning microscope and positioned deterministically onto the subwavelength-diameter waist of a tapered optical fiber (TOF) with the help of an atomic force microscope. Based on this nano-manipulation technique, we experimentally demonstrate the evanescent coupling of single fluorescence photons emitted by a single NV-center to the guided mode of the TOF. By comparing photon count rates of the fiber-guided and the free-space modes and with the help of numerical finite-difference time domain simulations, we determine a lower and upper bound for the coupling efficiency ofmore » (9.5 ± 0.6)% and (10.4 ± 0.7)%, respectively. Our results are a promising starting point for future integration of single photon sources into photonic quantum networks and applications in quantum information science.« less

On Transform Domain Communication Systems under Spectrum Sensing Mismatch: A Deterministic Analysis

PubMed Central

Jin, Chuanxue; Hu, Su; Huang, Yixuan; Luo, Qu; Huang, Dan; Li, Yi; Cheng, Shaochi

2017-01-01

Towards the era of mobile Internet and the Internet of Things (IoT), numerous sensors and devices are being introduced and interconnected. To support such an amount of data traffic, traditional wireless communication technologies are facing challenges both in terms of the increasing shortage of spectrum resources and massive multiple access. The transform-domain communication system (TDCS) is considered as an alternative multiple access system, where 5G and mobile IoT are mainly focused. However, previous studies about TDCS are under the assumption that the transceiver has the global spectrum information, without the consideration of spectrum sensing mismatch (SSM). In this paper, we present the deterministic analysis of TDCS systems under arbitrary given spectrum sensing scenarios, especially the influence of the SSM pattern to the signal to noise ratio (SNR) performance. Simulation results show that arbitrary SSM pattern can lead to inferior bit error rate (BER) performance. PMID:28698477

Nanotransfer and nanoreplication using deterministically grown sacrificial nanotemplates

DOEpatents

Melechko, Anatoli V [Oak Ridge, TN; McKnight, Timothy E. , Guillorn, Michael A.; Ilic, Bojan [Ithaca, NY; Merkulov, Vladimir I [Knoxville, TN; Doktycz, Mitchel J [Knoxville, TN; Lowndes, Douglas H [Knoxville, TN; Simpson, Michael L [Knoxville, TN

2011-05-17

Methods, manufactures, machines and compositions are described for nanotransfer and nanoreplication using deterministically grown sacrificial nanotemplates. A method includes depositing a catalyst particle on a surface of a substrate to define a deterministically located position; growing an aligned elongated nanostructure on the substrate, an end of the aligned elongated nanostructure coupled to the substrate at the deterministically located position; coating the aligned elongated nanostructure with a conduit material; removing a portion of the conduit material to expose the catalyst particle; removing the catalyst particle; and removing the elongated nanostructure to define a nanoconduit.

Human brain detects short-time nonlinear predictability in the temporal fine structure of deterministic chaotic sounds

NASA Astrophysics Data System (ADS)

Itoh, Kosuke; Nakada, Tsutomu

2013-04-01

Deterministic nonlinear dynamical processes are ubiquitous in nature. Chaotic sounds generated by such processes may appear irregular and random in waveform, but these sounds are mathematically distinguished from random stochastic sounds in that they contain deterministic short-time predictability in their temporal fine structures. We show that the human brain distinguishes deterministic chaotic sounds from spectrally matched stochastic sounds in neural processing and perception. Deterministic chaotic sounds, even without being attended to, elicited greater cerebral cortical responses than the surrogate control sounds after about 150 ms in latency after sound onset. Listeners also clearly discriminated these sounds in perception. The results support the hypothesis that the human auditory system is sensitive to the subtle short-time predictability embedded in the temporal fine structure of sounds.

Evidence for deterministic chaos in aperiodic oscillations of acute lymphoblastic leukemia cells in long-term culture

NASA Astrophysics Data System (ADS)

Lambrou, George I.; Chatziioannou, Aristotelis; Vlahopoulos, Spiros; Moschovi, Maria; Chrousos, George P.

Biological systems are dynamic and possess properties that depend on two key elements: initial conditions and the response of the system over time. Conceptualizing this on tumor models will influence conclusions drawn with regard to disease initiation and progression. Alterations in initial conditions dynamically reshape the properties of proliferating tumor cells. The present work aims to test the hypothesis of Wolfrom et al., that proliferation shows evidence for deterministic chaos in a manner such that subtle differences in the initial conditions give rise to non-linear response behavior of the system. Their hypothesis, tested on adherent Fao rat hepatoma cells, provides evidence that these cells manifest aperiodic oscillations in their proliferation rate. We have tested this hypothesis with some modifications to the proposed experimental setup. We have used the acute lymphoblastic leukemia cell line CCRF-CEM, as it provides an excellent substrate for modeling proliferation dynamics. Measurements were taken at time points varying from 24h to 48h, extending the assayed populations beyond that of previous published reports that dealt with the complex dynamic behavior of animal cell populations. We conducted flow cytometry studies to examine the apoptotic and necrotic rate of the system, as well as DNA content changes of the cells over time. The cells exhibited a proliferation rate of nonlinear nature, as this rate presented oscillatory behavior. The obtained data have been fit in known models of growth, such as logistic and Gompertzian growth.

A real time sorting algorithm to time sort any deterministic time disordered data stream

NASA Astrophysics Data System (ADS)

Saini, J.; Mandal, S.; Chakrabarti, A.; Chattopadhyay, S.

2017-12-01

In new generation high intensity high energy physics experiments, millions of free streaming high rate data sources are to be readout. Free streaming data with associated time-stamp can only be controlled by thresholds as there is no trigger information available for the readout. Therefore, these readouts are prone to collect large amount of noise and unwanted data. For this reason, these experiments can have output data rate of several orders of magnitude higher than the useful signal data rate. It is therefore necessary to perform online processing of the data to extract useful information from the full data set. Without trigger information, pre-processing on the free streaming data can only be done with time based correlation among the data set. Multiple data sources have different path delays and bandwidth utilizations and therefore the unsorted merged data requires significant computational efforts for real time manifestation of sorting before analysis. Present work reports a new high speed scalable data stream sorting algorithm with its architectural design, verified through Field programmable Gate Array (FPGA) based hardware simulation. Realistic time based simulated data likely to be collected in an high energy physics experiment have been used to study the performance of the algorithm. The proposed algorithm uses parallel read-write blocks with added memory management and zero suppression features to make it efficient for high rate data-streams. This algorithm is best suited for online data streams with deterministic time disorder/unsorting on FPGA like hardware.

Entrepreneurs, chance, and the deterministic concentration of wealth.

PubMed

Fargione, Joseph E; Lehman, Clarence; Polasky, Stephen

2011-01-01

In many economies, wealth is strikingly concentrated. Entrepreneurs--individuals with ownership in for-profit enterprises--comprise a large portion of the wealthiest individuals, and their behavior may help explain patterns in the national distribution of wealth. Entrepreneurs are less diversified and more heavily invested in their own companies than is commonly assumed in economic models. We present an intentionally simplified individual-based model of wealth generation among entrepreneurs to assess the role of chance and determinism in the distribution of wealth. We demonstrate that chance alone, combined with the deterministic effects of compounding returns, can lead to unlimited concentration of wealth, such that the percentage of all wealth owned by a few entrepreneurs eventually approaches 100%. Specifically, concentration of wealth results when the rate of return on investment varies by entrepreneur and by time. This result is robust to inclusion of realities such as differing skill among entrepreneurs. The most likely overall growth rate of the economy decreases as businesses become less diverse, suggesting that high concentrations of wealth may adversely affect a country's economic growth. We show that a tax on large inherited fortunes, applied to a small portion of the most fortunate in the population, can efficiently arrest the concentration of wealth at intermediate levels.

Uncertainty analysis on reactivity and discharged inventory for a pressurized water reactor fuel assembly due to {sup 235,238}U nuclear data uncertainties

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

Da Cruz, D. F.; Rochman, D.; Koning, A. J.

2012-07-01

This paper discusses the uncertainty analysis on reactivity and inventory for a typical PWR fuel element as a result of uncertainties in {sup 235,238}U nuclear data. A typical Westinghouse 3-loop fuel assembly fuelled with UO{sub 2} fuel with 4.8% enrichment has been selected. The Total Monte-Carlo method has been applied using the deterministic transport code DRAGON. This code allows the generation of the few-groups nuclear data libraries by directly using data contained in the nuclear data evaluation files. The nuclear data used in this study is from the JEFF3.1 evaluation, and the nuclear data files for {sup 238}U and {supmore » 235}U (randomized for the generation of the various DRAGON libraries) are taken from the nuclear data library TENDL. The total uncertainty (obtained by randomizing all {sup 238}U and {sup 235}U nuclear data in the ENDF files) on the reactor parameters has been split into different components (different nuclear reaction channels). Results show that the TMC method in combination with a deterministic transport code constitutes a powerful tool for performing uncertainty and sensitivity analysis of reactor physics parameters. (authors)« less

Deterministic and Stochastic Analysis of a Prey-Dependent Predator-Prey System

ERIC Educational Resources Information Center

Maiti, Alakes; Samanta, G. P.

2005-01-01

This paper reports on studies of the deterministic and stochastic behaviours of a predator-prey system with prey-dependent response function. The first part of the paper deals with the deterministic analysis of uniform boundedness, permanence, stability and bifurcation. In the second part the reproductive and mortality factors of the prey and…

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas.

PubMed

Morota, Gota

2017-12-20

Deterministic formulas for the accuracy of genomic predictions highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation. Visualizing such deterministic formulas in an interactive manner may lead to a better understanding of how genetic factors control prediction accuracy. The software to simulate deterministic formulas for genomic prediction accuracy was implemented in R and encapsulated as a web-based Shiny application. Shiny genomic prediction accuracy simulator (ShinyGPAS) simulates various deterministic formulas and delivers dynamic scatter plots of prediction accuracy versus genetic factors impacting prediction accuracy, while requiring only mouse navigation in a web browser. ShinyGPAS is available at: https://chikudaisei.shinyapps.io/shinygpas/ . ShinyGPAS is a shiny-based interactive genomic prediction accuracy simulator using deterministic formulas. It can be used for interactively exploring potential factors that influence prediction accuracy in genome-enabled prediction, simulating achievable prediction accuracy prior to genotyping individuals, or supporting in-class teaching. ShinyGPAS is open source software and it is hosted online as a freely available web-based resource with an intuitive graphical user interface.

Atomic layer deposition of metal sulfide materials

DOE PAGES

Dasgupta, Neil P.; Meng, Xiangbo; Elam, Jeffrey W.; ...

2015-01-12

The field of nanoscience is delivering increasingly intricate yet elegant geometric structures incorporating an ever-expanding palette of materials. Atomic layer deposition (ALD) is a powerful driver of this field, providing exceptionally conformal coatings spanning the periodic table and atomic-scale precision independent of substrate geometry. This versatility is intrinsic to ALD and results from sequential and self-limiting surface reactions. This characteristic facilitates digital synthesis, in which the film grows linearly with the number of reaction cycles. While the majority of ALD processes identified to date produce metal oxides, novel applications in areas such as energy storage, catalysis, and nanophotonics are motivatingmore » interest in sulfide materials. Recent progress in ALD of sulfides has expanded the diversity of accessible materials as well as a more complete understanding of the unique chalcogenide surface chemistry. ALD of sulfide materials typically uses metalorganic precursors and hydrogen sulfide (H 2S). As in oxide ALD, the precursor chemistry is critical to controlling both the film growth and properties including roughness, crystallinity, and impurity levels. By modification of the precursor sequence, multicomponent sulfides have been deposited, although challenges remain because of the higher propensity for cation exchange reactions, greater diffusion rates, and unintentional annealing of this more labile class of materials. A deeper understanding of these surface chemical reactions has been achieved through a combination of in situ studies and quantum-chemical calculations. As this understanding matures, so does our ability to deterministically tailor film properties to new applications and more sophisticated devices. This Account highlights the attributes of ALD chemistry that are unique to metal sulfides and surveys recent applications of these materials in photovoltaics, energy storage, and photonics. Within each application space, the benefits and challenges of novel ALD processes are emphasized and common trends are summarized. We conclude with a perspective on potential future directions for metal chalcogenide ALD as well as untapped opportunities. As a result, we consider challenges that must be addressed prior to implementing ALD metal sulfides into future device architectures.« less

A numerical study of mixing in stationary, nonpremixed, turbulent reacting flows

NASA Astrophysics Data System (ADS)

Overholt, Matthew Ryan

1998-10-01

In this work a detailed numerical study is made of a statistically-stationary, non-premixed, turbulent reacting model flow known as Periodic Reaction Zones. The mixture fraction-progress variable approach is used, with a mean gradient in the mixture fraction and a model, single-step, reversible, finite-rate thermochemistry, yielding both stationary and local extinction behavior. The passive scalar is studied first, using a statistical forcing scheme to achieve stationarity of the velocity field. Multiple independent direct numerical simulations (DNS) are performed for a wide range of Reynolds numbers with a number of results including a bilinear model for scalar mixing jointly conditioned on the scalar and x2-component of velocity, Gaussian scalar probability density function tails which were anticipated to be exponential, and the quantification of the dissipation of scalar flux. A new deterministic forcing scheme for DNS is then developed which yields reduced fluctuations in many quantities and a more natural evolution of the velocity fields. This forcing method is used for the final portion of this work. DNS results for Periodic Reaction Zones are compared with the Conditional Moment Closure (CMC) model, the Quasi-Equilibrium Distributed Reaction (QEDR) model, and full probability density function (PDF) simulations using the Euclidean Minimum Spanning Tree (EMST) and the Interaction by Exchange with the Mean (IEM) mixing models. It is shown that CMC and QEDR results based on the local scalar dissipation match DNS wherever local extinction is not present. However, due to the large spatial variations of scalar dissipation, and hence local Damkohler number, local extinction is present even when the global Damkohler number is twenty-five times the critical value for extinction. Finally, in the PDF simulations the EMST mixing model closely reproduces CMC and DNS results when local extinction is not present, whereas the IEM model results in large error.

Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes

PubMed Central

2018-01-01

Single-cell experiments show that gene expression is stochastic and bursty, a feature that can emerge from slow switching between promoter states with different activities. In addition to slow chromatin and/or DNA looping dynamics, one source of long-lived promoter states is the slow binding and unbinding kinetics of transcription factors to promoters, i.e. the non-adiabatic binding regime. Here, we introduce a simple analytical framework, known as a piecewise deterministic Markov process (PDMP), that accurately describes the stochastic dynamics of gene expression in the non-adiabatic regime. We illustrate the utility of the PDMP on a non-trivial dynamical system by analysing the properties of a titration-based oscillator in the non-adiabatic limit. We first show how to transform the underlying chemical master equation into a PDMP where the slow transitions between promoter states are stochastic, but whose rates depend upon the faster deterministic dynamics of the transcription factors regulated by these promoters. We show that the PDMP accurately describes the observed periods of stochastic cycles in activator and repressor-based titration oscillators. We then generalize our PDMP analysis to more complicated versions of titration-based oscillators to explain how multiple binding sites lengthen the period and improve coherence. Last, we show how noise-induced oscillation previously observed in a titration-based oscillator arises from non-adiabatic and discrete binding events at the promoter site. PMID:29386401

Propagation of neutron-reaction uncertainties through multi-physics models of novel LWR's

NASA Astrophysics Data System (ADS)

Hernandez-Solis, Augusto; Sjöstrand, Henrik; Helgesson, Petter

2017-09-01

The novel design of the renewable boiling water reactor (RBWR) allows a breeding ratio greater than unity and thus, it aims at providing for a self-sustained fuel cycle. The neutron reactions that compose the different microscopic cross-sections and angular distributions are uncertain, so when they are employed in the determination of the spatial distribution of the neutron flux in a nuclear reactor, a methodology should be employed to account for these associated uncertainties. In this work, the Total Monte Carlo (TMC) method is used to propagate the different neutron-reactions (as well as angular distributions) covariances that are part of the TENDL-2014 nuclear data (ND) library. The main objective is to propagate them through coupled neutronic and thermal-hydraulic models in order to assess the uncertainty of important safety parameters related to multi-physics, such as peak cladding temperature along the axial direction of an RBWR fuel assembly. The objective of this study is to quantify the impact that ND covariances of important nuclides such as U-235, U-238, Pu-239 and the thermal scattering of hydrogen in H2O have in the deterministic safety analysis of novel nuclear reactors designs.

Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods☆

PubMed Central

Bucci, Monica; Mandelli, Maria Luisa; Berman, Jeffrey I.; Amirbekian, Bagrat; Nguyen, Christopher; Berger, Mitchel S.; Henry, Roland G.

2013-01-01

Introduction Diffusion MRI tractography has been increasingly used to delineate white matter pathways in vivo for which the leading clinical application is presurgical mapping of eloquent regions. However, there is rare opportunity to quantify the accuracy or sensitivity of these approaches to delineate white matter fiber pathways in vivo due to the lack of a gold standard. Intraoperative electrical stimulation (IES) provides a gold standard for the location and existence of functional motor pathways that can be used to determine the accuracy and sensitivity of fiber tracking algorithms. In this study we used intraoperative stimulation from brain tumor patients as a gold standard to estimate the sensitivity and accuracy of diffusion tensor MRI (DTI) and q-ball models of diffusion with deterministic and probabilistic fiber tracking algorithms for delineation of motor pathways. Methods We used preoperative high angular resolution diffusion MRI (HARDI) data (55 directions, b = 2000 s/mm2) acquired in a clinically feasible time frame from 12 patients who underwent a craniotomy for resection of a cerebral glioma. The corticospinal fiber tracts were delineated with DTI and q-ball models using deterministic and probabilistic algorithms. We used cortical and white matter IES sites as a gold standard for the presence and location of functional motor pathways. Sensitivity was defined as the true positive rate of delineating fiber pathways based on cortical IES stimulation sites. For accuracy and precision of the course of the fiber tracts, we measured the distance between the subcortical stimulation sites and the tractography result. Positive predictive rate of the delineated tracts was assessed by comparison of subcortical IES motor function (upper extremity, lower extremity, face) with the connection of the tractography pathway in the motor cortex. Results We obtained 21 cortical and 8 subcortical IES sites from intraoperative mapping of motor pathways. Probabilistic q-ball had the best sensitivity (79%) as determined from cortical IES compared to deterministic q-ball (50%), probabilistic DTI (36%), and deterministic DTI (10%). The sensitivity using the q-ball algorithm (65%) was significantly higher than using DTI (23%) (p < 0.001) and the probabilistic algorithms (58%) were more sensitive than deterministic approaches (30%) (p = 0.003). Probabilistic q-ball fiber tracks had the smallest offset to the subcortical stimulation sites. The offsets between diffusion fiber tracks and subcortical IES sites were increased significantly for those cases where the diffusion fiber tracks were visibly thinner than expected. There was perfect concordance between the subcortical IES function (e.g. hand stimulation) and the cortical connection of the nearest diffusion fiber track (e.g. upper extremity cortex). Discussion This study highlights the tremendous utility of intraoperative stimulation sites to provide a gold standard from which to evaluate diffusion MRI fiber tracking methods and has provided an object standard for evaluation of different diffusion models and approaches to fiber tracking. The probabilistic q-ball fiber tractography was significantly better than DTI methods in terms of sensitivity and accuracy of the course through the white matter. The commonly used DTI fiber tracking approach was shown to have very poor sensitivity (as low as 10% for deterministic DTI fiber tracking) for delineation of the lateral aspects of the corticospinal tract in our study. Effects of the tumor/edema resulted in significantly larger offsets between the subcortical IES and the preoperative fiber tracks. The provided data show that probabilistic HARDI tractography is the most objective and reproducible analysis but given the small sample and number of stimulation points a generalization about our results should be given with caution. Indeed our results inform the capabilities of preoperative diffusion fiber tracking and indicate that such data should be used carefully when making pre-surgical and intra-operative management decisions. PMID:24273719

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

Yang, Y M; Bush, K; Han, B

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) methodmore » that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.« less

RAINIER: A simulation tool for distributions of excited nuclear states and cascade fluctuations

DOE PAGES

Kirsch, L. E.; Bernstein, L. A.

2018-03-04

In this paper, a new code has been developed named RAINIER that simulates the γ-ray decay of discrete and quasi-continuum nuclear levels for a user-specified range of energy, angular momentum, and parity including a realistic treatment of level spacing and transition width fluctuations. A similar program, DICEBOX, uses the Monte Carlo method to simulate level and width fluctuations but is restricted in its initial level population algorithm. On the other hand, modern reaction codes such as TALYS and EMPIRE populate a wide range of states in the residual nucleus prior to γ-ray decay, but do not go beyond the usemore » of deterministic functions and therefore neglect cascade fluctuations. This combination of capabilities allows RAINIER to be used to determine quasi-continuum properties through comparison with experimental data. Finally, several examples are given that demonstrate how cascade fluctuations influence experimental high-resolution γ-ray spectra from reactions that populate a wide range of initial states.« less

RAINIER: A simulation tool for distributions of excited nuclear states and cascade fluctuations

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

Kirsch, L. E.; Bernstein, L. A.

In this paper, a new code has been developed named RAINIER that simulates the γ-ray decay of discrete and quasi-continuum nuclear levels for a user-specified range of energy, angular momentum, and parity including a realistic treatment of level spacing and transition width fluctuations. A similar program, DICEBOX, uses the Monte Carlo method to simulate level and width fluctuations but is restricted in its initial level population algorithm. On the other hand, modern reaction codes such as TALYS and EMPIRE populate a wide range of states in the residual nucleus prior to γ-ray decay, but do not go beyond the usemore » of deterministic functions and therefore neglect cascade fluctuations. This combination of capabilities allows RAINIER to be used to determine quasi-continuum properties through comparison with experimental data. Finally, several examples are given that demonstrate how cascade fluctuations influence experimental high-resolution γ-ray spectra from reactions that populate a wide range of initial states.« less

Noise induced oscillations and coherence resonance in a generic model of the nonisothermal chemical oscillator

PubMed Central

Simakov, David S. A.; Pérez-Mercader, Juan

2013-01-01

Oscillating chemical reactions are common in biological systems and they also occur in artificial non-biological systems. Generally, these reactions are subject to random fluctuations in environmental conditions which translate into fluctuations in the values of physical variables, for example, temperature. We formulate a mathematical model for a nonisothermal minimal chemical oscillator containing a single negative feedback loop and study numerically the effects of stochastic fluctuations in temperature in the absence of any deterministic limit cycle or periodic forcing. We show that noise in temperature can induce sustained limit cycle oscillations with a relatively narrow frequency distribution and some characteristic frequency. These properties differ significantly depending on the noise correlation. Here, we have explored white and colored (correlated) noise. A plot of the characteristic frequency of the noise induced oscillations as a function of the correlation exponent shows a maximum, therefore indicating the existence of autonomous stochastic resonance, i.e. coherence resonance. PMID:23929212

Computer program for prediction of capture maneuver probability for an on-off reaction controlled upper stage

NASA Technical Reports Server (NTRS)

Knauber, R. N.

1982-01-01

A FORTRAN coded computer program which computes the capture transient of a launch vehicle upper stage at the ignition and/or separation event is presented. It is for a single degree-of-freedom on-off reaction jet attitude control system. The Monte Carlo method is used to determine the statistical value of key parameters at the outcome of the event. Aerodynamic and booster induced disturbances, vehicle and control system characteristics, and initial conditions are treated as random variables. By appropriate selection of input data pitch, yaw and roll axes can be analyzed. Transient response of a single deterministic case can be computed. The program is currently set up on a CDC CYBER 175 computer system but is compatible with ANSI FORTRAN computer language. This routine has been used over the past fifteen (15) years for the SCOUT Launch Vehicle and has been run on RECOMP III, IBM 7090, IBM 360/370, CDC6600 and CDC CYBER 175 computers with little modification.

Definitions of Complexity are Notoriously Difficult

NASA Astrophysics Data System (ADS)

Schuster, Peter

Definitions of complexity are notoriously difficult if not impossible at all. A good working hypothesis might be: Everything is complex that is not simple. This is precisely the way in which we define nonlinear behavior. Things appear complex for different reasons: i) Complexity may result from lack of insight, ii) complexity may result from lack of methods, and (iii) complexity may be inherent to the system. The best known example for i) is celestial mechanics: The highly complex Pythagorean epicycles become obsolete by the introduction of Newton's law of universal gravitation. To give an example for ii), pattern formation and deterministic chaos became not really understandable before extensive computer simulations became possible. Cellular metabolism may serve as an example for iii) and is caused by the enormous complexity of biochemical reaction networks with up to one hundred individual reaction fluxes. Nevertheless, only few fluxes are dominant in the sense that using Pareto optimal values for them provides near optimal values for all the others...

The past, present and future of cyber-physical systems: a focus on models.

PubMed

Lee, Edward A

2015-02-26

This paper is about better engineering of cyber-physical systems (CPSs) through better models. Deterministic models have historically proven extremely useful and arguably form the kingpin of the industrial revolution and the digital and information technology revolutions. Key deterministic models that have proven successful include differential equations, synchronous digital logic and single-threaded imperative programs. Cyber-physical systems, however, combine these models in such a way that determinism is not preserved. Two projects show that deterministic CPS models with faithful physical realizations are possible and practical. The first project is PRET, which shows that the timing precision of synchronous digital logic can be practically made available at the software level of abstraction. The second project is Ptides (programming temporally-integrated distributed embedded systems), which shows that deterministic models for distributed cyber-physical systems have practical faithful realizations. These projects are existence proofs that deterministic CPS models are possible and practical.

The Past, Present and Future of Cyber-Physical Systems: A Focus on Models

PubMed Central

Lee, Edward A.

2015-01-01

This paper is about better engineering of cyber-physical systems (CPSs) through better models. Deterministic models have historically proven extremely useful and arguably form the kingpin of the industrial revolution and the digital and information technology revolutions. Key deterministic models that have proven successful include differential equations, synchronous digital logic and single-threaded imperative programs. Cyber-physical systems, however, combine these models in such a way that determinism is not preserved. Two projects show that deterministic CPS models with faithful physical realizations are possible and practical. The first project is PRET, which shows that the timing precision of synchronous digital logic can be practically made available at the software level of abstraction. The second project is Ptides (programming temporally-integrated distributed embedded systems), which shows that deterministic models for distributed cyber-physical systems have practical faithful realizations. These projects are existence proofs that deterministic CPS models are possible and practical. PMID:25730486

Robust High Data Rate MIMO Underwater Acoustic Communications

DTIC Science & Technology

2011-09-30

We solved it via exploiting FFTs. The extended CAN algorithm is referred to as periodic CAN ( PeCAN ). Unlike most existing sequence construction...methods which are algebraic and deterministic in nature, we start the iteration of PeCAN from random phase initializations and then proceed to...covert UAC applications. We will use PeCAN sequences for more in-water experimentations to demonstrate their effectiveness. Temporal Resampling: In

Economic analysis of interventions to improve village chicken production in Myanmar.

PubMed

Henning, J; Morton, J; Pym, R; Hla, T; Sunn, K; Meers, J

2013-07-01

A cost-benefit analysis using deterministic and stochastic modelling was conducted to identify the net benefits for households that adopt (1) vaccination of individual birds against Newcastle disease (ND) or (2) improved management of chick rearing by providing coops for the protection of chicks from predation and chick starter feed inside a creep feeder to support chicks' nutrition in village chicken flocks in Myanmar. Partial budgeting was used to assess the additional costs and benefits associated with each of the two interventions tested relative to neither strategy. In the deterministic model, over the first 3 years after the introduction of the interventions, the cumulative sum of the net differences from neither strategy was 13,189Kyat for ND vaccination and 77,645Kyat for improved chick management (effective exchange rate in 2005: 1000Kyat=1$US). Both interventions were also profitable after discounting over a 10-year period; Net Present Values for ND vaccination and improved chick management were 30,791 and 167,825Kyat, respectively. The Benefit-Cost Ratio for ND vaccination was very high (28.8). This was lower for improved chick management, due to greater costs of the intervention, but still favourable at 4.7. Using both interventions concurrently yielded a Net Present Value of 470,543Kyat and a Benefit-Cost Ratio of 11.2 over the 10-year period in the deterministic model. Using the stochastic model, for the first 3 years following the introduction of the interventions, the mean cumulative sums of the net difference were similar to those values obtained from the deterministic model. Sensitivity analysis indicated that the cumulative net differences were strongly influenced by grower bird sale income, particularly under improved chick management. The effects of the strategies on odds of households selling and consuming birds after 7 months, and numbers of birds being sold or consumed after this period also influenced profitability. Cost variations for equipment used under improved chick management were not markedly associated with profitability. Net Present Values and Benefit-Cost Ratios discounted over a 10-year period were also similar to the deterministic model when mean values obtained through stochastic modelling were used. In summary, the study showed that ND vaccination and improved chick management can improve the viability and profitability of village chicken production in Myanmar. Copyright © 2013 Elsevier B.V. All rights reserved.

Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

PubMed Central

2010-01-01

Background Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors. Methods In this study, efforts were focused in the construction of a relatively well informed, deterministic, non-linear dynamic model, accounting for reaction mechanisms grounded on standard mass action and Hill saturation kinetics, of the canonical reaction topology underlying Toll-like receptor 4 (TLR4)-mediated signaling events. This signaling mechanism has been shown to be deployed in macrophages during a relatively short time window in response to lypopolysaccharyde (LPS) stimulation, which leads to a rapidly mounted innate immune response. An extensive computational exploration of the biochemical reaction space inhabited by this signal transduction network was performed via local and global perturbation strategies. Importantly, a broad spectrum of biologically plausible dynamical regimes accessible to the network in widely scattered regions of parameter space was reconstructed computationally. Additionally, experimentally reported transcriptional readouts of target pro-inflammatory genes, which are actively modulated by the network in response to LPS stimulation, were also simulated. This was done with the main goal of carrying out an unbiased statistical assessment of the intrinsic robustness properties of this canonical reaction topology. Results Our simulation results provide convincing numerical evidence supporting the idea that a canonical reaction mechanism of the TLR4 signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology), but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space. PMID:20230643

Diffusion-controlled interface kinetics-inclusive system-theoretic propagation models for molecular communication systems

NASA Astrophysics Data System (ADS)

Chude-Okonkwo, Uche A. K.; Malekian, Reza; Maharaj, B. T.

2015-12-01

Inspired by biological systems, molecular communication has been proposed as a new communication paradigm that uses biochemical signals to transfer information from one nano device to another over a short distance. The biochemical nature of the information transfer process implies that for molecular communication purposes, the development of molecular channel models should take into consideration diffusion phenomenon as well as the physical/biochemical kinetic possibilities of the process. The physical and biochemical kinetics arise at the interfaces between the diffusion channel and the transmitter/receiver units. These interfaces are herein termed molecular antennas. In this paper, we present the deterministic propagation model of the molecular communication between an immobilized nanotransmitter and nanoreceiver, where the emission and reception kinetics are taken into consideration. Specifically, we derived closed-form system-theoretic models and expressions for configurations that represent different communication systems based on the type of molecular antennas used. The antennas considered are the nanopores at the transmitter and the surface receptor proteins/enzymes at the receiver. The developed models are simulated to show the influence of parameters such as the receiver radius, surface receptor protein/enzyme concentration, and various reaction rate constants. Results show that the effective receiver surface area and the rate constants are important to the system's output performance. Assuming high rate of catalysis, the analysis of the frequency behavior of the developed propagation channels in the form of transfer functions shows significant difference introduce by the inclusion of the molecular antennas into the diffusion-only model. It is also shown that for t > > 0 and with the information molecules' concentration greater than the Michaelis-Menten kinetic constant of the systems, the inclusion of surface receptors proteins and enzymes in the models makes the system act like a band-stop filter over an infinite frequency range.

Internal cycle modeling and environmental assessment of multiple cycle consumer products.

PubMed

Tsiliyannis, C A

2012-01-01

Dynamic annual flow models incorporating consumer discard and usage loss and featuring deterministic and stochastic end-of-cycle (EOC) return by the consumer are developed for reused or remanufactured products (multiple cycle products, MCPs), including fast and slow cycling, short and long-lived products. It is shown that internal flows (reuse and overall consumption) increase proportionally to the dimensionless internal cycle factor (ICF) which is related to environmental impact reduction factors. The combined reuse/recycle (or cycle) rate is shown capable for shortcut, albeit effective, monitoring of environmental performance in terms of waste production, virgin material extraction and manufacturing impacts of all MCPs, a task, which physical variables (lifetime, cycling frequency, mean or total number of return trips) and conventional rates, via which environmental policy has been officially implemented (e.g. recycling rate) cannot accomplish. The cycle rate is shown to be an increasing (hyperbolic) function of ICF. The impact of the stochastic EOC return characteristics on total reuse and consumption flows, as well as on eco-performance, is assessed: symmetric EOC return has a small, positive effect on performance compared to deterministic, while early shifted EOC return is more beneficial. In order to be efficient, environmental policy should set higher minimum reuse targets for higher trippage MCPs. The results may serve for monitoring, flow accounting and comparative eco-assessment of MCPs. They may be useful in identifying reachable and efficient reuse/recycle targets for consumer products and in planning return via appropriate labelling and digital coding for enhancing environmental performance, while satisfying consumer demand. Copyright © 2011 Elsevier Ltd. All rights reserved.

INCREASING HEAVY OIL RESERVES IN THE WILMINGTON OIL FIELD THROUGH ADVANCED RESERVOIR CHARACTERIZATION AND THERMAL PRODUCTION TECHNOLOGIES

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

Scott Hara

2000-02-18

The project involves using advanced reservoir characterization and thermal production technologies to improve thermal recovery techniques and lower operating and capital costs in a slope and basin clastic (SBC) reservoir in the Wilmington field, Los Angeles Co., CA. Through March 1999, project work has been completed related to data preparation, basic reservoir engineering, developing a deterministic three dimensional (3-D) geologic model, a 3-D deterministic reservoir simulation model, and a rock-log model, well drilling and completions, and surface facilities. Work is continuing on the stochastic geologic model, developing a 3-D stochastic thermal reservoir simulation model of the Fault Block IIA Tarmore » (Tar II-A) Zone, and operational work and research studies to prevent thermal-related formation compaction. Thermal-related formation compaction is a concern of the project team due to observed surface subsidence in the local area above the steamflood project. Last quarter on January 12, the steamflood project lost its inexpensive steam source from the Harbor Cogeneration Plant as a result of the recent deregulation of electrical power rates in California. An operational plan was developed and implemented to mitigate the effects of the two situations. Seven water injection wells were placed in service in November and December 1998 on the flanks of the Phase 1 steamflood area to pressure up the reservoir to fill up the existing steam chest. Intensive reservoir engineering and geomechanics studies are continuing to determine the best ways to shut down the steamflood operations in Fault Block II while minimizing any future surface subsidence. The new 3-D deterministic thermal reservoir simulator model is being used to provide sensitivity cases to optimize production, steam injection, future flank cold water injection and reservoir temperature and pressure. According to the model, reservoir fill up of the steam chest at the current injection rate of 28,000 BPD and gross and net oil production rates of 7,700 BPD and 750 BOPD (injection to production ratio of 4) will occur in October 1999. At that time, the reservoir should act more like a waterflood and production and cold water injection can be operated at lower net injection rates to be determined. Modeling runs developed this quarter found that varying individual well injection rates to meet added production and local pressure problems by sub-zone could reduce steam chest fill-up by up to one month.« less

Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics.

PubMed

Marquez-Lago, Tatiana T; Burrage, Kevin

2007-09-14

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.

Foundations of modelling of nonequilibrium low-temperature plasmas

NASA Astrophysics Data System (ADS)

Alves, L. L.; Bogaerts, A.; Guerra, V.; Turner, M. M.

2018-02-01

This work explains the need for plasma models, introduces arguments for choosing the type of model that better fits the purpose of each study, and presents the basics of the most common nonequilibrium low-temperature plasma models and the information available from each one, along with an extensive list of references for complementary in-depth reading. The paper presents the following models, organised according to the level of multi-dimensional description of the plasma: kinetic models, based on either a statistical particle-in-cell/Monte-Carlo approach or the solution to the Boltzmann equation (in the latter case, special focus is given to the description of the electron kinetics); multi-fluid models, based on the solution to the hydrodynamic equations; global (spatially-average) models, based on the solution to the particle and energy rate-balance equations for the main plasma species, usually including a very complete reaction chemistry; mesoscopic models for plasma-surface interaction, adopting either a deterministic approach or a stochastic dynamical Monte-Carlo approach. For each plasma model, the paper puts forward the physics context, introduces the fundamental equations, presents advantages and limitations, also from a numerical perspective, and illustrates its application with some examples. Whenever pertinent, the interconnection between models is also discussed, in view of multi-scale hybrid approaches.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Emerging issues in radiogenic cataracts and cardiovascular disease.

PubMed

Hamada, Nobuyuki; Fujimichi, Yuki; Iwasaki, Toshiyasu; Fujii, Noriko; Furuhashi, Masato; Kubo, Eri; Minamino, Tohru; Nomura, Takaharu; Sato, Hitoshi

2014-09-01

In 2011, the International Commission on Radiological Protection issued a statement on tissue reactions (formerly termed non-stochastic or deterministic effects) to recommend lowering the threshold for cataracts and the occupational equivalent dose limit for the crystalline lens of the eye. Furthermore, this statement was the first to list circulatory disease (cardiovascular and cerebrovascular disease) as a health hazard of radiation exposure and to assign its threshold for the heart and brain. These changes have stimulated various discussions and may have impacts on some radiation workers, such as those in the medical sector. This paper considers emerging issues associated with cataracts and cardiovascular disease. For cataracts, topics dealt with herein include (i) the progressive nature, stochastic nature, target cells and trigger events of lens opacification, (ii) roles of lens protein denaturation, oxidative stress, calcium ions, tumor suppressors and DNA repair factors in cataractogenesis, (iii) dose rate effect, radiation weighting factor, and classification systems for cataracts, and (iv) estimation of the lens dose in clinical settings. Topics for cardiovascular disease include experimental animal models, relevant surrogate markers, latency period, target tissues, and roles of inflammation and cellular senescence. Future research needs are also discussed. © The Author 2014. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Deterministic and stochastic CTMC models from Zika disease transmission

NASA Astrophysics Data System (ADS)

Zevika, Mona; Soewono, Edy

2018-03-01

Zika infection is one of the most important mosquito-borne diseases in the world. Zika virus (ZIKV) is transmitted by many Aedes-type mosquitoes including Aedes aegypti. Pregnant women with the Zika virus are at risk of having a fetus or infant with a congenital defect and suffering from microcephaly. Here, we formulate a Zika disease transmission model using two approaches, a deterministic model and a continuous-time Markov chain stochastic model. The basic reproduction ratio is constructed from a deterministic model. Meanwhile, the CTMC stochastic model yields an estimate of the probability of extinction and outbreaks of Zika disease. Dynamical simulations and analysis of the disease transmission are shown for the deterministic and stochastic models.

Distinguishing between stochasticity and determinism: Examples from cell cycle duration variability.

PubMed

Pearl Mizrahi, Sivan; Sandler, Oded; Lande-Diner, Laura; Balaban, Nathalie Q; Simon, Itamar

2016-01-01

We describe a recent approach for distinguishing between stochastic and deterministic sources of variability, focusing on the mammalian cell cycle. Variability between cells is often attributed to stochastic noise, although it may be generated by deterministic components. Interestingly, lineage information can be used to distinguish between variability and determinism. Analysis of correlations within a lineage of the mammalian cell cycle duration revealed its deterministic nature. Here, we discuss the sources of such variability and the possibility that the underlying deterministic process is due to the circadian clock. Finally, we discuss the "kicked cell cycle" model and its implication on the study of the cell cycle in healthy and cancerous tissues. © 2015 WILEY Periodicals, Inc.

Modeling Warfare in Social Animals: A "Chemical" Approach

PubMed Central

Santarlasci, Alisa; Martelloni, Gianluca; Frizzi, Filippo; Santini, Giacomo; Bagnoli, Franco

2014-01-01

We present here a general method for modelling the dynamics of battles among social animals. The proposed method exploits the procedures widely used to model chemical reactions, but still uncommon in behavioural studies. We applied this methodology to the interpretation of experimental observations of battles between two species of ants (Lasius neglectus and Lasius paralienus), but this scheme may have a wider applicability and can be extended to other species as well. We performed two types of experiment labelled as interaction and mortality. The interaction experiments are designed to obtain information on the combat dynamics and lasted one hour. The mortality ones provide information on the casualty rates of the two species and lasted five hours. We modelled the interactions among ants using a chemical model which considers the single ant individuals and fighting groups analogously to atoms and molecules. The mean-field behaviour of the model is described by a set of non-linear differential equations. We also performed stochastic simulations of the corresponding agent-based model by means of the Gillespie event-driven integration scheme. By fitting the stochastic trajectories with the deterministic model, we obtained the probability distribution of the reaction parameters. The main result that we obtained is a dominance phase diagram, that gives the average trajectory of a generic battle, for an arbitrary number of opponents. This phase diagram was validated with some extra experiments. With respect to other war models (e.g., Lanchester's ones), our chemical model considers all phases of the battle and not only casualties. This allows a more detailed description of the battle (with a larger number of parameters), allowing the development of more sophisticated models (e.g., spatial ones), with the goal of distinguishing collective effects from the strategic ones. PMID:25369269

Modeling warfare in social animals: a "chemical" approach.

PubMed

Santarlasci, Alisa; Martelloni, Gianluca; Frizzi, Filippo; Santini, Giacomo; Bagnoli, Franco

2014-01-01

We present here a general method for modelling the dynamics of battles among social animals. The proposed method exploits the procedures widely used to model chemical reactions, but still uncommon in behavioural studies. We applied this methodology to the interpretation of experimental observations of battles between two species of ants (Lasius neglectus and Lasius paralienus), but this scheme may have a wider applicability and can be extended to other species as well. We performed two types of experiment labelled as interaction and mortality. The interaction experiments are designed to obtain information on the combat dynamics and lasted one hour. The mortality ones provide information on the casualty rates of the two species and lasted five hours. We modelled the interactions among ants using a chemical model which considers the single ant individuals and fighting groups analogously to atoms and molecules. The mean-field behaviour of the model is described by a set of non-linear differential equations. We also performed stochastic simulations of the corresponding agent-based model by means of the Gillespie event-driven integration scheme. By fitting the stochastic trajectories with the deterministic model, we obtained the probability distribution of the reaction parameters. The main result that we obtained is a dominance phase diagram, that gives the average trajectory of a generic battle, for an arbitrary number of opponents. This phase diagram was validated with some extra experiments. With respect to other war models (e.g., Lanchester's ones), our chemical model considers all phases of the battle and not only casualties. This allows a more detailed description of the battle (with a larger number of parameters), allowing the development of more sophisticated models (e.g., spatial ones), with the goal of distinguishing collective effects from the strategic ones.

Disentangling Mechanisms That Mediate the Balance Between Stochastic and Deterministic Processes in Microbial Succession

DOE PAGES

Dini-Andreote, Francisco; Stegen, James C.; van Elsas, Jan D.; ...

2015-03-17

Despite growing recognition that deterministic and stochastic factors simultaneously influence bacterial communities, little is known about mechanisms shifting their relative importance. To better understand underlying mechanisms, we developed a conceptual model linking ecosystem development during primary succession to shifts in the stochastic/deterministic balance. To evaluate the conceptual model we coupled spatiotemporal data on soil bacterial communities with environmental conditions spanning 105 years of salt marsh development. At the local scale there was a progression from stochasticity to determinism due to Na accumulation with increasing ecosystem age, supporting a main element of the conceptual model. At the regional-scale, soil organic mattermore » (SOM) governed the relative influence of stochasticity and the type of deterministic ecological selection, suggesting scale-dependency in how deterministic ecological selection is imposed. Analysis of a new ecological simulation model supported these conceptual inferences. Looking forward, we propose an extended conceptual model that integrates primary and secondary succession in microbial systems.« less

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California

USGS Publications Warehouse

Guymon, Gary L.; Yen, Chung-Cheng

1990-01-01

The applicability of a deterministic-probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two-layer deterministic model that is cascaded with a two-point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source-sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two-point probability method.

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California

NASA Astrophysics Data System (ADS)

Guymon, Gary L.; Yen, Chung-Cheng

1990-07-01

The applicability of a deterministic-probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two-layer deterministic model that is cascaded with a two-point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source-sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two-point probability method.

Statistics of Delta v magnitude for a trajectory correction maneuver containing deterministic and random components

NASA Technical Reports Server (NTRS)

Bollman, W. E.; Chadwick, C.

1982-01-01

A number of interplanetary missions now being planned involve placing deterministic maneuvers along the flight path to alter the trajectory. Lee and Boain (1973) examined the statistics of trajectory correction maneuver (TCM) magnitude with no deterministic ('bias') component. The Delta v vector magnitude statistics were generated for several values of random Delta v standard deviations using expansions in terms of infinite hypergeometric series. The present investigation uses a different technique (Monte Carlo simulation) to generate Delta v magnitude statistics for a wider selection of random Delta v standard deviations and also extends the analysis to the case of nonzero deterministic Delta v's. These Delta v magnitude statistics are plotted parametrically. The plots are useful in assisting the analyst in quickly answering questions about the statistics of Delta v magnitude for single TCM's consisting of both a deterministic and a random component. The plots provide quick insight into the nature of the Delta v magnitude distribution for the TCM.

Proceedings of the 2nd Experimental Chaos Conference

NASA Astrophysics Data System (ADS)

Ditto, William; Pecora, Lou; Shlesinger, Michael; Spano, Mark; Vohra, Sandeep

1995-02-01

The Table of Contents for the full book PDF is as follows: * Introduction * Spatiotemporal Phenomena * Experimental Studies of Chaotic Mixing * Using Random Maps in the Analysis of Experimental Fluid Flows * Transition to Spatiotemporal Chaos in a Reaction-Diffusion System * Ion-Dynamical Chaos in Plasmas * Optics * Chaos in a Synchronously Driven Optical Resonator * Chaos, Patterns and Defects in Stimulated Scattering Phenomena * Test of the Normal Form for a Subcritical Bifurcation * Observation of Bifurcations and Chaos in a Driven Fiber Optic Coil * Applications -- Communications * Robustness and Signal Recovery in a Synchronized Chaotic System * Synchronizing Nonautonomous Chaotic Circuits * Synchronization of Pulse-Coupled Chaotic Oscillators * Ocean Transmission Effects on Chaotic Signals * Controlling Symbolic Dynamics for Communication * Applications -- Control * Analysis of Nonlinear Actuators Using Chaotic Waveforms * Controlling Chaos in a Quasiperiodic Electronic System * Control of Chaos in a CO2 Laser * General Research * Video-Based Analysis of Bifurcation Phenomena in Radio-Frequency-Excited Inert Gas Plasmas * Transition from Soliton to Chaotic Motion During the Impact of a Nonlinear Structure * Sonoluminescence in a Single Bubble: Periodic, Quasiperiodic and Chaotic Light Source * Quantum Chaos Experiments Using Microwave Cavities * Experiments on Quantum Chaos With and Without Time Reversibility * When Small Noise Imposed on Deterministic Dynamics Becomes Important * Biology * Chaos Control for Cardiac Arrhythmias * Irregularities in Spike Trains of Cat Retinal Ganglion Cells * Broad-Band Synchronization in Monkey Neocortex * Applicability of Correlation Dimension Calculations to Blood Pressure Signal in Rats * Tests for Deterministic Chaos in Noisy Time Series * The Crayfish Mechanoreceptor Cell: A Biological Example of Stochastic Resonance * Chemistry * Chaos During Heterogeneous Chemical Reactions * Stabilizing and Tracking Unstable Periodic Orbits and Stationary States in Chemical Systems * Recursive Proportional-Feedback and Its Use to Control Chaos in an Electrochemical System * Temperature Patterns on Catalytic Surfaces * Meteorology/Oceanography * Nonlinear Evolution of Water Waves: Hilbert's View * Fractal Properties of Isoconcentration Surfaces in a Smoke Plume * Fractal Dimensions of Remotely Sensed Atmospheric Signals * Are Ocean Surface Waves Chaotic? * Dynamical Attractor Reconstruction for a Marine Stratocumulus Cloud

Inference of Epidemiological Dynamics Based on Simulated Phylogenies Using Birth-Death and Coalescent Models

PubMed Central

Boskova, Veronika; Bonhoeffer, Sebastian; Stadler, Tanja

2014-01-01

Quantifying epidemiological dynamics is crucial for understanding and forecasting the spread of an epidemic. The coalescent and the birth-death model are used interchangeably to infer epidemiological parameters from the genealogical relationships of the pathogen population under study, which in turn are inferred from the pathogen genetic sequencing data. To compare the performance of these widely applied models, we performed a simulation study. We simulated phylogenetic trees under the constant rate birth-death model and the coalescent model with a deterministic exponentially growing infected population. For each tree, we re-estimated the epidemiological parameters using both a birth-death and a coalescent based method, implemented as an MCMC procedure in BEAST v2.0. In our analyses that estimate the growth rate of an epidemic based on simulated birth-death trees, the point estimates such as the maximum a posteriori/maximum likelihood estimates are not very different. However, the estimates of uncertainty are very different. The birth-death model had a higher coverage than the coalescent model, i.e. contained the true value in the highest posterior density (HPD) interval more often (2–13% vs. 31–75% error). The coverage of the coalescent decreases with decreasing basic reproductive ratio and increasing sampling probability of infecteds. We hypothesize that the biases in the coalescent are due to the assumption of deterministic rather than stochastic population size changes. Both methods performed reasonably well when analyzing trees simulated under the coalescent. The methods can also identify other key epidemiological parameters as long as one of the parameters is fixed to its true value. In summary, when using genetic data to estimate epidemic dynamics, our results suggest that the birth-death method will be less sensitive to population fluctuations of early outbreaks than the coalescent method that assumes a deterministic exponentially growing infected population. PMID:25375100

Diagnostic Assessment of the Difficulty Using Direct Policy Search in Many-Objective Reservoir Control

NASA Astrophysics Data System (ADS)

Zatarain-Salazar, J.; Reed, P. M.; Herman, J. D.; Giuliani, M.; Castelletti, A.

2014-12-01

Globally reservoir operations provide fundamental services to water supply, energy generation, recreation, and ecosystems. The pressures of expanding populations, climate change, and increased energy demands are motivating a significant investment in re-operationalizing existing reservoirs or defining operations for new reservoirs. Recent work has highlighted the potential benefits of exploiting recent advances in many-objective optimization and direct policy search (DPS) to aid in addressing these systems' multi-sector demand tradeoffs. This study contributes to a comprehensive diagnostic assessment of multi-objective evolutionary optimization algorithms (MOEAs) efficiency, effectiveness, reliability, and controllability when supporting DPS for the Conowingo dam in the Lower Susquehanna River Basin. The Lower Susquehanna River is an interstate water body that has been subject to intensive water management efforts due to the system's competing demands from urban water supply, atomic power plant cooling, hydropower production, and federally regulated environmental flows. Seven benchmark and state-of-the-art MOEAs are tested on deterministic and stochastic instances of the Susquehanna test case. In the deterministic formulation, the operating objectives are evaluated over the historical realization of the hydroclimatic variables (i.e., inflows and evaporation rates). In the stochastic formulation, the same objectives are instead evaluated over an ensemble of stochastic inflows and evaporation rates realizations. The algorithms are evaluated in their ability to support DPS in discovering reservoir operations that compose the tradeoffs for six multi-sector performance objectives with thirty-two decision variables. Our diagnostic results highlight that many-objective DPS is very challenging for modern MOEAs and that epsilon dominance is critical for attaining high levels of performance. Epsilon dominance algorithms epsilon-MOEA, epsilon-NSGAII and the auto adaptive Borg MOEA, are statistically superior for the six-objective Susquehanna instance of this important class of problems. Additionally, shifting from deterministic history-based DPS to stochastic DPS significantly increases the difficulty of the problem.

Did the ever dead outnumber the living and when? A birth-and-death approach

NASA Astrophysics Data System (ADS)

Avan, Jean; Grosjean, Nicolas; Huillet, Thierry

2015-02-01

This paper is an attempt to formalize analytically the question raised in 'World Population Explained: Do Dead People Outnumber Living, Or Vice Versa?' Huffington Post, Howard (2012). We start developing simple deterministic Malthusian growth models of the problem (with birth and death rates either constant or time-dependent) before running into both linear birth and death Markov chain models and age-structured models.

Robust High Data Rate MIMO Underwater Acoustic Communications

DTIC Science & Technology

2010-12-31

algorithm is referred to as periodic CAN ( PeCAN ). Unlike most existing sequence construction methods which are algebraic and deterministic in nature, we...start the iteration of PeCAN from random phase initializations and then proceed to cyclically minimize the desired metric. In this way, through...by the foe and hence are especially useful as training sequences or as spreading sequences for UAC applications. We will use PeCAN sequences for

How to Quantify Deterministic and Random Influences on the Statistics of the Foreign Exchange Market

NASA Astrophysics Data System (ADS)

Friedrich, R.; Peinke, J.; Renner, Ch.

2000-05-01

It is shown that price changes of the U.S. dollar-German mark exchange rates upon different delay times can be regarded as a stochastic Marcovian process. Furthermore, we show how Kramers-Moyal coefficients can be estimated from the empirical data. Finally, we present an explicit Fokker-Planck equation which models very precisely the empirical probability distributions, in particular, their non-Gaussian heavy tails.

Simultaneous estimation of deterministic and fractal stochastic components in non-stationary time series

NASA Astrophysics Data System (ADS)

García, Constantino A.; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G.

2018-07-01

In the past few decades, it has been recognized that 1 / f fluctuations are ubiquitous in nature. The most widely used mathematical models to capture the long-term memory properties of 1 / f fluctuations have been stochastic fractal models. However, physical systems do not usually consist of just stochastic fractal dynamics, but they often also show some degree of deterministic behavior. The present paper proposes a model based on fractal stochastic and deterministic components that can provide a valuable basis for the study of complex systems with long-term correlations. The fractal stochastic component is assumed to be a fractional Brownian motion process and the deterministic component is assumed to be a band-limited signal. We also provide a method that, under the assumptions of this model, is able to characterize the fractal stochastic component and to provide an estimate of the deterministic components present in a given time series. The method is based on a Bayesian wavelet shrinkage procedure that exploits the self-similar properties of the fractal processes in the wavelet domain. This method has been validated over simulated signals and over real signals with economical and biological origin. Real examples illustrate how our model may be useful for exploring the deterministic-stochastic duality of complex systems, and uncovering interesting patterns present in time series.

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model

PubMed Central

Nené, Nuno R.; Dunham, Alistair S.; Illingworth, Christopher J. R.

2018-01-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. PMID:29500183

Comparison of the effects of enteral feeding with continuous and intermittent parenteral nutrition on hepatic triglyceride secretion in human beings

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

Isabel-Martinez, L.; Skinner, C.; Parkin, A.

Plasma triglyceride turnover was measured during steady-state conditions in 22 postoperative patients. Nine had received nutritional support with an enteral regimen, seven had received an equivalent regimen as continuous parenteral nutrition, and six received the same parenteral regimen as a cyclical infusion. After 5 days of nutritional support, each patient received an intravenous bolus of tritiated glycerol. Plasma radiolabeled triglyceride content was measured during the subsequent 24 hours. The data were analyzed by means of a simple deterministic model of plasma triglyceride kinetics and compared with the results obtained by stochastic analysis. The rates of hepatic triglyceride secretion obtained bymore » deterministic analysis were higher than those obtained by the stochastic approach. However, the mode of delivery of the nutritional regimen did not affect the rate of hepatic triglyceride secretion regardless of the method of analysis. The results suggest that neither complete nutritional bypass of the gastrointestinal tract nor interruption of parenteral nutrition in an attempt to mimic normal eating has any effect on hepatic triglyceride secretion. Any beneficial effect that enteral feeding or cyclical parenteral nutrition may have on liver dysfunction associated with standard parenteral nutrition appears to be unrelated to changes in hepatic triglyceride secretion.« less

Entrepreneurs, Chance, and the Deterministic Concentration of Wealth

PubMed Central

Fargione, Joseph E.; Lehman, Clarence; Polasky, Stephen

2011-01-01

In many economies, wealth is strikingly concentrated. Entrepreneurs–individuals with ownership in for-profit enterprises–comprise a large portion of the wealthiest individuals, and their behavior may help explain patterns in the national distribution of wealth. Entrepreneurs are less diversified and more heavily invested in their own companies than is commonly assumed in economic models. We present an intentionally simplified individual-based model of wealth generation among entrepreneurs to assess the role of chance and determinism in the distribution of wealth. We demonstrate that chance alone, combined with the deterministic effects of compounding returns, can lead to unlimited concentration of wealth, such that the percentage of all wealth owned by a few entrepreneurs eventually approaches 100%. Specifically, concentration of wealth results when the rate of return on investment varies by entrepreneur and by time. This result is robust to inclusion of realities such as differing skill among entrepreneurs. The most likely overall growth rate of the economy decreases as businesses become less diverse, suggesting that high concentrations of wealth may adversely affect a country's economic growth. We show that a tax on large inherited fortunes, applied to a small portion of the most fortunate in the population, can efficiently arrest the concentration of wealth at intermediate levels. PMID:21814540

Analytical approximations for spatial stochastic gene expression in single cells and tissues

PubMed Central

Smith, Stephen; Cianci, Claudia; Grima, Ramon

2016-01-01

Gene expression occurs in an environment in which both stochastic and diffusive effects are significant. Spatial stochastic simulations are computationally expensive compared with their deterministic counterparts, and hence little is currently known of the significance of intrinsic noise in a spatial setting. Starting from the reaction–diffusion master equation (RDME) describing stochastic reaction–diffusion processes, we here derive expressions for the approximate steady-state mean concentrations which are explicit functions of the dimensionality of space, rate constants and diffusion coefficients. The expressions have a simple closed form when the system consists of one effective species. These formulae show that, even for spatially homogeneous systems, mean concentrations can depend on diffusion coefficients: this contradicts the predictions of deterministic reaction–diffusion processes, thus highlighting the importance of intrinsic noise. We confirm our theory by comparison with stochastic simulations, using the RDME and Brownian dynamics, of two models of stochastic and spatial gene expression in single cells and tissues. PMID:27146686

Deterministic and stochastic algorithms for resolving the flow fields in ducts and networks using energy minimization

NASA Astrophysics Data System (ADS)

Sochi, Taha

2016-09-01

Several deterministic and stochastic multi-variable global optimization algorithms (Conjugate Gradient, Nelder-Mead, Quasi-Newton and global) are investigated in conjunction with energy minimization principle to resolve the pressure and volumetric flow rate fields in single ducts and networks of interconnected ducts. The algorithms are tested with seven types of fluid: Newtonian, power law, Bingham, Herschel-Bulkley, Ellis, Ree-Eyring and Casson. The results obtained from all those algorithms for all these types of fluid agree very well with the analytically derived solutions as obtained from the traditional methods which are based on the conservation principles and fluid constitutive relations. The results confirm and generalize the findings of our previous investigations that the energy minimization principle is at the heart of the flow dynamics systems. The investigation also enriches the methods of computational fluid dynamics for solving the flow fields in tubes and networks for various types of Newtonian and non-Newtonian fluids.

Monitoring and exposure assessment of pesticide residues in cowpea (Vigna unguiculata L. Walp) from five provinces of southern China.

PubMed

Huan, Zhibo; Xu, Zhi; Luo, Jinhui; Xie, Defang

2016-11-01

Residues of 14 pesticides were determined in 150 cowpea samples collected in five southern Chinese provinces in 2013 and 2014.70% samples were detected one or more residues. 61.3% samples were illegal mainly because of detection of unauthorized pesticides. 14.0% samples contained more than three pesticides. Deterministic and probabilistic methods were used to assess the chronic and acute risk of pesticides in cowpea to eight subgroups of people. Deterministic assessment showed that the estimated short-term intakes (ESTIs) of carbofuran were 1199.4%-2621.9% of the acute reference doses (ARfD) while the rates were 985.9%-4114.7% using probabilistic assessment. Probabilistic assessment showed 4.2%-7.8% subjects may suffer from unacceptable acute risk from carbofuran contaminated cowpeas from the five provinces (especially children). But undue concern is not necessary, because all the estimations are based on conservative assumption. Copyright © 2016 Elsevier Inc. All rights reserved.

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III: Scenario analysis

USGS Publications Warehouse

Huisman, J.A.; Breuer, L.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.; Willems, P.

2009-01-01

An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions. ?? 2008 Elsevier Ltd.

Faster PET reconstruction with a stochastic primal-dual hybrid gradient method

NASA Astrophysics Data System (ADS)

Ehrhardt, Matthias J.; Markiewicz, Pawel; Chambolle, Antonin; Richtárik, Peter; Schott, Jonathan; Schönlieb, Carola-Bibiane

2017-08-01

Image reconstruction in positron emission tomography (PET) is computationally challenging due to Poisson noise, constraints and potentially non-smooth priors-let alone the sheer size of the problem. An algorithm that can cope well with the first three of the aforementioned challenges is the primal-dual hybrid gradient algorithm (PDHG) studied by Chambolle and Pock in 2011. However, PDHG updates all variables in parallel and is therefore computationally demanding on the large problem sizes encountered with modern PET scanners where the number of dual variables easily exceeds 100 million. In this work, we numerically study the usage of SPDHG-a stochastic extension of PDHG-but is still guaranteed to converge to a solution of the deterministic optimization problem with similar rates as PDHG. Numerical results on a clinical data set show that by introducing randomization into PDHG, similar results as the deterministic algorithm can be achieved using only around 10 % of operator evaluations. Thus, making significant progress towards the feasibility of sophisticated mathematical models in a clinical setting.

A robust multi-objective global supplier selection model under currency fluctuation and price discount

NASA Astrophysics Data System (ADS)

Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman

2017-06-01

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.

Deterministic secure quantum communication using a single d-level system

PubMed Central

Jiang, Dong; Chen, Yuanyuan; Gu, Xuemei; Xie, Ling; Chen, Lijun

2017-01-01

Deterministic secure quantum communication (DSQC) can transmit secret messages between two parties without first generating a shared secret key. Compared with quantum key distribution (QKD), DSQC avoids the waste of qubits arising from basis reconciliation and thus reaches higher efficiency. In this paper, based on data block transmission and order rearrangement technologies, we propose a DSQC protocol. It utilizes a set of single d-level systems as message carriers, which are used to directly encode the secret message in one communication process. Theoretical analysis shows that these employed technologies guarantee the security, and the use of a higher dimensional quantum system makes our protocol achieve higher security and efficiency. Since only quantum memory is required for implementation, our protocol is feasible with current technologies. Furthermore, Trojan horse attack (THA) is taken into account in our protocol. We give a THA model and show that THA significantly increases the multi-photon rate and can thus be detected. PMID:28327557

An optimal policy for deteriorating items with time-proportional deterioration rate and constant and time-dependent linear demand rate

NASA Astrophysics Data System (ADS)

Singh, Trailokyanath; Mishra, Pandit Jagatananda; Pattanayak, Hadibandhu

2017-12-01

In this paper, an economic order quantity (EOQ) inventory model for a deteriorating item is developed with the following characteristics: (i) The demand rate is deterministic and two-staged, i.e., it is constant in first part of the cycle and linear function of time in the second part. (ii) Deterioration rate is time-proportional. (iii) Shortages are not allowed to occur. The optimal cycle time and the optimal order quantity have been derived by minimizing the total average cost. A simple solution procedure is provided to illustrate the proposed model. The article concludes with a numerical example and sensitivity analysis of various parameters as illustrations of the theoretical results.

Improving ground-penetrating radar data in sedimentary rocks using deterministic deconvolution

USGS Publications Warehouse

Xia, J.; Franseen, E.K.; Miller, R.D.; Weis, T.V.; Byrnes, A.P.

2003-01-01

Resolution is key to confidently identifying unique geologic features using ground-penetrating radar (GPR) data. Source wavelet "ringing" (related to bandwidth) in a GPR section limits resolution because of wavelet interference, and can smear reflections in time and/or space. The resultant potential for misinterpretation limits the usefulness of GPR. Deconvolution offers the ability to compress the source wavelet and improve temporal resolution. Unlike statistical deconvolution, deterministic deconvolution is mathematically simple and stable while providing the highest possible resolution because it uses the source wavelet unique to the specific radar equipment. Source wavelets generated in, transmitted through and acquired from air allow successful application of deterministic approaches to wavelet suppression. We demonstrate the validity of using a source wavelet acquired in air as the operator for deterministic deconvolution in a field application using "400-MHz" antennas at a quarry site characterized by interbedded carbonates with shale partings. We collected GPR data on a bench adjacent to cleanly exposed quarry faces in which we placed conductive rods to provide conclusive groundtruth for this approach to deconvolution. The best deconvolution results, which are confirmed by the conductive rods for the 400-MHz antenna tests, were observed for wavelets acquired when the transmitter and receiver were separated by 0.3 m. Applying deterministic deconvolution to GPR data collected in sedimentary strata at our study site resulted in an improvement in resolution (50%) and improved spatial location (0.10-0.15 m) of geologic features compared to the same data processed without deterministic deconvolution. The effectiveness of deterministic deconvolution for increased resolution and spatial accuracy of specific geologic features is further demonstrated by comparing results of deconvolved data with nondeconvolved data acquired along a 30-m transect immediately adjacent to a fresh quarry face. The results at this site support using deterministic deconvolution, which incorporates the GPR instrument's unique source wavelet, as a standard part of routine GPR data processing. ?? 2003 Elsevier B.V. All rights reserved.

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.

Active adaptive management for reintroduction of an animal population

USGS Publications Warehouse

Runge, Michael C.

2013-01-01

Captive animals are frequently reintroduced to the wild in the face of uncertainty, but that uncertainty can often be reduced over the course of the reintroduction effort, providing the opportunity for adaptive management. One common uncertainty in reintroductions is the short-term survival rate of released adults (a release cost), an important factor because it can affect whether releasing adults or juveniles is better. Information about this rate can improve the success of the reintroduction program, but does the expected gain offset the costs of obtaining the information? I explored this question for reintroduction of the griffon vulture (Gyps fulvus) by framing the management question as a belief Markov decision process, characterizing uncertainty about release cost with 2 information state variables, and finding the solution using stochastic dynamic programming. For a reintroduction program of fixed length (e.g., 5 years of releases), the optimal policy in the final release year resembles the deterministic solution: release either all adults or all juveniles depending on whether the point estimate for the survival rate in question is above or below a specific threshold. But the optimal policy in the earlier release years 1) includes release of a mixture of juveniles and adults under some circumstances, and 2) recommends release of adults even when the point estimate of survival is much less than the deterministic threshold. These results show that in an iterated decision setting, the optimal decision in early years can be quite different from that in later years because of the value of learning. 

Probabilistic arithmetic automata and their applications.

PubMed

Marschall, Tobias; Herms, Inke; Kaltenbach, Hans-Michael; Rahmann, Sven

2012-01-01

We present a comprehensive review on probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two algorithms to numerically compute the distribution of the results of such probabilistic calculations. PAAs provide a unifying framework to approach many problems arising in computational biology and elsewhere. We present five different applications, namely 1) pattern matching statistics on random texts, including the computation of the distribution of occurrence counts, waiting times, and clump sizes under hidden Markov background models; 2) exact analysis of window-based pattern matching algorithms; 3) sensitivity of filtration seeds used to detect candidate sequence alignments; 4) length and mass statistics of peptide fragments resulting from enzymatic cleavage reactions; and 5) read length statistics of 454 and IonTorrent sequencing reads. The diversity of these applications indicates the flexibility and unifying character of the presented framework. While the construction of a PAA depends on the particular application, we single out a frequently applicable construction method: We introduce deterministic arithmetic automata (DAAs) to model deterministic calculations on sequences, and demonstrate how to construct a PAA from a given DAA and a finite-memory random text model. This procedure is used for all five discussed applications and greatly simplifies the construction of PAAs. Implementations are available as part of the MoSDi package. Its application programming interface facilitates the rapid development of new applications based on the PAA framework.

Proposed principles of maximum local entropy production.

PubMed

Ross, John; Corlan, Alexandru D; Müller, Stefan C

2012-07-12

Articles have appeared that rely on the application of some form of "maximum local entropy production principle" (MEPP). This is usually an optimization principle that is supposed to compensate for the lack of structural information and measurements about complex systems, even systems as complex and as little characterized as the whole biosphere or the atmosphere of the Earth or even of less known bodies in the solar system. We select a number of claims from a few well-known papers that advocate this principle and we show that they are in error with the help of simple examples of well-known chemical and physical systems. These erroneous interpretations can be attributed to ignoring well-established and verified theoretical results such as (1) entropy does not necessarily increase in nonisolated systems, such as "local" subsystems; (2) macroscopic systems, as described by classical physics, are in general intrinsically deterministic-there are no "choices" in their evolution to be selected by using supplementary principles; (3) macroscopic deterministic systems are predictable to the extent to which their state and structure is sufficiently well-known; usually they are not sufficiently known, and probabilistic methods need to be employed for their prediction; and (4) there is no causal relationship between the thermodynamic constraints and the kinetics of reaction systems. In conclusion, any predictions based on MEPP-like principles should not be considered scientifically founded.

Cost-Utility Analysis of Telemonitoring Interventions for Patients with Chronic Obstructive Pulmonary Disease (COPD) in Germany.

PubMed

Hofer, Florian; Achelrod, Dmitrij; Stargardt, Tom

2016-12-01

Chronic obstructive pulmonary disease (COPD) poses major challenges for health care systems. Previous studies suggest that telemonitoring could be effective in preventing hospitalisations and hence reduce costs. The aim was to evaluate whether telemonitoring interventions for COPD are cost-effective from the perspective of German statutory sickness funds. A cost-utility analysis was conducted using a combination of a Markov model and a decision tree. Telemonitoring as add-on to standard treatment was compared with standard treatment alone. The model consisted of four transition stages to account for COPD severity, and a terminal stage for death. Within each cycle, the frequency of exacerbations as well as outcomes for 2015 costs and quality adjusted life years (QALYs) for each stage were calculated. Values for input parameters were taken from the literature. Deterministic and probabilistic sensitivity analyses were conducted. In the base case, telemonitoring led to an increase in incremental costs (€866 per patient) but also in incremental QALYs (0.05 per patient). The incremental cost-effectiveness ratio (ICER) was thus €17,410 per QALY gained. A deterministic sensitivity analysis showed that hospitalisation rate and costs for telemonitoring equipment greatly affected results. The probabilistic ICER averaged €34,432 per QALY (95 % confidence interval 12,161-56,703). We provide evidence that telemonitoring may be cost-effective in Germany from a payer's point of view. This holds even after deterministic and probabilistic sensitivity analyses.

Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes

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

Lin, Yen Ting; Buchler, Nicolas E.

Single-cell experiments show that gene expression is stochastic and bursty, a feature that can emerge from slow switching between promoter states with different activities. In addition to slow chromatin and/or DNA looping dynamics, one source of long-lived promoter states is the slow binding and unbinding kinetics of transcription factors to promoters, i.e. the non-adiabatic binding regime. Here, we introduce a simple analytical framework, known as a piecewise deterministic Markov process (PDMP), that accurately describes the stochastic dynamics of gene expression in the non-adiabatic regime. We illustrate the utility of the PDMP on a non-trivial dynamical system by analysing the propertiesmore » of a titration-based oscillator in the non-adiabatic limit. We first show how to transform the underlying chemical master equation into a PDMP where the slow transitions between promoter states are stochastic, but whose rates depend upon the faster deterministic dynamics of the transcription factors regulated by these promoters. We show that the PDMP accurately describes the observed periods of stochastic cycles in activator and repressor-based titration oscillators. We then generalize our PDMP analysis to more complicated versions of titration-based oscillators to explain how multiple binding sites lengthen the period and improve coherence. Finally, we show how noise-induced oscillation previously observed in a titration-based oscillator arises from non-adiabatic and discrete binding events at the promoter site.« less

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.

Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes

DOE PAGES

Lin, Yen Ting; Buchler, Nicolas E.

2018-01-31

Single-cell experiments show that gene expression is stochastic and bursty, a feature that can emerge from slow switching between promoter states with different activities. In addition to slow chromatin and/or DNA looping dynamics, one source of long-lived promoter states is the slow binding and unbinding kinetics of transcription factors to promoters, i.e. the non-adiabatic binding regime. Here, we introduce a simple analytical framework, known as a piecewise deterministic Markov process (PDMP), that accurately describes the stochastic dynamics of gene expression in the non-adiabatic regime. We illustrate the utility of the PDMP on a non-trivial dynamical system by analysing the propertiesmore » of a titration-based oscillator in the non-adiabatic limit. We first show how to transform the underlying chemical master equation into a PDMP where the slow transitions between promoter states are stochastic, but whose rates depend upon the faster deterministic dynamics of the transcription factors regulated by these promoters. We show that the PDMP accurately describes the observed periods of stochastic cycles in activator and repressor-based titration oscillators. We then generalize our PDMP analysis to more complicated versions of titration-based oscillators to explain how multiple binding sites lengthen the period and improve coherence. Finally, we show how noise-induced oscillation previously observed in a titration-based oscillator arises from non-adiabatic and discrete binding events at the promoter site.« less

Estimating the epidemic threshold on networks by deterministic connections

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

Li, Kezan, E-mail: lkzzr@sohu.com; Zhu, Guanghu; Fu, Xinchu

2014-12-15

For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect thanmore » those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.« less

Experimental demonstration on the deterministic quantum key distribution based on entangled photons.

PubMed

Chen, Hua; Zhou, Zhi-Yuan; Zangana, Alaa Jabbar Jumaah; Yin, Zhen-Qiang; Wu, Juan; Han, Yun-Guang; Wang, Shuang; Li, Hong-Wei; He, De-Yong; Tawfeeq, Shelan Khasro; Shi, Bao-Sen; Guo, Guang-Can; Chen, Wei; Han, Zheng-Fu

2016-02-10

As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified "Ping-Pong"(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based quantum communications.

Experimental demonstration on the deterministic quantum key distribution based on entangled photons

PubMed Central

Chen, Hua; Zhou, Zhi-Yuan; Zangana, Alaa Jabbar Jumaah; Yin, Zhen-Qiang; Wu, Juan; Han, Yun-Guang; Wang, Shuang; Li, Hong-Wei; He, De-Yong; Tawfeeq, Shelan Khasro; Shi, Bao-Sen; Guo, Guang-Can; Chen, Wei; Han, Zheng-Fu

2016-01-01

As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based quantum communications. PMID:26860582

Multiscale Hy3S: hybrid stochastic simulation for supercomputers.

PubMed

Salis, Howard; Sotiropoulos, Vassilios; Kaznessis, Yiannis N

2006-02-24

Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users create biological systems and analyze data. We demonstrate the accuracy and efficiency of Hy3S with examples, including a large-scale system benchmark and a complex bistable biochemical network with positive feedback. The software itself is open-sourced under the GPL license and is modular, allowing users to modify it for their own purposes. Hy3S is a powerful suite of simulation programs for simulating the stochastic dynamics of networks of biochemical reactions. Its first public version enables computational biologists to more efficiently investigate the dynamics of realistic biological systems.

Characterization of normality of chaotic systems including prediction and detection of anomalies

NASA Astrophysics Data System (ADS)

Engler, Joseph John

Accurate prediction and control pervades domains such as engineering, physics, chemistry, and biology. Often, it is discovered that the systems under consideration cannot be well represented by linear, periodic nor random data. It has been shown that these systems exhibit deterministic chaos behavior. Deterministic chaos describes systems which are governed by deterministic rules but whose data appear to be random or quasi-periodic distributions. Deterministically chaotic systems characteristically exhibit sensitive dependence upon initial conditions manifested through rapid divergence of states initially close to one another. Due to this characterization, it has been deemed impossible to accurately predict future states of these systems for longer time scales. Fortunately, the deterministic nature of these systems allows for accurate short term predictions, given the dynamics of the system are well understood. This fact has been exploited in the research community and has resulted in various algorithms for short term predictions. Detection of normality in deterministically chaotic systems is critical in understanding the system sufficiently to able to predict future states. Due to the sensitivity to initial conditions, the detection of normal operational states for a deterministically chaotic system can be challenging. The addition of small perturbations to the system, which may result in bifurcation of the normal states, further complicates the problem. The detection of anomalies and prediction of future states of the chaotic system allows for greater understanding of these systems. The goal of this research is to produce methodologies for determining states of normality for deterministically chaotic systems, detection of anomalous behavior, and the more accurate prediction of future states of the system. Additionally, the ability to detect subtle system state changes is discussed. The dissertation addresses these goals by proposing new representational techniques and novel prediction methodologies. The value and efficiency of these methods are explored in various case studies. Presented is an overview of chaotic systems with examples taken from the real world. A representation schema for rapid understanding of the various states of deterministically chaotic systems is presented. This schema is then used to detect anomalies and system state changes. Additionally, a novel prediction methodology which utilizes Lyapunov exponents to facilitate longer term prediction accuracy is presented and compared with other nonlinear prediction methodologies. These novel methodologies are then demonstrated on applications such as wind energy, cyber security and classification of social networks.

Modeling heterogeneous responsiveness of intrinsic apoptosis pathway

PubMed Central

2013-01-01

Background Apoptosis is a cell suicide mechanism that enables multicellular organisms to maintain homeostasis and to eliminate individual cells that threaten the organism’s survival. Dependent on the type of stimulus, apoptosis can be propagated by extrinsic pathway or intrinsic pathway. The comprehensive understanding of the molecular mechanism of apoptotic signaling allows for development of mathematical models, aiming to elucidate dynamical and systems properties of apoptotic signaling networks. There have been extensive efforts in modeling deterministic apoptosis network accounting for average behavior of a population of cells. Cellular networks, however, are inherently stochastic and significant cell-to-cell variability in apoptosis response has been observed at single cell level. Results To address the inevitable randomness in the intrinsic apoptosis mechanism, we develop a theoretical and computational modeling framework of intrinsic apoptosis pathway at single-cell level, accounting for both deterministic and stochastic behavior. Our deterministic model, adapted from the well-accepted Fussenegger model, shows that an additional positive feedback between the executioner caspase and the initiator caspase plays a fundamental role in yielding the desired property of bistability. We then examine the impact of intrinsic fluctuations of biochemical reactions, viewed as intrinsic noise, and natural variation of protein concentrations, viewed as extrinsic noise, on behavior of the intrinsic apoptosis network. Histograms of the steady-state output at varying input levels show that the intrinsic noise could elicit a wider region of bistability over that of the deterministic model. However, the system stochasticity due to intrinsic fluctuations, such as the noise of steady-state response and the randomness of response delay, shows that the intrinsic noise in general is insufficient to produce significant cell-to-cell variations at physiologically relevant level of molecular numbers. Furthermore, the extrinsic noise represented by random variations of two key apoptotic proteins, namely Cytochrome C and inhibitor of apoptosis proteins (IAP), is modeled separately or in combination with intrinsic noise. The resultant stochasticity in the timing of intrinsic apoptosis response shows that the fluctuating protein variations can induce cell-to-cell stochastic variability at a quantitative level agreeing with experiments. Finally, simulations illustrate that the mean abundance of fluctuating IAP protein is positively correlated with the degree of cellular stochasticity of the intrinsic apoptosis pathway. Conclusions Our theoretical and computational study shows that the pronounced non-genetic heterogeneity in intrinsic apoptosis responses among individual cells plausibly arises from extrinsic rather than intrinsic origin of fluctuations. In addition, it predicts that the IAP protein could serve as a potential therapeutic target for suppression of the cell-to-cell variation in the intrinsic apoptosis responsiveness. PMID:23875784

Quantized orbits in weakly coupled Belousov-Zhabotinsky reactors

NASA Astrophysics Data System (ADS)

Weiss, S.; Deegan, R. D.

2015-06-01

Using numerical and experimental tools, we study the motion of two coupled spiral cores in a light-sensitive variant of the Belousov-Zhabotinsky reaction. Each core resides on a separate two-dimensional domain, and is coupled to the other by light. When both spirals have the same sense of rotation, the cores are attracted to a circular trajectory with a diameter quantized in integer units of the spiral wavelength λ. When the spirals have opposite senses of rotation, the cores are attracted towards different but parallel straight trajectories, separated by an integer multiple of λ/2. We present a model that explains this behavior as the result of a spiral wavefront-core interaction that produces a deterministic displacement of the core and a retardation of its phase.

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.

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.

PubMed

Nené, Nuno R; Dunham, Alistair S; Illingworth, Christopher J R

2018-05-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. Copyright © 2018 Nené et al.

Cost-Effectiveness Analysis of Diagnosis of Duchenne/Becker Muscular Dystrophy in Colombia.

PubMed

Atehortúa, Sara C; Lugo, Luz H; Ceballos, Mateo; Orozco, Esteban; Castro, Paula A; Arango, Juan C; Mateus, Heidi E

2018-03-09

To determine the cost-effectiveness ratio of different courses of action for the diagnosis of Duchenne or Becker muscular dystrophy in Colombia. The cost-effectiveness analysis was performed from the Colombian health system perspective. Decision trees were constructed, and different courses of action were compared considering the following tests: immunohistochemistry (IHC), Western blot (WB), multiplex polymerase chain reaction, multiplex ligation-dependent probe amplification (MLPA), and the complete sequencing of the dystrophin gene. The time horizon matched the duration of sample extraction and analysis. Transition probabilities were obtained from a systematic review. Costs were constructed with a type-case methodology using the consensus of experts and the valuation of resources from consulting laboratories and the 2001 Social Security Institute cost manual. Deterministic sensitivity and scenario analyses were performed with one or more unavailable alternatives. Costs were converted from Colombian pesos to US dollars using the 2014 exchange rate. In the base case, WB was the dominant strategy, with a cost of US $419.07 and a sensitivity of 100%. This approach remains the dominant strategy down to a 98.2% sensitivity and while costs do not exceed US $837.38. If WB was not available, IHC had the best cost-effectiveness ratio, followed by MLPA and sequencing. WB is a cost-effective alternative for the diagnosis of patients suspected of having Duchenne or Becker muscular dystrophy in the Colombian health system. The IHC test is rated as the second-best detection method. If these tests are not available, MLPA followed by sequencing would be the most cost-effective alternative. Copyright © 2018. Published by Elsevier Inc.

Enhancing quality of carbon nanotubes through a real-time controlled CVD process with application to next-generation nanosystems

NASA Astrophysics Data System (ADS)

Laxminarayana, Karthik; Jalili, Nader

2004-07-01

Nanocrystals and nanostructures will be the building blocks for future materials that will exhibit enhanced or entirely new combinations of properties with tremendous opportunity for novel technologies that can have far-reaching impact on our society. It is, however, realized that a major challenge for the near future is the design, synthesis and integration of nanostructures to develop functional nanosystems. In view of this, this exploratory research seeks to facilitate the development of a controlled and deterministic framework for nanomanufacturing of nanotubes as the most suitable choice among nanostructures for a plethora of potential applications in areas such as nanoelectronic devices, biological probes, fuel cell electrodes, supercapacitors and filed emission devices. Specifically, this paper proposes to control and maintain the most common nanotube growth parameters (i.e., reaction temperature and gas flow rate) through both software and hardware modifications. The influence of such growth parameters in a CVD process on some of the most vital and crucial aspects of nanotubes (e.g., length, diameter, yield, growth rate and structure) can be utilized to arrive at some unique and remarkable properties for the nanotubes. The objective here is, therefore, to control the process parameters to pinpoint accuracy, which would enable us to fabricate nanotubes having the desired properties and thereby maximize their ability to function at its fullest potential. To achieve this and in order to provide for experimental validation of the proposed research program, an experimental test-bed using the nanotube processing test chamber and a mechatronics workstation are being constructed.

Fractal-Based Image Compression

DTIC Science & Technology

1990-01-01

used Ziv - Lempel - experiments and for software development. Addi- Welch compression algorithm (ZLW) [51 [4] was used tional thanks to Roger Boss, Bill...vol17no. 6 (June 4) and with the minimum number of maps. [5] J. Ziv and A. Lempel , Compression of !ndivid- 5 Summary ual Sequences via Variable-Rate...transient and should be discarded. 2.5 Collage Theorem algorithm2 C3.2 Deterministic Algorithm for IFS Attractor For fast image compression the best

Controllability of Deterministic Networks with the Identical Degree Sequence

PubMed Central

Ma, Xiujuan; Zhao, Haixing; Wang, Binghong

2015-01-01

Controlling complex network is an essential problem in network science and engineering. Recent advances indicate that the controllability of complex network is dependent on the network's topology. Liu and Barabási, et.al speculated that the degree distribution was one of the most important factors affecting controllability for arbitrary complex directed network with random link weights. In this paper, we analysed the effect of degree distribution to the controllability for the deterministic networks with unweighted and undirected. We introduce a class of deterministic networks with identical degree sequence, called (x,y)-flower. We analysed controllability of the two deterministic networks ((1, 3)-flower and (2, 2)-flower) by exact controllability theory in detail and give accurate results of the minimum number of driver nodes for the two networks. In simulation, we compare the controllability of (x,y)-flower networks. Our results show that the family of (x,y)-flower networks have the same degree sequence, but their controllability is totally different. So the degree distribution itself is not sufficient to characterize the controllability of deterministic networks with unweighted and undirected. PMID:26020920

Inverse kinematic problem for a random gradient medium in geometric optics approximation

NASA Astrophysics Data System (ADS)

Petersen, N. V.

1990-03-01

Scattering at random inhomogeneities in a gradient medium results in systematic deviations of the rays and travel times of refracted body waves from those corresponding to the deterministic velocity component. The character of the difference depends on the parameters of the deterministic and random velocity component. However, at great distances to the source, independently of the velocity parameters (weakly or strongly inhomogeneous medium), the most probable depth of the ray turning point is smaller than that corresponding to the deterministic velocity component, the most probable travel times also being lower. The relative uncertainty in the deterministic velocity component, derived from the mean travel times using methods developed for laterally homogeneous media (for instance, the Herglotz-Wiechert method), is systematic in character, but does not exceed the contrast of velocity inhomogeneities by magnitude. The gradient of the deterministic velocity component has a significant effect on the travel-time fluctuations. The variance at great distances to the source is mainly controlled by shallow inhomogeneities. The travel-time flucutations are studied only for weakly inhomogeneous media.

Extension of a Kinetic-Theory Approach for Computing Chemical-Reaction Rates to Reactions with Charged Particles

NASA Technical Reports Server (NTRS)

Liechty, Derek S.; Lewis, Mark J.

2010-01-01

Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties (i.e., no macroscopic reaction rate information) are extended to include reactions involving charged particles and electronic energy levels. The proposed extensions include ionization reactions, exothermic associative ionization reactions, endothermic and exothermic charge exchange reactions, and other exchange reactions involving ionized species. The extensions are shown to agree favorably with the measured Arrhenius rates for near-equilibrium conditions.

Quasi-Static Probabilistic Structural Analyses Process and Criteria

NASA Technical Reports Server (NTRS)

Goldberg, B.; Verderaime, V.

1999-01-01

Current deterministic structural methods are easily applied to substructures and components, and analysts have built great design insights and confidence in them over the years. However, deterministic methods cannot support systems risk analyses, and it was recently reported that deterministic treatment of statistical data is inconsistent with error propagation laws that can result in unevenly conservative structural predictions. Assuming non-nal distributions and using statistical data formats throughout prevailing stress deterministic processes lead to a safety factor in statistical format, which integrated into the safety index, provides a safety factor and first order reliability relationship. The embedded safety factor in the safety index expression allows a historically based risk to be determined and verified over a variety of quasi-static metallic substructures consistent with the traditional safety factor methods and NASA Std. 5001 criteria.

Effect of Uncertainty on Deterministic Runway Scheduling

NASA Technical Reports Server (NTRS)

Gupta, Gautam; Malik, Waqar; Jung, Yoon C.

2012-01-01

Active runway scheduling involves scheduling departures for takeoffs and arrivals for runway crossing subject to numerous constraints. This paper evaluates the effect of uncertainty on a deterministic runway scheduler. The evaluation is done against a first-come- first-serve scheme. In particular, the sequence from a deterministic scheduler is frozen and the times adjusted to satisfy all separation criteria; this approach is tested against FCFS. The comparison is done for both system performance (throughput and system delay) and predictability, and varying levels of congestion are considered. The modeling of uncertainty is done in two ways: as equal uncertainty in availability at the runway as for all aircraft, and as increasing uncertainty for later aircraft. Results indicate that the deterministic approach consistently performs better than first-come-first-serve in both system performance and predictability.

Efficient room-temperature source of polarized single photons

DOEpatents

Lukishova, Svetlana G.; Boyd, Robert W.; Stroud, Carlos R.

2007-08-07

An efficient technique for producing deterministically polarized single photons uses liquid-crystal hosts of either monomeric or oligomeric/polymeric form to preferentially align the single emitters for maximum excitation efficiency. Deterministic molecular alignment also provides deterministically polarized output photons; using planar-aligned cholesteric liquid crystal hosts as 1-D photonic-band-gap microcavities tunable to the emitter fluorescence band to increase source efficiency, using liquid crystal technology to prevent emitter bleaching. Emitters comprise soluble dyes, inorganic nanocrystals or trivalent rare-earth chelates.

Assessing nonlinear structures in real exchange rates using recurrence plot strategies

NASA Astrophysics Data System (ADS)

Belaire-Franch, Jorge; Contreras, Dulce; Tordera-Lledó, Lorena

2002-11-01

Purchasing power parity (PPP) is an important theory at the basis of a large number of economic models. However, the implication derived from the theory that real exchange rates must follow stationary processes is not conclusively supported by empirical studies. In a recent paper, Serletis and Gogas [Appl. Finance Econ. 10 (2000) 615] show evidence of deterministic chaos in several OECD exchange rates. As a consequence, PPP rejections could be spurious. In this work, we follow a two-stage testing procedure to test for nonlinearities and chaos in real exchange rates, using a new set of techniques designed by Webber and Zbilut [J. Appl. Physiol. 76 (1994) 965], called recurrence quantification analysis (RQA). Our conclusions differ slightly from Serletis and Gogas [Appl. Finance Econ. 10 (2000) 615], but they are also supportive of chaos for some exchange rates.

Effective grid-dependent dispersion coefficient for conservative and reactive transport simulations in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cortinez, J. M.; Valocchi, A. J.; Herrera, P. A.

2013-12-01

Because of the finite size of numerical grids, it is very difficult to correctly account for processes that occur at different spatial scales to accurately simulate the migration of conservative and reactive compounds dissolved in groundwater. In one hand, transport processes in heterogeneous porous media are controlled by local-scale dispersion associated to transport processes at the pore-scale. On the other hand, variations of velocity at the continuum- or Darcy-scale produce spreading of the contaminant plume, which is referred to as macro-dispersion. Furthermore, under some conditions both effects interact, so that spreading may enhance the action of local-scale dispersion resulting in higher mixing, dilution and reaction rates. Traditionally, transport processes at different spatial scales have been included in numerical simulations by using a single dispersion coefficient. This approach implicitly assumes that the separate effects of local-dispersion and macro-dispersion can be added and represented by a unique effective dispersion coefficient. Moreover, the selection of the effective dispersion coefficient for numerical simulations usually do not consider the filtering effect of the grid size over the small-scale flow features. We have developed a multi-scale Lagragian numerical method that allows using two different dispersion coefficients to represent local- and macro-scale dispersion. This technique considers fluid particles that carry solute mass and whose locations evolve according to a deterministic component given by the grid-scale velocity and a stochastic component that corresponds to a block-effective macro-dispersion coefficient. Mass transfer between particles due to local-scale dispersion is approximated by a meshless method. We use our model to test under which transport conditions the combined effect of local- and macro-dispersion are additive and can be represented by a single effective dispersion coefficient. We also demonstrate that for the situations where both processes are additive, an effective grid-dependent dispersion coefficient can be derived based on the concept of block-effective dispersion. We show that the proposed effective dispersion coefficient is able to reproduce dilution, mixing and reaction rates for a wide range of transport conditions similar to the ones found in many practical applications.

Development of the MCNPX depletion capability: A Monte Carlo linked depletion method that automates the coupling between MCNPX and CINDER90 for high fidelity burnup calculations

NASA Astrophysics Data System (ADS)

Fensin, Michael Lorne

Monte Carlo-linked depletion methods have gained recent interest due to the ability to more accurately model complex 3-dimesional geometries and better track the evolution of temporal nuclide inventory by simulating the actual physical process utilizing continuous energy coefficients. The integration of CINDER90 into the MCNPX Monte Carlo radiation transport code provides a high-fidelity completely self-contained Monte-Carlo-linked depletion capability in a well established, widely accepted Monte Carlo radiation transport code that is compatible with most nuclear criticality (KCODE) particle tracking features in MCNPX. MCNPX depletion tracks all necessary reaction rates and follows as many isotopes as cross section data permits in order to achieve a highly accurate temporal nuclide inventory solution. This work chronicles relevant nuclear history, surveys current methodologies of depletion theory, details the methodology in applied MCNPX and provides benchmark results for three independent OECD/NEA benchmarks. Relevant nuclear history, from the Oklo reactor two billion years ago to the current major United States nuclear fuel cycle development programs, is addressed in order to supply the motivation for the development of this technology. A survey of current reaction rate and temporal nuclide inventory techniques is then provided to offer justification for the depletion strategy applied within MCNPX. The MCNPX depletion strategy is then dissected and each code feature is detailed chronicling the methodology development from the original linking of MONTEBURNS and MCNP to the most recent public release of the integrated capability (MCNPX 2.6.F). Calculation results of the OECD/NEA Phase IB benchmark, H. B. Robinson benchmark and OECD/NEA Phase IVB are then provided. The acceptable results of these calculations offer sufficient confidence in the predictive capability of the MCNPX depletion method. This capability sets up a significant foundation, in a well established and supported radiation transport code, for further development of a Monte Carlo-linked depletion methodology which is essential to the future development of advanced reactor technologies that exceed the limitations of current deterministic based methods.

Nanotransfer and nanoreplication using deterministically grown sacrificial nanotemplates

DOEpatents

Melechko, Anatoli V [Oak Ridge, TN; McKnight, Timothy E [Greenback, TN; Guillorn, Michael A [Ithaca, NY; Ilic, Bojan [Ithaca, NY; Merkulov, Vladimir I [Knoxville, TN; Doktycz, Mitchel J [Knoxville, TN; Lowndes, Douglas H [Knoxville, TN; Simpson, Michael L [Knoxville, TN

2011-08-23

Methods, manufactures, machines and compositions are described for nanotransfer and nanoreplication using deterministically grown sacrificial nanotemplates. An apparatus, includes a substrate and a nanoreplicant structure coupled to a surface of the substrate.

Stochasticity and determinism in models of hematopoiesis.

PubMed

Kimmel, Marek

2014-01-01

This chapter represents a novel view of modeling in hematopoiesis, synthesizing both deterministic and stochastic approaches. Whereas the stochastic models work in situations where chance dominates, for example when the number of cells is small, or under random mutations, the deterministic models are more important for large-scale, normal hematopoiesis. New types of models are on the horizon. These models attempt to account for distributed environments such as hematopoietic niches and their impact on dynamics. Mixed effects of such structures and chance events are largely unknown and constitute both a challenge and promise for modeling. Our discussion is presented under the separate headings of deterministic and stochastic modeling; however, the connections between both are frequently mentioned. Four case studies are included to elucidate important examples. We also include a primer of deterministic and stochastic dynamics for the reader's use.

The Nonstationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation

PubMed Central

Martin, Guillaume; Roques, Lionel

2016-01-01

Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher’s geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a “phase transition” with mutation rate. Beyond this phase transition, in Fisher’s geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies. PMID:27770037

Failed rib region prediction in a human body model during crash events with precrash braking.

PubMed

Guleyupoglu, B; Koya, B; Barnard, R; Gayzik, F S

2018-02-28

The objective of this study is 2-fold. We used a validated human body finite element model to study the predicted chest injury (focusing on rib fracture as a function of element strain) based on varying levels of simulated precrash braking. Furthermore, we compare deterministic and probabilistic methods of rib injury prediction in the computational model. The Global Human Body Models Consortium (GHBMC) M50-O model was gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and airbag. Twelve cases were investigated with permutations for failure, precrash braking system, and crash severity. The severities used were median (17 kph), severe (34 kph), and New Car Assessment Program (NCAP; 56.4 kph). Cases with failure enabled removed rib cortical bone elements once 1.8% effective plastic strain was exceeded. Alternatively, a probabilistic framework found in the literature was used to predict rib failure. Both the probabilistic and deterministic methods take into consideration location (anterior, lateral, and posterior). The deterministic method is based on a rubric that defines failed rib regions dependent on a threshold for contiguous failed elements. The probabilistic method depends on age-based strain and failure functions. Kinematics between both methods were similar (peak max deviation: ΔX head = 17 mm; ΔZ head = 4 mm; ΔX thorax = 5 mm; ΔZ thorax = 1 mm). Seat belt forces at the time of probabilistic failed region initiation were lower than those at deterministic failed region initiation. The probabilistic method for rib fracture predicted more failed regions in the rib (an analog for fracture) than the deterministic method in all but 1 case where they were equal. The failed region patterns between models are similar; however, there are differences that arise due to stress reduced from element elimination that cause probabilistic failed regions to continue to rise after no deterministic failed region would be predicted. Both the probabilistic and deterministic methods indicate similar trends with regards to the effect of precrash braking; however, there are tradeoffs. The deterministic failed region method is more spatially sensitive to failure and is more sensitive to belt loads. The probabilistic failed region method allows for increased capability in postprocessing with respect to age. The probabilistic failed region method predicted more failed regions than the deterministic failed region method due to force distribution differences.

Adaptation to Temporally Fluctuating Environments by the Evolution of Maternal Effects.

PubMed

Dey, Snigdhadip; Proulx, Stephen R; Teotónio, Henrique

2016-02-01

All organisms live in temporally fluctuating environments. Theory predicts that the evolution of deterministic maternal effects (i.e., anticipatory maternal effects or transgenerational phenotypic plasticity) underlies adaptation to environments that fluctuate in a predictably alternating fashion over maternal-offspring generations. In contrast, randomizing maternal effects (i.e., diversifying and conservative bet-hedging), are expected to evolve in response to unpredictably fluctuating environments. Although maternal effects are common, evidence for their adaptive significance is equivocal since they can easily evolve as a correlated response to maternal selection and may or may not increase the future fitness of offspring. Using the hermaphroditic nematode Caenorhabditis elegans, we here show that the experimental evolution of maternal glycogen provisioning underlies adaptation to a fluctuating normoxia-anoxia hatching environment by increasing embryo survival under anoxia. In strictly alternating environments, we found that hermaphrodites evolved the ability to increase embryo glycogen provisioning when they experienced normoxia and to decrease embryo glycogen provisioning when they experienced anoxia. At odds with existing theory, however, populations facing irregularly fluctuating normoxia-anoxia hatching environments failed to evolve randomizing maternal effects. Instead, adaptation in these populations may have occurred through the evolution of fitness effects that percolate over multiple generations, as they maintained considerably high expected growth rates during experimental evolution despite evolving reduced fecundity and reduced embryo survival under one or two generations of anoxia. We develop theoretical models that explain why adaptation to a wide range of patterns of environmental fluctuations hinges on the existence of deterministic maternal effects, and that such deterministic maternal effects are more likely to contribute to adaptation than randomizing maternal effects.

Adaptation to Temporally Fluctuating Environments by the Evolution of Maternal Effects

PubMed Central

Dey, Snigdhadip; Proulx, Stephen R.; Teotónio, Henrique

2016-01-01

All organisms live in temporally fluctuating environments. Theory predicts that the evolution of deterministic maternal effects (i.e., anticipatory maternal effects or transgenerational phenotypic plasticity) underlies adaptation to environments that fluctuate in a predictably alternating fashion over maternal-offspring generations. In contrast, randomizing maternal effects (i.e., diversifying and conservative bet-hedging), are expected to evolve in response to unpredictably fluctuating environments. Although maternal effects are common, evidence for their adaptive significance is equivocal since they can easily evolve as a correlated response to maternal selection and may or may not increase the future fitness of offspring. Using the hermaphroditic nematode Caenorhabditis elegans, we here show that the experimental evolution of maternal glycogen provisioning underlies adaptation to a fluctuating normoxia–anoxia hatching environment by increasing embryo survival under anoxia. In strictly alternating environments, we found that hermaphrodites evolved the ability to increase embryo glycogen provisioning when they experienced normoxia and to decrease embryo glycogen provisioning when they experienced anoxia. At odds with existing theory, however, populations facing irregularly fluctuating normoxia–anoxia hatching environments failed to evolve randomizing maternal effects. Instead, adaptation in these populations may have occurred through the evolution of fitness effects that percolate over multiple generations, as they maintained considerably high expected growth rates during experimental evolution despite evolving reduced fecundity and reduced embryo survival under one or two generations of anoxia. We develop theoretical models that explain why adaptation to a wide range of patterns of environmental fluctuations hinges on the existence of deterministic maternal effects, and that such deterministic maternal effects are more likely to contribute to adaptation than randomizing maternal effects. PMID:26910440

Successional dynamics in Neotropical forests are as uncertain as they are predictable

PubMed Central

Norden, Natalia; Angarita, Héctor A.; Bongers, Frans; Martínez-Ramos, Miguel; Granzow-de la Cerda, Iñigo; van Breugel, Michiel; Lebrija-Trejos, Edwin; Meave, Jorge A.; Vandermeer, John; Williamson, G. Bruce; Finegan, Bryan; Mesquita, Rita; Chazdon, Robin L.

2015-01-01

Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes—stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration. PMID:26080411

Successional dynamics in Neotropical forests are as uncertain as they are predictable.

PubMed

Norden, Natalia; Angarita, Héctor A; Bongers, Frans; Martínez-Ramos, Miguel; Granzow-de la Cerda, Iñigo; van Breugel, Michiel; Lebrija-Trejos, Edwin; Meave, Jorge A; Vandermeer, John; Williamson, G Bruce; Finegan, Bryan; Mesquita, Rita; Chazdon, Robin L

2015-06-30

Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes--stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration.

The Dripping Handrail Model: Transient Chaos in Accretion Systems

NASA Technical Reports Server (NTRS)

Young, Karl; Scargle, Jeffrey D.; Cuzzi, Jeffrey (Technical Monitor)

1995-01-01

We define and study a simple dynamical model for accretion systems, the "dripping handrail" (DHR). The time evolution of this spatially extended system is a mixture of periodic and apparently random (but actually deterministic) behavior. The nature of this mixture depends on the values of its physical parameters - the accretion rate, diffusion coefficient, and density threshold. The aperiodic component is a special kind of deterministic chaos called transient chaos. The model can simultaneously exhibit both the quasiperiodic oscillations (QPO) and very low frequency noise (VLFN) that characterize the power spectra of fluctuations of several classes of accretion systems in astronomy. For this reason, our model may be relevant to many such astrophysical systems, including binary stars with accretion onto a compact object - white dwarf, neutron star, or black hole - as well as active galactic nuclei. We describe the systematics of the DHR's temporal behavior, by exploring its physical parameter space using several diagnostics: power spectra, wavelet "scalegrams," and Lyapunov exponents. In addition, we note that for large accretion rates the DHR has periodic modes; the effective pulse shapes for these modes - evaluated by folding the time series at the known period - bear a resemblance to the similarly- determined shapes for some x-ray pulsars. The pulsing observed in some of these systems may be such periodic-mode accretion, and not due to pure rotation as in the standard pulsar model.

Forecasting the Change of Renal Stone Occurrence Rates in Astronauts

NASA Technical Reports Server (NTRS)

Myers, J.; Goodenow, D.; Gokoglu, S.; Kassemi, M.

2016-01-01

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidences of renal stones in US astronauts exists and the question How much does this risk change with space flight? remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone occurrence.

A model for a spatially structured metapopulation accounting for within patch dynamics.

PubMed

Smith, Andrew G; McVinish, Ross; Pollett, Philip K

2014-01-01

We develop a stochastic metapopulation model that accounts for spatial structure as well as within patch dynamics. Using a deterministic approximation derived from a functional law of large numbers, we develop conditions for extinction and persistence of the metapopulation in terms of the birth, death and migration parameters. Interestingly, we observe the Allee effect in a metapopulation comprising two patches of greatly different sizes, despite there being decreasing patch specific per-capita birth rates. We show that the Allee effect is due to the way the migration rates depend on the population density of the patches. Copyright © 2013 Elsevier Inc. All rights reserved.

Pro Free Will Priming Enhances “Risk-Taking” Behavior in the Iowa Gambling Task, but Not in the Balloon Analogue Risk Task: Two Independent Priming Studies

PubMed Central

Schrag, Yann; Tremea, Alessandro; Lagger, Cyril; Ohana, Noé; Mohr, Christine

2016-01-01

Studies indicated that people behave less responsibly after exposure to information containing deterministic statements as compared to free will statements or neutral statements. Thus, deterministic primes should lead to enhanced risk-taking behavior. We tested this prediction in two studies with healthy participants. In experiment 1, we tested 144 students (24 men) in the laboratory using the Iowa Gambling Task. In experiment 2, we tested 274 participants (104 men) online using the Balloon Analogue Risk Task. In the Iowa Gambling Task, the free will priming condition resulted in more risky decisions than both the deterministic and neutral priming conditions. We observed no priming effects on risk-taking behavior in the Balloon Analogue Risk Task. To explain these unpredicted findings, we consider the somatic marker hypothesis, a gain frequency approach as well as attention to gains and / or inattention to losses. In addition, we highlight the necessity to consider both pro free will and deterministic priming conditions in future studies. Importantly, our and previous results indicate that the effects of pro free will and deterministic priming do not oppose each other on a frequently assumed continuum. PMID:27018854

Pro Free Will Priming Enhances "Risk-Taking" Behavior in the Iowa Gambling Task, but Not in the Balloon Analogue Risk Task: Two Independent Priming Studies.

PubMed

Schrag, Yann; Tremea, Alessandro; Lagger, Cyril; Ohana, Noé; Mohr, Christine

2016-01-01

Studies indicated that people behave less responsibly after exposure to information containing deterministic statements as compared to free will statements or neutral statements. Thus, deterministic primes should lead to enhanced risk-taking behavior. We tested this prediction in two studies with healthy participants. In experiment 1, we tested 144 students (24 men) in the laboratory using the Iowa Gambling Task. In experiment 2, we tested 274 participants (104 men) online using the Balloon Analogue Risk Task. In the Iowa Gambling Task, the free will priming condition resulted in more risky decisions than both the deterministic and neutral priming conditions. We observed no priming effects on risk-taking behavior in the Balloon Analogue Risk Task. To explain these unpredicted findings, we consider the somatic marker hypothesis, a gain frequency approach as well as attention to gains and / or inattention to losses. In addition, we highlight the necessity to consider both pro free will and deterministic priming conditions in future studies. Importantly, our and previous results indicate that the effects of pro free will and deterministic priming do not oppose each other on a frequently assumed continuum.

Ion implantation for deterministic single atom devices

NASA Astrophysics Data System (ADS)

Pacheco, J. L.; Singh, M.; Perry, D. L.; Wendt, J. R.; Ten Eyck, G.; Manginell, R. P.; Pluym, T.; Luhman, D. R.; Lilly, M. P.; Carroll, M. S.; Bielejec, E.

2017-12-01

We demonstrate a capability of deterministic doping at the single atom level using a combination of direct write focused ion beam and solid-state ion detectors. The focused ion beam system can position a single ion to within 35 nm of a targeted location and the detection system is sensitive to single low energy heavy ions. This platform can be used to deterministically fabricate single atom devices in materials where the nanostructure and ion detectors can be integrated, including donor-based qubits in Si and color centers in diamond.

Counterfactual Quantum Deterministic Key Distribution

NASA Astrophysics Data System (ADS)

Zhang, Sheng; Wang, Jian; Tang, Chao-Jing

2013-01-01

We propose a new counterfactual quantum cryptography protocol concerning about distributing a deterministic key. By adding a controlled blocking operation module to the original protocol [T.G. Noh, Phys. Rev. Lett. 103 (2009) 230501], the correlation between the polarizations of the two parties, Alice and Bob, is extended, therefore, one can distribute both deterministic keys and random ones using our protocol. We have also given a simple proof of the security of our protocol using the technique we ever applied to the original protocol. Most importantly, our analysis produces a bound tighter than the existing ones.

Ion implantation for deterministic single atom devices

DOE PAGES

Pacheco, J. L.; Singh, M.; Perry, D. L.; ...

2017-12-04

Here, we demonstrate a capability of deterministic doping at the single atom level using a combination of direct write focused ion beam and solid-state ion detectors. The focused ion beam system can position a single ion to within 35 nm of a targeted location and the detection system is sensitive to single low energy heavy ions. This platform can be used to deterministically fabricate single atom devices in materials where the nanostructure and ion detectors can be integrated, including donor-based qubits in Si and color centers in diamond.

Deterministic quantum splitter based on time-reversed Hong-Ou-Mandel interference

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

Chen, Jun; Lee, Kim Fook; Kumar, Prem

2007-09-15

By utilizing a fiber-based indistinguishable photon-pair source in the 1.55 {mu}m telecommunications band [J. Chen et al., Opt. Lett. 31, 2798 (2006)], we present the first, to the best of our knowledge, deterministic quantum splitter based on the principle of time-reversed Hong-Ou-Mandel quantum interference. The deterministically separated identical photons' indistinguishability is then verified by using a conventional Hong-Ou-Mandel quantum interference, which exhibits a near-unity dip visibility of 94{+-}1%, making this quantum splitter useful for various quantum information processing applications.

A hydro-meteorological ensemble prediction system for real-time flood forecasting purposes in the Milano area

NASA Astrophysics Data System (ADS)

Ravazzani, Giovanni; Amengual, Arnau; Ceppi, Alessandro; Romero, Romualdo; Homar, Victor; Mancini, Marco

2015-04-01

Analysis of forecasting strategies that can provide a tangible basis for flood early warning procedures and mitigation measures over the Western Mediterranean region is one of the fundamental motivations of the European HyMeX programme. Here, we examine a set of hydro-meteorological episodes that affected the Milano urban area for which the complex flood protection system of the city did not completely succeed before the occurred flash-floods. Indeed, flood damages have exponentially increased in the area during the last 60 years, due to industrial and urban developments. Thus, the improvement of the Milano flood control system needs a synergism between structural and non-structural approaches. The flood forecasting system tested in this work comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models, in order to provide a hydrological ensemble prediction system (HEPS). Deterministic and probabilistic quantitative precipitation forecasts (QPFs) have been provided by WRF model in a set of 48-hours experiments. HEPS has been generated by combining different physical parameterizations (i.e. cloud microphysics, moist convection and boundary-layer schemes) of the WRF model in order to better encompass the atmospheric processes leading to high precipitation amounts. We have been able to test the value of a probabilistic versus a deterministic framework when driving Quantitative Discharge Forecasts (QDFs). Results highlight (i) the benefits of using a high-resolution HEPS in conveying uncertainties for this complex orographic area and (ii) a better simulation of the most of extreme precipitation events, potentially enabling valuable probabilistic QDFs. Hence, the HEPS copes with the significant deficiencies found in the deterministic QPFs. These shortcomings would prevent to correctly forecast the location and timing of high precipitation rates and total amounts at the catchment scale, thus impacting heavily the deterministic QDFs. In contrast, early warnings would have been possible within a HEPS context for the Milano area, proving the suitability of such system for civil protection purposes.

Appearance of deterministic mixing behavior from ensembles of fluctuating hydrodynamics simulations of the Richtmyer-Meshkov instability

NASA Astrophysics Data System (ADS)

Narayanan, Kiran; Samtaney, Ravi

2018-04-01

We obtain numerical solutions of the two-fluid fluctuating compressible Navier-Stokes (FCNS) equations, which consistently account for thermal fluctuations from meso- to macroscales, in order to study the effect of such fluctuations on the mixing behavior in the Richtmyer-Meshkov instability (RMI). The numerical method used was successfully verified in two stages: for the deterministic fluxes by comparison against air-SF6 RMI experiment, and for the stochastic terms by comparison against the direct simulation Monte Carlo results for He-Ar RMI. We present results from fluctuating hydrodynamic RMI simulations for three He-Ar systems having length scales with decreasing order of magnitude that span from macroscopic to mesoscopic, with different levels of thermal fluctuations characterized by a nondimensional Boltzmann number (Bo). For a multidimensional FCNS system on a regular Cartesian grid, when using a discretization of a space-time stochastic flux Z (x ,t ) of the form Z (x ,t ) →1 /√{h ▵ t }N (i h ,n Δ t ) for spatial interval h , time interval Δ t , h , and Gaussian noise N should be greater than h0, with h0 corresponding to a cell volume that contains a sufficient number of molecules of the fluid such that the fluctuations are physically meaningful and produce the right equilibrium spectrum. For the mesoscale RMI systems simulated, it was desirable to use a cell size smaller than this limit in order to resolve the viscous shock. This was achieved by using a modified regularization of the noise term via Z (h3,h03)>x ,t →1 /√ ▵ t max(i h ,n Δ t ) , with h0=ξ h ∀h

Changing contributions of stochastic and deterministic processes in community assembly over a successional gradient.

PubMed

Måren, Inger Elisabeth; Kapfer, Jutta; Aarrestad, Per Arild; Grytnes, John-Arvid; Vandvik, Vigdis

2018-01-01

Successional dynamics in plant community assembly may result from both deterministic and stochastic ecological processes. The relative importance of different ecological processes is expected to vary over the successional sequence, between different plant functional groups, and with the disturbance levels and land-use management regimes of the successional systems. We evaluate the relative importance of stochastic and deterministic processes in bryophyte and vascular plant community assembly after fire in grazed and ungrazed anthropogenic coastal heathlands in Northern Europe. A replicated series of post-fire successions (n = 12) were initiated under grazed and ungrazed conditions, and vegetation data were recorded in permanent plots over 13 years. We used redundancy analysis (RDA) to test for deterministic successional patterns in species composition repeated across the replicate successional series and analyses of co-occurrence to evaluate to what extent species respond synchronously along the successional gradient. Change in species co-occurrences over succession indicates stochastic successional dynamics at the species level (i.e., species equivalence), whereas constancy in co-occurrence indicates deterministic dynamics (successional niche differentiation). The RDA shows high and deterministic vascular plant community compositional change, especially early in succession. Co-occurrence analyses indicate stochastic species-level dynamics the first two years, which then give way to more deterministic replacements. Grazed and ungrazed successions are similar, but the early stage stochasticity is higher in ungrazed areas. Bryophyte communities in ungrazed successions resemble vascular plant communities. In contrast, bryophytes in grazed successions showed consistently high stochasticity and low determinism in both community composition and species co-occurrence. In conclusion, stochastic and individualistic species responses early in succession give way to more niche-driven dynamics in later successional stages. Grazing reduces predictability in both successional trends and species-level dynamics, especially in plant functional groups that are not well adapted to disturbance. © 2017 The Authors. Ecology, published by Wiley Periodicals, Inc., on behalf of the Ecological Society of America.

[Adverse reaction caused by rabies vaccine in China: a Meta-analysis].

PubMed

Zhang, X R; Wu, Z G; Zhang, W S

2017-06-10

Objective: To conduct a Meta-analysis on the rate of adverse reaction related to rabies vaccine, so as to provide reference for rabies vaccine immunization in China. Methods: We electronically searched databases including CNKI, VIP information resource integration service platform, WanFang Data, CBM, PubMed and The Cochrane Library, to collect studies on Chinese people who had received full rabies vaccination and recording all the adverse reactions, from January 2000 to July 2016. Inclusion and exclusion criteria were strictly followed. Meta-analysis for the adverse reaction rate was performed using the R software. Results: A total of 29 related papers had met the inclusion criteria, with no publication bias noticed. A total number of 11 020 cases had adverse reactions, among all the 94 222 respondents, with an incidence of adverse reactions as 1.04 % -47.78 % . The overall incidence rate of adverse reaction was 9.82 % (95 %CI : 7.58 % -12.72 % ). A combined local adverse reaction rate appeared as 12.05 % (95 % CI : 9.26 % -15.69 % ). The systemic adverse reaction rate was 9.06 % (95 %CI : 7.07 % -11.61 % ). The overall adverse reaction rate on aqueous vaccine was 32.39 % (95 %CI : 21.88 % -47.94 % ). Combined adverse reaction rate of freeze dried vaccine appeared as 8.65 % (95 %CI : 4.54 % -16.51 % ). Significant differences were seen between both groups ( P <0.05). Conclusions: The local adverse reaction rate caused by rabies vaccination was higher than the systemic adverse reaction rate. The adverse reaction rate of aqueous rabies vaccine was higher than that of freeze dried rabies vaccine. Our results suggested that the aqueous vaccine should gradually be eliminated.

An error-dependent model of instrument-scanning behavior in commercial airline pilots. Ph.D. Thesis - May 1983

NASA Technical Reports Server (NTRS)

Jones, D. H.

1985-01-01

A new flexible model of pilot instrument scanning behavior is presented which assumes that the pilot uses a set of deterministic scanning patterns on the pilot's perception of error in the state of the aircraft, and the pilot's knowledge of the interactive nature of the aircraft's systems. Statistical analyses revealed that a three stage Markov process composed of the pilot's three predicted lookpoints (LP), occurring 1/30, 2/30, and 3/30 of a second prior to each LP, accurately modelled the scanning behavior of 14 commercial airline pilots while flying steep turn maneuvers in a Boeing 737 flight simulator. The modelled scanning data for each pilot were not statistically different from the observed scanning data in comparisons of mean dwell time, entropy, and entropy rate. These findings represent the first direct evidence that pilots are using deterministic scanning patterns during instrument flight. The results are interpreted as direct support for the error dependent model and suggestions are made for further research that could allow for identification of the specific scanning patterns suggested by the model.

RES: Regularized Stochastic BFGS Algorithm

NASA Astrophysics Data System (ADS)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

Dispersion-relation phase spectroscopy of neuron transport

NASA Astrophysics Data System (ADS)

Wang, Ru; Wang, Zhuo; Millet, Larry; Gillette, Martha; Leigh, Joseph Robert; Sobh, Nahil; Levine, Alex; Popescu, Gabreil

2012-02-01

Molecular motors move materials along prescribed biopolymer tracks. This sort of active transport is required to rapidly move products over large distances within the cell, where passive diffusion is too slow. We examine intracellular traffic patterns using a new application of spatial light interference microscopy (SLIM) and measure the dispersion relation, i.e. decay rate vs. spatial mode, associated with mass transport in live cells. This approach applies equally well to both discrete and continuous mass distributions without the need for particle tracking. From the quadratic experimental curve specific to diffusion, we extracted the diffusion coefficient as the only fitting parameter. The linear portion of the dispersion relation reveals the deterministic component of the intracellular transport. Our data show a universal behavior where the intracellular transport is diffusive at small scales and deterministic at large scales. We further applied this method to studying transport in neurons and are able to use SLIM to map the changes in index of refraction across the neuron and its extended processes. We found that in dendrites and axons, the transport is mostly active, i.e., diffusion is subdominant.

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.

Dynamics of a stochastic multi-strain SIS epidemic model driven by Lévy noise

NASA Astrophysics Data System (ADS)

Chen, Can; Kang, Yanmei

2017-01-01

A stochastic multi-strain SIS epidemic model is formulated by introducing Lévy noise into the disease transmission rate of each strain. First, we prove that the stochastic model admits a unique global positive solution, and, by the comparison theorem, we show that the solution remains within a positively invariant set almost surely. Next we investigate stochastic stability of the disease-free equilibrium, including stability in probability and pth moment asymptotic stability. Then sufficient conditions for persistence in the mean of the disease are established. Finally, based on an Euler scheme for Lévy-driven stochastic differential equations, numerical simulations for a stochastic two-strain model are carried out to verify the theoretical results. Moreover, numerical comparison results of the stochastic two-strain model and the deterministic version are also given. Lévy noise can cause the two strains to become extinct almost surely, even though there is a dominant strain that persists in the deterministic model. It can be concluded that the introduction of Lévy noise reduces the disease extinction threshold, which indicates that Lévy noise may suppress the disease outbreak.

Health safety nets can break cycles of poverty and disease: a stochastic ecological model.

PubMed

Plucinski, Mateusz M; Ngonghala, Calistus N; Bonds, Matthew H

2011-12-07

The persistence of extreme poverty is increasingly attributed to dynamic interactions between biophysical processes and economics, though there remains a dearth of integrated theoretical frameworks that can inform policy. Here, we present a stochastic model of disease-driven poverty traps. Whereas deterministic models can result in poverty traps that can only be broken by substantial external changes to the initial conditions, in the stochastic model there is always some probability that a population will leave or enter a poverty trap. We show that a 'safety net', defined as an externally enforced minimum level of health or economic conditions, can guarantee ultimate escape from a poverty trap, even if the safety net is set within the basin of attraction of the poverty trap, and even if the safety net is only in the form of a public health measure. Whereas the deterministic model implies that small improvements in initial conditions near the poverty-trap equilibrium are futile, the stochastic model suggests that the impact of changes in the location of the safety net on the rate of development may be strongest near the poverty-trap equilibrium.

Detection of chaotic determinism in time series from randomly forced maps

NASA Technical Reports Server (NTRS)

Chon, K. H.; Kanters, J. K.; Cohen, R. J.; Holstein-Rathlou, N. H.

1997-01-01

Time series from biological system often display fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". Despite this effort, it has been difficult to establish the presence of chaos in time series from biological sytems. The output from a biological system is probably the result of both its internal dynamics, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes, i.e., a positive characteristic exponent that leads to sensitivity to initial conditions. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Deterministic multidimensional nonuniform gap sampling.

PubMed

Worley, Bradley; Powers, Robert

2015-12-01

Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates to minimize the gaps between sampled grid points. We describe a deterministic gap sampling method, based on the average behavior of Poisson-gap sampling, which performs comparably to its random counterpart with the additional benefit of completely deterministic behavior. We also introduce a general algorithm for multidimensional nonuniform sampling based on a gap equation, and apply it to yield a deterministic sampling scheme that combines burst-mode sampling features with those of Poisson-gap schemes. Finally, we derive a relationship between stochastic gap equations and the expectation value of their sampling probability densities. Copyright © 2015 Elsevier Inc. All rights reserved.

A Comparison of Probabilistic and Deterministic Campaign Analysis for Human Space Exploration

NASA Technical Reports Server (NTRS)

Merrill, R. Gabe; Andraschko, Mark; Stromgren, Chel; Cirillo, Bill; Earle, Kevin; Goodliff, Kandyce

2008-01-01

Human space exploration is by its very nature an uncertain endeavor. Vehicle reliability, technology development risk, budgetary uncertainty, and launch uncertainty all contribute to stochasticity in an exploration scenario. However, traditional strategic analysis has been done in a deterministic manner, analyzing and optimizing the performance of a series of planned missions. History has shown that exploration scenarios rarely follow such a planned schedule. This paper describes a methodology to integrate deterministic and probabilistic analysis of scenarios in support of human space exploration. Probabilistic strategic analysis is used to simulate "possible" scenario outcomes, based upon the likelihood of occurrence of certain events and a set of pre-determined contingency rules. The results of the probabilistic analysis are compared to the nominal results from the deterministic analysis to evaluate the robustness of the scenario to adverse events and to test and optimize contingency planning.

First Order Reliability Application and Verification Methods for Semistatic Structures

NASA Technical Reports Server (NTRS)

Verderaime, Vincent

1994-01-01

Escalating risks of aerostructures stimulated by increasing size, complexity, and cost should no longer be ignored by conventional deterministic safety design methods. The deterministic pass-fail concept is incompatible with probability and risk assessments, its stress audits are shown to be arbitrary and incomplete, and it compromises high strength materials performance. A reliability method is proposed which combines first order reliability principles with deterministic design variables and conventional test technique to surmount current deterministic stress design and audit deficiencies. Accumulative and propagation design uncertainty errors are defined and appropriately implemented into the classical safety index expression. The application is reduced to solving for a factor that satisfies the specified reliability and compensates for uncertainty errors, and then using this factor as, and instead of, the conventional safety factor in stress analyses. The resulting method is consistent with current analytical skills and verification practices, the culture of most designers, and with the pace of semistatic structural designs.

Apparatus for fixing latency

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

Hall, David R; Bartholomew, David B; Moon, Justin

2009-09-08

An apparatus for fixing computational latency within a deterministic region on a network comprises a network interface modem, a high priority module and at least one deterministic peripheral device. The network interface modem is in communication with the network. The high priority module is in communication with the network interface modem. The at least one deterministic peripheral device is connected to the high priority module. The high priority module comprises a packet assembler/disassembler, and hardware for performing at least one operation. Also disclosed is an apparatus for executing at least one instruction on a downhole device within a deterministic region,more » the apparatus comprising a control device, a downhole network, and a downhole device. The control device is near the surface of a downhole tool string. The downhole network is integrated into the tool string. The downhole device is in communication with the downhole network.« less

Stochastic Petri Net extension of a yeast cell cycle model.

PubMed

Mura, Ivan; Csikász-Nagy, Attila

2008-10-21

This paper presents the definition, solution and validation of a stochastic model of the budding yeast cell cycle, based on Stochastic Petri Nets (SPN). A specific family of SPNs is selected for building a stochastic version of a well-established deterministic model. We describe the procedure followed in defining the SPN model from the deterministic ODE model, a procedure that can be largely automated. The validation of the SPN model is conducted with respect to both the results provided by the deterministic one and the experimental results available from literature. The SPN model catches the behavior of the wild type budding yeast cells and a variety of mutants. We show that the stochastic model matches some characteristics of budding yeast cells that cannot be found with the deterministic model. The SPN model fine-tunes the simulation results, enriching the breadth and the quality of its outcome.

Effect of sample volume on metastable zone width and induction time

NASA Astrophysics Data System (ADS)

Kubota, Noriaki

2012-04-01

The metastable zone width (MSZW) and the induction time, measured for a large sample (say>0.1 L) are reproducible and deterministic, while, for a small sample (say<1 mL), these values are irreproducible and stochastic. Such behaviors of MSZW and induction time were theoretically discussed both with stochastic and deterministic models. Equations for the distribution of stochastic MSZW and induction time were derived. The average values of stochastic MSZW and induction time both decreased with an increase in sample volume, while, the deterministic MSZW and induction time remained unchanged. Such different behaviors with variation in sample volume were explained in terms of detection sensitivity of crystallization events. The average values of MSZW and induction time in the stochastic model were compared with the deterministic MSZW and induction time, respectively. Literature data reported for paracetamol aqueous solution were explained theoretically with the presented models.

Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-07-07

Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to a deterministic data communications network through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and the deterministic data communications network; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.

Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-07-14

Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to a deterministic data communications network through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and the deterministic data communications network; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.

Stochastic switching in biology: from genotype to phenotype

NASA Astrophysics Data System (ADS)

Bressloff, Paul C.

2017-03-01

There has been a resurgence of interest in non-equilibrium stochastic processes in recent years, driven in part by the observation that the number of molecules (genes, mRNA, proteins) involved in gene expression are often of order 1-1000. This means that deterministic mass-action kinetics tends to break down, and one needs to take into account the discrete, stochastic nature of biochemical reactions. One of the major consequences of molecular noise is the occurrence of stochastic biological switching at both the genotypic and phenotypic levels. For example, individual gene regulatory networks can switch between graded and binary responses, exhibit translational/transcriptional bursting, and support metastability (noise-induced switching between states that are stable in the deterministic limit). If random switching persists at the phenotypic level then this can confer certain advantages to cell populations growing in a changing environment, as exemplified by bacterial persistence in response to antibiotics. Gene expression at the single-cell level can also be regulated by changes in cell density at the population level, a process known as quorum sensing. In contrast to noise-driven phenotypic switching, the switching mechanism in quorum sensing is stimulus-driven and thus noise tends to have a detrimental effect. A common approach to modeling stochastic gene expression is to assume a large but finite system and to approximate the discrete processes by continuous processes using a system-size expansion. However, there is a growing need to have some familiarity with the theory of stochastic processes that goes beyond the standard topics of chemical master equations, the system-size expansion, Langevin equations and the Fokker-Planck equation. Examples include stochastic hybrid systems (piecewise deterministic Markov processes), large deviations and the Wentzel-Kramers-Brillouin (WKB) method, adiabatic reductions, and queuing/renewal theory. The major aim of this review is to provide a self-contained survey of these mathematical methods, mainly within the context of biological switching processes at both the genotypic and phenotypic levels. However, applications to other examples of biological switching are also discussed, including stochastic ion channels, diffusion in randomly switching environments, bacterial chemotaxis, and stochastic neural networks.

Effects of stochastic time-delayed feedback on a dynamical system modeling a chemical oscillator.

PubMed

González Ochoa, Héctor O; Perales, Gualberto Solís; Epstein, Irving R; Femat, Ricardo

2018-05-01

We examine how stochastic time-delayed negative feedback affects the dynamical behavior of a model oscillatory reaction. We apply constant and stochastic time-delayed negative feedbacks to a point Field-Körös-Noyes photosensitive oscillator and compare their effects. Negative feedback is applied in the form of simulated inhibitory electromagnetic radiation with an intensity proportional to the concentration of oxidized light-sensitive catalyst in the oscillator. We first characterize the system under nondelayed inhibitory feedback; then we explore and compare the effects of constant (deterministic) versus stochastic time-delayed feedback. We find that the oscillatory amplitude, frequency, and waveform are essentially preserved when low-dispersion stochastic delayed feedback is used, whereas small but measurable changes appear when a large dispersion is applied.

Effects of stochastic time-delayed feedback on a dynamical system modeling a chemical oscillator

NASA Astrophysics Data System (ADS)

González Ochoa, Héctor O.; Perales, Gualberto Solís; Epstein, Irving R.; Femat, Ricardo

2018-05-01

We examine how stochastic time-delayed negative feedback affects the dynamical behavior of a model oscillatory reaction. We apply constant and stochastic time-delayed negative feedbacks to a point Field-Körös-Noyes photosensitive oscillator and compare their effects. Negative feedback is applied in the form of simulated inhibitory electromagnetic radiation with an intensity proportional to the concentration of oxidized light-sensitive catalyst in the oscillator. We first characterize the system under nondelayed inhibitory feedback; then we explore and compare the effects of constant (deterministic) versus stochastic time-delayed feedback. We find that the oscillatory amplitude, frequency, and waveform are essentially preserved when low-dispersion stochastic delayed feedback is used, whereas small but measurable changes appear when a large dispersion is applied.

Topological protection of multiparticle dissipative transport

NASA Astrophysics Data System (ADS)

Loehr, Johannes; Loenne, Michael; Ernst, Adrian; de Las Heras, Daniel; Fischer, Thomas M.

2016-06-01

Topological protection allows robust transport of localized phenomena such as quantum information, solitons and dislocations. The transport can be either dissipative or non-dissipative. Here, we experimentally demonstrate and theoretically explain the topologically protected dissipative motion of colloidal particles above a periodic hexagonal magnetic pattern. By driving the system with periodic modulation loops of an external and spatially homogeneous magnetic field, we achieve total control over the motion of diamagnetic and paramagnetic colloids. We can transport simultaneously and independently each type of colloid along any of the six crystallographic directions of the pattern via adiabatic or deterministic ratchet motion. Both types of motion are topologically protected. As an application, we implement an automatic topologically protected quality control of a chemical reaction between functionalized colloids. Our results are relevant to other systems with the same symmetry.

The noisy edge of traveling waves

PubMed Central

Hallatschek, Oskar

2011-01-01

Traveling waves are ubiquitous in nature and control the speed of many important dynamical processes, including chemical reactions, epidemic outbreaks, and biological evolution. Despite their fundamental role in complex systems, traveling waves remain elusive because they are often dominated by rare fluctuations in the wave tip, which have defied any rigorous analysis so far. Here, we show that by adjusting nonlinear model details, noisy traveling waves can be solved exactly. The moment equations of these tuned models are closed and have a simple analytical structure resembling the deterministic approximation supplemented by a nonlocal cutoff term. The peculiar form of the cutoff shapes the noisy edge of traveling waves and is critical for the correct prediction of the wave speed and its fluctuations. Our approach is illustrated and benchmarked using the example of fitness waves arising in simple models of microbial evolution, which are highly sensitive to number fluctuations. We demonstrate explicitly how these models can be tuned to account for finite population sizes and determine how quickly populations adapt as a function of population size and mutation rates. More generally, our method is shown to apply to a broad class of models, in which number fluctuations are generated by branching processes. Because of this versatility, the method of model tuning may serve as a promising route toward unraveling universal properties of complex discrete particle systems. PMID:21187435

Typewriting rate as a function of reaction time.

PubMed

Hayes, V; Wilson, G D; Schafer, R L

1977-12-01

This study was designed to determine the relationship between reaction time and typewriting rate. Subjects were 24 typists ranging in age from 19 to 39 yr. Reaction times (.001 sec) to a light were recorded for each finger and to each alphabetic character and three punctuation marks. Analysis of variance yielded significant differences in reaction time among subjects and fingers. Correlation between typewriting rate and average reaction time to the alphabetic characters and three punctuation marks was --.75. Correlation between typewriting rate and the difference between the reaction time of the hands was --.42. Factors influencing typewriting rate may include reaction time of the fingers, difference between the reaction time of the hands, and reaction time to individual keys on the typewriter. Implications exist for instructional methodology and further research.

Realistic Simulation for Body Area and Body-To-Body Networks

PubMed Central

Alam, Muhammad Mahtab; Ben Hamida, Elyes; Ben Arbia, Dhafer; Maman, Mickael; Mani, Francesco; Denis, Benoit; D’Errico, Raffaele

2016-01-01

In this paper, we present an accurate and realistic simulation for body area networks (BAN) and body-to-body networks (BBN) using deterministic and semi-deterministic approaches. First, in the semi-deterministic approach, a real-time measurement campaign is performed, which is further characterized through statistical analysis. It is able to generate link-correlated and time-varying realistic traces (i.e., with consistent mobility patterns) for on-body and body-to-body shadowing and fading, including body orientations and rotations, by means of stochastic channel models. The full deterministic approach is particularly targeted to enhance IEEE 802.15.6 proposed channel models by introducing space and time variations (i.e., dynamic distances) through biomechanical modeling. In addition, it helps to accurately model the radio link by identifying the link types and corresponding path loss factors for line of sight (LOS) and non-line of sight (NLOS). This approach is particularly important for links that vary over time due to mobility. It is also important to add that the communication and protocol stack, including the physical (PHY), medium access control (MAC) and networking models, is developed for BAN and BBN, and the IEEE 802.15.6 compliance standard is provided as a benchmark for future research works of the community. Finally, the two approaches are compared in terms of the successful packet delivery ratio, packet delay and energy efficiency. The results show that the semi-deterministic approach is the best option; however, for the diversity of the mobility patterns and scenarios applicable, biomechanical modeling and the deterministic approach are better choices. PMID:27104537

Realistic Simulation for Body Area and Body-To-Body Networks.

PubMed

Alam, Muhammad Mahtab; Ben Hamida, Elyes; Ben Arbia, Dhafer; Maman, Mickael; Mani, Francesco; Denis, Benoit; D'Errico, Raffaele

2016-04-20

In this paper, we present an accurate and realistic simulation for body area networks (BAN) and body-to-body networks (BBN) using deterministic and semi-deterministic approaches. First, in the semi-deterministic approach, a real-time measurement campaign is performed, which is further characterized through statistical analysis. It is able to generate link-correlated and time-varying realistic traces (i.e., with consistent mobility patterns) for on-body and body-to-body shadowing and fading, including body orientations and rotations, by means of stochastic channel models. The full deterministic approach is particularly targeted to enhance IEEE 802.15.6 proposed channel models by introducing space and time variations (i.e., dynamic distances) through biomechanical modeling. In addition, it helps to accurately model the radio link by identifying the link types and corresponding path loss factors for line of sight (LOS) and non-line of sight (NLOS). This approach is particularly important for links that vary over time due to mobility. It is also important to add that the communication and protocol stack, including the physical (PHY), medium access control (MAC) and networking models, is developed for BAN and BBN, and the IEEE 802.15.6 compliance standard is provided as a benchmark for future research works of the community. Finally, the two approaches are compared in terms of the successful packet delivery ratio, packet delay and energy efficiency. The results show that the semi-deterministic approach is the best option; however, for the diversity of the mobility patterns and scenarios applicable, biomechanical modeling and the deterministic approach are better choices.

Sensitivity analysis of the parameters of an HIV/AIDS model with condom campaign and antiretroviral therapy

NASA Astrophysics Data System (ADS)

Marsudi, Hidayat, Noor; Wibowo, Ratno Bagus Edy

2017-12-01

In this article, we present a deterministic model for the transmission dynamics of HIV/AIDS in which condom campaign and antiretroviral therapy are both important for the disease management. We calculate the effective reproduction number using the next generation matrix method and investigate the local and global stability of the disease-free equilibrium of the model. Sensitivity analysis of the effective reproduction number with respect to the model parameters were carried out. Our result shows that efficacy rate of condom campaign, transmission rate for contact with the asymptomatic infective, progression rate from the asymptomatic infective to the pre-AIDS infective, transmission rate for contact with the pre-AIDS infective, ARV therapy rate, proportion of the susceptible receiving condom campaign and proportion of the pre-AIDS receiving ARV therapy are highly sensitive parameters that effect the transmission dynamics of HIV/AIDS infection.

({The) Solar System Large Planets influence on a new Maunder Miniμm}

NASA Astrophysics Data System (ADS)

Yndestad, Harald; Solheim, Jan-Erik

2016-04-01

In 1890´s G. Spörer and E. W. Maunder (1890) reported that the solar activity stopped in a period of 70 years from 1645 to 1715. Later a reconstruction of the solar activity confirms the grand minima Maunder (1640-1720), Spörer (1390-1550), Wolf (1270-1340), and the minima Oort (1010-1070) and Dalton (1785-1810) since the year 1000 A.D. (Usoskin et al. 2007). These minimum periods have been associated with less irradiation from the Sun and cold climate periods on Earth. An identification of a three grand Maunder type periods and two Dalton type periods in a period thousand years, indicates that sooner or later there will be a colder climate on Earth from a new Maunder- or Dalton- type period. The cause of these minimum periods, are not well understood. An expected new Maunder-type period is based on the properties of solar variability. If the solar variability has a deterministic element, we can estimate better a new Maunder grand minimum. A random solar variability can only explain the past. This investigation is based on the simple idea that if the solar variability has a deterministic property, it must have a deterministic source, as a first cause. If this deterministic source is known, we can compute better estimates the next expected Maunder grand minimum period. The study is based on a TSI ACRIM data series from 1700, a TSI ACRIM data series from 1000 A.D., sunspot data series from 1611 and a Solar Barycenter orbit data series from 1000. The analysis method is based on a wavelet spectrum analysis, to identify stationary periods, coincidence periods and their phase relations. The result shows that the TSI variability and the sunspots variability have deterministic oscillations, controlled by the large planets Jupiter, Uranus and Neptune, as the first cause. A deterministic model of TSI variability and sunspot variability confirms the known minimum and grand minimum periods since 1000. From this deterministic model we may expect a new Maunder type sunspot minimum period from about 2018 to 2055. The deterministic model of a TSI ACRIM data series from 1700 computes a new Maunder type grand minimum period from 2015 to 2071. A model of the longer TSI ACRIM data series from 1000 computes a new Dalton to Maunder type minimum irradiation period from 2047 to 2068.

What Is a Reaction Rate?

ERIC Educational Resources Information Center

Schmitz, Guy

2005-01-01

The definition of reaction rate is derived and demonstrations are made for the care to be taken while using the term. Reaction rate can be in terms of a reaction property, the extent of reaction and thus it is possible to give a definition applicable in open and closed systems.

Development of Fast Deterministic Physically Accurate Solvers for Kinetic Collision Integral for Applications of Near Space Flight and Control Devices

DTIC Science & Technology

2015-08-31

following functions were used: where are the Legendre polynomials of degree . It is assumed that the coefficient standing with has the form...enforce relaxation rates of high order moments, higher order polynomial basis functions are used. The use of high order polynomials results in strong...enforced while only polynomials up to second degree were used in the representation of the collision frequency. It can be seen that the new model

Microcanonical model for interface formation

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

Rucklidge, A.; Zaleski, S.

1988-04-01

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

Modeling seasonal measles transmission in China

NASA Astrophysics Data System (ADS)

Bai, Zhenguo; Liu, Dan

2015-08-01

A discrete-time deterministic measles model with periodic transmission rate is formulated and studied. The basic reproduction number R0 is defined and used as the threshold parameter in determining the dynamics of the model. It is shown that the disease will die out if R0 < 1 , and the disease will persist in the population if R0 > 1 . Parameters in the model are estimated on the basis of demographic and epidemiological data. Numerical simulations are presented to describe the seasonal fluctuation of measles infection in China.

Correlations in electrically coupled chaotic lasers.

PubMed

Rosero, E J; Barbosa, W A S; Martinez Avila, J F; Khoury, A Z; Rios Leite, J R

2016-09-01

We show how two electrically coupled semiconductor lasers having optical feedback can present simultaneous antiphase correlated fast power fluctuations, and strong in-phase synchronized spikes of chaotic power drops. This quite counterintuitive phenomenon is demonstrated experimentally and confirmed by numerical solutions of a deterministic dynamical system of rate equations. The occurrence of negative and positive cross correlation between parts of a complex system according to time scales, as proved in our simple arrangement, is relevant for the understanding and characterization of collective properties in complex networks.

Heralded ions via ionization coincidence

NASA Astrophysics Data System (ADS)

McCulloch, A. J.; Speirs, R. W.; Wissenberg, S. H.; Tielen, R. P. M.; Sparkes, B. M.; Scholten, R. E.

2018-04-01

We demonstrate a method for the deterministic production of single ions by exploiting the correlation between an electron and associated ion following ionization. Coincident detection and feedback in combination with Coulomb-driven particle selection allows for high-fidelity heralding of ions at a high repetition rate. Extension of the scheme beyond time-correlated feedback to position- and momentum-correlated feedback will provide a general and powerful means to optimize the ion beam brightness for the development of next-generation focused ion beam technologies.

Evaluating the risk of death via the hematopoietic syndrome mode for prolonged exposure of nuclear workers to radiation delivered at very low rates.

PubMed

Scott, B R; Lyzlov, A F; Osovets, S V

1998-05-01

During a Phase-I effort, studies were planned to evaluate deterministic (nonstochastic) effects of chronic exposure of nuclear workers at the Mayak atomic complex in the former Soviet Union to relatively high levels (> 0.25 Gy) of ionizing radiation. The Mayak complex has been used, since the late 1940's, to produce plutonium for nuclear weapons. Workers at Site A of the complex were involved in plutonium breeding using nuclear reactors, and some were exposed to relatively large doses of gamma rays plus relatively small neutron doses. The Weibull normalized-dose model, which has been set up to evaluate the risk of specific deterministic effects of combined, continuous exposure of humans to alpha, beta, and gamma radiations, is here adapted for chronic exposure to gamma rays and neutrons during repeated 6-h work shifts--as occurred for some nuclear workers at Site A. Using the adapted model, key conclusions were reached that will facilitate a Phase-II study of deterministic effects among Mayak workers. These conclusions include the following: (1) neutron doses may be more important for Mayak workers than for Japanese A-bomb victims in Hiroshima and can be accounted for using an adjusted dose (which accounts for neutron relative biological effectiveness); (2) to account for dose-rate effects, normalized dose X (a dimensionless fraction of an LD50 or ED50) can be evaluated in terms of an adjusted dose; (3) nonlinear dose-response curves for the risk of death via the hematopoietic mode can be converted to linear dose-response curves (for low levels of risk) using a newly proposed dimensionless dose, D = X(V), in units of Oklad (where D is pronounced "deh"), and V is the shape parameter in the Weibull model; (4) for X < or = Xo, where Xo is the threshold normalized dose, D = 0; (5) unlike absorbed dose, the dose D can be averaged over different Mayak workers in order to calculate the average risk of death via the hematopoietic mode for the population exposed at Site A; and (6) the expected cases of death via the hematopoietic syndrome mode for Mayak workers chronically exposed during work shifts at Site A to gamma rays and neutrons can be predicted using ln(2)B M[D]; where B (pronounced "beh") is the number of workers at risk (criticality accident victims excluded); and M[D] is the average (mean) value of D (averaged over the worker population at risk, for Site A, for the time period considered). These results can be used to facilitate a Phase II study of deterministic radiation effects among Mayak workers chronically exposed to gamma rays and neutrons.

Solving difficult problems creatively: a role for energy optimised deterministic/stochastic hybrid computing

PubMed Central

Palmer, Tim N.; O’Shea, Michael

2015-01-01

How is the brain configured for creativity? What is the computational substrate for ‘eureka’ moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal (ultimately quantum decoherent) noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete. PMID:26528173

Deterministic and efficient quantum cryptography based on Bell's theorem

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

Chen Zengbing; Pan Jianwei; Physikalisches Institut, Universitaet Heidelberg, Philosophenweg 12, 69120 Heidelberg

2006-05-15

We propose a double-entanglement-based quantum cryptography protocol that is both efficient and deterministic. The proposal uses photon pairs with entanglement both in polarization and in time degrees of freedom; each measurement in which both of the two communicating parties register a photon can establish one and only one perfect correlation, and thus deterministically create a key bit. Eavesdropping can be detected by violation of local realism. A variation of the protocol shows a higher security, similar to the six-state protocol, under individual attacks. Our scheme allows a robust implementation under the current technology.

Stochastic assembly in a subtropical forest chronosequence: evidence from contrasting changes of species, phylogenetic and functional dissimilarity over succession.

PubMed

Mi, Xiangcheng; Swenson, Nathan G; Jia, Qi; Rao, Mide; Feng, Gang; Ren, Haibao; Bebber, Daniel P; Ma, Keping

2016-09-07

Deterministic and stochastic processes jointly determine the community dynamics of forest succession. However, it has been widely held in previous studies that deterministic processes dominate forest succession. Furthermore, inference of mechanisms for community assembly may be misleading if based on a single axis of diversity alone. In this study, we evaluated the relative roles of deterministic and stochastic processes along a disturbance gradient by integrating species, functional, and phylogenetic beta diversity in a subtropical forest chronosequence in Southeastern China. We found a general pattern of increasing species turnover, but little-to-no change in phylogenetic and functional turnover over succession at two spatial scales. Meanwhile, the phylogenetic and functional beta diversity were not significantly different from random expectation. This result suggested a dominance of stochastic assembly, contrary to the general expectation that deterministic processes dominate forest succession. On the other hand, we found significant interactions of environment and disturbance and limited evidence for significant deviations of phylogenetic or functional turnover from random expectations for different size classes. This result provided weak evidence of deterministic processes over succession. Stochastic assembly of forest succession suggests that post-disturbance restoration may be largely unpredictable and difficult to control in subtropical forests.

Discrete-State Stochastic Models of Calcium-Regulated Calcium Influx and Subspace Dynamics Are Not Well-Approximated by ODEs That Neglect Concentration Fluctuations

PubMed Central

Weinberg, Seth H.; Smith, Gregory D.

2012-01-01

Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597

Mixing Single Scattering Properties in Vector Radiative Transfer for Deterministic and Stochastic Solutions

NASA Astrophysics Data System (ADS)

Mukherjee, L.; Zhai, P.; Hu, Y.; Winker, D. M.

2016-12-01

Among the primary factors, which determine the polarized radiation, field of a turbid medium are the single scattering properties of the medium. When multiple types of scatterers are present, the single scattering properties of the scatterers need to be properly mixed in order to find the solutions to the vector radiative transfer theory (VRT). The VRT solvers can be divided into two types: deterministic and stochastic. The deterministic solver can only accept one set of single scattering property in its smallest discretized spatial volume. When the medium contains more than one kind of scatterer, their single scattering properties are averaged, and then used as input for the deterministic solver. The stochastic solver, can work with different kinds of scatterers explicitly. In this work, two different mixing schemes are studied using the Successive Order of Scattering (SOS) method and Monte Carlo (MC) methods. One scheme is used for deterministic and the other is used for the stochastic Monte Carlo method. It is found that the solutions from the two VRT solvers using two different mixing schemes agree with each other extremely well. This confirms the equivalence to the two mixing schemes and also provides a benchmark for the VRT solution for the medium studied.

A simple reaction-rate model for turbulent diffusion flames

NASA Technical Reports Server (NTRS)

Bangert, L. H.

1975-01-01

A simple reaction rate model is proposed for turbulent diffusion flames in which the reaction rate is proportional to the turbulence mixing rate. The reaction rate is also dependent on the mean mass fraction and the mean square fluctuation of mass fraction of each reactant. Calculations are compared with experimental data and are generally successful in predicting the measured quantities.

Effect of static porosity fluctuations on reactive transport in a porous medium

NASA Astrophysics Data System (ADS)

L'Heureux, Ivan

2018-02-01

Reaction-diffusive transport phenomena in porous media are ubiquitous in engineering applications, biological and geochemical systems. The porosity field is usually random in space, but most models consider the porosity field as a well-defined deterministic function of space and time and ignore the porosity fluctuations. They use a reaction-diffusion equation written in terms of an average porosity and average concentration fields. In this contribution, we treat explicitly the effect of spatial porosity fluctuations on the dynamics of a concentration field for the case of a one-dimensional reaction-transport system with nonlinear kinetics. Three basic assumptions are considered. (i) The porosity fluctuations are assumed to have Gaussian properties and an arbitrary variance; (ii) we assume that the noise correlation length is small compared to the relevant macroscopic length scale; (iii) and we assume that the kinetics of the reactive term in the equations for the fluctuations is a self-consistently determined constant. Elimination of the fluctuating part of the concentration field from the dynamics leads to a renormalized equation involving the average concentration field. It is shown that the noise leads to a renormalized (generally smaller) diffusion coefficient and renormalized kinetics. Within the framework of the approximations used, numerical simulations are in agreement with our theory. We show that the porosity fluctuations may have a significant effect on the transport of a reactive species, even in the case of a homogeneous average porosity.

On the ambiguity of the reaction rate constants in multivariate curve resolution for reversible first-order reaction systems.

PubMed

Schröder, Henning; Sawall, Mathias; Kubis, Christoph; Selent, Detlef; Hess, Dieter; Franke, Robert; Börner, Armin; Neymeyr, Klaus

2016-07-13

If for a chemical reaction with a known reaction mechanism the concentration profiles are accessible only for certain species, e.g. only for the main product, then often the reaction rate constants cannot uniquely be determined from the concentration data. This is a well-known fact which includes the so-called slow-fast ambiguity. This work combines the question of unique or non-unique reaction rate constants with factor analytic methods of chemometrics. The idea is to reduce the rotational ambiguity of pure component factorizations by considering only those concentration factors which are possible solutions of the kinetic equations for a properly adapted set of reaction rate constants. The resulting set of reaction rate constants corresponds to those solutions of the rate equations which appear as feasible factors in a pure component factorization. The new analysis of the ambiguity of reaction rate constants extends recent research activities on the Area of Feasible Solutions (AFS). The consistency with a given chemical reaction scheme is shown to be a valuable tool in order to reduce the AFS. The new methods are applied to model and experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

Probabilistic Modeling of the Renal Stone Formation Module

NASA Technical Reports Server (NTRS)

Best, Lauren M.; Myers, Jerry G.; Goodenow, Debra A.; McRae, Michael P.; Jackson, Travis C.

2013-01-01

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

Reaction Event Counting Statistics of Biopolymer Reaction Systems with Dynamic Heterogeneity.

PubMed

Lim, Yu Rim; Park, Seong Jun; Park, Bo Jung; Cao, Jianshu; Silbey, Robert J; Sung, Jaeyoung

2012-04-10

We investigate the reaction event counting statistics (RECS) of an elementary biopolymer reaction in which the rate coefficient is dependent on states of the biopolymer and the surrounding environment and discover a universal kinetic phase transition in the RECS of the reaction system with dynamic heterogeneity. From an exact analysis for a general model of elementary biopolymer reactions, we find that the variance in the number of reaction events is dependent on the square of the mean number of the reaction events when the size of measurement time is small on the relaxation time scale of rate coefficient fluctuations, which does not conform to renewal statistics. On the other hand, when the size of the measurement time interval is much greater than the relaxation time of rate coefficient fluctuations, the variance becomes linearly proportional to the mean reaction number in accordance with renewal statistics. Gillespie's stochastic simulation method is generalized for the reaction system with a rate coefficient fluctuation. The simulation results confirm the correctness of the analytic results for the time dependent mean and variance of the reaction event number distribution. On the basis of the obtained results, we propose a method of quantitative analysis for the reaction event counting statistics of reaction systems with rate coefficient fluctuations, which enables one to extract information about the magnitude and the relaxation times of the fluctuating reaction rate coefficient, without a bias that can be introduced by assuming a particular kinetic model of conformational dynamics and the conformation dependent reactivity. An exact relationship is established between a higher moment of the reaction event number distribution and the multitime correlation of the reaction rate for the reaction system with a nonequilibrium initial state distribution as well as for the system with the equilibrium initial state distribution.

Evaluation of biofidelity of THUMS pedestrian model under a whole-body impact conditions with a generic sedan buck.

PubMed

Wu, Taotao; Kim, Taewung; Bollapragada, Varun; Poulard, David; Chen, Huipeng; Panzer, Matthew B; Forman, Jason L; Crandall, Jeff R; Pipkorn, Bengt

2017-05-29

The goal of this study was to evaluate the biofidelity of the Total Human Model for Safety (THUMS; Ver. 4.01) pedestrian finite element models (PFEM) in a whole-body pedestrian impact condition using a well-characterized generic pedestrian buck model. The biofidelity of THUMS PFEM was evaluated with respect to data from 3 full-scale postmortem human subject (PMHS) pedestrian impact tests, in which a pedestrian buck laterally struck the subjects using a pedestrian buck at 40 km/h. The pedestrian model was scaled to match the anthropometry of the target subjects and then positioned to match the pre-impact postures of the target subjects based on the 3-dimensional motion tracking data obtained during the experiments. An objective rating method was employed to quantitatively evaluate the correlation between the responses of the models and the PMHS. Injuries in the models were predicted both probabilistically and deterministically using empirical injury risk functions and strain measures, respectively, and compared with those of the target PMHS. In general, the model exhibited biofidelic kinematic responses (in the Y-Z plane) regarding trajectories (International Organization for Standardization [ISO] ratings: Y = 0.90 ± 0.11, Z = 0.89 ± 0.09), linear resultant velocities (ISO ratings: 0.83 ± 0.07), accelerations (ISO ratings: Y = 0.58 ± 0.11, Z = 0.52 ± 0.12), and angular velocities (ISO ratings: X = 0.48 ± 0.13) but exhibited stiffer leg responses and delayed head responses compared to those of the PMHS. This indicates potential biofidelity issues with the PFEM for regions below the knee and in the neck. The model also demonstrated comparable reaction forces at the buck front-end regions to those from the PMHS tests. The PFEM generally predicted the injuries that the PMHS sustained but overestimated injuries in the ankle and leg regions. Based on the data considered, the THUMS PFEM was considered to be biofidelic for this pedestrian impact condition and vehicle. Given the capability of the model to reproduce biomechanical responses, it shows potential as a valuable tool for developing novel pedestrian safety systems.

Representing Rate Equations for Enzyme-Catalyzed Reactions

ERIC Educational Resources Information Center

Ault, Addison

2011-01-01

Rate equations for enzyme-catalyzed reactions are derived and presented in a way that makes it easier for the nonspecialist to see how the rate of an enzyme-catalyzed reaction depends upon kinetic constants and concentrations. This is done with distribution equations that show how the rate of the reaction depends upon the relative quantities of…

Renyi entropy measures of heart rate Gaussianity.

PubMed

Lake, Douglas E

2006-01-01

Sample entropy and approximate entropy are measures that have been successfully utilized to study the deterministic dynamics of heart rate (HR). A complementary stochastic point of view and a heuristic argument using the Central Limit Theorem suggests that the Gaussianity of HR is a complementary measure of the physiological complexity of the underlying signal transduction processes. Renyi entropy (or q-entropy) is a widely used measure of Gaussianity in many applications. Particularly important members of this family are differential (or Shannon) entropy (q = 1) and quadratic entropy (q = 2). We introduce the concepts of differential and conditional Renyi entropy rate and, in conjunction with Burg's theorem, develop a measure of the Gaussianity of a linear random process. Robust algorithms for estimating these quantities are presented along with estimates of their standard errors.

Beyond the conventional understanding of water-rock reactivity

NASA Astrophysics Data System (ADS)

Fischer, Cornelius; Luttge, Andreas

2017-01-01

A common assumption is that water-rock reaction rates should converge to a mean value. There is, however, an emerging consensus on the genuine nature of reaction rate variations under identical chemical conditions. Thus, the further use of mean reaction rates for the prediction of material fluxes is environmentally and economically risky, manifest for example in the management of nuclear waste or the evolution of reservoir rocks. Surface-sensitive methods and resulting information about heterogeneous surface reactivity illustrate the inherent rate variability. Consequently, a statistical analysis was developed in order to quantify the heterogeneity of surface rates. We show how key components of the rate combine to give an overall rate and how the identification of those individual rate contributors provide mechanistic insight into complex heterogeneous reactions. This generates a paradigm change by proposing a new pathway to reaction model parameterization and for the prediction of reaction rates.

Deterministic models for traffic jams

NASA Astrophysics Data System (ADS)

Nagel, Kai; Herrmann, Hans J.

1993-10-01

We study several deterministic one-dimensional traffic models. For integer positions and velocities we find the typical high and low density phases separated by a simple transition. If positions and velocities are continuous variables the model shows self-organized critically driven by the slowest car.

Kinetic phase evolution of spinel cobalt oxide during lithiation

DOE PAGES

Li, Jing; He, Kai; Meng, Qingping; ...

2016-09-15

Spinel cobalt oxide has been proposed to undergo a multiple-step reaction during the electrochemical lithiation process. Understanding the kinetics of the lithiation process in this compound is crucial to optimize its performance and cyclability. In this work, we have utilized a low-angle annular dark-field scanning transmission electron microscopy method to visualize the dynamic reaction process in real time and study the reaction kinetics at different rates. We show that the particles undergo a two-step reaction at the single-particle level, which includes an initial intercalation reaction followed by a conversion reaction. At low rates, the conversion reaction starts after the intercalationmore » reaction has fully finished, consistent with the prediction of density functional theoretical calculations. At high rates, the intercalation reaction is overwhelmed by the subsequently nucleated conversion reaction, and the reaction speeds of both the intercalation and conversion reactions are increased. Phase-field simulations show the crucial role of surface diffusion rates of lithium ions in controlling this process. Furthermore, this work provides microscopic insights into the reaction dynamics in non-equilibrium conditions and highlights the effect of lithium diffusion rates on the overall reaction homogeneity as well as the performance.« less

Kinetic phase evolution of spinel cobalt oxide during lithiation

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

Li, Jing; He, Kai; Meng, Qingping

Spinel cobalt oxide has been proposed to undergo a multiple-step reaction during the electrochemical lithiation process. Understanding the kinetics of the lithiation process in this compound is crucial to optimize its performance and cyclability. In this work, we have utilized a low-angle annular dark-field scanning transmission electron microscopy method to visualize the dynamic reaction process in real time and study the reaction kinetics at different rates. We show that the particles undergo a two-step reaction at the single-particle level, which includes an initial intercalation reaction followed by a conversion reaction. At low rates, the conversion reaction starts after the intercalationmore » reaction has fully finished, consistent with the prediction of density functional theoretical calculations. At high rates, the intercalation reaction is overwhelmed by the subsequently nucleated conversion reaction, and the reaction speeds of both the intercalation and conversion reactions are increased. Phase-field simulations show the crucial role of surface diffusion rates of lithium ions in controlling this process. Furthermore, this work provides microscopic insights into the reaction dynamics in non-equilibrium conditions and highlights the effect of lithium diffusion rates on the overall reaction homogeneity as well as the performance.« less

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

The meta-Gaussian Bayesian Processor of forecasts and associated preliminary experiments

NASA Astrophysics Data System (ADS)

Chen, Fajing; Jiao, Meiyan; Chen, Jing

2013-04-01

Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.

Deterministic Factors Overwhelm Stochastic Environmental Fluctuations as Drivers of Jellyfish Outbreaks.

PubMed

Benedetti-Cecchi, Lisandro; Canepa, Antonio; Fuentes, Veronica; Tamburello, Laura; Purcell, Jennifer E; Piraino, Stefano; Roberts, Jason; Boero, Ferdinando; Halpin, Patrick

2015-01-01

Jellyfish outbreaks are increasingly viewed as a deterministic response to escalating levels of environmental degradation and climate extremes. However, a comprehensive understanding of the influence of deterministic drivers and stochastic environmental variations favouring population renewal processes has remained elusive. This study quantifies the deterministic and stochastic components of environmental change that lead to outbreaks of the jellyfish Pelagia noctiluca in the Mediterranen Sea. Using data of jellyfish abundance collected at 241 sites along the Catalan coast from 2007 to 2010 we: (1) tested hypotheses about the influence of time-varying and spatial predictors of jellyfish outbreaks; (2) evaluated the relative importance of stochastic vs. deterministic forcing of outbreaks through the environmental bootstrap method; and (3) quantified return times of extreme events. Outbreaks were common in May and June and less likely in other summer months, which resulted in a negative relationship between outbreaks and SST. Cross- and along-shore advection by geostrophic flow were important concentrating forces of jellyfish, but most outbreaks occurred in the proximity of two canyons in the northern part of the study area. This result supported the recent hypothesis that canyons can funnel P. noctiluca blooms towards shore during upwelling. This can be a general, yet unappreciated mechanism leading to outbreaks of holoplanktonic jellyfish species. The environmental bootstrap indicated that stochastic environmental fluctuations have negligible effects on return times of outbreaks. Our analysis emphasized the importance of deterministic processes leading to jellyfish outbreaks compared to the stochastic component of environmental variation. A better understanding of how environmental drivers affect demographic and population processes in jellyfish species will increase the ability to anticipate jellyfish outbreaks in the future.

Deterministic MDI QKD with two secret bits per shared entangled pair

NASA Astrophysics Data System (ADS)

Zebboudj, Sofia; Omar, Mawloud

2018-03-01

Although quantum key distribution schemes have been proven theoretically secure, they are based on assumptions about the devices that are not yet satisfied with today's technology. The measurement-device-independent scheme has been proposed to shorten the gap between theory and practice by removing all detector side-channel attacks. On the other hand, two-way quantum key distribution schemes have been proposed to raise the secret key generation rate. In this paper, we propose a new quantum key distribution scheme able to achieve a relatively high secret key generation rate based on two-way quantum key distribution that also inherits the robustness of the measurement-device-independent scheme against detector side-channel attacks.

Stochastic gain in finite populations

NASA Astrophysics Data System (ADS)

Röhl, Torsten; Traulsen, Arne; Claussen, Jens Christian; Schuster, Heinz Georg

2008-08-01

Flexible learning rates can lead to increased payoffs under the influence of noise. In a previous paper [Traulsen , Phys. Rev. Lett. 93, 028701 (2004)], we have demonstrated this effect based on a replicator dynamics model which is subject to external noise. Here, we utilize recent advances on finite population dynamics and their connection to the replicator equation to extend our findings and demonstrate the stochastic gain effect in finite population systems. Finite population dynamics is inherently stochastic, depending on the population size and the intensity of selection, which measures the balance between the deterministic and the stochastic parts of the dynamics. This internal noise can be exploited by a population using an appropriate microscopic update process, even if learning rates are constant.

A reliable simultaneous representation of seismic hazard and of ground shaking recurrence

NASA Astrophysics Data System (ADS)

Peresan, A.; Panza, G. F.; Magrin, A.; Vaccari, F.

2015-12-01

Different earthquake hazard maps may be appropriate for different purposes - such as emergency management, insurance and engineering design. Accounting for the lower occurrence rate of larger sporadic earthquakes may allow to formulate cost-effective policies in some specific applications, provided that statistically sound recurrence estimates are used, which is not typically the case of PSHA (Probabilistic Seismic Hazard Assessment). We illustrate the procedure to associate the expected ground motions from Neo-deterministic Seismic Hazard Assessment (NDSHA) to an estimate of their recurrence. Neo-deterministic refers to a scenario-based approach, which allows for the construction of a broad range of earthquake scenarios via full waveforms modeling. From the synthetic seismograms the estimates of peak ground acceleration, velocity and displacement, or any other parameter relevant to seismic engineering, can be extracted. NDSHA, in its standard form, defines the hazard computed from a wide set of scenario earthquakes (including the largest deterministically or historically defined credible earthquake, MCE) and it does not supply the frequency of occurrence of the expected ground shaking. A recent enhanced variant of NDSHA that reliably accounts for recurrence has been developed and it is applied to the Italian territory. The characterization of the frequency-magnitude relation can be performed by any statistically sound method supported by data (e.g. multi-scale seismicity model), so that a recurrence estimate is associated to each of the pertinent sources. In this way a standard NDSHA map of ground shaking is obtained simultaneously with the map of the corresponding recurrences. The introduction of recurrence estimates in NDSHA naturally allows for the generation of ground shaking maps at specified return periods. This permits a straightforward comparison between NDSHA and PSHA maps.

Deterministic quantum teleportation with feed-forward in a solid state system.

PubMed

Steffen, L; Salathe, Y; Oppliger, M; Kurpiers, P; Baur, M; Lang, C; Eichler, C; Puebla-Hellmann, G; Fedorov, A; Wallraff, A

2013-08-15

Engineered macroscopic quantum systems based on superconducting electronic circuits are attractive for experimentally exploring diverse questions in quantum information science. At the current state of the art, quantum bits (qubits) are fabricated, initialized, controlled, read out and coupled to each other in simple circuits. This enables the realization of basic logic gates, the creation of complex entangled states and the demonstration of algorithms or error correction. Using different variants of low-noise parametric amplifiers, dispersive quantum non-demolition single-shot readout of single-qubit states with high fidelity has enabled continuous and discrete feedback control of single qubits. Here we realize full deterministic quantum teleportation with feed-forward in a chip-based superconducting circuit architecture. We use a set of two parametric amplifiers for both joint two-qubit and individual qubit single-shot readout, combined with flexible real-time digital electronics. Our device uses a crossed quantum bus technology that allows us to create complex networks with arbitrary connecting topology in a planar architecture. The deterministic teleportation process succeeds with order unit probability for any input state, as we prepare maximally entangled two-qubit states as a resource and distinguish all Bell states in a single two-qubit measurement with high efficiency and high fidelity. We teleport quantum states between two macroscopic systems separated by 6 mm at a rate of 10(4) s(-1), exceeding other reported implementations. The low transmission loss of superconducting waveguides is likely to enable the range of this and other schemes to be extended to significantly larger distances, enabling tests of non-locality and the realization of elements for quantum communication at microwave frequencies. The demonstrated feed-forward may also find application in error correction schemes.

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

Duncan, Andrew, E-mail: a.duncan@imperial.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk; Zygalakis, Konstantinos, E-mail: k.zygalakis@ed.ac.uk

Stochasticity plays a fundamental role in various biochemical processes, such as cell regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be modelled as Markov processes, typically simulated using the Gillespie Stochastic Simulation Algorithm (SSA) [25]. While easy to implement and exact, the computational cost of using the Gillespie SSA to simulate such systems can become prohibitive as the frequency of reaction events increases. This has motivated numerous coarse-grained schemes, where the “fast” reactions are approximated either using Langevin dynamics or deterministically. While such approaches provide a good approximation when all reactants are abundant, the approximation breaks down when onemore » or more species exist only in small concentrations and the fluctuations arising from the discrete nature of the reactions become significant. This is particularly problematic when using such methods to compute statistics of extinction times for chemical species, as well as simulating non-equilibrium systems such as cell-cycle models in which a single species can cycle between abundance and scarcity. In this paper, a hybrid jump-diffusion model for simulating well-mixed stochastic kinetics is derived. It acts as a bridge between the Gillespie SSA and the chemical Langevin equation. For low reactant reactions the underlying behaviour is purely discrete, while purely diffusive when the concentrations of all species are large, with the two different behaviours coexisting in the intermediate region. A bound on the weak error in the classical large volume scaling limit is obtained, and three different numerical discretisations of the jump-diffusion model are described. The benefits of such a formalism are illustrated using computational examples.« less

Non-linear stochastic growth rates and redshift space distortions

DOE PAGES

Jennings, Elise; Jennings, David

2015-04-09

The linear growth rate is commonly defined through a simple deterministic relation between the velocity divergence and the matter overdensity in the linear regime. We introduce a formalism that extends this to a non-linear, stochastic relation between θ = ∇ ∙ v(x,t)/aH and δ. This provides a new phenomenological approach that examines the conditional mean , together with the fluctuations of θ around this mean. We also measure these stochastic components using N-body simulations and find they are non-negative and increase with decreasing scale from ~10 per cent at k < 0.2 h Mpc -1 to 25 per cent atmore » k ~ 0.45 h Mpc -1 at z = 0. Both the stochastic relation and non-linearity are more pronounced for haloes, M ≤ 5 × 10 12 M ⊙ h -1, compared to the dark matter at z = 0 and 1. Non-linear growth effects manifest themselves as a rotation of the mean away from the linear theory prediction -f LTδ, where f LT is the linear growth rate. This rotation increases with wavenumber, k, and we show that it can be well-described by second-order Lagrangian perturbation theory (2LPT) fork < 0.1 h Mpc -1. Furthermore, the stochasticity in the θ – δ relation is not so simply described by 2LPT, and we discuss its impact on measurements of f LT from two-point statistics in redshift space. Furthermore, given that the relationship between δ and θ is stochastic and non-linear, this will have implications for the interpretation and precision of f LT extracted using models which assume a linear, deterministic expression.« less

Time-dependent earthquake probabilities

USGS Publications Warehouse

Gomberg, J.; Belardinelli, M.E.; Cocco, M.; Reasenberg, P.

2005-01-01

We have attempted to provide a careful examination of a class of approaches for estimating the conditional probability of failure of a single large earthquake, particularly approaches that account for static stress perturbations to tectonic loading as in the approaches of Stein et al. (1997) and Hardebeck (2004). We have loading as in the framework based on a simple, generalized rate change formulation and applied it to these two approaches to show how they relate to one another. We also have attempted to show the connection between models of seismicity rate changes applied to (1) populations of independent faults as in background and aftershock seismicity and (2) changes in estimates of the conditional probability of failures of different members of a the notion of failure rate corresponds to successive failures of different members of a population of faults. The latter application requires specification of some probability distribution (density function of PDF) that describes some population of potential recurrence times. This PDF may reflect our imperfect knowledge of when past earthquakes have occurred on a fault (epistemic uncertainty), the true natural variability in failure times, or some combination of both. We suggest two end-member conceptual single-fault models that may explain natural variability in recurrence times and suggest how they might be distinguished observationally. When viewed deterministically, these single-fault patch models differ significantly in their physical attributes, and when faults are immature, they differ in their responses to stress perturbations. Estimates of conditional failure probabilities effectively integrate over a range of possible deterministic fault models, usually with ranges that correspond to mature faults. Thus conditional failure probability estimates usually should not differ significantly for these models. Copyright 2005 by the American Geophysical Union.

Non-equilibrium reaction rates in chemical kinetic equations

NASA Astrophysics Data System (ADS)

Gorbachev, Yuriy

2018-05-01

Within the recently proposed asymptotic method for solving the Boltzmann equation for chemically reacting gas mixture, the chemical kinetic equations has been derived. Corresponding one-temperature non-equilibrium reaction rates are expressed in terms of specific heat capacities of the species participate in the chemical reactions, bracket integrals connected with the internal energy transfer in inelastic non-reactive collisions and energy transfer coefficients. Reactions of dissociation/recombination of homonuclear and heteronuclear diatomic molecules are considered. It is shown that all reaction rates are the complex functions of the species densities, similarly to the unimolecular reaction rates. For determining the rate coefficients it is recommended to tabulate corresponding bracket integrals, additionally to the equilibrium rate constants. Correlation of the obtained results with the irreversible thermodynamics is established.

A comprehensive model to determine the effects of temperature and species fluctuations on reaction rates in turbulent reacting flows

NASA Technical Reports Server (NTRS)

Foy, E.; Ronan, G.; Chinitz, W.

1982-01-01

A principal element to be derived from modeling turbulent reacting flows is an expression for the reaction rates of the various species involved in any particular combustion process under consideration. A temperature-derived most-likely probability density function (pdf) was used to describe the effects of temperature fluctuations on the Arrhenius reaction rate constant. A most-likely bivariate pdf described the effects of temperature and species concentrations fluctuations on the reaction rate. A criterion is developed for the use of an "appropriate" temperature pdf. The formulation of models to calculate the mean turbulent Arrhenius reaction rate constant and the mean turbulent reaction rate is considered and the results of calculations using these models are presented.

Cognitive Diagnostic Analysis Using Hierarchically Structured Skills

ERIC Educational Resources Information Center

Su, Yu-Lan

2013-01-01

This dissertation proposes two modified cognitive diagnostic models (CDMs), the deterministic, inputs, noisy, "and" gate with hierarchy (DINA-H) model and the deterministic, inputs, noisy, "or" gate with hierarchy (DINO-H) model. Both models incorporate the hierarchical structures of the cognitive skills in the model estimation…

Deterministic Mean-Field Ensemble Kalman Filtering

DOE PAGES

Law, Kody J. H.; Tembine, Hamidou; Tempone, Raul

2016-05-03

The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. In this paper, a density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence κ between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d

Active temporal multiplexing of indistinguishable heralded single photons

PubMed Central

Xiong, C.; Zhang, X.; Liu, Z.; Collins, M. J.; Mahendra, A.; Helt, L. G.; Steel, M. J.; Choi, D. -Y.; Chae, C. J.; Leong, P. H. W.; Eggleton, B. J.

2016-01-01

It is a fundamental challenge in quantum optics to deterministically generate indistinguishable single photons through non-deterministic nonlinear optical processes, due to the intrinsic coupling of single- and multi-photon-generation probabilities in these processes. Actively multiplexing photons generated in many temporal modes can decouple these probabilities, but key issues are to minimize resource requirements to allow scalability, and to ensure indistinguishability of the generated photons. Here we demonstrate the multiplexing of photons from four temporal modes solely using fibre-integrated optics and off-the-shelf electronic components. We show a 100% enhancement to the single-photon output probability without introducing additional multi-photon noise. Photon indistinguishability is confirmed by a fourfold Hong–Ou–Mandel quantum interference with a 91±16% visibility after subtracting multi-photon noise due to high pump power. Our demonstration paves the way for scalable multiplexing of many non-deterministic photon sources to a single near-deterministic source, which will be of benefit to future quantum photonic technologies. PMID:26996317

Recent progress in the assembly of nanodevices and van der Waals heterostructures by deterministic placement of 2D materials.

PubMed

Frisenda, Riccardo; Navarro-Moratalla, Efrén; Gant, Patricia; Pérez De Lara, David; Jarillo-Herrero, Pablo; Gorbachev, Roman V; Castellanos-Gomez, Andres

2018-01-02

Designer heterostructures can now be assembled layer-by-layer with unmatched precision thanks to the recently developed deterministic placement methods to transfer two-dimensional (2D) materials. This possibility constitutes the birth of a very active research field on the so-called van der Waals heterostructures. Moreover, these deterministic placement methods also open the door to fabricate complex devices, which would be otherwise very difficult to achieve by conventional bottom-up nanofabrication approaches, and to fabricate fully-encapsulated devices with exquisite electronic properties. The integration of 2D materials with existing technologies such as photonic and superconducting waveguides and fiber optics is another exciting possibility. Here, we review the state-of-the-art of the deterministic placement methods, describing and comparing the different alternative methods available in the literature, and we illustrate their potential to fabricate van der Waals heterostructures, to integrate 2D materials into complex devices and to fabricate artificial bilayer structures where the layers present a user-defined rotational twisting angle.

First-order reliability application and verification methods for semistatic structures

NASA Astrophysics Data System (ADS)

Verderaime, V.

1994-11-01

Escalating risks of aerostructures stimulated by increasing size, complexity, and cost should no longer be ignored in conventional deterministic safety design methods. The deterministic pass-fail concept is incompatible with probability and risk assessments; stress audits are shown to be arbitrary and incomplete, and the concept compromises the performance of high-strength materials. A reliability method is proposed that combines first-order reliability principles with deterministic design variables and conventional test techniques to surmount current deterministic stress design and audit deficiencies. Accumulative and propagation design uncertainty errors are defined and appropriately implemented into the classical safety-index expression. The application is reduced to solving for a design factor that satisfies the specified reliability and compensates for uncertainty errors, and then using this design factor as, and instead of, the conventional safety factor in stress analyses. The resulting method is consistent with current analytical skills and verification practices, the culture of most designers, and the development of semistatic structural designs.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

PubMed

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

Deterministic Mean-Field Ensemble Kalman Filtering

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

Law, Kody J. H.; Tembine, Hamidou; Tempone, Raul

The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. In this paper, a density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence κ between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d

Lessons with a Fizz.

ERIC Educational Resources Information Center

Faulkner, Samuel P.

1993-01-01

Describes inexpensive and safe activities centered around the chemistry of effervescent products such as Alka-Seltzer. Activities demonstrate the following: water-induced reactions, the influence of humidity, temperature and rate of reaction, particle size and rate of reaction, concentration and rate of reaction, the neutralizing power of…

Comparing transfusion reaction rates for various plasma types: a systematic review and meta-analysis/regression.

PubMed

Saadah, Nicholas H; van Hout, Fabienne M A; Schipperus, Martin R; le Cessie, Saskia; Middelburg, Rutger A; Wiersum-Osselton, Johanna C; van der Bom, Johanna G

2017-09-01

We estimated rates for common plasma-associated transfusion reactions and compared reported rates for various plasma types. We performed a systematic review and meta-analysis of peer-reviewed articles that reported plasma transfusion reaction rates. Random-effects pooled rates were calculated and compared between plasma types. Meta-regression was used to compare various plasma types with regard to their reported plasma transfusion reaction rates. Forty-eight studies reported transfusion reaction rates for fresh-frozen plasma (FFP; mixed-sex and male-only), amotosalen INTERCEPT FFP, methylene blue-treated FFP, and solvent/detergent-treated pooled plasma. Random-effects pooled average rates for FFP were: allergic reactions, 92/10 5 units transfused (95% confidence interval [CI], 46-184/10 5 units transfused); febrile nonhemolytic transfusion reactions (FNHTRs), 12/10 5 units transfused (95% CI, 7-22/10 5 units transfused); transfusion-associated circulatory overload (TACO), 6/10 5 units transfused (95% CI, 1-30/10 5 units transfused); transfusion-related acute lung injury (TRALI), 1.8/10 5 units transfused (95% CI, 1.2-2.7/10 5 units transfused); and anaphylactic reactions, 0.8/10 5 units transfused (95% CI, 0-45.7/10 5 units transfused). Risk differences between plasma types were not significant for allergic reactions, TACO, or anaphylactic reactions. Methylene blue-treated FFP led to fewer FNHTRs than FFP (risk difference = -15.3 FNHTRs/10 5 units transfused; 95% CI, -24.7 to -7.1 reactions/10 5 units transfused); and male-only FFP led to fewer cases of TRALI than mixed-sex FFP (risk difference = -0.74 TRALI/10 5 units transfused; 95% CI, -2.42 to -0.42 injuries/10 5 units transfused). Meta-regression demonstrates that the rate of FNHTRs is lower for methylene blue-treated compared with FFP, and the rate of TRALI is lower for male-only than for mixed-sex FFP; whereas no significant differences are observed between plasma types for allergic reactions, TACO, or anaphylactic reactions. Reported transfusion reaction rates suffer from high heterogeneity. © 2017 AABB.

The effect of addition of primary positive salts, complex salt, on the ionic strength and rate constant at various temperatures by reaction kinetics

NASA Astrophysics Data System (ADS)

Kurade, S. S.; Ramteke, A. A.

2018-05-01

In this work, we have investigated the rate of reaction by using ionic strength at different temperatures. The main goal of this experiment is to determine the relation between ionic strength with reaction rate, reaction time and rate constant with temperature. It is observed that the addition of positive salt indicate the increasing ionic strength with increase in run time at various temperatures. Thus the temperature affects the speed of reaction and mechanism by which chemical reaction occurs and time variable plays vital role in the progress of reaction at different temperatures.

Improving Deterministic Reserve Requirements for Security Constrained Unit Commitment and Scheduling Problems in Power Systems

NASA Astrophysics Data System (ADS)

Wang, Fengyu

Traditional deterministic reserve requirements rely on ad-hoc, rule of thumb methods to determine adequate reserve in order to ensure a reliable unit commitment. Since congestion and uncertainties exist in the system, both the quantity and the location of reserves are essential to ensure system reliability and market efficiency. The modeling of operating reserves in the existing deterministic reserve requirements acquire the operating reserves on a zonal basis and do not fully capture the impact of congestion. The purpose of a reserve zone is to ensure that operating reserves are spread across the network. Operating reserves are shared inside each reserve zone, but intra-zonal congestion may block the deliverability of operating reserves within a zone. Thus, improving reserve policies such as reserve zones may improve the location and deliverability of reserve. As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired. One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones. Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch structure, especially with the consideration of renewables, 2) to develop a market settlement scheme of proposed dynamic reserve policies such that the market efficiency is improved, 3) to evaluate the market impacts and price signal of the proposed dynamic reserve policies.

Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.

USGS Publications Warehouse

Flint, Paul L.; Grand, James B.; Petersen, Margaret; Rockwell, Robert F.

2016-01-01

Spectacled eider Somateria fischeri numbers have declined and they are considered threatened in accordance with the US Endangered Species Act throughout their range. We synthesized the available information for spectacled eiders to construct deterministic, stochastic, and metapopulation models for this species that incorporated current estimates of vital rates such as nest success, adult survival, and the impact of lead poisoning on survival. Elasticities of our deterministic models suggested that the populations would respond most dramatically to changes in adult female survival and that the reductions in adult female survival related to lead poisoning were locally important. We also examined the sensitivity of the population to changes in lead exposure rates. With the knowledge that some vital rates vary with environmental conditions, we cast stochastic models that mimicked observed variation in productivity. We also used the stochastic model to examine the probability that a specific population will persist for periods of up to 50 y. Elasticity analysis of these models was consistent with that for the deterministic models, with perturbations to adult female survival having the greatest effect on population projections. When used in single population models, demographic data for some localities predicted rapid declines that were inconsistent with our observations in the field. Thus, we constructed a metapopulation model and examined the predictions for local subpopulations and the metapopulation over a wide range of dispersal rates. Using the metapopulation model, we were able to simulate the observed stability of local subpopulations as well as that of the metapopulation. Finally, we developed a global metapopulation model that simulates periodic winter habitat limitation, similar to that which might be experienced in years of heavy sea ice in the core wintering area of spectacled eiders in the central Bering Sea. Our metapopulation analyses suggested that no subpopulation is independent and that future management actions may be improved through a metapopulation framework. For example, management actions could include displacement of breeding females from"sink" areas that reduce the growth potential of the population as a whole. However, this action is contingent upon dispersal among local populations, for which there is limited information. Thus, we recommend that researchers examine dispersal behavior among areas on the Yukon-Kuskokwim Delta in western Alaska. The metapopulation framework could also be applied at the rangewide scale to address the density-dependent limitation of available polynya habitat during winter that may limit the recovery of small subpopulations, such as that on the Yukon-Kuskokwim Delta. Reductions in other subpopulations may be necessary to ensure an increase in the Yukon-Kuskokwim Delta population. Thus, we recommend that managers consider the interpopulation dynamics of spectacled eiders at different spatial scales in future management actions.

Accumulation of neutral mutations in growing cell colonies with competition.

PubMed

Sorace, Ron; Komarova, Natalia L

2012-12-07

Neutral mutations play an important role in many biological processes including cancer initiation and progression, the generation of drug resistance in bacterial and viral diseases as well as cancers, and the development of organs in multicellular organisms. In this paper we study how neutral mutants are accumulated in nonlinearly growing colonies of cells subject to growth constraints such as crowding or lack of resources. We investigate different types of growth control which range from "division-controlled" to "death-controlled" growth (and various mixtures of both). In division-controlled growth, the burden of handling overcrowding lies with the process of cell-divisions, the divisions slow down as the carrying capacity is approached. In death-controlled growth, it is death rate that increases to slow down expansion. We show that division-controlled growth minimizes the number of accumulated mutations, and death-controlled growth corresponds to the maximum number of mutants. We check that these results hold in both deterministic and stochastic settings. We further develop a general (deterministic) theory of neutral mutations and achieve an analytical understanding of the mutant accumulation in colonies of a given size in the absence of back-mutations. The long-term dynamics of mutants in the presence of back-mutations is also addressed. In particular, with equal forward- and back-mutation rates, if division-controlled and a death-controlled types are competing for space and nutrients, cells obeying division-controlled growth will dominate the population. Copyright © 2012 Elsevier Ltd. All rights reserved.

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

2011-09-01

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

Inherent Conservatism in Deterministic Quasi-Static Structural Analysis

NASA Technical Reports Server (NTRS)

Verderaime, V.

1997-01-01

The cause of the long-suspected excessive conservatism in the prevailing structural deterministic safety factor has been identified as an inherent violation of the error propagation laws when reducing statistical data to deterministic values and then combining them algebraically through successive structural computational processes. These errors are restricted to the applied stress computations, and because mean and variations of the tolerance limit format are added, the errors are positive, serially cumulative, and excessively conservative. Reliability methods circumvent these errors and provide more efficient and uniform safe structures. The document is a tutorial on the deficiencies and nature of the current safety factor and of its improvement and transition to absolute reliability.

Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

NASA Astrophysics Data System (ADS)

Iliadis, Christian; Longland, Richard; Coc, Alain; Timmes, F. X.; Champagne, Art E.

2015-03-01

Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting thermonuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statistically meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

Multistage adsorption of diffusing macromolecules and viruses

NASA Astrophysics Data System (ADS)

Chou, Tom; D'Orsogna, Maria R.

2007-09-01

We derive the equations that describe adsorption of diffusing particles onto a surface followed by additional surface kinetic steps before being transported across the interface. Multistage surface kinetics occurs during membrane protein insertion, cell signaling, and the infection of cells by virus particles. For example, viral entry into healthy cells is possible only after a series of receptor and coreceptor binding events occurs at the cellular surface. We couple the diffusion of particles in the bulk phase with the multistage surface kinetics and derive an effective, integrodifferential boundary condition that contains a memory kernel embodying the delay induced by the surface reactions. This boundary condition takes the form of a singular perturbation problem in the limit where particle-surface interactions are short ranged. Moreover, depending on the surface kinetics, the delay kernel induces a nonmonotonic, transient replenishment of the bulk particle concentration near the interface. The approach generalizes that of Ward and Tordai [J. Chem. Phys. 14, 453 (1946)] and Diamant and Andelman [Colloids Surf. A 183-185, 259 (2001)] to include surface kinetics, giving rise to qualitatively new behaviors. Our analysis also suggests a simple scheme by which stochastic surface reactions may be coupled to deterministic bulk diffusion.

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

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

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. In this work, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We demonstratemore » the modeling approach with the example of chalcopyrite Cu(InGa)(SeS){sub 2} thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS){sub 2} thin films arises and persists. We believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

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

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. Here, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We also demonstrate themore » modeling approach with the example of chalcopyrite Cu(InGa)(SeS) 2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS) 2 thin films arises and persists. Finally, we believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

DOE PAGES

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.; ...

2016-04-01

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. Here, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We also demonstrate themore » modeling approach with the example of chalcopyrite Cu(InGa)(SeS) 2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS) 2 thin films arises and persists. Finally, we believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

Internal cycle modeling and environmental assessment of multiple cycle consumer products

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

Tsiliyannis, C.A., E-mail: anion@otenet.gr

2012-01-15

Highlights: Black-Right-Pointing-Pointer Dynamic flow models are presented for remanufactured, reused or recycled products. Black-Right-Pointing-Pointer Early loss and stochastic return are included for fast and slow cycling products. Black-Right-Pointing-Pointer The reuse-to-input flow ratio (Internal Cycle Factor, ICF) is determined. Black-Right-Pointing-Pointer The cycle rate, which is increasing with the ICF, monitors eco-performance. Black-Right-Pointing-Pointer Early internal cycle losses diminish the ICF, the cycle rate and performance. - Abstract: Dynamic annual flow models incorporating consumer discard and usage loss and featuring deterministic and stochastic end-of-cycle (EOC) return by the consumer are developed for reused or remanufactured products (multiple cycle products, MCPs), including fast andmore » slow cycling, short and long-lived products. It is shown that internal flows (reuse and overall consumption) increase proportionally to the dimensionless internal cycle factor (ICF) which is related to environmental impact reduction factors. The combined reuse/recycle (or cycle) rate is shown capable for shortcut, albeit effective, monitoring of environmental performance in terms of waste production, virgin material extraction and manufacturing impacts of all MCPs, a task, which physical variables (lifetime, cycling frequency, mean or total number of return trips) and conventional rates, via which environmental policy has been officially implemented (e.g. recycling rate) cannot accomplish. The cycle rate is shown to be an increasing (hyperbolic) function of ICF. The impact of the stochastic EOC return characteristics on total reuse and consumption flows, as well as on eco-performance, is assessed: symmetric EOC return has a small, positive effect on performance compared to deterministic, while early shifted EOC return is more beneficial. In order to be efficient, environmental policy should set higher minimum reuse targets for higher trippage MCPs. The results may serve for monitoring, flow accounting and comparative eco-assessment of MCPs. They may be useful in identifying reachable and efficient reuse/recycle targets for consumer products and in planning return via appropriate labelling and digital coding for enhancing environmental performance, while satisfying consumer demand.« less

STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies.

PubMed

Hepburn, Iain; Chen, Weiliang; Wils, Stefan; De Schutter, Erik

2012-05-10

Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems. We describe STEPS, a stochastic reaction-diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction-diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation. STEPS simulates models of cellular reaction-diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/

Comparison of space radiation calculations for deterministic and Monte Carlo transport codes

NASA Astrophysics Data System (ADS)

Lin, Zi-Wei; Adams, James; Barghouty, Abdulnasser; Randeniya, Sharmalee; Tripathi, Ram; Watts, John; Yepes, Pablo

For space radiation protection of astronauts or electronic equipments, it is necessary to develop and use accurate radiation transport codes. Radiation transport codes include deterministic codes, such as HZETRN from NASA and UPROP from the Naval Research Laboratory, and Monte Carlo codes such as FLUKA, the Geant4 toolkit and HETC-HEDS. The deterministic codes and Monte Carlo codes complement each other in that deterministic codes are very fast while Monte Carlo codes are more elaborate. Therefore it is important to investigate how well the results of deterministic codes compare with those of Monte Carlo transport codes and where they differ. In this study we evaluate these different codes in their space radiation applications by comparing their output results in the same given space radiation environments, shielding geometry and material. Typical space radiation environments such as the 1977 solar minimum galactic cosmic ray environment are used as the well-defined input, and simple geometries made of aluminum, water and/or polyethylene are used to represent the shielding material. We then compare various outputs of these codes, such as the dose-depth curves and the flux spectra of different fragments and other secondary particles. These comparisons enable us to learn more about the main differences between these space radiation transport codes. At the same time, they help us to learn the qualitative and quantitative features that these transport codes have in common.

Extraction of angle deterministic signals in the presence of stationary speed fluctuations with cyclostationary blind source separation

NASA Astrophysics Data System (ADS)

Delvecchio, S.; Antoni, J.

2012-02-01

This paper addresses the use of a cyclostationary blind source separation algorithm (namely RRCR) to extract angle deterministic signals from mechanical rotating machines in presence of stationary speed fluctuations. This means that only phase fluctuations while machine is running in steady-state conditions are considered while run-up or run-down speed variations are not taken into account. The machine is also supposed to run in idle conditions so non-stationary phenomena due to the load are not considered. It is theoretically assessed that in such operating conditions the deterministic (periodic) signal in the angle domain becomes cyclostationary at first and second orders in the time domain. This fact justifies the use of the RRCR algorithm, which is able to directly extract the angle deterministic signal from the time domain without performing any kind of interpolation. This is particularly valuable when angular resampling fails because of uncontrolled speed fluctuations. The capability of the proposed approach is verified by means of simulated and actual vibration signals captured on a pneumatic screwdriver handle. In this particular case not only the extraction of the angle deterministic part can be performed but also the separation of the main sources of excitation (i.e. motor shaft imbalance, epyciloidal gear meshing and air pressure forces) affecting the user hand during operations.

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.

Tag-mediated cooperation with non-deterministic genotype-phenotype mapping

NASA Astrophysics Data System (ADS)

Zhang, Hong; Chen, Shu

2016-01-01

Tag-mediated cooperation provides a helpful framework for resolving evolutionary social dilemmas. However, most of the previous studies have not taken into account genotype-phenotype distinction in tags, which may play an important role in the process of evolution. To take this into consideration, we introduce non-deterministic genotype-phenotype mapping into a tag-based model with spatial prisoner's dilemma. By our definition, the similarity between genotypic tags does not directly imply the similarity between phenotypic tags. We find that the non-deterministic mapping from genotypic tag to phenotypic tag has non-trivial effects on tag-mediated cooperation. Although we observe that high levels of cooperation can be established under a wide variety of conditions especially when the decisiveness is moderate, the uncertainty in the determination of phenotypic tags may have a detrimental effect on the tag mechanism by disturbing the homophilic interaction structure which can explain the promotion of cooperation in tag systems. Furthermore, the non-deterministic mapping may undermine the robustness of the tag mechanism with respect to various factors such as the structure of the tag space and the tag flexibility. This observation warns us about the danger of applying the classical tag-based models to the analysis of empirical phenomena if genotype-phenotype distinction is significant in real world. Non-deterministic genotype-phenotype mapping thus provides a new perspective to the understanding of tag-mediated cooperation.

On the origins of approximations for stochastic chemical kinetics.

PubMed

Haseltine, Eric L; Rawlings, James B

2005-10-22

This paper considers the derivation of approximations for stochastic chemical kinetics governed by the discrete master equation. Here, the concepts of (1) partitioning on the basis of fast and slow reactions as opposed to fast and slow species and (2) conditional probability densities are used to derive approximate, partitioned master equations, which are Markovian in nature, from the original master equation. Under different conditions dictated by relaxation time arguments, such approximations give rise to both the equilibrium and hybrid (deterministic or Langevin equations coupled with discrete stochastic simulation) approximations previously reported. In addition, the derivation points out several weaknesses in previous justifications of both the hybrid and equilibrium systems and demonstrates the connection between the original and approximate master equations. Two simple examples illustrate situations in which these two approximate methods are applicable and demonstrate the two methods' efficiencies.

The use of the SRIM code for calculation of radiation damage induced by neutrons

NASA Astrophysics Data System (ADS)

Mohammadi, A.; Hamidi, S.; Asadabad, Mohsen Asadi

2017-12-01

Materials subjected to neutron irradiation will being evolve to structural changes by the displacement cascades initiated by nuclear reaction. This study discusses a methodology to compute primary knock-on atoms or PKAs information that lead to radiation damage. A program AMTRACK has been developed for assessing of the PKAs information. This software determines the specifications of recoil atoms (using PTRAC card of MCNPX code) and also the kinematics of interactions. The deterministic method was used for verification of the results of (MCNPX+AMTRACK). The SRIM (formely TRIM) code is capable to compute neutron radiation damage. The PKAs information was extracted by AMTRACK program, which can be used as an input of SRIM codes for systematic analysis of primary radiation damage. Then the Bushehr Nuclear Power Plant (BNPP) radiation damage on reactor pressure vessel is calculated.

Noise effects in nonlinear biochemical signaling

NASA Astrophysics Data System (ADS)

Bostani, Neda; Kessler, David A.; Shnerb, Nadav M.; Rappel, Wouter-Jan; Levine, Herbert

2012-01-01

It has been generally recognized that stochasticity can play an important role in the information processing accomplished by reaction networks in biological cells. Most treatments of that stochasticity employ Gaussian noise even though it is a priori obvious that this approximation can violate physical constraints, such as the positivity of chemical concentrations. Here, we show that even when such nonphysical fluctuations are rare, an exact solution of the Gaussian model shows that the model can yield unphysical results. This is done in the context of a simple incoherent-feedforward model which exhibits perfect adaptation in the deterministic limit. We show how one can use the natural separation of time scales in this model to yield an approximate model, that is analytically solvable, including its dynamical response to an environmental change. Alternatively, one can employ a cutoff procedure to regularize the Gaussian result.

An in-situ stimulation experiment in crystalline rock - assessment of induced seismicity levels during stimulation and related hazard for nearby infrastructure

NASA Astrophysics Data System (ADS)

Gischig, Valentin; Broccardo, Marco; Amann, Florian; Jalali, Mohammadreza; Esposito, Simona; Krietsch, Hannes; Doetsch, Joseph; Madonna, Claudio; Wiemer, Stefan; Loew, Simon; Giardini, Domenico

2016-04-01

A decameter in-situ stimulation experiment is currently being performed at the Grimsel Test Site in Switzerland by the Swiss Competence Center for Energy Research - Supply of Electricity (SCCER-SoE). The underground research laboratory lies in crystalline rock at a depth of 480 m, and exhibits well-documented geology that is presenting some analogies with the crystalline basement targeted for the exploitation of deep geothermal energy resources in Switzerland. The goal is to perform a series of stimulation experiments spanning from hydraulic fracturing to controlled fault-slip experiments in an experimental volume approximately 30 m in diameter. The experiments will contribute to a better understanding of hydro-mechanical phenomena and induced seismicity associated with high-pressure fluid injections. Comprehensive monitoring during stimulation will include observation of injection rate and pressure, pressure propagation in the reservoir, permeability enhancement, 3D dislocation along the faults, rock mass deformation near the fault zone, as well as micro-seismicity. The experimental volume is surrounded by other in-situ experiments (at 50 to 500 m distance) and by infrastructure of the local hydropower company (at ~100 m to several kilometres distance). Although it is generally agreed among stakeholders related to the experiments that levels of induced seismicity may be low given the small total injection volumes of less than 1 m3, detailed analysis of the potential impact of the stimulation on other experiments and surrounding infrastructure is essential to ensure operational safety. In this contribution, we present a procedure how induced seismic hazard can be estimated for an experimental situation that is untypical for injection-induced seismicity in terms of injection volumes, injection depths and proximity to affected objects. Both, deterministic and probabilistic methods are employed to estimate that maximum possible and the maximum expected induced earthquake magnitude. Deterministic methods are based on McGarr's upper limit for the maximum induced seismic moment. Probabilistic methods rely on estimates of Shapiro's seismogenic index and seismicity rates from past stimulation experiments that are scaled to injection volumes of interest. Using rate-and-state frictional modelling coupled to a hydro-mechanical fracture flow model, we demonstrate that large uncontrolled rupture events are unlikely to occur and that deterministic upper limits may be sufficiently conservative. The proposed workflow can be applied to similar injection experiments, for which hazard to nearby infrastructure may limit experimental design.

Effects of reaction-kinetic parameters on modeling reaction pathways in GaN MOVPE growth

NASA Astrophysics Data System (ADS)

Zhang, Hong; Zuo, Ran; Zhang, Guoyi

2017-11-01

In the modeling of the reaction-transport process in GaN MOVPE growth, the selections of kinetic parameters (activation energy Ea and pre-exponential factor A) for gas reactions are quite uncertain, which cause uncertainties in both gas reaction path and growth rate. In this study, numerical modeling of the reaction-transport process for GaN MOVPE growth in a vertical rotating disk reactor is conducted with varying kinetic parameters for main reaction paths. By comparisons of the molar concentrations of major Ga-containing species and the growth rates, the effects of kinetic parameters on gas reaction paths are determined. The results show that, depending on the values of the kinetic parameters, the gas reaction path may be dominated either by adduct/amide formation path, or by TMG pyrolysis path, or by both. Although the reaction path varies with different kinetic parameters, the predicted growth rates change only slightly because the total transport rate of Ga-containing species to the substrate changes slightly with reaction paths. This explains why previous authors using different chemical models predicted growth rates close to the experiment values. By varying the pre-exponential factor for the amide trimerization, it is found that the more trimers are formed, the lower the growth rates are than the experimental value, which indicates that trimers are poor growth precursors, because of thermal diffusion effect caused by high temperature gradient. The effective order for the contribution of major species to growth rate is found as: pyrolysis species > amides > trimers. The study also shows that radical reactions have little effect on gas reaction path because of the generation and depletion of H radicals in the chain reactions when NH2 is considered as the end species.

A Unit on Deterministic Chaos for Student Teachers

ERIC Educational Resources Information Center

Stavrou, D.; Assimopoulos, S.; Skordoulis, C.

2013-01-01

A unit aiming to introduce pre-service teachers of primary education to the limited predictability of deterministic chaotic systems is presented. The unit is based on a commercial chaotic pendulum system connected with a data acquisition interface. The capabilities and difficulties in understanding the notion of limited predictability of 18…

A Deterministic Annealing Approach to Clustering AIRS Data

NASA Technical Reports Server (NTRS)

Guillaume, Alexandre; Braverman, Amy; Ruzmaikin, Alexander

2012-01-01

We will examine the validity of means and standard deviations as a basis for climate data products. We will explore the conditions under which these two simple statistics are inadequate summaries of the underlying empirical probability distributions by contrasting them with a nonparametric, method called Deterministic Annealing technique

INTEGRATED PROBABILISTIC AND DETERMINISTIC MODELING TECHNIQUES IN ESTIMATING EXPOSURE TO WATER-BORNE CONTAMINANTS: PART 2 PHARMACOKINETIC MODELING

EPA Science Inventory

The Total Exposure Model (TEM) uses deterministic and stochastic methods to estimate the exposure of a person performing daily activities of eating, drinking, showering, and bathing. There were 250 time histories generated, by subject with activities, for the three exposure ro...

Integrability and Chaos: The Classical Uncertainty

ERIC Educational Resources Information Center

Masoliver, Jaume; Ros, Ana

2011-01-01

In recent years there has been a considerable increase in the publishing of textbooks and monographs covering what was formerly known as random or irregular deterministic motion, now referred to as deterministic chaos. There is still substantial interest in a matter that is included in many graduate and even undergraduate courses on classical…

The development of the deterministic nonlinear PDEs in particle physics to stochastic case

NASA Astrophysics Data System (ADS)

Abdelrahman, Mahmoud A. E.; Sohaly, M. A.

2018-06-01

In the present work, accuracy method called, Riccati-Bernoulli Sub-ODE technique is used for solving the deterministic and stochastic case of the Phi-4 equation and the nonlinear Foam Drainage equation. Also, the control on the randomness input is studied for stability stochastic process solution.

Contemporary Genetics for Gender Researchers: Not Your Grandma's Genetics Anymore

ERIC Educational Resources Information Center

Salk, Rachel H.; Hyde, Janet S.

2012-01-01

Over the past century, much of genetics was deterministic, and feminist researchers framed justified criticisms of genetics research. However, over the past two decades, genetics research has evolved remarkably and has moved far from earlier deterministic approaches. Our article provides a brief primer on modern genetics, emphasizing contemporary…

Technological Utopia, Dystopia and Ambivalence: Teaching with Social Media at a South African University

ERIC Educational Resources Information Center

Rambe, Patient; Nel, Liezel

2015-01-01

The discourse of social media adoption in higher education has often been funnelled through utopian and dystopian perspectives, which are polarised but determinist theorisations of human engagement with educational technologies. Consequently, these determinist approaches have obscured a broadened grasp of the situated, socially constructed nature…

A hybrid algorithm for coupling partial differential equation and compartment-based dynamics.

PubMed

Harrison, Jonathan U; Yates, Christian A

2016-09-01

Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations (PDEs). Although the numerical solution of such PDEs is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, while maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time. © 2016 The Authors.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

PubMed

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks

PubMed Central

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-01-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is “non-intrusive” and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design. PMID:26317784

A deterministic mathematical model for bidirectional excluded flow with Langmuir kinetics.

PubMed

Zarai, Yoram; Margaliot, Michael; Tuller, Tamir

2017-01-01

In many important cellular processes, including mRNA translation, gene transcription, phosphotransfer, and intracellular transport, biological "particles" move along some kind of "tracks". The motion of these particles can be modeled as a one-dimensional movement along an ordered sequence of sites. The biological particles (e.g., ribosomes or RNAPs) have volume and cannot surpass one another. In some cases, there is a preferred direction of movement along the track, but in general the movement may be bidirectional, and furthermore the particles may attach or detach from various regions along the tracks. We derive a new deterministic mathematical model for such transport phenomena that may be interpreted as a dynamic mean-field approximation of an important model from mechanical statistics called the asymmetric simple exclusion process (ASEP) with Langmuir kinetics. Using tools from the theory of monotone dynamical systems and contraction theory we show that the model admits a unique steady-state, and that every solution converges to this steady-state. Furthermore, we show that the model entrains (or phase locks) to periodic excitations in any of its forward, backward, attachment, or detachment rates. We demonstrate an application of this phenomenological transport model for analyzing ribosome drop off in mRNA translation.

Uncertainty Quantification of Non-linear Oscillation Triggering in a Multi-injector Liquid-propellant Rocket Combustion Chamber

NASA Astrophysics Data System (ADS)

Popov, Pavel; Sideris, Athanasios; Sirignano, William

2014-11-01

We examine the non-linear dynamics of the transverse modes of combustion-driven acoustic instability in a liquid-propellant rocket engine. Triggering can occur, whereby small perturbations from mean conditions decay, while larger disturbances grow to a limit-cycle of amplitude that may compare to the mean pressure. For a deterministic perturbation, the system is also deterministic, computed by coupled finite-volume solvers at low computational cost for a single realization. The randomness of the triggering disturbance is captured by treating the injector flow rates, local pressure disturbances, and sudden acceleration of the entire combustion chamber as random variables. The combustor chamber with its many sub-fields resulting from many injector ports may be viewed as a multi-scale complex system wherein the developing acoustic oscillation is the emergent structure. Numerical simulation of the resulting stochastic PDE system is performed using the polynomial chaos expansion method. The overall probability of unstable growth is assessed in different regions of the parameter space. We address, in particular, the seven-injector, rectangular Purdue University experimental combustion chamber. In addition to the novel geometry, new features include disturbances caused by engine acceleration and unsteady thruster nozzle flow.

Deterministic chaos and fractal complexity in the dynamics of cardiovascular behavior: perspectives on a new frontier.

PubMed

Sharma, Vijay

2009-09-10

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts.

Deterministic Chaos and Fractal Complexity in the Dynamics of Cardiovascular Behavior: Perspectives on a New Frontier

PubMed Central

Sharma, Vijay

2009-01-01

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts. PMID:19812706

Health safety nets can break cycles of poverty and disease: a stochastic ecological model

PubMed Central

Pluciński, Mateusz M.; Ngonghala, Calistus N.; Bonds, Matthew H.

2011-01-01

The persistence of extreme poverty is increasingly attributed to dynamic interactions between biophysical processes and economics, though there remains a dearth of integrated theoretical frameworks that can inform policy. Here, we present a stochastic model of disease-driven poverty traps. Whereas deterministic models can result in poverty traps that can only be broken by substantial external changes to the initial conditions, in the stochastic model there is always some probability that a population will leave or enter a poverty trap. We show that a ‘safety net’, defined as an externally enforced minimum level of health or economic conditions, can guarantee ultimate escape from a poverty trap, even if the safety net is set within the basin of attraction of the poverty trap, and even if the safety net is only in the form of a public health measure. Whereas the deterministic model implies that small improvements in initial conditions near the poverty-trap equilibrium are futile, the stochastic model suggests that the impact of changes in the location of the safety net on the rate of development may be strongest near the poverty-trap equilibrium. PMID:21593026

Deterministic chaos in an ytterbium-doped mode-locked fiber laser

NASA Astrophysics Data System (ADS)

Mélo, Lucas B. A.; Palacios, Guillermo F. R.; Carelli, Pedro V.; Acioli, Lúcio H.; Rios Leite, José R.; de Miranda, Marcio H. G.

2018-05-01

We experimentally study the nonlinear dynamics of a femtosecond ytterbium doped mode-locked fiber laser. With the laser operating in the pulsed regime a route to chaos is presented, starting from stable mode-locking, period two, period four, chaos and period three regimes. Return maps and bifurcation diagrams were extracted from time series for each regime. The analysis of the time series with the laser operating in the quasi mode-locked regime presents deterministic chaos described by an unidimensional Rossler map. A positive Lyapunov exponent $\\lambda = 0.14$ confirms the deterministic chaos of the system. We suggest an explanation about the observed map by relating gain saturation and intra-cavity loss.

The viability of ADVANTG deterministic method for synthetic radiography generation

NASA Astrophysics Data System (ADS)

Bingham, Andrew; Lee, Hyoung K.

2018-07-01

Fast simulation techniques to generate synthetic radiographic images of high resolution are helpful when new radiation imaging systems are designed. However, the standard stochastic approach requires lengthy run time with poorer statistics at higher resolution. The investigation of the viability of a deterministic approach to synthetic radiography image generation was explored. The aim was to analyze a computational time decrease over the stochastic method. ADVANTG was compared to MCNP in multiple scenarios including a small radiography system prototype, to simulate high resolution radiography images. By using ADVANTG deterministic code to simulate radiography images the computational time was found to decrease 10 to 13 times compared to the MCNP stochastic approach while retaining image quality.

First-passage problems: A probabilistic dynamic analysis for degraded structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1990-01-01

Structures subjected to random excitations with uncertain system parameters degraded by surrounding environments (a random time history) are studied. Methods are developed to determine the statistics of dynamic responses, such as the time-varying mean, the standard deviation, the autocorrelation functions, and the joint probability density function of any response and its derivative. Moreover, the first-passage problems with deterministic and stationary/evolutionary random barriers are evaluated. The time-varying (joint) mean crossing rate and the probability density function of the first-passage time for various random barriers are derived.

A binomial stochastic kinetic approach to the Michaelis-Menten mechanism

NASA Astrophysics Data System (ADS)

Lente, Gábor

2013-05-01

This Letter presents a new method that gives an analytical approximation of the exact solution of the stochastic Michaelis-Menten mechanism without computationally demanding matrix operations. The method is based on solving the deterministic rate equations and then using the results as guiding variables of calculating probability values using binomial distributions. This principle can be generalized to a number of different kinetic schemes and is expected to be very useful in the evaluation of measurements focusing on the catalytic activity of one or a few individual enzyme molecules.

Effect of thermal noise on vesicles and capsules in shear flow.

PubMed

Abreu, David; Seifert, Udo

2012-07-01

We add thermal noise consistently to reduced models of undeformable vesicles and capsules in shear flow and derive analytically the corresponding stochastic equations of motion. We calculate the steady-state probability distribution function and construct the corresponding phase diagrams for the different dynamical regimes. For fluid vesicles, we predict that at small shear rates thermal fluctuations induce a tumbling motion for any viscosity contrast. For elastic capsules, due to thermal mixing, an intermittent regime appears in regions where deterministic models predict only pure tank treading or tumbling.

Linear free energy relationships between aqueous phase hydroxyl radical reaction rate constants and free energy of activation.

PubMed

Minakata, Daisuke; Crittenden, John

2011-04-15

The hydroxyl radical (HO(•)) is a strong oxidant that reacts with electron-rich sites on organic compounds and initiates complex radical chain reactions in aqueous phase advanced oxidation processes (AOPs). Computer based kinetic modeling requires a reaction pathway generator and predictions of associated reaction rate constants. Previously, we reported a reaction pathway generator that can enumerate the most important elementary reactions for aliphatic compounds. For the reaction rate constant predictor, we develop linear free energy relationships (LFERs) between aqueous phase literature-reported HO(•) reaction rate constants and theoretically calculated free energies of activation for H-atom abstraction from a C-H bond and HO(•) addition to alkenes. The theoretical method uses ab initio quantum mechanical calculations, Gaussian 1-3, for gas phase reactions and a solvation method, COSMO-RS theory, to estimate the impact of water. Theoretically calculated free energies of activation are found to be within approximately ±3 kcal/mol of experimental values. Considering errors that arise from quantum mechanical calculations and experiments, this should be within the acceptable errors. The established LFERs are used to predict the HO(•) reaction rate constants within a factor of 5 from the experimental values. This approach may be applied to other reaction mechanisms to establish a library of rate constant predictions for kinetic modeling of AOPs.

The Impact of Nuclear Reaction Rate Uncertainties on the Evolution of Core-collapse Supernova Progenitors

NASA Astrophysics Data System (ADS)

Fields, C. E.; Timmes, F. X.; Farmer, R.; Petermann, I.; Wolf, William M.; Couch, S. M.

2018-02-01

We explore properties of core-collapse supernova progenitors with respect to the composite uncertainties in the thermonuclear reaction rates by coupling the probability density functions of the reaction rates provided by the STARLIB reaction rate library with MESA stellar models. We evolve 1000 models of 15{M}ȯ from the pre-main sequence to core O-depletion at solar and subsolar metallicities for a total of 2000 Monte Carlo stellar models. For each stellar model, we independently and simultaneously sample 665 thermonuclear reaction rates and use them in a MESA in situ reaction network that follows 127 isotopes from 1H to 64Zn. With this framework we survey the core mass, burning lifetime, composition, and structural properties at five different evolutionary epochs. At each epoch we measure the probability distribution function of the variations of each property and calculate Spearman rank-order correlation coefficients for each sampled reaction rate to identify which reaction rate has the largest impact on the variations on each property. We find that uncertainties in the reaction rates of {}14{{N}}{({{p}},γ )}15{{O}}, triple-α, {}12{{C}}{(α ,γ )}16{{O}}, 12C(12C,p)23Na, 12C(16O, p)27Al, 16O(16O,n)31S, 16O(16O, p)31P, and 16O(16O,α)28Si dominate the variations of the properties surveyed. We find that variations induced by uncertainties in nuclear reaction rates grow with each passing phase of evolution, and at core H-, He-depletion they are of comparable magnitude to the variations induced by choices of mass resolution and network resolution. However, at core C-, Ne-, and O-depletion, the reaction rate uncertainties can dominate the variation, causing uncertainty in various properties of the stellar model in the evolution toward iron core-collapse.

Reaction of atomic bromine with acetylene and loss rate of atmospheric acetylene due to reaction with OH, Cl, O, and Br

NASA Technical Reports Server (NTRS)

Payne, W. A.; Nava, D. F.; Brunning, J.; Stief, L. J.

1986-01-01

The first-order, diffusion, and bimolecular rate constants for the reaction Br + C2H2 yields C2H3Br are evaluated. The rate constants are measured at 210, 248, 298, and 393 K and at pressures between 15-100 torr Ar using flash photolysis combined with time-resolved detection of atomic bromine via Br resonance radiation. It is observed that the reaction is not affected by pressure or temperature and the bimolecular constant = (4.0 + or - 0.8) x 10 to the -15th cu cm/sec with an error of two standard deviations. The C2H2 + Br reaction rates are compared with reactions of C2H2 with Cl, OH, NH2, and H. The loss rates for atmospheric C2H2 for reactions with OH, Cl, O, and Br are calculated as a function of altitude.

A DETERMINISTIC GEOMETRIC REPRESENTATION OF TEMPORAL RAINFALL: SENSITIVITY ANALYSIS FOR A STORM IN BOSTON. (R824780)

EPA Science Inventory

In an earlier study, Puente and Obregón [Water Resour. Res. 32(1996)2825] reported on the usage of a deterministic fractal–multifractal (FM) methodology to faithfully describe an 8.3 h high-resolution rainfall time series in Boston, gathered every 15 s ...

Seed availability constrains plant species sorting along a soil fertility gradient

Treesearch

Bryan L. Foster; Erin J. Questad; Cathy D. Collins; Cheryl A. Murphy; Timothy L. Dickson; Val H. Smith

2011-01-01

1. Spatial variation in species composition within and among communities may be caused by deterministic, niche-based species sorting in response to underlying environmental heterogeneity as well as by stochastic factors such as dispersal limitation and variable species pools. An important goal in ecology is to reconcile deterministic and stochastic perspectives of...

The Role of Probability and Intentionality in Preschoolers' Causal Generalizations

ERIC Educational Resources Information Center

Sobel, David M.; Sommerville, Jessica A.; Travers, Lea V.; Blumenthal, Emily J.; Stoddard, Emily

2009-01-01

Three experiments examined whether preschoolers recognize that the causal properties of objects generalize to new members of the same set given either deterministic or probabilistic data. Experiment 1 found that 3- and 4-year-olds were able to make such a generalization given deterministic data but were at chance when they observed probabilistic…

Service-Oriented Architecture (SOA) Instantiation within a Hard Real-Time, Deterministic Combat System Environment

ERIC Educational Resources Information Center

Moreland, James D., Jr

2013-01-01

This research investigates the instantiation of a Service-Oriented Architecture (SOA) within a hard real-time (stringent time constraints), deterministic (maximum predictability) combat system (CS) environment. There are numerous stakeholders across the U.S. Department of the Navy who are affected by this development, and therefore the system…

CPT-based probabilistic and deterministic assessment of in situ seismic soil liquefaction potential

USGS Publications Warehouse

Moss, R.E.S.; Seed, R.B.; Kayen, R.E.; Stewart, J.P.; Der Kiureghian, A.; Cetin, K.O.

2006-01-01

This paper presents a complete methodology for both probabilistic and deterministic assessment of seismic soil liquefaction triggering potential based on the cone penetration test (CPT). A comprehensive worldwide set of CPT-based liquefaction field case histories were compiled and back analyzed, and the data then used to develop probabilistic triggering correlations. Issues investigated in this study include improved normalization of CPT resistance measurements for the influence of effective overburden stress, and adjustment to CPT tip resistance for the potential influence of "thin" liquefiable layers. The effects of soil type and soil character (i.e., "fines" adjustment) for the new correlations are based on a combination of CPT tip and sleeve resistance. To quantify probability for performancebased engineering applications, Bayesian "regression" methods were used, and the uncertainties of all variables comprising both the seismic demand and the liquefaction resistance were estimated and included in the analysis. The resulting correlations were developed using a Bayesian framework and are presented in both probabilistic and deterministic formats. The results are compared to previous probabilistic and deterministic correlations. ?? 2006 ASCE.

Comparison of Deterministic and Probabilistic Radial Distribution Systems Load Flow

NASA Astrophysics Data System (ADS)

Gupta, Atma Ram; Kumar, Ashwani

2017-12-01

Distribution system network today is facing the challenge of meeting increased load demands from the industrial, commercial and residential sectors. The pattern of load is highly dependent on consumer behavior and temporal factors such as season of the year, day of the week or time of the day. For deterministic radial distribution load flow studies load is taken as constant. But, load varies continually with a high degree of uncertainty. So, there is a need to model probable realistic load. Monte-Carlo Simulation is used to model the probable realistic load by generating random values of active and reactive power load from the mean and standard deviation of the load and for solving a Deterministic Radial Load Flow with these values. The probabilistic solution is reconstructed from deterministic data obtained for each simulation. The main contribution of the work is: Finding impact of probable realistic ZIP load modeling on balanced radial distribution load flow. Finding impact of probable realistic ZIP load modeling on unbalanced radial distribution load flow. Compare the voltage profile and losses with probable realistic ZIP load modeling for balanced and unbalanced radial distribution load flow.

Unsteady Flows in a Single-Stage Transonic Axial-Flow Fan Stator Row. Ph.D. Thesis - Iowa State Univ.

NASA Technical Reports Server (NTRS)

Hathaway, Michael D.

1986-01-01

Measurements of the unsteady velocity field within the stator row of a transonic axial-flow fan were acquired using a laser anemometer. Measurements were obtained on axisymmetric surfaces located at 10 and 50 percent span from the shroud, with the fan operating at maximum efficiency at design speed. The ensemble-average and variance of the measured velocities are used to identify rotor-wake-generated (deterministic) unsteadiness and turbulence, respectively. Correlations of both deterministic and turbulent velocity fluctuations provide information on the characteristics of unsteady interactions within the stator row. These correlations are derived from the Navier-Stokes equation in a manner similar to deriving the Reynolds stress terms, whereby various averaging operators are used to average the aperiodic, deterministic, and turbulent velocity fluctuations which are known to be present in multistage turbomachines. The correlations of deterministic and turbulent velocity fluctuations throughout the axial fan stator row are presented. In particular, amplification and attenuation of both types of unsteadiness are shown to occur within the stator blade passage.

Precision production: enabling deterministic throughput for precision aspheres with MRF

NASA Astrophysics Data System (ADS)

Maloney, Chris; Entezarian, Navid; Dumas, Paul

2017-10-01

Aspherical lenses offer advantages over spherical optics by improving image quality or reducing the number of elements necessary in an optical system. Aspheres are no longer being used exclusively by high-end optical systems but are now replacing spherical optics in many applications. The need for a method of production-manufacturing of precision aspheres has emerged and is part of the reason that the optics industry is shifting away from artisan-based techniques towards more deterministic methods. Not only does Magnetorheological Finishing (MRF) empower deterministic figure correction for the most demanding aspheres but it also enables deterministic and efficient throughput for series production of aspheres. The Q-flex MRF platform is designed to support batch production in a simple and user friendly manner. Thorlabs routinely utilizes the advancements of this platform and has provided results from using MRF to finish a batch of aspheres as a case study. We have developed an analysis notebook to evaluate necessary specifications for implementing quality control metrics. MRF brings confidence to optical manufacturing by ensuring high throughput for batch processing of aspheres.

Down to the roughness scale assessment of piston-ring/liner contacts

NASA Astrophysics Data System (ADS)

Checo, H. M.; Jaramillo, A.; Ausas, R. F.; Jai, M.; Buscaglia, G. C.

2017-02-01

The effects of surface roughness in hydrodynamic bearings been accounted for through several approaches, the most widely used being averaging or stochastic techniques. With these the surface is not treated “as it is”, but by means of an assumed probability distribution for the roughness. The so called direct, deterministic or measured-surface simulation) solve the lubrication problem with realistic surfaces down to the roughness scale. This leads to expensive computational problems. Most researchers have tackled this problem considering non-moving surfaces and neglecting the ring dynamics to reduce the computational burden. What is proposed here is to solve the fully-deterministic simulation both in space and in time, so that the actual movement of the surfaces and the rings dynamics are taken into account. This simulation is much more complex than previous ones, as it is intrinsically transient. The feasibility of these fully-deterministic simulations is illustrated two cases: fully deterministic simulation of liner surfaces with diverse finishings (honed and coated bores) with constant piston velocity and load on the ring and also in real engine conditions.

Correlated uncertainties in Monte Carlo reaction rate calculations

NASA Astrophysics Data System (ADS)

Longland, Richard

2017-07-01

Context. Monte Carlo methods have enabled nuclear reaction rates from uncertain inputs to be presented in a statistically meaningful manner. However, these uncertainties are currently computed assuming no correlations between the physical quantities that enter those calculations. This is not always an appropriate assumption. Astrophysically important reactions are often dominated by resonances, whose properties are normalized to a well-known reference resonance. This insight provides a basis from which to develop a flexible framework for including correlations in Monte Carlo reaction rate calculations. Aims: The aim of this work is to develop and test a method for including correlations in Monte Carlo reaction rate calculations when the input has been normalized to a common reference. Methods: A mathematical framework is developed for including correlations between input parameters in Monte Carlo reaction rate calculations. The magnitude of those correlations is calculated from the uncertainties typically reported in experimental papers, where full correlation information is not available. The method is applied to four illustrative examples: a fictional 3-resonance reaction, 27Al(p, γ)28Si, 23Na(p, α)20Ne, and 23Na(α, p)26Mg. Results: Reaction rates at low temperatures that are dominated by a few isolated resonances are found to minimally impacted by correlation effects. However, reaction rates determined from many overlapping resonances can be significantly affected. Uncertainties in the 23Na(α, p)26Mg reaction, for example, increase by up to a factor of 5. This highlights the need to take correlation effects into account in reaction rate calculations, and provides insight into which cases are expected to be most affected by them. The impact of correlation effects on nucleosynthesis is also investigated.

Characterization of shock-dependent reaction rates in an aluminum/perfluoropolyether pyrolant

NASA Astrophysics Data System (ADS)

Wilson, Dennis; Granier, John; Johnson, Richard; Littrell, Donald

2017-01-01

Energetic formulations of perfluoropolyether (PFPE) and aluminum are highly non-ideal. They release energy via a fast self-oxidized combustion wave rather than a true self-sustaining detonation. Unlike high explosives, the reactions are shock dependent and can be overdriven to control energy release rate. Reaction rate experiments show that the velocity can vary from 1.25 to 3 km/s. This paper examines the effect of the initial shock conditions upon the reaction rate of the explosive. The following conditions were varied in a series of reaction rate experiments: the high explosive booster mass and geometry; shock attenuation; confinement; and rate stick diameter and length. Several experiments designed to isolate and quantify these dependencies are described and summarized.

Pop-it beads to introduce catalysis of reaction rate and substrate depletion effects.

PubMed

Gehret, Austin U

2017-03-04

A kinesthetic classroom activity was designed to help students understand enzyme activity and catalysis of reaction rate. Students served the role of enzymes by manipulating Pop-It Beads as the catalytic event. This activity illuminates the relationship between reaction rate and reaction progress by allowing students to experience first-hand the effect of substrate depletion on catalyzed reaction rate. Preliminary findings based on survey results and exam performance suggest the activity could prove beneficial to students in the targeted learning outcomes. Unique to previous kinesthetic approaches that model Michaelis-Menten kinetics, this activity models the effects of substrate depletion on catalyzed reaction rate. Therefore, it could prove beneficial for conveying the reasoning behind the initial rate simplification used in Michaelis-Menten kinetics. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(2):179-183, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

Optimal Control Inventory Stochastic With Production Deteriorating

NASA Astrophysics Data System (ADS)

Affandi, Pardi

2018-01-01

In this paper, we are using optimal control approach to determine the optimal rate in production. Most of the inventory production models deal with a single item. First build the mathematical models inventory stochastic, in this model we also assume that the items are in the same store. The mathematical model of the problem inventory can be deterministic and stochastic models. In this research will be discussed how to model the stochastic as well as how to solve the inventory model using optimal control techniques. The main tool in the study problems for the necessary optimality conditions in the form of the Pontryagin maximum principle involves the Hamilton function. So we can have the optimal production rate in a production inventory system where items are subject deterioration.

Chaos-assisted tunneling in the presence of Anderson localization.

PubMed

Doggen, Elmer V H; Georgeot, Bertrand; Lemarié, Gabriel

2017-10-01

Tunneling between two classically disconnected regular regions can be strongly affected by the presence of a chaotic sea in between. This phenomenon, known as chaos-assisted tunneling, gives rise to large fluctuations of the tunneling rate. Here we study chaos-assisted tunneling in the presence of Anderson localization effects in the chaotic sea. Our results show that the standard tunneling rate distribution is strongly modified by localization, going from the Cauchy distribution in the ergodic regime to a log-normal distribution in the strongly localized case, for both a deterministic and a disordered model. We develop a single-parameter scaling description which accurately describes the numerical data. Several possible experimental implementations using cold atoms, photonic lattices, or microwave billiards are discussed.

Spatial scaling patterns and functional redundancies in a changing boreal lake landscape

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Uden, Daniel R.; Johnson, Richard K.

2015-01-01

Global transformations extend beyond local habitats; therefore, larger-scale approaches are needed to assess community-level responses and resilience to unfolding environmental changes. Using longterm data (1996–2011), we evaluated spatial patterns and functional redundancies in the littoral invertebrate communities of 85 Swedish lakes, with the objective of assessing their potential resilience to environmental change at regional scales (that is, spatial resilience). Multivariate spatial modeling was used to differentiate groups of invertebrate species exhibiting spatial patterns in composition and abundance (that is, deterministic species) from those lacking spatial patterns (that is, stochastic species). We then determined the functional feeding attributes of the deterministic and stochastic invertebrate species, to infer resilience. Between one and three distinct spatial patterns in invertebrate composition and abundance were identified in approximately one-third of the species; the remainder were stochastic. We observed substantial differences in metrics between deterministic and stochastic species. Functional richness and diversity decreased over time in the deterministic group, suggesting a loss of resilience in regional invertebrate communities. However, taxon richness and redundancy increased monotonically in the stochastic group, indicating the capacity of regional invertebrate communities to adapt to change. Our results suggest that a refined picture of spatial resilience emerges if patterns of both the deterministic and stochastic species are accounted for. Spatially extensive monitoring may help increase our mechanistic understanding of community-level responses and resilience to regional environmental change, insights that are critical for developing management and conservation agendas in this current period of rapid environmental transformation.

Pop-It Beads to Introduce Catalysis of Reaction Rate and Substrate Depletion Effects

ERIC Educational Resources Information Center

Gehret, Austin U.

2017-01-01

A kinesthetic classroom activity was designed to help students understand enzyme activity and catalysis of reaction rate. Students served the role of enzymes by manipulating Pop-It Beads as the catalytic event. This activity illuminates the relationship between reaction rate and reaction progress by allowing students to experience first-hand the…

Temperature-Dependent Rate Coefficients for the Reaction of CH2OO with Hydrogen Sulfide.

PubMed

Smith, Mica C; Chao, Wen; Kumar, Manoj; Francisco, Joseph S; Takahashi, Kaito; Lin, Jim Jr-Min

2017-02-09

The reaction of the simplest Criegee intermediate CH 2 OO with hydrogen sulfide was measured with transient UV absorption spectroscopy in a temperature-controlled flow reactor, and bimolecular rate coefficients were obtained from 278 to 318 K and from 100 to 500 Torr. The average rate coefficient at 298 K and 100 Torr was (1.7 ± 0.2) × 10 -13 cm 3 s -1 . The reaction was found to be independent of pressure and exhibited a weak negative temperature dependence. Ab initio quantum chemistry calculations of the temperature-dependent reaction rate coefficient at the QCISD(T)/CBS level are in reasonable agreement with the experiment. The reaction of CH 2 OO with H 2 S is 2-3 orders of magnitude faster than the reaction with H 2 O monomer. Though rates of CH 2 OO scavenging by water vapor under atmospheric conditions are primarily controlled by the reaction with water dimer, the H 2 S loss pathway will be dominated by the reaction with monomer. The agreement between experiment and theory for the CH 2 OO + H 2 S reaction lends credence to theoretical descriptions of other Criegee intermediate reactions that cannot easily be probed experimentally.

Determining Role of the Chain Mechanism in the Temperature Dependence of the Gas-Phase Rate of Combustion Reactions

NASA Astrophysics Data System (ADS)

Azatyan, V. V.; Bolod'yan, I. A.; Kopylov, N. P.; Kopylov, S. N.; Prokopenko, V. M.; Shebeko, Yu. N.

2018-05-01

It is shown that the strong dependence of the rate of gas-phase combustion reactions on temperature is determined by the high values of the reaction rate constants of free atoms and radicals. It is established that with a branched chain mechanism, a special role in the reaction rate temperature dependence is played by positive feedback between the concentrations of active intermediate species and the rate of their change. The role of the chemical mechanism in the temperature dependence of the process rate with and without inhibitors is considered.

Discovery of a Significant Acetone•Hydroperoxy Adduct Chaperone Effect and Its Impact on the Determination of Room Temperature Rate Constants for Acetonylperoxy/Hydroperoxy Self-Reactions and Cross Reaction Via Infrared Kinetic Spectroscopy.

NASA Astrophysics Data System (ADS)

Grieman, F. J.; Hui, A. O.; Okumura, M.; Sander, S. P.

2017-12-01

In order to model the upper troposphere/lower stratosphere in regions containing acetone properly, the kinetics of the acetonylperoxy/hydroperoxy self-reactions and cross reaction have been studied over a wide temperature range using Infrared Kinetic Spectroscopy. We report here the determination of different rate constants for the acetonylperoxy chemistry that we obtained at 298 K compared to currently accepted values. A considerable increase in the observed HO2 self-reaction rate constant due to rate enhancement via the chaperone effect from the reaction between HO2 and the (CH3)2CO•HO2 hydrogen-bonded adduct, even at room temperature, was discovered that was previously ignored. Correct determination of the acetonylperoxy and hydroperoxy kinetics must include this dependence of the HO2 self-reaction rate on acetone concentration. Via excimer laser flash photolysis to create the radical reactants, HO2 absorption was monitored in the infrared by diode laser wavelength modulation detection simultaneously with CH3C(O)CH2O2absorption monitored in the ultraviolet at 300 nm as a function of time. Resulting decay curves were fit concurrently first over a short time scale to obtain the rate constants minimizing subsequent product reactions. Modeling/fitting with a complete reaction scheme was then performed to refine the rate constants and test their veracity. Experiments were carried out over a variety of concentrations of acetone and methanol. Although no effect due to methanol concentration was found at room temperature, the rate constant for the hydroperoxy self-reaction was found to increase linearly with acetone concentration which is interpreted as the adduct being formed and resulting in a chaperone mechanism that enhances the self-reaction rate: (CH3)2CO·HO2 + HO2 → H2O2 + O2 + (CH3)2CO Including this effect, the resulting room temperature rate constants for the cross reaction and the acetonylperoxy self-reaction were found to be 2-3 times smaller than previously reported. This complex formation/chaperone mechanism is similar to that found for methanol, but different in that it occurs at room temperature. No precursor concentration dependence was found for the acetonylperoxy radical reactions. The equilibrium constant for the complex formation will also be presented.

Neutronics Investigations for the Lower Part of a Westinghouse SVEA-96+ Assembly

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

Murphy, M.F.; Luethi, A.; Seiler, R.

2002-05-15

Accurate critical experiments have been performed for the validation of total fission (F{sub tot}) and {sup 238}U-capture (C{sub 8}) reaction rate distributions obtained with CASMO-4, HELIOS, BOXER, and MCNP4B for the lower axial region of a real Westinghouse SVEA-96+ fuel assembly. The assembly comprised fresh fuel with an average {sup 235}U enrichment of 4.02 wt%, a maximum enrichment of 4.74 wt%, 14 burnable-absorber fuel pins, and full-density water moderation. The experimental configuration investigated was core 1A of the LWR-PROTEUS Phase I project, where 61 different fuel pins, representing {approx}64% of the assembly, were gamma-scanned individually. Calculated (C) and measured (E)more » values have been compared in terms of C/E distributions. For F{sub tot}, the standard deviations are 1.2% for HELIOS, 0.9% for CASMO-4, 0.8% for MCNP4B, and 1.7% for BOXER. Standard deviations of 1.1% for HELIOS, CASMO-4, and MCNP4B and 1.2% for BOXER were obtained in the case of C{sub 8}. Despite the high degree of accuracy observed on the average, it was found that the five burnable-absorber fuel pins investigated showed a noticeable underprediction of F{sub tot}, quite systematically, for the deterministic codes evaluated (average C/E for the burnable-absorber fuel pins in the range 0.974 to 0.988, depending on the code)« less

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.

Impact of refining the assessment of dietary exposure to cadmium in the European adult population.

PubMed

Ferrari, Pietro; Arcella, Davide; Heraud, Fanny; Cappé, Stefano; Fabiansson, Stefan

2013-01-01

Exposure assessment constitutes an important step in any risk assessment of potentially harmful substances present in food. The European Food Safety Authority (EFSA) first assessed dietary exposure to cadmium in Europe using a deterministic framework, resulting in mean values of exposure in the range of health-based guidance values. Since then, the characterisation of foods has been refined to better match occurrence and consumption data, and a new strategy to handle left-censoring in occurrence data was devised. A probabilistic assessment was performed and compared with deterministic estimates, using occurrence values at the European level and consumption data from 14 national dietary surveys. Mean estimates in the probabilistic assessment ranged from 1.38 (95% CI = 1.35-1.44) to 2.08 (1.99-2.23) µg kg⁻¹ bodyweight (bw) week⁻¹ across the different surveys, which were less than 10% lower than deterministic (middle bound) mean values that ranged from 1.50 to 2.20 µg kg⁻¹ bw week⁻¹. Probabilistic 95th percentile estimates of dietary exposure ranged from 2.65 (2.57-2.72) to 4.99 (4.62-5.38) µg kg⁻¹ bw week⁻¹, which were, with the exception of one survey, between 3% and 17% higher than middle-bound deterministic estimates. Overall, the proportion of subjects exceeding the tolerable weekly intake of 2.5 µg kg⁻¹ bw ranged from 14.8% (13.6-16.0%) to 31.2% (29.7-32.5%) according to the probabilistic assessment. The results of this work indicate that mean values of dietary exposure to cadmium in the European population were of similar magnitude using determinist or probabilistic assessments. For higher exposure levels, probabilistic estimates were almost consistently larger than deterministic counterparts, thus reflecting the impact of using the full distribution of occurrence values to determine exposure levels. It is considered prudent to use probabilistic methodology should exposure estimates be close to or exceeding health-based guidance values.

Comparison of probabilistic and deterministic fiber tracking of cranial nerves.

PubMed

Zolal, Amir; Sobottka, Stephan B; Podlesek, Dino; Linn, Jennifer; Rieger, Bernhard; Juratli, Tareq A; Schackert, Gabriele; Kitzler, Hagen H

2017-09-01

OBJECTIVE The depiction of cranial nerves (CNs) using diffusion tensor imaging (DTI) is of great interest in skull base tumor surgery and DTI used with deterministic tracking methods has been reported previously. However, there are still no good methods usable for the elimination of noise from the resulting depictions. The authors have hypothesized that probabilistic tracking could lead to more accurate results, because it more efficiently extracts information from the underlying data. Moreover, the authors have adapted a previously described technique for noise elimination using gradual threshold increases to probabilistic tracking. To evaluate the utility of this new approach, a comparison is provided with this work between the gradual threshold increase method in probabilistic and deterministic tracking of CNs. METHODS Both tracking methods were used to depict CNs II, III, V, and the VII+VIII bundle. Depiction of 240 CNs was attempted with each of the above methods in 30 healthy subjects, which were obtained from 2 public databases: the Kirby repository (KR) and Human Connectome Project (HCP). Elimination of erroneous fibers was attempted by gradually increasing the respective thresholds (fractional anisotropy [FA] and probabilistic index of connectivity [PICo]). The results were compared with predefined ground truth images based on corresponding anatomical scans. Two label overlap measures (false-positive error and Dice similarity coefficient) were used to evaluate the success of both methods in depicting the CN. Moreover, the differences between these parameters obtained from the KR and HCP (with higher angular resolution) databases were evaluated. Additionally, visualization of 10 CNs in 5 clinical cases was attempted with both methods and evaluated by comparing the depictions with intraoperative findings. RESULTS Maximum Dice similarity coefficients were significantly higher with probabilistic tracking (p < 0.001; Wilcoxon signed-rank test). The false-positive error of the last obtained depiction was also significantly lower in probabilistic than in deterministic tracking (p < 0.001). The HCP data yielded significantly better results in terms of the Dice coefficient in probabilistic tracking (p < 0.001, Mann-Whitney U-test) and in deterministic tracking (p = 0.02). The false-positive errors were smaller in HCP data in deterministic tracking (p < 0.001) and showed a strong trend toward significance in probabilistic tracking (p = 0.06). In the clinical cases, the probabilistic method visualized 7 of 10 attempted CNs accurately, compared with 3 correct depictions with deterministic tracking. CONCLUSIONS High angular resolution DTI scans are preferable for the DTI-based depiction of the cranial nerves. Probabilistic tracking with a gradual PICo threshold increase is more effective for this task than the previously described deterministic tracking with a gradual FA threshold increase and might represent a method that is useful for depicting cranial nerves with DTI since it eliminates the erroneous fibers without manual intervention.

Power hand tool kinetics associated with upper limb injuries in an automobile assembly plant.

PubMed

Ku, Chia-Hua; Radwin, Robert G; Karsh, Ben-Tzion

2007-06-01

This study investigated the relationship between pneumatic nutrunner handle reactions, workstation characteristics, and prevalence of upper limb injuries in an automobile assembly plant. Tool properties (geometry, inertial properties, and motor characteristics), fastener properties, orientation relative to the fastener, and the position of the tool operator (horizontal and vertical distances) were measured for 69 workstations using 15 different pneumatic nutrunners. Handle reaction response was predicted using a deterministic mechanical model of the human operator and tool that was previously developed in our laboratory, specific to the measured tool, workstation, and job factors. Handle force was a function of target torque, tool geometry and inertial properties, motor speed, work orientation, and joint hardness. The study found that tool target torque was not well correlated with predicted handle reaction force (r=0.495) or displacement (r=0.285). The individual tool, tool shape, and threaded fastener joint hardness all affected predicted forces and displacements (p<0.05). The average peak handle force and displacement for right-angle tools were twice as great as pistol grip tools. Soft-threaded fastener joints had the greatest average handle forces and displacements. Upper limb injury cases were identified using plant OSHA 200 log and personnel records. Predicted handle forces for jobs where injuries were reported were significantly greater than those jobs free of injuries (p<0.05), whereas target torque and predicted handle displacement did not show statistically significant differences. The study concluded that quantification of handle reaction force, rather than target torque alone, is necessary for identifying stressful power hand tool operations and for controlling exposure to forces in manufacturing jobs involving power nutrunners. Therefore, a combination of tool, work station, and task requirements should be considered.

Will Coral Islands Maintain Their Growth over the Next Century? A Deterministic Model of Sediment Availability at Lady Elliot Island, Great Barrier Reef

PubMed Central

Hamylton, Sarah

2014-01-01

A geomorphic assessment of reef system calcification is conducted for past (3200 Ka to present), present and future (2010–2100) time periods. Reef platform sediment production is estimated at 569 m3 yr−1 using rate laws that express gross community carbonate production as a function of seawater aragonite saturation, community composition and rugosity and incorporating estimates of carbonate removal from the reef system. Key carbonate producers including hard coral, crustose coralline algae and Halimeda are mapped accurately (mean R2 = 0.81). Community net production estimates correspond closely to independent census-based estimates made in-situ (R2 = 0.86). Reef-scale outputs are compared with historic rates of production generated from (i) radiocarbon evidence of island deposition initiation around 3200 years ago, and (ii) island volume calculated from a high resolution island digital elevation model. Contemporary carbonate production rates appear to be remarkably similar to historical values of 573 m3 yr−1. Anticipated future seawater chemistry parameters associated with an RCP8.5 emissions scenario are employed to model rates of net community calcification for the period 2000–2100 on the basis of an inorganic aragonite precipitation law, under the assumption of constant benthic community character. Simulations indicate that carbonate production will decrease linearly to a level of 118 m3 yr−1 by 2100 and that by 2150 aragonite saturation levels may no longer support the positive budgetary status necessary to sustain island accretion. Novel aspects of this assessment include the development of rate law parameters to realistically represent the variable composition of coral reef benthic carbonate producers, incorporation of three dimensional rugosity of the entire reef platform and the coupling of model outputs with both historical radiocarbon dating evidence and forward hydrochemical projections to conduct an assessment of island evolution through time. By combining several lines of evidence in a deterministic manner, an assessment of changes in carbonate production is carried out that has tangible geomorphic implications for sediment availability and associated island evolution. PMID:24759700

Will Coral Islands maintain their growth over the next century? A deterministic model of sediment availability at Lady Elliot Island, Great Barrier Reef.

PubMed

Hamylton, Sarah

2014-01-01

A geomorphic assessment of reef system calcification is conducted for past (3200 Ka to present), present and future (2010-2100) time periods. Reef platform sediment production is estimated at 569 m3 yr-1 using rate laws that express gross community carbonate production as a function of seawater aragonite saturation, community composition and rugosity and incorporating estimates of carbonate removal from the reef system. Key carbonate producers including hard coral, crustose coralline algae and Halimeda are mapped accurately (mean R2 = 0.81). Community net production estimates correspond closely to independent census-based estimates made in-situ (R2 = 0.86). Reef-scale outputs are compared with historic rates of production generated from (i) radiocarbon evidence of island deposition initiation around 3200 years ago, and (ii) island volume calculated from a high resolution island digital elevation model. Contemporary carbonate production rates appear to be remarkably similar to historical values of 573 m3 yr-1. Anticipated future seawater chemistry parameters associated with an RCP8.5 emissions scenario are employed to model rates of net community calcification for the period 2000-2100 on the basis of an inorganic aragonite precipitation law, under the assumption of constant benthic community character. Simulations indicate that carbonate production will decrease linearly to a level of 118 m3 yr-1 by 2100 and that by 2150 aragonite saturation levels may no longer support the positive budgetary status necessary to sustain island accretion. Novel aspects of this assessment include the development of rate law parameters to realistically represent the variable composition of coral reef benthic carbonate producers, incorporation of three dimensional rugosity of the entire reef platform and the coupling of model outputs with both historical radiocarbon dating evidence and forward hydrochemical projections to conduct an assessment of island evolution through time. By combining several lines of evidence in a deterministic manner, an assessment of changes in carbonate production is carried out that has tangible geomorphic implications for sediment availability and associated island evolution.

A mesoscopic reaction rate model for shock initiation of multi-component PBX explosives.

PubMed

Liu, Y R; Duan, Z P; Zhang, Z Y; Ou, Z C; Huang, F L

2016-11-05

The primary goal of this research is to develop a three-term mesoscopic reaction rate model that consists of a hot-spot ignition, a low-pressure slow burning and a high-pressure fast reaction terms for shock initiation of multi-component Plastic Bonded Explosives (PBX). Thereinto, based on the DZK hot-spot model for a single-component PBX explosive, the hot-spot ignition term as well as its reaction rate is obtained through a "mixing rule" of the explosive components; new expressions for both the low-pressure slow burning term and the high-pressure fast reaction term are also obtained by establishing the relationships between the reaction rate of the multi-component PBX explosive and that of its explosive components, based on the low-pressure slow burning term and the high-pressure fast reaction term of a mesoscopic reaction rate model. Furthermore, for verification, the new reaction rate model is incorporated into the DYNA2D code to simulate numerically the shock initiation process of the PBXC03 and the PBXC10 multi-component PBX explosives, and the numerical results of the pressure histories at different Lagrange locations in explosive are found to be in good agreements with previous experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

Rare events in finite and infinite dimensions

NASA Astrophysics Data System (ADS)

Reznikoff, Maria G.

Thermal noise introduces stochasticity into deterministic equations and makes possible events which are never seen in the zero temperature setting. The driving force behind the thesis work is a desire to bring analysis and probability to bear on a class of relevant and intriguing physical problems, and in so doing, to allow applications to drive the development of new mathematical theory. The unifying theme is the study of rare events under the influence of small, random perturbations, and the manifold mathematical problems which ensue. In the first part, we apply large deviation theory and prefactor estimates to a coherent rotation micromagnetic model in order to analyze thermally activated magnetic switching. We consider recent physical experiments and the mathematical questions "asked" by them. A stochastic resonance type phenomenon is discovered, leading to the definition of finite temperature astroids. Non-Arrhenius behavior is discussed. The analysis is extended to ramped astroids. In addition, we discover that for low damping and ultrashort pulses, deterministic effects can override thermal effects, in accord with very recent ultrashort pulse experiments. Even more interesting, perhaps, is the study of large deviations in the infinite dimensional context, i.e. in spatially extended systems. Inspired by recent numerical investigations, we study the stochastically perturbed Allen Cahn and Cahn Hilliard equations. For the Allen Cahn equation, we study the action minimization problem (a deterministic variational problem) and prove the action scaling in four parameter regimes, via upper and lower bounds. The sharp interface limit is studied. We formally derive a reduced action functional which lends insight into the connection between action minimization and curvature flow. For the Cahn Hilliard equation, we prove upper and lower bounds for the scaling of the energy barrier in the nucleation and growth regime. Finally, we consider rare events in large or infinite domains, in one spatial dimension. We introduce a natural reference measure through which to analyze the invariant measure of stochastically perturbed, nonlinear partial differential equations. Also, for noisy reaction diffusion equations with an asymmetric potential, we discover how to rescale space and time in order to map the dynamics in the zero temperature limit to the Poisson Model, a simple version of the Johnson-Mehl-Avrami-Kolmogorov model for nucleation and growth.

Estimation of Second Primary Cancer Risk After Treatment with Radioactive Iodine for Differentiated Thyroid Carcinoma.

PubMed

Corrêa, Nilton Lavatori; de Sá, Lidia Vasconcellos; de Mello, Rossana Corbo Ramalho

2017-02-01

An increase in the incidence of second primary cancers is the late effect of greatest concern that could occur in differentiated thyroid carcinoma (DTC) patients treated with radioactive iodine (RAI). The decision to treat a patient with RAI should therefore incorporate a careful risk-benefit analysis. The objective of this work was to adapt the risk-estimation models developed by the Biological Effects of Ionizing Radiation Committee to local epidemiological characteristics in order to assess the carcinogenesis risk from radiation in a population of Brazilian DTC patients treated with RAI. Absorbed radiation doses in critical organs were also estimated to determine whether they exceeded the thresholds for deterministic effects. A total of 416 DTC patients treated with RAI were retrospectively studied. Four organs were selected for absorbed dose estimation and subsequent calculation of carcinogenic risk: the kidney, stomach, salivary glands, and bone marrow. Absorbed doses were calculated by dose factors (absorbed dose per unit activity administered) previously established and based on standard human models. The lifetime attributable risk (LAR) of incidence of cancer as a function of age, sex, and organ-specific dose was estimated, relating it to the activity of RAI administered in the initial treatment. The salivary glands received the greatest absorbed doses of radiation, followed by the stomach, kidney, and bone marrow. None of these, however, surpassed the threshold for deterministic effects for a single administration of RAI. Younger patients received the same level of absorbed dose in the critical organs as older patients did. The lifetime attributable risk for stomach cancer incidence was by far the highest, followed in descending order by salivary-gland cancer, leukemia, and kidney cancer. RAI in a single administration is safe in terms of deterministic effects because even high-administered activities do not result in absorbed doses that exceed the thresholds for significant tissue reactions. The Biological Effects of Ionizing Radiation Committee mathematical models are a practical method of quantifying the risks of a second primary cancer, demonstrating a marked decrease in risk for younger patients with the administration of lower RAI activities and suggesting that only the smallest activities necessary to promote an effective ablation should be administered in low-risk DTC patients.

Method of controlling fusion reaction rates

DOEpatents

Kulsrud, Russell M.; Furth, Harold P.; Valeo, Ernest J.; Goldhaber, Maurice

1988-01-01

A method of controlling the reaction rates of the fuel atoms in a fusion reactor comprises the step of polarizing the nuclei of the fuel atoms in a particular direction relative to the plasma confining magnetic field. Fusion reaction rates can be increased or decreased, and the direction of emission of the reaction products can be controlled, depending on the choice of polarization direction.

Method of controlling fusion reaction rates

DOEpatents

Kulsrud, Russell M.; Furth, Harold P.; Valeo, Ernest J.; Goldhaber, Maurice

1988-03-01

A method of controlling the reaction rates of the fuel atoms in a fusion reactor comprises the step of polarizing the nuclei of the fuel atoms in a particular direction relative to the plasma confining magnetic field. Fusion reaction rates can be increased or decreased, and the direction of emission of the reaction products can be controlled, depending on the choice of polarization direction.

Dissolution Rates and Reaction Products of Olivine Interaction with Ammonia-Rich Fluid

NASA Astrophysics Data System (ADS)

Zandanel, A. E.; Truche, L.; Hellmann, R.; Tobie, G.; Marrocchi, Y.

2018-05-01

Olivine dissolution rates and reaction products in NH3-rich fluids are determined from experiments simulating H2O-rock interaction on Enceladus. Kinetic rates are calculated from flow through experiments and reaction products from static experiments.

Raman Spectral Determination of Chemical Reaction Rate Characteristics

NASA Astrophysics Data System (ADS)

Balakhnina, I. A.; Brandt, N. N.; Mankova, A. A.; Chikishev, A. Yu.; Shpachenko, I. G.

2017-09-01

The feasibility of using Raman spectroscopy to determine chemical reaction rates and activation energies has been demonstrated for the saponification of ethyl acetate. The temperature dependence of the reaction rate was found in the range from 15 to 45°C.

High temperature chemical kinetic study of the H2-CO-CO2-NO reaction system

NASA Technical Reports Server (NTRS)

Jachimowski, C. J.

1975-01-01

An experimental study of the kinetics of the H2-CO-CO2-NO reaction system was made behind incident shock waves at temperatures of 2460 and 2950 K. The overall rate of the reaction was measured by monitoring radiation from the CO + O yields CO2 + h upoilon reaction. Correlation of these data with a detailed reaction mechanism showed that the high-temperature rate of the reaction N + OH yields NO + H can be described by the low-temperature (320 K) rate coefficient. Catalytic dissociation of molecular hydrogen was an important reaction under the tests conditions.

Importance of tunneling in H-abstraction reactions by OH radicals. The case of CH4 + OH studied through isotope-substituted analogs

NASA Astrophysics Data System (ADS)

Lamberts, T.; Fedoseev, G.; Kästner, J.; Ioppolo, S.; Linnartz, H.

2017-03-01

We present a combined experimental and theoretical study focussing on the quantum tunneling of atoms in the reaction between CH4 and OH. The importance of this reaction pathway is derived by investigating isotope substituted analogs. Quantitative reaction rates needed for astrochemical models at low temperature are currently unavailable both in the solid state and in the gas phase. Here, we study tunneling effects upon hydrogen abstraction in CH4 + OH by focusing on two reactions: CH4 + OD → CH3 + HDO and CD4 + OH → CD3 + HDO. The experimental study shows that the solid-state reaction rate RCH4 + OD is higher than RCD4 + OH at 15 K. Experimental results are accompanied by calculations of the corresponding unimolecular and bimolecular reaction rate constants using instanton theory taking into account surface effects. For the work presented here, the unimolecular reactions are particularly interesting as these provide insight into reactions following a Langmuir-Hinshelwood process. The resulting ratio of the rate constants shows that the H abstraction (kCH4 + OD) is approximately ten times faster than D-abstraction (kCD4 + OH) at 65 K. We conclude that tunneling is involved at low temperatures in the abstraction reactions studied here. The unimolecular rate constants can be used by the modeling community as a first approach to describe OH-mediated abstraction reactions in the solid phase. For this reason we provide fits of our calculated rate constants that allow the inclusion of these reactions in models in a straightforward fashion.

Aspen succession in the Intermountain West: A deterministic model

Treesearch

Dale L. Bartos; Frederick R. Ward; George S. Innis

1983-01-01

A deterministic model of succession in aspen forests was developed using existing data and intuition. The degree of uncertainty, which was determined by allowing the parameter values to vary at random within limits, was larger than desired. This report presents results of an analysis of model sensitivity to changes in parameter values. These results have indicated...

Using stochastic models to incorporate spatial and temporal variability [Exercise 14

Treesearch

Carolyn Hull Sieg; Rudy M. King; Fred Van Dyke

2003-01-01

To this point, our analysis of population processes and viability in the western prairie fringed orchid has used only deterministic models. In this exercise, we conduct a similar analysis, using a stochastic model instead. This distinction is of great importance to population biology in general and to conservation biology in particular. In deterministic models,...

Taking Control: Stealth Assessment of Deterministic Behaviors within a Game-Based System

ERIC Educational Resources Information Center

Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S.

2016-01-01

Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…

Guidelines 13 and 14—Prediction uncertainty

USGS Publications Warehouse

Hill, Mary C.; Tiedeman, Claire

2005-01-01

An advantage of using optimization for model development and calibration is that optimization provides methods for evaluating and quantifying prediction uncertainty. Both deterministic and statistical methods can be used. Guideline 13 discusses using regression and post-audits, which we classify as deterministic methods. Guideline 14 discusses inferential statistics and Monte Carlo methods, which we classify as statistical methods.

Deterministic switching of hierarchy during wrinkling in quasi-planar bilayers

DOE PAGES

Saha, Sourabh K.; Culpepper, Martin L.

2016-04-25

Emergence of hierarchy during compression of quasi-planar bilayers is preceded by a mode-locked state during which the quasi-planar form persists. Transition to hierarchy is determined entirely by geometrically observable parameters. This results in a universal transition phase diagram that enables one to deterministically tune hierarchy even with limited knowledge about material properties.