Formation of the peak amplitude of blood flow oscillations at a frequency of 0.1 Hz in the human cardiovascular system by the noise effect on the heart

NASA Astrophysics Data System (ADS)

Grinevich, Andrey A.; Tankanag, Arina V.; Chemeris, Nikolay K.

2017-04-01

In the framework of our previous hypothesis about the participation of structural and hydrodynamic properties of the vascular bed in the formation of the 0.1-Hz component of blood flow oscillations in the human cardiovascular system and on the basis of the reduced hydrodynamic model, the role of additive stochastic perturbations of the operation of the single-chamber pump that simulates the heart was investigated. It was shown that aperiodic noise modulation of the rigidity of the walls of the pump or its valves generates low-frequency oscillations of pressure of arterial vascular bed with the spectral components at a frequency close to 0.1 Hz.

Quantifying stochasticity in the dynamics of delay-coupled semiconductor lasers via forbidden patterns.

PubMed

Tiana-Alsina, Jordi; Buldú, Javier M; Torrent, M C; García-Ojalvo, Jordi

2010-01-28

We quantify the level of stochasticity in the dynamics of two mutually coupled semiconductor lasers. Specifically, we concentrate on a regime in which the lasers synchronize their dynamics with a non-zero lag time, and the leader and laggard roles alternate irregularly between the lasers. We analyse this switching dynamics in terms of the number of forbidden patterns of the alternate time series. The results reveal that the system operates in a stochastic regime, with the level of stochasticity decreasing as the lasers are pumped further away from their lasing threshold. This behaviour is similar to that exhibited by a single semiconductor laser subject to external optical feedback, as its dynamics shifts from the regime of low-frequency fluctuations to coherence collapse. This journal is © 2010 The Royal Society

Stochastic modelling of temperatures affecting the in situ performance of a solar-assisted heat pump: The univariate approach

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

Loveday, D.L.; Craggs, C.

Univariate stochastic modeling, using Box-Jenkins methods, is carried out for three air temperatures which can influence the performance of a solar-assisted heat pump system. In this system, external ambient air (the low grade source) is pre-heated by the conventional tiled roof of an occupied domestic residence. The air then crosses the evaporator of an electrically driven split heat pump which is situated in the roof space. Autocorrelation coefficients are presented for time series of the following dry-bulb temperatures: the external air, the residence internal (lounge) air, and the air in the roofspace after pre-heating but prior to crossing the heatmore » pump evaporator. Hourly data relating to a two-week period in the heating season was utilized, providing a 336-h dataset. Univariate models fitted to the first 300 observations were validated by forecasting ahead for the remaining 36 h in steps of 1 h. Comparison of forecasted and measured values showed good agreement, except for a 4-h period in which the intensity of solar radiation exceeded that which prevailed during the modeled period. It is concluded that the Box-Jenkins approach can be used to develop univariate mathematical models which adequately describe building and climate thermal behavior, and that the importance of solar radiation in this respect should not be overlooked.« less

Broadband continuous-variable entanglement source using a chirped poling nonlinear crystal

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

Zhao, J. S.; Sun, L.; Yu, X. Q.

2010-01-15

Aperiodically poled nonlinear crystal can be used as a broadband continuous-variable entanglement source and has strong stability under perturbations. We study the conversion dynamics of the sum-frequency generation and the quantum correlation of the two pump fields in a chirped-structure nonlinear crystal using the quantum stochastic method. The results show that there exists a frequency window for the pumps where two optical fields can perform efficient upconversion. The two pump fields are demonstrated to be entangled in the window and the chirped-structure crystal can be used as a continuous-variable entanglement source with a broad response bandwidth.

Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability

NASA Astrophysics Data System (ADS)

Papoulakos, Konstantinos; Pollakis, Giorgos; Moustakis, Yiannis; Markopoulos, Apostolis; Iliopoulou, Theano; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; Efstratiadis, Andreas

2017-04-01

Small islands are regarded as promising areas for developing hybrid water-energy systems that combine multiple sources of renewable energy with pumped-storage facilities. Essential element of such systems is the water storage component (reservoir), which implements both flow and energy regulations. Apparently, the representation of the overall water-energy management problem requires the simulation of the operation of the reservoir system, which in turn requires a faithful estimation of water inflows and demands of water and energy. Yet, in small-scale reservoir systems, this task in far from straightforward, since both the availability and accuracy of associated information is generally very poor. For, in contrast to large-scale reservoir systems, for which it is quite easy to find systematic and reliable hydrological data, in the case of small systems such data may be minor or even totally missing. The stochastic approach is the unique means to account for input data uncertainties within the combined water-energy management problem. Using as example the Livadi reservoir, which is the pumped storage component of the small Aegean island of Astypalaia, Greece, we provide a simulation framework, comprising: (a) a stochastic model for generating synthetic rainfall and temperature time series; (b) a stochastic rainfall-runoff model, whose parameters cannot be inferred through calibration and, thus, they are represented as correlated random variables; (c) a stochastic model for estimating water supply and irrigation demands, based on simulated temperature and soil moisture, and (d) a daily operation model of the reservoir system, providing stochastic forecasts of water and energy outflows. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Relative phase noise induced impairment in M-ary phase-shift-keying coherent optical communication system using distributed fiber Raman amplifier.

PubMed

Cheng, Jingchi; Tang, Ming; Fu, Songnian; Shum, Perry Ping; Liu, Deming

2013-04-01

We show for the first time, to the best of our knowledge, that, in a coherent communication system that employs a phase-shift-keying signal and Raman amplification, besides the pump relative intensity noise (RIN) transfer to the amplitude, the signal's phase will also be affected by pump RIN through the pump-signal cross-phase modulation. Although the average pump power induced linear phase change can be compensated for by the phase-correction algorithm, a relative phase noise (RPN) parameter has been found to characterize pump RIN induced stochastic phase noise. This extra phase noise brings non-negligible system impairments in terms of the Q-factor penalty. The calculation shows that copumping leads to much more stringent requirements to pump RIN, and relatively larger fiber dispersion helps to suppress the RPN induced impairment. A higher-order phase-shift keying (PSK) signal is less tolerant to noise than a lower-order PSK.

Stochastic Analysis of Wind Energy for Wind Pump Irrigation in Coastal Andhra Pradesh, India

NASA Astrophysics Data System (ADS)

Raju, M. M.; Kumar, A.; Bisht, D.; Rao, D. B.

2014-09-01

The rapid escalation in the prices of oil and gas as well as increasing demand for energy has attracted the attention of scientists and researchers to explore the possibility of generating and utilizing the alternative and renewable sources of wind energy in the long coastal belt of India with considerable wind energy resources. A detailed analysis of wind potential is a prerequisite to harvest the wind energy resources efficiently. Keeping this in view, the present study was undertaken to analyze the wind energy potential to assess feasibility of the wind-pump operated irrigation system in the coastal region of Andhra Pradesh, India, where high ground water table conditions are available. The stochastic analysis of wind speed data were tested to fit a probability distribution, which describes the wind energy potential in the region. The normal and Weibull probability distributions were tested; and on the basis of Chi square test, the Weibull distribution gave better results. Hence, it was concluded that the Weibull probability distribution may be used to stochastically describe the annual wind speed data of coastal Andhra Pradesh with better accuracy. The size as well as the complete irrigation system with mass curve analysis was determined to satisfy various daily irrigation demands at different risk levels.

Groundwater withdrawal in randomly heterogeneous coastal aquifers

NASA Astrophysics Data System (ADS)

Siena, Martina; Riva, Monica

2018-05-01

We analyze the combined effects of aquifer heterogeneity and pumping operations on seawater intrusion (SWI), a phenomenon which is threatening coastal aquifers worldwide. Our investigation is set within a probabilistic framework and relies on a numerical Monte Carlo approach targeting transient variable-density flow and solute transport in a three-dimensional randomly heterogeneous porous domain. The geological setting is patterned after the Argentona river basin, in the Maresme region of Catalonia (Spain). Our numerical study is concerned with exploring the effects of (a) random heterogeneity of the domain on SWI in combination with (b) a variety of groundwater withdrawal schemes. The latter have been designed by varying the screen location along the vertical direction and the distance of the wellbore from the coastline and from the location of the freshwater-saltwater mixing zone which is in place prior to pumping. For each random realization of the aquifer permeability field and for each pumping scheme, a quantitative depiction of SWI phenomena is inferred from an original set of metrics characterizing (a) the inland penetration of the saltwater wedge and (b) the width of the mixing zone across the whole three-dimensional system. Our results indicate that the stochastic nature of the system heterogeneity significantly affects the statistical description of the main features of the seawater wedge either in the presence or in the absence of pumping, yielding a general reduction of toe penetration and an increase of the width of the mixing zone. Simultaneous extraction of fresh and saltwater from two screens along the same wellbore located, prior to pumping, within the freshwater-saltwater mixing zone is effective in limiting SWI in the context of groundwater resources exploitation.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Spontaneous Polariton Currents in Periodic Lateral Chains.

PubMed

Nalitov, A V; Liew, T C H; Kavokin, A V; Altshuler, B L; Rubo, Y G

2017-08-11

We predict spontaneous generation of superfluid polariton currents in planar microcavities with lateral periodic modulation of both the potential and decay rate. A spontaneous breaking of spatial inversion symmetry of a polariton condensate emerges at a critical pumping, and the current direction is stochastically chosen. We analyze the stability of the current with respect to the fluctuations of the condensate. A peculiar spatial current domain structure emerges, where the current direction is switched at the domain walls, and the characteristic domain size and lifetime scale with the pumping power.

Computer code for analyzing the performance of aquifer thermal energy storage systems

NASA Astrophysics Data System (ADS)

Vail, L. W.; Kincaid, C. T.; Kannberg, L. D.

1985-05-01

A code called Aquifer Thermal Energy Storage System Simulator (ATESSS) has been developed to analyze the operational performance of ATES systems. The ATESSS code provides an ability to examine the interrelationships among design specifications, general operational strategies, and unpredictable variations in the demand for energy. The uses of the code can vary the well field layout, heat exchanger size, and pumping/injection schedule. Unpredictable aspects of supply and demand may also be examined through the use of a stochastic model of selected system parameters. While employing a relatively simple model of the aquifer, the ATESSS code plays an important role in the design and operation of ATES facilities by augmenting experience provided by the relatively few field experiments and demonstration projects. ATESSS has been used to characterize the effect of different pumping/injection schedules on a hypothetical ATES system and to estimate the recovery at the St. Paul, Minnesota, field experiment.

Optimizing conjunctive use of surface water and groundwater resources with stochastic dynamic programming

NASA Astrophysics Data System (ADS)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter

2014-05-01

Optimal management of conjunctive use of surface water and groundwater has been attempted with different algorithms in the literature. In this study, a hydro-economic modelling approach to optimize conjunctive use of scarce surface water and groundwater resources under uncertainty is presented. A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due to head-dependent pumping costs. These dynamic pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment costs. As in traditional SDP approaches, one step-ahead sub-problems are solved to find the optimal management at any time knowing the inflow scenario and reservoir/aquifer storage levels. These non-linear sub-problems are solved using a genetic algorithm (GA) that minimizes the sum of the immediate and future costs for given surface water reservoir and groundwater aquifer end storages. The immediate cost is found by solving a simple linear allocation sub-problem, and the future costs are assessed by interpolation in the total cost matrix from the following time step. Total costs for all stages, reservoir states, and inflow scenarios are used as future costs to drive a forward moving simulation under uncertain water availability. The use of a GA to solve the sub-problems is computationally more costly than a traditional SDP approach with linearly interpolated future costs. However, in a two-reservoir system the future cost function would have to be represented by a set of planes, and strict convexity in both the surface water and groundwater dimension cannot be maintained. The optimization framework based on the GA is still computationally feasible and represents a clean and customizable method. The method has been applied to the Ziya River basin, China. The basin is located on the North China Plain and is subject to severe water scarcity, which includes surface water droughts and groundwater over-pumping. The head-dependent groundwater pumping costs will enable assessment of the long-term effects of increased electricity prices on the groundwater pumping. The coupled optimization framework is used to assess realistic alternative development scenarios for the basin. In particular the potential for using electricity pricing policies to reach sustainable groundwater pumping is investigated.

Radionuclide Gas Transport through Nuclear Explosion-Generated Fracture Networks

PubMed Central

Jordan, Amy B.; Stauffer, Philip H.; Knight, Earl E.; Rougier, Esteban; Anderson, Dale N.

2015-01-01

Underground nuclear weapon testing produces radionuclide gases which may seep to the surface. Barometric pumping of gas through explosion-fractured rock is investigated using a new sequentially-coupled hydrodynamic rock damage/gas transport model. Fracture networks are produced for two rock types (granite and tuff) and three depths of burial. The fracture networks are integrated into a flow and transport numerical model driven by surface pressure signals of differing amplitude and variability. There are major differences between predictions using a realistic fracture network and prior results that used a simplified geometry. Matrix porosity and maximum fracture aperture have the greatest impact on gas breakthrough time and window of opportunity for detection, with different effects between granite and tuff simulations highlighting the importance of accurately simulating the fracture network. In particular, maximum fracture aperture has an opposite effect on tuff and granite, due to different damage patterns and their effect on the barometric pumping process. From stochastic simulations using randomly generated hydrogeologic parameters, normalized detection curves are presented to show differences in optimal sampling time for granite and tuff simulations. Seasonal and location-based effects on breakthrough, which occur due to differences in barometric forcing, are stronger where the barometric signal is highly variable. PMID:26676058

Radionuclide Gas Transport through Nuclear Explosion-Generated Fracture Networks.

PubMed

Jordan, Amy B; Stauffer, Philip H; Knight, Earl E; Rougier, Esteban; Anderson, Dale N

2015-12-17

Underground nuclear weapon testing produces radionuclide gases which may seep to the surface. Barometric pumping of gas through explosion-fractured rock is investigated using a new sequentially-coupled hydrodynamic rock damage/gas transport model. Fracture networks are produced for two rock types (granite and tuff) and three depths of burial. The fracture networks are integrated into a flow and transport numerical model driven by surface pressure signals of differing amplitude and variability. There are major differences between predictions using a realistic fracture network and prior results that used a simplified geometry. Matrix porosity and maximum fracture aperture have the greatest impact on gas breakthrough time and window of opportunity for detection, with different effects between granite and tuff simulations highlighting the importance of accurately simulating the fracture network. In particular, maximum fracture aperture has an opposite effect on tuff and granite, due to different damage patterns and their effect on the barometric pumping process. From stochastic simulations using randomly generated hydrogeologic parameters, normalized detection curves are presented to show differences in optimal sampling time for granite and tuff simulations. Seasonal and location-based effects on breakthrough, which occur due to differences in barometric forcing, are stronger where the barometric signal is highly variable.

Combining Deterministic structures and stochastic heterogeneity for transport modeling

NASA Astrophysics Data System (ADS)

Zech, Alraune; Attinger, Sabine; Dietrich, Peter; Teutsch, Georg

2017-04-01

Contaminant transport in highly heterogeneous aquifers is extremely challenging and subject of current scientific debate. Tracer plumes often show non-symmetric but highly skewed plume shapes. Predicting such transport behavior using the classical advection-dispersion-equation (ADE) in combination with a stochastic description of aquifer properties requires a dense measurement network. This is in contrast to the available information for most aquifers. A new conceptual aquifer structure model is presented which combines large-scale deterministic information and the stochastic approach for incorporating sub-scale heterogeneity. The conceptual model is designed to allow for a goal-oriented, site specific transport analysis making use of as few data as possible. Thereby the basic idea is to reproduce highly skewed tracer plumes in heterogeneous media by incorporating deterministic contrasts and effects of connectivity instead of using unimodal heterogeneous models with high variances. The conceptual model consists of deterministic blocks of mean hydraulic conductivity which might be measured by pumping tests indicating values differing in orders of magnitudes. A sub-scale heterogeneity is introduced within every block. This heterogeneity can be modeled as bimodal or log-normal distributed. The impact of input parameters, structure and conductivity contrasts is investigated in a systematic manor. Furthermore, some first successful implementation of the model was achieved for the well known MADE site.

An ultra-high gain and efficient amplifier based on Raman amplification in plasma

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

Vieux, G.; Cipiccia, S.; Grant, D. W.

Raman amplification arising from the excitation of a density echelon in plasma could lead to amplifiers that significantly exceed current power limits of conventional laser media. Here we show that 1–100 J pump pulses can amplify picojoule seed pulses to nearly joule level. The extremely high gain also leads to significant amplification of backscattered radiation from “noise”, arising from stochastic plasma fluctuations that competes with externally injected seed pulses, which are amplified to similar levels at the highest pump energies. The pump energy is scattered into the seed at an oblique angle with 14 J sr -1, and net gainsmore » of more than eight orders of magnitude. The maximum gain coefficient, of 180 cm -1, exceeds high-power solid-state amplifying media by orders of magnitude. The observation of a minimum of 640 J sr -1 directly backscattered from noise, corresponding to ≈10% of the pump energy in the observation solid angle, implies potential overall efficiencies greater than 10%.« less

An ultra-high gain and efficient amplifier based on Raman amplification in plasma

DOE PAGES

Vieux, G.; Cipiccia, S.; Grant, D. W.; ...

2017-05-25

Raman amplification arising from the excitation of a density echelon in plasma could lead to amplifiers that significantly exceed current power limits of conventional laser media. Here we show that 1–100 J pump pulses can amplify picojoule seed pulses to nearly joule level. The extremely high gain also leads to significant amplification of backscattered radiation from “noise”, arising from stochastic plasma fluctuations that competes with externally injected seed pulses, which are amplified to similar levels at the highest pump energies. The pump energy is scattered into the seed at an oblique angle with 14 J sr -1, and net gainsmore » of more than eight orders of magnitude. The maximum gain coefficient, of 180 cm -1, exceeds high-power solid-state amplifying media by orders of magnitude. The observation of a minimum of 640 J sr -1 directly backscattered from noise, corresponding to ≈10% of the pump energy in the observation solid angle, implies potential overall efficiencies greater than 10%.« less

Rogue waves in a multistable system.

PubMed

Pisarchik, Alexander N; Jaimes-Reátegui, Rider; Sevilla-Escoboza, Ricardo; Huerta-Cuellar, G; Taki, Majid

2011-12-30

Clear evidence of rogue waves in a multistable system is revealed by experiments with an erbium-doped fiber laser driven by harmonic pump modulation. The mechanism for the rogue wave formation lies in the interplay of stochastic processes with multistable deterministic dynamics. Low-frequency noise applied to a diode pump current induces rare jumps to coexisting subharmonic states with high-amplitude pulses perceived as rogue waves. The probability of these events depends on the noise filtered frequency and grows up when the noise amplitude increases. The probability distribution of spike amplitudes confirms the rogue wave character of the observed phenomenon. The results of numerical simulations are in good agreement with experiments.

Stochastic driven systems far from equilibrium

NASA Astrophysics Data System (ADS)

Kim, Kyung Hyuk

We study the dynamics and steady states of two systems far from equilibrium: a 1-D driven lattice gas and a driven Brownian particle with inertia. (1) We investigate the dynamical scaling behavior of a 1-D driven lattice gas model with two species of particles hopping in opposite directions. We confirm numerically that the dynamic exponent is equal to z = 1.5. We show analytically that a quasi-particle representation relates all phase points to a special phase line directly related to the single-species asymmetric simple exclusion process. Quasi-particle two-point correlations decay exponentially, and in such a manner that quasi-particles of opposite charge dynamically screen each other with a special balance. The balance encompasses all over the phase space. These results indicate that the model belongs to the Kardar-Parisi-Zhang (KPZ) universality class. (2) We investigate the non-equilibrium thermodynamics of a Brownian particle with inertia under feedback control of its inertia. We find such open systems can act as a molecular refrigerator due to an entropy pumping mechanism. We extend the fluctuation theorems to the refrigerator. The entropy pumping modifies both the Jarzynski equality and the fluctuation theorems. We discover that the entropy pumping has a dual role of work and heat. We also investigate the thermodynamics of the particle under a hydrodynamic interaction described by a Langevin equation with a multiplicative noise. The Stratonovich stochastic integration prescription involved in the definition of heat is shown to be the unique physical choice.

Radionuclide gas transport through nuclear explosion-generated fracture networks

DOE PAGES

Jordan, Amy B.; Stauffer, Philip H.; Knight, Earl E.; ...

2015-12-17

Underground nuclear weapon testing produces radionuclide gases which may seep to the surface. Barometric pumping of gas through explosion-fractured rock is investigated using a new sequentially-coupled hydrodynamic rock damage/gas transport model. Fracture networks are produced for two rock types (granite and tuff) and three depths of burial. The fracture networks are integrated into a flow and transport numerical model driven by surface pressure signals of differing amplitude and variability. There are major differences between predictions using a realistic fracture network and prior results that used a simplified geometry. Matrix porosity and maximum fracture aperture have the greatest impact on gasmore » breakthrough time and window of opportunity for detection, with different effects between granite and tuff simulations highlighting the importance of accurately simulating the fracture network. In particular, maximum fracture aperture has an opposite effect on tuff and granite, due to different damage patterns and their effect on the barometric pumping process. From stochastic simulations using randomly generated hydrogeologic parameters, normalized detection curves are presented to show differences in optimal sampling time for granite and tuff simulations. In conclusion, seasonal and location-based effects on breakthrough, which occur due to differences in barometric forcing, are stronger where the barometric signal is highly variable.« less

Radionuclide gas transport through nuclear explosion-generated fracture networks

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

Jordan, Amy B.; Stauffer, Philip H.; Knight, Earl E.

Underground nuclear weapon testing produces radionuclide gases which may seep to the surface. Barometric pumping of gas through explosion-fractured rock is investigated using a new sequentially-coupled hydrodynamic rock damage/gas transport model. Fracture networks are produced for two rock types (granite and tuff) and three depths of burial. The fracture networks are integrated into a flow and transport numerical model driven by surface pressure signals of differing amplitude and variability. There are major differences between predictions using a realistic fracture network and prior results that used a simplified geometry. Matrix porosity and maximum fracture aperture have the greatest impact on gasmore » breakthrough time and window of opportunity for detection, with different effects between granite and tuff simulations highlighting the importance of accurately simulating the fracture network. In particular, maximum fracture aperture has an opposite effect on tuff and granite, due to different damage patterns and their effect on the barometric pumping process. From stochastic simulations using randomly generated hydrogeologic parameters, normalized detection curves are presented to show differences in optimal sampling time for granite and tuff simulations. In conclusion, seasonal and location-based effects on breakthrough, which occur due to differences in barometric forcing, are stronger where the barometric signal is highly variable.« less

Simulation of a proposed emergency outlet from Devils Lake, North Dakota

USGS Publications Warehouse

Vecchia, Aldo V.

2002-01-01

From 1993 to 2001, Devils Lake rose more than 25 feet, flooding farmland, roads, and structures around the lake and causing more than $400 million in damages in the Devils Lake Basin. In July 2001, the level of Devils Lake was at 1,448.0 feet above sea level1, which was the highest lake level in more than 160 years. The lake could continue to rise to several feet above its natural spill elevation to the Sheyenne River (1,459 feet above sea level) in future years, causing extensive additional flooding in the basin and, in the event of an uncontrolled natural spill, downstream in the Red River of the North Basin as well. The outlet simulation model described in this report was developed to determine the potential effects of various outlet alternatives on the future lake levels and water quality of Devils Lake.Lake levels of Devils Lake are controlled largely by precipitation on the lake surface, evaporation from the lake surface, and surface inflow. For this study, a monthly water-balance model was developed to compute the change in total volume of Devils Lake, and a regression model was used to estimate monthly water-balance data on the basis of limited recorded data. Estimated coefficients for the regression model indicated fitted precipitation on the lake surface was greater than measured precipitation in most months, fitted evaporation from the lake surface was less than estimated evaporation in most months, and ungaged inflow was about 2 percent of gaged inflow in most months. Dissolved sulfate was considered to be the key water-quality constituent for evaluating the effects of a proposed outlet on downstream water quality. Because large differences in sulfate concentrations existed among the various bays of Devils Lake, monthly water-balance data were used to develop detailed water and sulfate mass-balance models to compute changes in sulfate load for each of six major storage compartments in response to precipitation, evaporation, inflow, and outflow from each compartment. The storage compartments--five for Devils Lake and one for Stump Lake--were connected by bridge openings, culverts, or natural channels that restricted mixing between compartments. A numerical algorithm was developed to calculate inflow and outflow from each compartment. Sulfate loads for the storage compartments first were calculated using the assumptions that no interaction occurred between the bottom sediments and the water column and no wind- or buoyancy-induced mixing occurred between compartments. However, because the fitted sulfate loads did not agree with the estimated sulfate loads, which were obtained from recorded sulfate concentrations, components were added to the sulfate mass-balance model to account for the flux of sulfate between bottom sediments and the lake and for mixing between storage compartments. Mixing between compartments can occur during periods of open water because of wind and during periods of ice cover because of water-density differences between compartments. Sulfate loads calculated using the sulfate mass-balance model with sediment interaction and mixing between compartments closely matched sulfate loads computed from historical concentrations. The water and sulfate mass-balance models were used to calculate potential future lake levels and sulfate concentrations for Devils Lake and Stump Lake given potential future values of monthly precipitation, evaporation, and inflow. Potential future inputs were generated using a scenario approach and a stochastic approach. In the scenario approach, historical values of precipitation, evaporation, and inflow were repeated in the future for a particular sequence of historical years. In the stochastic approach, a statistical time-series model was developed to randomly generate potential future inputs. The scenario approach was used to evaluate the effectiveness of various outlet alternatives, and the stochastic approach was used to evaluate the hydrologic and water-quality effects of the potential outlet alternatives that were selected on the basis of the scenario analysis. Given potential future lake levels and sulfate concentrations generated using either the scenario or stochastic approach and potential future ambient flows and sulfate concentrations for the Sheyenne River receiving waters, daily outlet discharges could be calculated for virtually any outlet alternative. For the scenario approach, future ambient flows and sulfate concentrations for the Sheyenne River were generated using the same sequence of years used for generating water-balance data for Devils Lake. For the stochastic approach, a procedure was developed for generating daily Sheyenne River flows and sulfate concentrations that were "in-phase" with the generated water-balance data for Devils Lake. Simulation results for the scenario approach indicated that neither of the West Bay outlet alternatives provided effective flood-damage reduction without exceeding downstream water-quality constraints. However, both Pelican Lake outlet alternatives provided significant flood-damage reduction with only minor downstream water-quality changes. The most effective alternative for controlling rising lake levels was a Pelican Lake outlet with a 480-cubic-foot-per-second pump capacity and a 250-milligram-per-liter downstream sulfate constraint. However, this plan is costly because of the high pump capacity and the requirement of a control structure on Highway 19 to control the level of Pelican Lake. A less costly, though less effective for flood-damage reduction, plan is a Pelican Lake outlet with a 300-cubic-foot-per-second pump capacity and a 250-milligram-per-liter downstream sulfate constraint. The plan is less costly because the pump capacity is smaller and because the control structure on Highway 19 is not required. The less costly Pelican Lake alternative with a 450-milligramper- liter downstream sulfate constraint rather than a 250-milligram-per-liter downstream sulfate constraint was identified by the U.S. Army Corps of Engineers as the preferred alternative for detailed design and engineering analysis. Simulation results for the stochastic approach indicated that the geologic history of lake-level fluctuations of Devils Lake for the past 2,500 years was consistent with a climatic history that consisted of two climate states--a wet state, similar to conditions during 1980-99, and a normal state, similar to conditions during 1950-78. The transition times between the wet and normal climatic periods occurred randomly. The average duration of the wet climatic periods was 20 years, and the average duration of the normal climatic periods was 120 years. The stochastic approach was used to generate 10,000 independent sequences of lake levels and sulfate concentrations for Devils Lake for water years 2001-50. Each trace began with the same starting conditions, and the duration of the current wet cycle was generated randomly for each trace. Each trace was generated for the baseline (natural) condition and for the Pelican Lake outlet with a 300-cubic-foot-per-second pump capacity and a 450-milligram-per-liter downstream sulfate constraint. The outlet significantly lowered the probabilities of future lake-level increases within the next 50 years and did not substantially increase the probabilities of reaching low lake levels or poor water-quality conditions during the same period.

Optimal control of hydroelectric facilities

NASA Astrophysics Data System (ADS)

Zhao, Guangzhi

This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the challenging problem of optimizing a sequence of two hydro dams sharing the same river system. The complexity of this problem is magnified and we just scratch its surface here. The thesis concludes with suggestions for future work in this fertile area. Keywords: dynamic programming, hydroelectric facility, optimization, optimal control, switching cost, turbine efficiency.

Multiple well-shutdown tests and site-scale flow simulation in fractured rocks

USGS Publications Warehouse

Tiedeman, Claire; Lacombe, Pierre J.; Goode, Daniel J.

2010-01-01

A new method was developed for conducting aquifer tests in fractured-rock flow systems that have a pump-and-treat (P&T) operation for containing and removing groundwater contaminants. The method involves temporary shutdown of individual pumps in wells of the P&T system. Conducting aquifer tests in this manner has several advantages, including (1) no additional contaminated water is withdrawn, and (2) hydraulic containment of contaminants remains largely intact because pumping continues at most wells. The well-shutdown test method was applied at the former Naval Air Warfare Center (NAWC), West Trenton, New Jersey, where a P&T operation is designed to contain and remove trichloroethene and its daughter products in the dipping fractured sedimentary rocks underlying the site. The detailed site-scale subsurface geologic stratigraphy, a three-dimensional MODFLOW model, and inverse methods in UCODE_2005 were used to analyze the shutdown tests. In the model, a deterministic method was used for representing the highly heterogeneous hydraulic conductivity distribution and simulations were conducted using an equivalent porous media method. This approach was very successful for simulating the shutdown tests, contrary to a common perception that flow in fractured rocks must be simulated using a stochastic or discrete fracture representation of heterogeneity. Use of inverse methods to simultaneously calibrate the model to the multiple shutdown tests was integral to the effectiveness of the approach.

CIDME: Short distances measured with long chirp pulses.

PubMed

Doll, Andrin; Qi, Mian; Godt, Adelheid; Jeschke, Gunnar

2016-12-01

Frequency-swept pulses have recently been introduced as pump pulses into double electron-electron resonance (DEER) experiments. A limitation of this approach is that the pump pulses need to be short in comparison to dipolar evolution periods. The "chirp-induced dipolar modulation enhancement" (CIDME) pulse sequence introduced in this work circumvents this limitation by means of longitudinal storage during the application of one single or two consecutive pump pulses. The resulting six-pulse sequence is closely related to the five-pulse "relaxation-induced dipolar modulation enhancement" (RIDME) pulse sequence: While dipolar modulation in RIDME is due to stochastic spin flips during longitudinal storage, modulation in CIDME is due to the pump pulse during longitudinal storage. Experimentally, CIDME is examined for Gd-Gd and nitroxide-nitroxide distance determination using a high-power Q-band spectrometer. Since longitudinal storage results in a 50% signal loss, comparisons between DEER using short chirp pump pulses of 64ns duration and CIDME using longer pump pulses are in favor of DEER. While the lower sensitivity restrains the applicability of CIDME for routine distance determination on high-power spectrometers, this result is not to be generalized to spectrometers having lower power and to specialized "non-routine" applications or different types of spin labels. In particular, the advantage of prolonged CIDME pump pulses is demonstrated for experiments at large frequency offset between the pumped and observed spins. At a frequency separation of 1GHz, where broadening due to dipolar pseudo-secular contributions becomes largely suppressed, a Gd-Gd modulation depth larger than 10% is achieved. Moreover, a CIDME experiment at deliberately reduced power underlines the potential of the new technique for spectrometers with lower power, as often encountered at higher microwave frequencies. With longitudinal storage times T below 10μs, however, CIDME appears rather susceptible to artifacts. For nitroxide-nitroxide experiments, these currently inhibit a faithful data analysis. To facilitate further developments, the artifacts are characterized experimentally. In addition, effects that are specific to the high spin of S=7/2 Gd-centers are examined. Herein, population transfer within the observer spin's multiplet due to the pump pulse as well as excitation of dipolar harmonics are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Improved estimation of hydraulic conductivity by combining stochastically simulated hydrofacies with geophysical data.

PubMed

Zhu, Lin; Gong, Huili; Chen, Yun; Li, Xiaojuan; Chang, Xiang; Cui, Yijiao

2016-03-01

Hydraulic conductivity is a major parameter affecting the output accuracy of groundwater flow and transport models. The most commonly used semi-empirical formula for estimating conductivity is Kozeny-Carman equation. However, this method alone does not work well with heterogeneous strata. Two important parameters, grain size and porosity, often show spatial variations at different scales. This study proposes a method for estimating conductivity distributions by combining a stochastic hydrofacies model with geophysical methods. The Markov chain model with transition probability matrix was adopted to re-construct structures of hydrofacies for deriving spatial deposit information. The geophysical and hydro-chemical data were used to estimate the porosity distribution through the Archie's law. Results show that the stochastic simulated hydrofacies model reflects the sedimentary features with an average model accuracy of 78% in comparison with borehole log data in the Chaobai alluvial fan. The estimated conductivity is reasonable and of the same order of magnitude of the outcomes of the pumping tests. The conductivity distribution is consistent with the sedimentary distributions. This study provides more reliable spatial distributions of the hydraulic parameters for further numerical modeling.

Mimicking Nonequilibrium Steady States with Time-Periodic Driving

NASA Astrophysics Data System (ADS)

Raz, Oren; Subasi, Yigit; Jarzynski, Christopher

Under static conditions, a system satisfying detailed balance generically relaxes to an equilibrium state in which there are no currents: to generate persistent currents, either detailed balance must be broken or the system must be driven in a time-dependent manner. A stationary system that violates detailed balance evolves to a nonequilibrium steady state (NESS) characterized by fixed currents. Conversely, a system that satisfies instantaneous detailed balance but is driven by the time-periodic variation of external parameters - also known as a stochastic pump (SP) - reaches a periodic state with non-vanishing currents. In both cases, these currents are maintained at the cost of entropy production. Are these two paradigmatic scenarios effectively equivalent? For discrete-state systems we establish a mapping between NESS and SP. Given a NESS characterized by a particular set of stationary probabilities, currents and entropy production rates, we show how to construct a SP with exactly the same (time-averaged) values. The mapping works in the opposite direction as well. These results establish a proof of principle: they show that SP are able to mimic the behavior of NESS, and vice-versa, within the theoretical framework of discrete-state stochastic thermodynamics.

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.

Suppressing relaxation in superconducting qubits by quasiparticle pumping.

PubMed

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

2016-12-23

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

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

NASA Astrophysics Data System (ADS)

Williams, P. D.; Haine, T. W. N.; Read, P. L.; Lewis, S. R.; Yamazaki, Y. H.

2008-09-01

QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

NASA Astrophysics Data System (ADS)

Williams, P. D.; Haine, T. W. N.; Read, P. L.; Lewis, S. R.; Yamazaki, Y. H.

2009-02-01

QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

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.

Coronal heating by stochastic magnetic pumping

NASA Technical Reports Server (NTRS)

Sturrock, P. A.; Uchida, Y.

1980-01-01

Recent observational data cast serious doubt on the widely held view that the Sun's corona is heated by traveling waves (acoustic or magnetohydrodynamic). It is proposed that the energy responsible for heating the corona is derived from the free energy of the coronal magnetic field derived from motion of the 'feet' of magnetic field lines in the photosphere. Stochastic motion of the feet of magnetic field lines leads, on the average, to a linear increase of magnetic free energy with time. This rate of energy input is calculated for a simple model of a single thin flux tube. The model appears to agree well with observational data if the magnetic flux originates in small regions of high magnetic field strength. On combining this energy input with estimates of energy loss by radiation and of energy redistribution by thermal conduction, we obtain scaling laws for density and temperature in terms of length and coronal magnetic field strength.

Improved estimation of hydraulic conductivity by combining stochastically simulated hydrofacies with geophysical data

PubMed Central

Zhu, Lin; Gong, Huili; Chen, Yun; Li, Xiaojuan; Chang, Xiang; Cui, Yijiao

2016-01-01

Hydraulic conductivity is a major parameter affecting the output accuracy of groundwater flow and transport models. The most commonly used semi-empirical formula for estimating conductivity is Kozeny-Carman equation. However, this method alone does not work well with heterogeneous strata. Two important parameters, grain size and porosity, often show spatial variations at different scales. This study proposes a method for estimating conductivity distributions by combining a stochastic hydrofacies model with geophysical methods. The Markov chain model with transition probability matrix was adopted to re-construct structures of hydrofacies for deriving spatial deposit information. The geophysical and hydro-chemical data were used to estimate the porosity distribution through the Archie’s law. Results show that the stochastic simulated hydrofacies model reflects the sedimentary features with an average model accuracy of 78% in comparison with borehole log data in the Chaobai alluvial fan. The estimated conductivity is reasonable and of the same order of magnitude of the outcomes of the pumping tests. The conductivity distribution is consistent with the sedimentary distributions. This study provides more reliable spatial distributions of the hydraulic parameters for further numerical modeling. PMID:26927886

Using Cotton Model Simulations to Estimate Optimally Profitable Irrigation Strategies

NASA Astrophysics Data System (ADS)

Mauget, S. A.; Leiker, G.; Sapkota, P.; Johnson, J.; Maas, S.

2011-12-01

In recent decades irrigation pumping from the Ogallala Aquifer has led to declines in saturated thickness that have not been compensated for by natural recharge, which has led to questions about the long-term viability of agriculture in the cotton producing areas of west Texas. Adopting irrigation management strategies that optimize profitability while reducing irrigation waste is one way of conserving the aquifer's water resource. Here, a database of modeled cotton yields generated under drip and center pivot irrigated and dryland production scenarios is used in a stochastic dominance analysis that identifies such strategies under varying commodity price and pumping cost conditions. This database and analysis approach will serve as the foundation for a web-based decision support tool that will help producers identify optimal irrigation treatments under specified cotton price, electricity cost, and depth to water table conditions.

Modeling variability in porescale multiphase flow experiments

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

Ling, Bowen; Bao, Jie; Oostrom, Mart

Microfluidic devices and porescale numerical models are commonly used to study multiphase flow in biological, geological, and engineered porous materials. In this work, we perform a set of drainage and imbibition experiments in six identical microfluidic cells to study the reproducibility of multiphase flow experiments. We observe significant variations in the experimental results, which are smaller during the drainage stage and larger during the imbibition stage. We demonstrate that these variations are due to sub-porescale geometry differences in microcells (because of manufacturing defects) and variations in the boundary condition (i.e.,fluctuations in the injection rate inherent to syringe pumps). Computational simulationsmore » are conducted using commercial software STAR-CCM+, both with constant and randomly varying injection rate. Stochastic simulations are able to capture variability in the experiments associated with the varying pump injection rate.« less

Evolution of colloidal dispersions in novel time-varying optical potentials

NASA Astrophysics Data System (ADS)

Koss, Brian Alan

Optical traps use forces exerted by a tightly focused light beam to trap objects from tens of nanometers to tens of micrometers in size. Since their introduction in 1986, optical tweezers have become very useful to biology, chemistry, and soft condensed-matter physics. Work presented here, promises to advance optical tweezers not only in fundamental scientific research, but also in applications outside of the laboratory and into the mainstream of miniaturized manufacturing and diagnostics. By providing unprecedented access to the mesoscopic world, a new generation of optical traps, called Dynamic Holographic Optical Tweezers (HOTs) offers revolutionary new opportunities for fundamental and applied research. To demonstrate this technique, HOTs will be used to pump particles via a new method of transport called Optical Peristalsis (OP). OP is efficient method for transporting mesoscopic objects in three dimensions using short repetitive sequences of holographic optical trapping patterns. Transport in this process is analogous to peristaltic pumping, with the configurations of optical traps mimicking states of a peristaltic pump. While not limited to the deterministic particle transport, OP, can also be a platform to investigate the stochastic limit of particle transport. Advances in recent years have demonstrated that a variety of time-varying perturbations can induce drift in a diffusive system without exerting an overall force. Among these, are thermal ratchet models in which the system is subjected to time-varying energy landscapes that break spatiotemporal symmetry and thereby induce drift. Typically, the potential energy landscape is chosen to be the sawtooth potential. This work describes an alternate class of symmetric thermal ratchet models, that are not sawtooth, and demonstrates their efficacy in biasing the diffusion of colloidal spheres in both the stochastic and deterministic limits. Unlike previous models, each state in this thermal ratchet consists of discrete spatially-symmetric potential wells, which are implemented with an array of HOTs.

Optimizing Wellfield Operation in a Variable Power Price Regime.

PubMed

Bauer-Gottwein, Peter; Schneider, Raphael; Davidsen, Claus

2016-01-01

Wellfield management is a multiobjective optimization problem. One important objective has been energy efficiency in terms of minimizing the energy footprint (EFP) of delivered water (MWh/m(3) ). However, power systems in most countries are moving in the direction of deregulated markets and price variability is increasing in many markets because of increased penetration of intermittent renewable power sources. In this context the relevant management objective becomes minimizing the cost of electric energy used for pumping and distribution of groundwater from wells rather than minimizing energy use itself. We estimated EFP of pumped water as a function of wellfield pumping rate (EFP-Q relationship) for a wellfield in Denmark using a coupled well and pipe network model. This EFP-Q relationship was subsequently used in a Stochastic Dynamic Programming (SDP) framework to minimize total cost of operating the combined wellfield-storage-demand system over the course of a 2-year planning period based on a time series of observed price on the Danish power market and a deterministic, time-varying hourly water demand. In the SDP setup, hourly pumping rates are the decision variables. Constraints include storage capacity and hourly water demand fulfilment. The SDP was solved for a baseline situation and for five scenario runs representing different EFP-Q relationships and different maximum wellfield pumping rates. Savings were quantified as differences in total cost between the scenario and a constant-rate pumping benchmark. Minor savings up to 10% were found in the baseline scenario, while the scenario with constant EFP and unlimited pumping rate resulted in savings up to 40%. Key factors determining potential cost savings obtained by flexible wellfield operation under a variable power price regime are the shape of the EFP-Q relationship, the maximum feasible pumping rate and the capacity of available storage facilities. © 2015 The Authors. Groundwater published by Wiley Periodicals, Inc. on behalf of National Ground Water Association.

Stochastic effects in a seasonally forced epidemic model

NASA Astrophysics Data System (ADS)

Rozhnova, G.; Nunes, A.

2010-10-01

The interplay of seasonality, the system’s nonlinearities and intrinsic stochasticity, is studied for a seasonally forced susceptible-exposed-infective-recovered stochastic model. The model is explored in the parameter region that corresponds to childhood infectious diseases such as measles. The power spectrum of the stochastic fluctuations around the attractors of the deterministic system that describes the model in the thermodynamic limit is computed analytically and validated by stochastic simulations for large system sizes. Size effects are studied through additional simulations. Other effects such as switching between coexisting attractors induced by stochasticity often mentioned in the literature as playing an important role in the dynamics of childhood infectious diseases are also investigated. The main conclusion is that stochastic amplification, rather than these effects, is the key ingredient to understand the observed incidence patterns.

Stochastic joint inversion of hydrogeophysical data for salt tracer test monitoring and hydraulic conductivity imaging

NASA Astrophysics Data System (ADS)

Jardani, A.; Revil, A.; Dupont, J. P.

2013-02-01

The assessment of hydraulic conductivity of heterogeneous aquifers is a difficult task using traditional hydrogeological methods (e.g., steady state or transient pumping tests) due to their low spatial resolution. Geophysical measurements performed at the ground surface and in boreholes provide additional information for increasing the resolution and accuracy of the inverted hydraulic conductivity field. We used a stochastic joint inversion of Direct Current (DC) resistivity and self-potential (SP) data plus in situ measurement of the salinity in a downstream well during a synthetic salt tracer experiment to reconstruct the hydraulic conductivity field between two wells. The pilot point parameterization was used to avoid over-parameterization of the inverse problem. Bounds on the model parameters were used to promote a consistent Markov chain Monte Carlo sampling of the model parameters. To evaluate the effectiveness of the joint inversion process, we compared eight cases in which the geophysical data are coupled or not to the in situ sampling of the salinity to map the hydraulic conductivity. We first tested the effectiveness of the inversion of each type of data alone (concentration sampling, self-potential, and DC resistivity), and then we combined the data two by two. We finally combined all the data together to show the value of each type of geophysical data in the joint inversion process because of their different sensitivity map. We also investigated a case in which the data were contaminated with noise and the variogram unknown and inverted stochastically. The results of the inversion revealed that incorporating the self-potential data improves the estimate of hydraulic conductivity field especially when the self-potential data were combined to the salt concentration measurement in the second well or to the time-lapse cross-well electrical resistivity data. Various tests were also performed to quantify the uncertainty in the inverted hydraulic conductivity field.

Output Feedback Stabilization for a Class of Multi-Variable Bilinear Stochastic Systems with Stochastic Coupling Attenuation

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

Zhang, Qichun; Zhou, Jinglin; Wang, Hong

In this paper, stochastic coupling attenuation is investigated for a class of multi-variable bilinear stochastic systems and a novel output feedback m-block backstepping controller with linear estimator is designed, where gradient descent optimization is used to tune the design parameters of the controller. It has been shown that the trajectories of the closed-loop stochastic systems are bounded in probability sense and the stochastic coupling of the system outputs can be effectively attenuated by the proposed control algorithm. Moreover, the stability of the stochastic systems is analyzed and the effectiveness of the proposed method has been demonstrated using a simulated example.

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

NASA Astrophysics Data System (ADS)

Williams, P. D.; Haine, T. W. N.; Read, P. L.; Lewis, S. R.; Yamazaki, Y. H.

2009-04-01

The QUAGMIRE model has recently been made freely available for public use. QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. This presentation describes the model's main features. QUAGMIRE uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

Numerical simulation of incoherent optical wave propagation in nonlinear fibers

NASA Astrophysics Data System (ADS)

Fernandez, Arnaud; Balac, Stéphane; Mugnier, Alain; Mahé, Fabrice; Texier-Picard, Rozenn; Chartier, Thierry; Pureur, David

2013-11-01

The present work concerns the study of pulsed laser systems containing a fiber amplifier for boosting optical output power. In this paper, this fiber amplification device is included into a MOPFA laser, a master oscillator coupled with fiber amplifier, usually a cladding-pumped high-power amplifier often based on an ytterbium-doped fiber. An experimental study has established that the observed nonlinear effects (such as Kerr effect, four waves mixing, Raman effect) could behave very differently depending on the characteristics of the optical source emitted by the master laser. However, it has not yet been possible to determine from the experimental data if the statistics of the photons is alone responsible for the various nonlinear scenarios observed. Therefore, we have developed a numerical simulation software for solving the generalized nonlinear Schrödinger equation with a stochastic source term in order to validate the hypothesis that the coherence properties of the master laser are mainly liable for the behavior of the observed nonlinear effects. Contribution to the Topical Issue "Numelec 2012", Edited by Adel Razek.

Stochastic stimulated electronic x-ray Raman spectroscopy

PubMed Central

Kimberg, Victor; Rohringer, Nina

2016-01-01

Resonant inelastic x-ray scattering (RIXS) is a well-established tool for studying electronic, nuclear, and collective dynamics of excited atoms, molecules, and solids. An extension of this powerful method to a time-resolved probe technique at x-ray free electron lasers (XFELs) to ultimately unravel ultrafast chemical and structural changes on a femtosecond time scale is often challenging, due to the small signal rate in conventional implementations at XFELs that rely on the usage of a monochromator setup to select a small frequency band of the broadband, spectrally incoherent XFEL radiation. Here, we suggest an alternative approach, based on stochastic spectroscopy, which uses the full bandwidth of the incoming XFEL pulses. Our proposed method is relying on stimulated resonant inelastic x-ray scattering, where in addition to a pump pulse that resonantly excites the system a probe pulse on a specific electronic inelastic transition is provided, which serves as a seed in the stimulated scattering process. The limited spectral coherence of the XFEL radiation defines the energy resolution in this process and stimulated RIXS spectra of high resolution can be obtained by covariance analysis of the transmitted spectra. We present a detailed feasibility study and predict signal strengths for realistic XFEL parameters for the CO molecule resonantly pumped at the O1s→π* transition. Our theoretical model describes the evolution of the spectral and temporal characteristics of the transmitted x-ray radiation, by solving the equation of motion for the electronic and vibrational degrees of freedom of the system self consistently with the propagation by Maxwell equations. PMID:26958585

Persistence and stochastic periodicity in the intensity dynamics of a fiber laser during the transition to optical turbulence

NASA Astrophysics Data System (ADS)

Carpi, Laura; Masoller, Cristina

2018-02-01

Many natural systems display transitions among different dynamical regimes, which are difficult to identify when the data are noisy and high dimensional. A technologically relevant example is a fiber laser, which can display complex dynamical behaviors that involve nonlinear interactions of millions of cavity modes. Here we study the laminar-turbulence transition that occurs when the laser pump power is increased. By applying various data analysis tools to empirical intensity time series we characterize their persistence and demonstrate that at the transition temporal correlations can be precisely represented by a surprisingly simple model.

Time-delayed behaviors of transient four-wave mixing signal intensity in inverted semiconductor with carrier-injection pumping

NASA Astrophysics Data System (ADS)

Hu, Zhenhua; Gao, Shen; Xiang, Bowen

2016-01-01

An analytical expression of transient four-wave mixing (TFWM) in inverted semiconductor with carrier-injection pumping was derived from both the density matrix equation and the complex stochastic stationary statistical method of incoherent light. Numerical analysis showed that the TFWM decayed decay is towards the limit of extreme homogeneous and inhomogeneous broadenings in atoms and the decaying time is inversely proportional to half the power of the net carrier densities for a low carrier-density injection and other high carrier-density injection, while it obeys an usual exponential decay with other decaying time that is inversely proportional to half the power of the net carrier density or it obeys an unusual exponential decay with the decaying time that is inversely proportional to a third power of the net carrier density for a moderate carrier-density injection. The results can be applied to studying ultrafast carrier dephasing in the inverted semiconductors such as semiconductor laser amplifier and semiconductor optical amplifier.

Quantum correlation in degenerate optical parametric oscillators with mutual injections

NASA Astrophysics Data System (ADS)

Takata, Kenta; Marandi, Alireza; Yamamoto, Yoshihisa

2015-10-01

We theoretically and numerically study the quantum dynamics of two degenerate optical parametric oscillators with mutual injections. The cavity mode in the optical coupling path between the two oscillator facets is explicitly considered. Stochastic equations for the oscillators and mutual injection path based on the positive P representation are derived. The system of two gradually pumped oscillators with out-of-phase mutual injections is simulated, and its quantum state is investigated. When the incoherent loss of the oscillators other than the mutual injections is small, the squeezed quadratic amplitudes p ̂ in the oscillators are positively correlated near the oscillation threshold. It indicates finite quantum correlation, estimated via Gaussian quantum discord, and the entanglement between the intracavity subharmonic fields. When the loss in the injection path is low, each oscillator around the phase transition point forms macroscopic superposition even under a small pump noise. It suggests that the squeezed field stored in the low-loss injection path weakens the decoherence in the oscillators.

Stochastic effects in EUV lithography: random, local CD variability, and printing failures

NASA Astrophysics Data System (ADS)

De Bisschop, Peter

2017-10-01

Stochastic effects in lithography are usually quantified through local CD variability metrics, such as line-width roughness or local CD uniformity (LCDU), and these quantities have been measured and studied intensively, both in EUV and optical lithography. Next to the CD-variability, stochastic effects can also give rise to local, random printing failures, such as missing contacts or microbridges in spaces. When these occur, there often is no (reliable) CD to be measured locally, and then such failures cannot be quantified with the usual CD-measuring techniques. We have developed algorithms to detect such stochastic printing failures in regular line/space (L/S) or contact- or dot-arrays from SEM images, leading to a stochastic failure metric that we call NOK (not OK), which we consider a complementary metric to the CD-variability metrics. This paper will show how both types of metrics can be used to experimentally quantify dependencies of stochastic effects to, e.g., CD, pitch, resist, exposure dose, etc. As it is also important to be able to predict upfront (in the OPC verification stage of a production-mask tape-out) whether certain structures in the layout are likely to have a high sensitivity to stochastic effects, we look into the feasibility of constructing simple predictors, for both stochastic CD-variability and printing failure, that can be calibrated for the process and exposure conditions used and integrated into the standard OPC verification flow. Finally, we briefly discuss the options to reduce stochastic variability and failure, considering the entire patterning ecosystem.

Mixed Effects Modeling Using Stochastic Differential Equations: Illustrated by Pharmacokinetic Data of Nicotinic Acid in Obese Zucker Rats.

PubMed

Leander, Jacob; Almquist, Joachim; Ahlström, Christine; Gabrielsson, Johan; Jirstrand, Mats

2015-05-01

Inclusion of stochastic differential equations in mixed effects models provides means to quantify and distinguish three sources of variability in data. In addition to the two commonly encountered sources, measurement error and interindividual variability, we also consider uncertainty in the dynamical model itself. To this end, we extend the ordinary differential equation setting used in nonlinear mixed effects models to include stochastic differential equations. The approximate population likelihood is derived using the first-order conditional estimation with interaction method and extended Kalman filtering. To illustrate the application of the stochastic differential mixed effects model, two pharmacokinetic models are considered. First, we use a stochastic one-compartmental model with first-order input and nonlinear elimination to generate synthetic data in a simulated study. We show that by using the proposed method, the three sources of variability can be successfully separated. If the stochastic part is neglected, the parameter estimates become biased, and the measurement error variance is significantly overestimated. Second, we consider an extension to a stochastic pharmacokinetic model in a preclinical study of nicotinic acid kinetics in obese Zucker rats. The parameter estimates are compared between a deterministic and a stochastic NiAc disposition model, respectively. Discrepancies between model predictions and observations, previously described as measurement noise only, are now separated into a comparatively lower level of measurement noise and a significant uncertainty in model dynamics. These examples demonstrate that stochastic differential mixed effects models are useful tools for identifying incomplete or inaccurate model dynamics and for reducing potential bias in parameter estimates due to such model deficiencies.

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.

Stochastic Management of Non-Point Source Contamination: Joint Impact of Aquifer Heterogeneity and Well Characteristics

NASA Astrophysics Data System (ADS)

Henri, C. V.; Harter, T.

2017-12-01

Agricultural activities are recognized as the preeminent origin of non-point source (NPS) contamination of water bodies through the leakage of nitrate, salt and agrochemicals. A large fraction of world agricultural activities and therefore NPS contamination occurs over unconsolidated alluvial deposit basins offering soil composition and topography favorable to productive farming. These basins represent also important groundwater reservoirs. The over-exploitation of aquifers coupled with groundwater pollution by agriculture-related NPS contaminant has led to a rapid deterioration of the quality of these groundwater basins. The management of groundwater contamination from NPS is challenged by the inherent complexity of aquifers systems. Contaminant transport dynamics are highly uncertain due to the heterogeneity of hydraulic parameters controlling groundwater flow. Well characteristics are also key uncertain elements affecting pollutant transport and NPS management but quantifying uncertainty in NPS management under these conditions is not well documented. Our work focuses on better understanding the joint impact of aquifer heterogeneity and pumping well characteristics (extraction rate and depth) on (1) the transport of contaminants from NPS and (2) the spatio-temporal extension of the capture zone. To do so, we generate a series of geostatistically equivalent 3D heterogeneous aquifers and simulate the flow and non-reactive solute transport from NPS to extraction wells within a stochastic framework. The propagation of the uncertainty on the hydraulic conductivity field is systematically analyzed. A sensitivity analysis of the impact of extraction well characteristics (pumping rate and screen depth) is also conducted. Results highlight the significant role that heterogeneity and well characteristics plays on management metrics. We finally show that, in case of NPS contamination, the joint impact of regional longitudinal and transverse vertical hydraulic gradients and well depth strongly constrain the average travel times and extension of the contributing area.

Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

NASA Astrophysics Data System (ADS)

Turner, Douglas C.; Ladde, Gangaram S.

2018-03-01

Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

Stochastic analyses to identify wellfield withdrawal effects on surface-water and groundwater in Miami-Dade County, Florida.

PubMed

Swain, Eric

2012-12-30

Several stochastic analyses were conducted in Miami-Dade County, Florida, to evaluate the effects of wellfield withdrawal on aquifer water levels, canal stage, and canal flow. Multiyear data for withdrawals at four water-supply wellfields, water levels at the S-121 canal control structure and groundwater head at a nearby monitoring well were used to determine the interrelation between wellfield withdrawals and water levels in the canal and aquifer. A spectral analysis was performed first on the wellfield withdrawals, showing similar patterns of fluctuations, but no well-defined seasonality. In order to compare water-level response with withdrawals at each wellfield, the intercorrelation effects between wellfields was removed through a 'causal chain' approach where the inter-wellfield correlation is used to isolate the wellfield/water-level correlation. Most computed correlations have magnitudes less than 5 percent, but with statistical significance above 90 percent. Results indicate that withdrawals from the wellfields most distant from the canal had no significant correlation to the canal levels. However the highest correlation was not at the wellfield closest to the canal, but at the two wellfields at the intermediate distance that have higher withdrawal rates. The hydraulic interconnectivity of the canal with the rest of the canal network, covering the study area, allows the canal equalizes with all connected canals. This explains why proximity to a particular canal location does not appear to be as important a factor as the withdrawal rate. Groundwater levels are more highly correlated to a wellfield on the same side of the canal, and to pumping wells in the same wellfield on the same side of the canal. This indicates that canals are an effective barrier and source/sink for the groundwater. Further nonlinear correlation analysis indicates that high withdrawal rates disproportionally affect water levels and are the predominant effect on the canal. Published by Elsevier Ltd.

Statistically qualified neuro-analytic failure detection method and system

DOEpatents

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

2002-03-02

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

Karhunen-Loève treatment to remove noise and facilitate data analysis in sensing, spectroscopy and other applications.

PubMed

Zaharov, V V; Farahi, R H; Snyder, P J; Davison, B H; Passian, A

2014-11-21

Resolving weak spectral variations in the dynamic response of materials that are either dominated or excited by stochastic processes remains a challenge. Responses that are thermal in origin are particularly relevant examples due to the delocalized nature of heat. Despite its inherent properties in dealing with stochastic processes, the Karhunen-Loève expansion has not been fully exploited in measurement of systems that are driven solely by random forces or can exhibit large thermally driven random fluctuations. Here, we present experimental results and analysis of the archetypes (a) the resonant excitation and transient response of an atomic force microscope probe by the ambient random fluctuations and nanoscale photothermal sample response, and (b) the photothermally scattered photons in pump-probe spectroscopy. In each case, the dynamic process is represented as an infinite series with random coefficients to obtain pertinent frequency shifts and spectral peaks and demonstrate spectral enhancement for a set of compounds including the spectrally complex biomass. The considered cases find important applications in nanoscale material characterization, biosensing, and spectral identification of biological and chemical agents.

Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects.

PubMed

Huang, Tingwen; Li, Chuandong; Duan, Shukai; Starzyk, Janusz A

2012-06-01

This paper focuses on the hybrid effects of parameter uncertainty, stochastic perturbation, and impulses on global stability of delayed neural networks. By using the Ito formula, Lyapunov function, and Halanay inequality, we established several mean-square stability criteria from which we can estimate the feasible bounds of impulses, provided that parameter uncertainty and stochastic perturbations are well-constrained. Moreover, the present method can also be applied to general differential systems with stochastic perturbation and impulses.

Gompertzian stochastic model with delay effect to cervical cancer growth

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

Mazlan, Mazma Syahidatul Ayuni binti; Rosli, Norhayati binti; Bahar, Arifah

2015-02-03

In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits.

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.

Impact of stochasticity in immigration and reintroduction on colonizing and extirpating populations.

PubMed

Rajakaruna, Harshana; Potapov, Alexei; Lewis, Mark

2013-05-01

A thorough quantitative understanding of populations at the edge of extinction is needed to manage both invasive and extirpating populations. Immigration can govern the population dynamics when the population levels are low. It increases the probability of a population establishing (or reestablishing) before going extinct (EBE). However, the rate of immigration can be highly fluctuating. Here, we investigate how the stochasticity in immigration impacts the EBE probability for small populations in variable environments. We use a population model with an Allee effect described by a stochastic differential equation (SDE) and employ the Fokker-Planck diffusion approximation to quantify the EBE probability. We find that, the effect of the stochasticity in immigration on the EBE probability depends on both the intrinsic growth rate (r) and the mean rate of immigration (p). In general, if r is large and positive (e.g. invasive species introduced to favorable habitats), or if p is greater than the rate of population decline due to the demographic Allee effect (e.g., effective stocking of declining populations), then the stochasticity in immigration decreases the EBE probability. If r is large and negative (e.g. endangered populations in unfavorable habitats), or if the rate of decline due to the demographic Allee effect is much greater than p (e.g., weak stocking of declining populations), then the stochasticity in immigration increases the EBE probability. However, the mean time for EBE decreases with the increasing stochasticity in immigration with both positive and negative large r. Thus, results suggest that ecological management of populations involves a tradeoff as to whether to increase or decrease the stochasticity in immigration in order to optimize the desired outcome. Moreover, the control of invasive species spread through stochastic means, for example, by stochastic monitoring and treatment of vectors such as ship-ballast water, may be suitable strategies given the environmental and demographic uncertainties at introductions. Similarly, the recovery of declining and extirpated populations through stochastic stocking, translocation, and reintroduction, may also be suitable strategies. Copyright © 2013 Elsevier Inc. All rights reserved.

Complex groundwater flow systems as traveling agent models

PubMed Central

Padilla, Pablo; Escolero, Oscar; González, Tomas; Morales-Casique, Eric; Osorio-Olvera, Luis

2014-01-01

Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow. PMID:25337455

Anatomy of North Pacific Decadal Variability.

NASA Astrophysics Data System (ADS)

Schneider, Niklas; Miller, Arthur J.; Pierce, David W.

2002-03-01

A systematic analysis of North Pacific decadal variability in a full-physics coupled ocean-atmosphere model is executed. The model is an updated and improved version of the coupled model studied by Latif and Barnett. Evidence is sought for determining the details of the mechanism responsible for the enhanced variance of some variables at 20-30-yr timescales. The possible mechanisms include a midlatitude gyre ocean-atmosphere feedback loop, stochastic forcing, remote forcing, or sampling error.Decadal variability in the model is expressed most prominently in anomalies of upper-ocean streamfunction, sea surface temperature (SST), and latent surface heat flux in the Kuroshio-Oyashio extension (KOE) region off Japan. The decadal signal off Japan is initiated by changes in strength and position of the Aleutian low. The atmospheric perturbations excite SST anomalies in the central and eastern North Pacific (with opposing signs and canonical structure). The atmospheric perturbations also change the Ekman pumping over the North Pacific, which excites equivalent barotropic Rossby waves that carry thermocline depth perturbations toward the west. This gyre adjustment results in a shift in the border between subtropical and subpolar gyres after about five years. This process consequently excites SST anomalies (bearing the same sign as the central North Pacific) in the KOE region. The SST anomalies are generated by subsurface temperature anomalies that are brought to the surface during winter by deep mixing and are damped by air-sea winter heat exchange (primarily latent heat flux). This forcing of the atmosphere by the ocean in the KOE region is associated with changes of winter precipitation over the northwestern Pacific Ocean. The polarity of SST and Ekman pumping is such that warm central and cool eastern Pacific anomalies are associated with a deep thermocline, a poleward shift of the border between subtropical and subpolar gyres, and warm SST anomalies and an increase of rain in the KOE region.The preponderance of variance at decadal timescales in the KOE results from the integration of stochastic Ekman pumping along Rossby wave trajectories. The Ekman pumping is primarily due to atmospheric variability that expresses itself worldwide including in the tropical Pacific. A positive feedback between the coupled model KOE SST (driven by the ocean streamfunction) and North Pacific Ekman pumping is consistent with the enhanced variance of the coupled model at 20-30-yr periods. However, the time series are too short to unambiguously distinguish this positive feedback hypothesis from sampling variability. No evidence is found for a midlatitude gyre ocean-atmosphere delayed negative feedback loop.Comparisons with available observations confirm the seasonality of the forcing, the up to 5-yr time lag between like-signed central North Pacific and KOE SST anomalies, and the associated damping of SST in the KOE region by the latent heat flux. The coupled model results also suggest that observed SST anomalies in the KOE region may be predictable from the history of the wind-stress curl over the North Pacific.

Didactic discussion of stochastic resonance effects and weak signals

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

Adair, R.K.

1996-12-01

A simple, paradigmatic, model is used to illustrate some general properties of effects subsumed under the label stochastic resonance. In particular, analyses of the transparent model show that (1) a small amount of noise added to a much larger signal can greatly increase the response to the signal, but (2) a weak signal added to much larger noise will not generate a substantial added response. The conclusions drawn from the model illustrate the general result that stochastic resonance effects do not provide an avenue for signals that are much smaller than noise to affect biology. A further analysis demonstrates themore » effects of small signals in the shifting of biologically important chemical equilibria under conditions where stochastic resonance effects are significant.« less

MarkoLAB: A simulator to study ionic channel's stochastic behavior.

PubMed

da Silva, Robson Rodrigues; Goroso, Daniel Gustavo; Bers, Donald M; Puglisi, José Luis

2017-08-01

Mathematical models of the cardiac cell have started to include markovian representations of the ionic channels instead of the traditional Hodgkin & Huxley formulations. There are many reasons for this: Markov models are not restricted to the idea of independent gates defining the channel, they allow more complex description with specific transitions between open, closed or inactivated states, and more importantly those states can be closely related to the underlying channel structure and conformational changes. We used the LabVIEW ® and MATLAB ® programs to implement the simulator MarkoLAB that allow a dynamical 3D representation of the markovian model of the channel. The Monte Carlo simulation was used to implement the stochastic transitions among states. The user can specify the voltage protocol by setting the holding potential, the step-to voltage and the duration of the stimuli. The most studied feature of a channel is the current flowing through it. This happens when the channel stays in the open state, but most of the time, as revealed by the low open probability values, the channel remains on the inactive or closed states. By focusing only when the channel enters or leaves the open state we are missing most of its activity. MarkoLAB proved to be quite useful to visualize the whole behavior of the channel and not only when the channel produces a current. Such dynamic representation provides more complete information about channel kinetics and will be a powerful tool to demonstrate the effect of gene mutations or drugs on the channel function. MarkoLAB provides an original way of visualizing the stochastic behavior of a channel. It clarifies concepts, such as recovery from inactivation, calcium- versus voltage-dependent inactivation, and tail currents. It is not restricted to ionic channels only but it can be extended to other transporters, such as exchangers and pumps. This program is intended as a didactical tool to illustrate the dynamical behavior of a channel. It has been implemented in two platforms MATLAB ® and LabVIEW ® to enhance the target users of this new didactical tool. The computational cost of implementing a stochastic simulation is within the range of a personal computer performance; making MarkoLAB suitable to be run during a lecture or presentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two-Dimensional Vlasov Simulations of Fast Stochastic Electron Heating in Ionospheric Modification Experiments

NASA Astrophysics Data System (ADS)

Speirs, David Carruthers; Eliasson, Bengt; Daldorff, Lars K. S.

2017-10-01

Ionospheric heating experiments using high-frequency ordinary (O)-mode electromagnetic waves have shown the induced formation of magnetic field-aligned density striations in the ionospheric F region, in association with lower hybrid (LH) and upper hybrid (UH) turbulence. In recent experiments using high-power transmitters, the creation of new plasma regions and the formation of descending artificial ionospheric layers (DAILs) have been observed. These are attributed to suprathermal electrons ionizing the neutral gas, so that the O-mode reflection point and associated turbulence is moving to a progressively lower altitude. We present the results of two-dimensional (2-D) Vlasov simulations used to study the mode conversion of an O-mode pump wave to trapped UH waves in a small-scale density striation of circular cross section. Subsequent multiwave parametric decays lead to UH and LH turbulence and to the excitation of electron Bernstein (EB) waves. Large-amplitude EB waves result in rapid stochastic electron heating when the wave amplitude exceeds a threshold value. For typical experimental parameters, the electron temperature is observed to rise from 1,500 K to about 8,000 K in a fraction of a millisecond, much faster than Ohmic heating due to collisions which occurs on a timescale of an order of a second. This initial heating could then lead to further acceleration due to Langmuir turbulence near the critical layer. Stochastic electron heating therefore represents an important potential mechanism for the formation of DAILs.

Effect of the heterogeneous neuron and information transmission delay on stochastic resonance of neuronal networks

NASA Astrophysics Data System (ADS)

Wang, Qingyun; Zhang, Honghui; Chen, Guanrong

2012-12-01

We study the effect of heterogeneous neuron and information transmission delay on stochastic resonance of scale-free neuronal networks. For this purpose, we introduce the heterogeneity to the specified neuron with the highest degree. It is shown that in the absence of delay, an intermediate noise level can optimally assist spike firings of collective neurons so as to achieve stochastic resonance on scale-free neuronal networks for small and intermediate αh, which plays a heterogeneous role. Maxima of stochastic resonance measure are enhanced as αh increases, which implies that the heterogeneity can improve stochastic resonance. However, as αh is beyond a certain large value, no obvious stochastic resonance can be observed. If the information transmission delay is introduced to neuronal networks, stochastic resonance is dramatically affected. In particular, the tuned information transmission delay can induce multiple stochastic resonance, which can be manifested as well-expressed maximum in the measure for stochastic resonance, appearing every multiple of one half of the subthreshold stimulus period. Furthermore, we can observe that stochastic resonance at odd multiple of one half of the subthreshold stimulus period is subharmonic, as opposed to the case of even multiple of one half of the subthreshold stimulus period. More interestingly, multiple stochastic resonance can also be improved by the suitable heterogeneous neuron. Presented results can provide good insights into the understanding of the heterogeneous neuron and information transmission delay on realistic neuronal networks.

The threshold of a stochastic avian-human influenza epidemic model with psychological effect

NASA Astrophysics Data System (ADS)

Zhang, Fengrong; Zhang, Xinhong

2018-02-01

In this paper, a stochastic avian-human influenza epidemic model with psychological effect in human population and saturation effect within avian population is investigated. This model describes the transmission of avian influenza among avian population and human population in random environments. For stochastic avian-only system, persistence in the mean and extinction of the infected avian population are studied. For the avian-human influenza epidemic system, sufficient conditions for the existence of an ergodic stationary distribution are obtained. Furthermore, a threshold of this stochastic model which determines the outcome of the disease is obtained. Finally, numerical simulations are given to support the theoretical results.

Persistence and extinction of a stochastic single-species model under regime switching in a polluted environment II.

PubMed

Liu, Meng; Wang, Ke

2010-12-07

This is a continuation of our paper [Liu, M., Wang, K., 2010. Persistence and extinction of a stochastic single-species model under regime switching in a polluted environment, J. Theor. Biol. 264, 934-944]. Taking both white noise and colored noise into account, a stochastic single-species model under regime switching in a polluted environment is studied. Sufficient conditions for extinction, stochastic nonpersistence in the mean, stochastic weak persistence and stochastic permanence are established. The threshold between stochastic weak persistence and extinction is obtained. The results show that a different type of noise has a different effect on the survival results. Copyright © 2010 Elsevier Ltd. All rights reserved.

Persistence and extinction of a stochastic single-specie model under regime switching in a polluted environment.

PubMed

Liu, Meng; Wang, Ke

2010-06-07

A new single-species model disturbed by both white noise and colored noise in a polluted environment is developed and analyzed. Sufficient criteria for extinction, stochastic nonpersistence in the mean, stochastic weak persistence in the mean, stochastic strong persistence in the mean and stochastic permanence of the species are established. The threshold between stochastic weak persistence in the mean and extinction is obtained. The results show that both white and colored environmental noises have sufficient effect to the survival results. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Hybrid ODE/SSA methods and the cell cycle model

NASA Astrophysics Data System (ADS)

Wang, S.; Chen, M.; Cao, Y.

2017-07-01

Stochastic effect in cellular systems has been an important topic in systems biology. Stochastic modeling and simulation methods are important tools to study stochastic effect. Given the low efficiency of stochastic simulation algorithms, the hybrid method, which combines an ordinary differential equation (ODE) system with a stochastic chemically reacting system, shows its unique advantages in the modeling and simulation of biochemical systems. The efficiency of hybrid method is usually limited by reactions in the stochastic subsystem, which are modeled and simulated using Gillespie's framework and frequently interrupt the integration of the ODE subsystem. In this paper we develop an efficient implementation approach for the hybrid method coupled with traditional ODE solvers. We also compare the efficiency of hybrid methods with three widely used ODE solvers RADAU5, DASSL, and DLSODAR. Numerical experiments with three biochemical models are presented. A detailed discussion is presented for the performances of three ODE solvers.

Theoretical study of the effect of pump wavelength drift on mode instability in a high-power fiber amplifier

NASA Astrophysics Data System (ADS)

Liu, Yakun; Tao, Rumao; Su, Rongtao; Wang, Xiaolin; Ma, Pengfei; Zhang, Hanwei; Zhou, Pu; Si, Lei

2018-04-01

This paper presents an investigation of the effect of pump wavelength drift on the threshold of mode instability (MI) in high-power ytterbium-doped fiber lasers. By using a semi-analytical model, we study the effects of pump wavelength drift with a central pump wavelength around 976 nm and 915 nm, respectively. The influences of the pump absorption coefficient and total pump absorption are considered simultaneously. The results indicate that the effect of pump wavelength drift around 976 nm is stronger than that around 915 nm. For more efficient suppression of MI by shifting the pump wavelength, efficient absorption of pump power is required. The MI thresholds for fibers with different total pump absorptions and cladding diameters are compared. When the total pump absorption is increased, the gain saturation is enhanced, which results in the MI being mitigated more effectively and being more sensitive to pump wavelength drift. The MI threshold in gain fibers with larger inner cladding diameter is higher but more dependent upon pump wavelength. The results of this work can help in optimizing the pump wavelength and fiber parameters and suppressing MI in high-power fiber lasers.

Stochastic Galerkin methods for the steady-state Navier–Stokes equations

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

Sousedík, Bedřich, E-mail: sousedik@umbc.edu; Elman, Howard C., E-mail: elman@cs.umd.edu

2016-07-01

We study the steady-state Navier–Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion. For the resulting stochastic problem, we formulate the model and linearization schemes using Picard and Newton iterations in the framework of the stochastic Galerkin method, and we explore properties of the resulting stochastic solutions. We also propose a preconditioner for solving the linear systems of equations arising at each step of the stochastic (Galerkin) nonlinear iteration and demonstrate its effectiveness for solving a set of benchmarkmore » problems.« less

Stochastic Galerkin methods for the steady-state Navier–Stokes equations

DOE PAGES

Sousedík, Bedřich; Elman, Howard C.

2016-04-12

We study the steady-state Navier–Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion. For the resulting stochastic problem, we formulate the model and linearization schemes using Picard and Newton iterations in the framework of the stochastic Galerkin method, and we explore properties of the resulting stochastic solutions. We also propose a preconditioner for solving the linear systems of equations arising at each step of the stochastic (Galerkin) nonlinear iteration and demonstrate its effectiveness for solving a set of benchmarkmore » problems.« less

Approximate Dynamic Programming and Aerial Refueling

DTIC Science & Technology

2007-06-01

by two Army Air Corps de Havilland DH -4Bs (9). While crude by modern standards, the passing of hoses be- tween planes is effectively the same approach...incorporating stochastic data sets. . . . . . . . . . . 106 55 Total Cost Stochastically Trained Simulations versus Deterministically Trained Simulations...incorporating stochastic data sets. 106 To create meaningful results when testing stochastic data, the data sets are av- eraged so that conclusions are not

Noise Characterization of Erbium-Doped Fiber Amplifiers and Avalanche Photodiodes in Optical Communication Systems.

NASA Astrophysics Data System (ADS)

Kahraman, Gokalp

We examine the performance of optical communication systems using erbium-doped fiber amplifiers (OFAs) and avalanche photodiodes (APDs) including nonlinear and transient effects in the former and transient effects in the latter. Transient effects become important as these amplifiers are operated at very high data rates. Nonlinear effects are important for high gain amplifiers. In most studies of noise in these devices, the temporal and nonlinear effects have been ignored. We present a quantum theory of noise in OFAs including the saturation of the atomic population inversion and the pump depletion. We study the quantum-statistical properties of pulse amplification. The generating function of the output photon number distribution (PND) is determined as a function of time during the course of the pulse with an arbitrary input PND assumed. Under stationary conditions, we determine the Kolmogorov equation obeyed by the PND. The PND at the output is determined for arbitrary input distributions. The effect of the counting time and the filter bandwidth used by the detection circuit is determined. We determine the gain, the noise figure, and the sensitivity of receivers using OFAs as preamplifiers, including the effect of backward amplified spontaneous emission (ASE). Backward ASE degrades the noise figure and the sensitivity by depleting the population inversion at the input side of the fiber and thus increasing the noise during signal amplification. We show that the sensitivity improves with the bit rate at low rates but degrades at high rates. We provide a stochastic model that describes the time dynamics in a double-carrier multiplication (DCM) APD. A discrete stochastic model for the electron/hole motion and multiplication is defined on a spatio-temporal lattice and used to derive recursive equations for the mean, the variance, and the autocorrelation of the impulse response as functions of time. The power spectral density of the photocurrent produced in response to a Poisson-distributed stream of photons of uniform rate is evaluated. A method is also developed for solving the coupled transport equations that describe the electron and hole currents in a DCM-APD of arbitrary structure.

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing

PubMed Central

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery. PMID:27711246

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

PubMed

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

Dynamical and statistical phenomena of circulation and heat transfer in periodically forced rotating turbulent Rayleigh-Bénard convection

NASA Astrophysics Data System (ADS)

Sterl, Sebastian; Li, Hui-Min; Zhong, Jin-Qiang

2016-12-01

In this paper, we present results from an experimental study into turbulent Rayleigh-Bénard convection forced externally by periodically modulated unidirectional rotation rates. We find that the azimuthal rotation velocity θ ˙(t ) and thermal amplitude δ (t ) of the large-scale circulation (LSC) are modulated by the forcing, exhibiting a variety of dynamics including increasing phase delays and a resonant peak in the amplitude of θ ˙(t ) . We also focus on the influence of modulated rotation rates on the frequency of occurrence η of stochastic cessation or reorientation events, and on the interplay between such events and the periodically modulated response of θ ˙(t ) . Here we identify a mechanism by which η can be amplified by the modulated response, and these normally stochastic events can occur with high regularity. We provide a modeling framework that explains the observed amplitude and phase responses, and we extend this approach to make predictions for the occurrence of cessation events and the probability distributions of θ ˙(t ) and δ (t ) during different phases of a modulation cycle, based on an adiabatic approach that treats each phase separately. Last, we show that such periodic forcing has consequences beyond influencing LSC dynamics, by investigating how it can modify the heat transport even under conditions where the Ekman pumping effect is predominant and strong enhancement of heat transport occurs. We identify phase and amplitude responses of the heat transport, and we show how increased modulations influence the average Nusselt number.

Ignition probability of polymer-bonded explosives accounting for multiple sources of material stochasticity

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

Kim, S.; Barua, A.; Zhou, M., E-mail: min.zhou@me.gatech.edu

2014-05-07

Accounting for the combined effect of multiple sources of stochasticity in material attributes, we develop an approach that computationally predicts the probability of ignition of polymer-bonded explosives (PBXs) under impact loading. The probabilistic nature of the specific ignition processes is assumed to arise from two sources of stochasticity. The first source involves random variations in material microstructural morphology; the second source involves random fluctuations in grain-binder interfacial bonding strength. The effect of the first source of stochasticity is analyzed with multiple sets of statistically similar microstructures and constant interfacial bonding strength. Subsequently, each of the microstructures in the multiple setsmore » is assigned multiple instantiations of randomly varying grain-binder interfacial strengths to analyze the effect of the second source of stochasticity. Critical hotspot size-temperature states reaching the threshold for ignition are calculated through finite element simulations that explicitly account for microstructure and bulk and interfacial dissipation to quantify the time to criticality (t{sub c}) of individual samples, allowing the probability distribution of the time to criticality that results from each source of stochastic variation for a material to be analyzed. Two probability superposition models are considered to combine the effects of the multiple sources of stochasticity. The first is a parallel and series combination model, and the second is a nested probability function model. Results show that the nested Weibull distribution provides an accurate description of the combined ignition probability. The approach developed here represents a general framework for analyzing the stochasticity in the material behavior that arises out of multiple types of uncertainty associated with the structure, design, synthesis and processing of materials.« less

A Pumping Algorithm for Ergodic Stochastic Mean Payoff Games with Perfect Information

NASA Astrophysics Data System (ADS)

Boros, Endre; Elbassioni, Khaled; Gurvich, Vladimir; Makino, Kazuhisa

In this paper, we consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph G = (V = V B ∪ V W ∪ V R , E), with local rewards r: E to { R}, and three types of vertices: black V B , white V W , and random V R . The game is played by two players, White and Black: When the play is at a white (black) vertex v, White (Black) selects an outgoing arc (v,u). When the play is at a random vertex v, a vertex u is picked with the given probability p(v,u). In all cases, Black pays White the value r(v,u). The play continues forever, and White aims to maximize (Black aims to minimize) the limiting mean (that is, average) payoff. It was recently shown in [7] that BWR-games are polynomially equivalent with the classical Gillette games, which include many well-known subclasses, such as cyclic games, simple stochastic games (SSG's), stochastic parity games, and Markov decision processes. In this paper, we give a new algorithm for solving BWR-games in the ergodic case, that is when the optimal values do not depend on the initial position. Our algorithm solves a BWR-game by reducing it, using a potential transformation, to a canonical form in which the optimal strategies of both players and the value for every initial position are obvious, since a locally optimal move in it is optimal in the whole game. We show that this algorithm is pseudo-polynomial when the number of random nodes is constant. We also provide an almost matching lower bound on its running time, and show that this bound holds for a wider class of algorithms. Let us add that the general (non-ergodic) case is at least as hard as SSG's, for which no pseudo-polynomial algorithm is known.

Stochastic simulation and analysis of biomolecular reaction networks

PubMed Central

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

2009-01-01

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

Stochastic Nature in Cellular Processes

NASA Astrophysics Data System (ADS)

Liu, Bo; Liu, Sheng-Jun; Wang, Qi; Yan, Shi-Wei; Geng, Yi-Zhao; Sakata, Fumihiko; Gao, Xing-Fa

2011-11-01

The importance of stochasticity in cellular processes is increasingly recognized in both theoretical and experimental studies. General features of stochasticity in gene regulation and expression are briefly reviewed in this article, which include the main experimental phenomena, classification, quantization and regulation of noises. The correlation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methods that can capture effects of intrinsic and extrinsic noise are described.

Multivariate moment closure techniques for stochastic kinetic models

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

Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.

2015-09-07

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporallymore » evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.« less

The ESPAT tool: a general-purpose DSS shell for solving stochastic optimization problems in complex river-aquifer systems

NASA Astrophysics Data System (ADS)

Macian-Sorribes, Hector; Pulido-Velazquez, Manuel; Tilmant, Amaury

2015-04-01

Stochastic programming methods are better suited to deal with the inherent uncertainty of inflow time series in water resource management. However, one of the most important hurdles in their use in practical implementations is the lack of generalized Decision Support System (DSS) shells, usually based on a deterministic approach. The purpose of this contribution is to present a general-purpose DSS shell, named Explicit Stochastic Programming Advanced Tool (ESPAT), able to build and solve stochastic programming problems for most water resource systems. It implements a hydro-economic approach, optimizing the total system benefits as the sum of the benefits obtained by each user. It has been coded using GAMS, and implements a Microsoft Excel interface with a GAMS-Excel link that allows the user to introduce the required data and recover the results. Therefore, no GAMS skills are required to run the program. The tool is divided into four modules according to its capabilities: 1) the ESPATR module, which performs stochastic optimization procedures in surface water systems using a Stochastic Dual Dynamic Programming (SDDP) approach; 2) the ESPAT_RA module, which optimizes coupled surface-groundwater systems using a modified SDDP approach; 3) the ESPAT_SDP module, capable of performing stochastic optimization procedures in small-size surface systems using a standard SDP approach; and 4) the ESPAT_DET module, which implements a deterministic programming procedure using non-linear programming, able to solve deterministic optimization problems in complex surface-groundwater river basins. The case study of the Mijares river basin (Spain) is used to illustrate the method. It consists in two reservoirs in series, one aquifer and four agricultural demand sites currently managed using historical (XIV century) rights, which give priority to the most traditional irrigation district over the XX century agricultural developments. Its size makes it possible to use either the SDP or the SDDP methods. The independent use of surface and groundwater can be examined with and without the aquifer. The ESPAT_DET, ESPATR and ESPAT_SDP modules were executed for the surface system, while the ESPAT_RA and the ESPAT_DET modules were run for the surface-groundwater system. The surface system's results show a similar performance between the ESPAT_SDP and ESPATR modules, with outperform the one showed by the current policies besides being outperformed by the ESPAT_DET results, which have the advantage of the perfect foresight. The surface-groundwater system's results show a robust situation in which the differences between the module's results and the current policies are lower due the use of pumped groundwater in the XX century crops when surface water is scarce. The results are realistic, with the deterministic optimization outperforming the stochastic one, which at the same time outperforms the current policies; showing that the tool is able to stochastically optimize river-aquifer water resources systems. We are currently working in the application of these tools in the analysis of changes in systems' operation under global change conditions. ACKNOWLEDGEMENT: This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) funds.

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

A study about the existence of the leverage effect in stochastic volatility models

NASA Astrophysics Data System (ADS)

Florescu, Ionuţ; Pãsãricã, Cristian Gabriel

2009-02-01

The empirical relationship between the return of an asset and the volatility of the asset has been well documented in the financial literature. Named the leverage effect or sometimes risk-premium effect, it is observed in real data that, when the return of the asset decreases, the volatility increases and vice versa. Consequently, it is important to demonstrate that any formulated model for the asset price is capable of generating this effect observed in practice. Furthermore, we need to understand the conditions on the parameters present in the model that guarantee the apparition of the leverage effect. In this paper we analyze two general specifications of stochastic volatility models and their capability of generating the perceived leverage effect. We derive conditions for the apparition of leverage effect in both of these stochastic volatility models. We exemplify using stochastic volatility models used in practice and we explicitly state the conditions for the existence of the leverage effect in these examples.

Persistence and ergodicity of a stochastic single species model with Allee effect under regime switching

NASA Astrophysics Data System (ADS)

Yu, Xingwang; Yuan, Sanling; Zhang, Tonghua

2018-06-01

Allee effect can interact with environment stochasticity and is active when population numbers are small. Our goal of this paper is to investigate such effect on population dynamics. More precisely, we develop and investigate a stochastic single species model with Allee effect under regime switching. We first prove the existence of global positive solution of the model. Then, we perform the survival analysis to seek sufficient conditions for the extinction, non-persistence in mean, persistence in mean and stochastic permanence. By constructing a suitable Lyapunov function, we show that the model is positive recurrent and ergodic. Our results indicate that the regime switching can suppress the extinction of the species. Finally, numerical simulations are carried out to illustrate the obtained theoretical results, where a real-life example is also discussed showing the inclusion of Allee effect in the model provides a better match to the data.

Temperature variation effects on stochastic characteristics for low-cost MEMS-based inertial sensor error

NASA Astrophysics Data System (ADS)

El-Diasty, M.; El-Rabbany, A.; Pagiatakis, S.

2007-11-01

We examine the effect of varying the temperature points on MEMS inertial sensors' noise models using Allan variance and least-squares spectral analysis (LSSA). Allan variance is a method of representing root-mean-square random drift error as a function of averaging times. LSSA is an alternative to the classical Fourier methods and has been applied successfully by a number of researchers in the study of the noise characteristics of experimental series. Static data sets are collected at different temperature points using two MEMS-based IMUs, namely MotionPakII and Crossbow AHRS300CC. The performance of the two MEMS inertial sensors is predicted from the Allan variance estimation results at different temperature points and the LSSA is used to study the noise characteristics and define the sensors' stochastic model parameters. It is shown that the stochastic characteristics of MEMS-based inertial sensors can be identified using Allan variance estimation and LSSA and the sensors' stochastic model parameters are temperature dependent. Also, the Kaiser window FIR low-pass filter is used to investigate the effect of de-noising stage on the stochastic model. It is shown that the stochastic model is also dependent on the chosen cut-off frequency.

Evolution in fluctuating environments: decomposing selection into additive components of the Robertson-Price equation.

PubMed

Engen, Steinar; Saether, Bernt-Erik

2014-03-01

We analyze the stochastic components of the Robertson-Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Simple Map with Low MN Perturbation for a Single-Null Divertor Tokamak with Constant Width of Stochastic Layer

NASA Astrophysics Data System (ADS)

Verma, Arun; Smith, Terry; Punjabi, Alkesh; Boozer, Allen

1996-11-01

In this work, we investigate the effects of low MN perturbations in a single-null divertor tokamak with stochastic scrape-off layer. The unperturbed magnetic topology of a single-null divertor tokamak is represented by Simple Map (Punjabi A, Verma A and Boozer A, Phys Rev Lett), 69, 3322 (1992) and J Plasma Phys, 52, 91 (1994). We choose the combinations of the map parameter k, and the strength of the low MN perturbation such that the width of stochastic layer remains unchanged. We give detailed results on the effects of low MN perturbation on the magnetic topology of the stochastic layer and on the footprint of field lines on the divertor plate given the constraint of constant width of the stochastic layer. The low MN perturbations occur naturally and therefore their effects are of considerable importance in tokamak divertor physics. This work is supported by US DOE OFES. Use of CRAY at HU and at NERSC is gratefully acknowledged.

Stochastic Modeling of Laminar-Turbulent Transition

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Choudhari, Meelan

2002-01-01

Stochastic versions of stability equations are developed in order to develop integrated models of transition and turbulence and to understand the effects of uncertain initial conditions on disturbance growth. Stochastic forms of the resonant triad equations, a high Reynolds number asymptotic theory, and the parabolized stability equations are developed.

Modelling the cancer growth process by Stochastic Differential Equations with the effect of Chondroitin Sulfate (CS) as anticancer therapeutics

NASA Astrophysics Data System (ADS)

Syahidatul Ayuni Mazlan, Mazma; Rosli, Norhayati; Jauhari Arief Ichwan, Solachuddin; Suhaity Azmi, Nina

2017-09-01

A stochastic model is introduced to describe the growth of cancer affected by anti-cancer therapeutics of Chondroitin Sulfate (CS). The parameters values of the stochastic model are estimated via maximum likelihood function. The numerical method of Euler-Maruyama will be employed to solve the model numerically. The efficiency of the stochastic model is measured by comparing the simulated result with the experimental data.

Effects of stochastic sodium channels on extracellular excitation of myelinated nerve fibers.

PubMed

Mino, Hiroyuki; Grill, Warren M

2002-06-01

The effects of the stochastic gating properties of sodium channels on the extracellular excitation properties of mammalian nerve fibers was determined by computer simulation. To reduce computation time, a hybrid multicompartment cable model including five central nodes of Ranvier containing stochastic sodium channels and 16 flanking nodes containing detenninistic membrane dynamics was developed. The excitation properties of the hybrid cable model were comparable with those of a full stochastic cable model including 21 nodes of Ranvier containing stochastic sodium channels, indicating the validity of the hybrid cable model. The hybrid cable model was used to investigate whether or not the excitation properties of extracellularly activated fibers were influenced by the stochastic gating of sodium channels, including spike latencies, strength-duration (SD), current-distance (IX), and recruitment properties. The stochastic properties of the sodium channels in the hybrid cable model had the greatest impact when considering the temporal dynamics of nerve fibers, i.e., a large variability in latencies, while they did not influence the SD, IX, or recruitment properties as compared with those of the conventional deterministic cable model. These findings suggest that inclusion of stochastic nodes is not important for model-based design of stimulus waveforms for activation of motor nerve fibers. However, in cases where temporal fine structure is important, for example in sensory neural prostheses in the auditory and visual systems, the stochastic properties of the sodium channels may play a key role in the design of stimulus waveforms.

Biochemical simulations: stochastic, approximate stochastic and hybrid approaches.

PubMed

Pahle, Jürgen

2009-01-01

Computer simulations have become an invaluable tool to study the sometimes counterintuitive temporal dynamics of (bio-)chemical systems. In particular, stochastic simulation methods have attracted increasing interest recently. In contrast to the well-known deterministic approach based on ordinary differential equations, they can capture effects that occur due to the underlying discreteness of the systems and random fluctuations in molecular numbers. Numerous stochastic, approximate stochastic and hybrid simulation methods have been proposed in the literature. In this article, they are systematically reviewed in order to guide the researcher and help her find the appropriate method for a specific problem.

Biochemical simulations: stochastic, approximate stochastic and hybrid approaches

PubMed Central

2009-01-01

Computer simulations have become an invaluable tool to study the sometimes counterintuitive temporal dynamics of (bio-)chemical systems. In particular, stochastic simulation methods have attracted increasing interest recently. In contrast to the well-known deterministic approach based on ordinary differential equations, they can capture effects that occur due to the underlying discreteness of the systems and random fluctuations in molecular numbers. Numerous stochastic, approximate stochastic and hybrid simulation methods have been proposed in the literature. In this article, they are systematically reviewed in order to guide the researcher and help her find the appropriate method for a specific problem. PMID:19151097

Towards sub-optimal stochastic control of partially observable stochastic systems

NASA Technical Reports Server (NTRS)

Ruzicka, G. J.

1980-01-01

A class of multidimensional stochastic control problems with noisy data and bounded controls encountered in aerospace design is examined. The emphasis is on suboptimal design, the optimality being taken in quadratic mean sense. To that effect the problem is viewed as a stochastic version of the Lurie problem known from nonlinear control theory. The main result is a separation theorem (involving a nonlinear Kalman-like filter) suitable for Lurie-type approximations. The theorem allows for discontinuous characteristics. As a byproduct the existence of strong solutions to a class of non-Lipschitzian stochastic differential equations in dimensions is proven.

Stochastic reaction-diffusion algorithms for macromolecular crowding

NASA Astrophysics Data System (ADS)

Sturrock, Marc

2016-06-01

Compartment-based (lattice-based) reaction-diffusion algorithms are often used for studying complex stochastic spatio-temporal processes inside cells. In this paper the influence of macromolecular crowding on stochastic reaction-diffusion simulations is investigated. Reaction-diffusion processes are considered on two different kinds of compartmental lattice, a cubic lattice and a hexagonal close packed lattice, and solved using two different algorithms, the stochastic simulation algorithm and the spatiocyte algorithm (Arjunan and Tomita 2010 Syst. Synth. Biol. 4, 35-53). Obstacles (modelling macromolecular crowding) are shown to have substantial effects on the mean squared displacement and average number of molecules in the domain but the nature of these effects is dependent on the choice of lattice, with the cubic lattice being more susceptible to the effects of the obstacles. Finally, improvements for both algorithms are presented.

Universal fuzzy integral sliding-mode controllers for stochastic nonlinear systems.

PubMed

Gao, Qing; Liu, Lu; Feng, Gang; Wang, Yong

2014-12-01

In this paper, the universal integral sliding-mode controller problem for the general stochastic nonlinear systems modeled by Itô type stochastic differential equations is investigated. One of the main contributions is that a novel dynamic integral sliding mode control (DISMC) scheme is developed for stochastic nonlinear systems based on their stochastic T-S fuzzy approximation models. The key advantage of the proposed DISMC scheme is that two very restrictive assumptions in most existing ISMC approaches to stochastic fuzzy systems have been removed. Based on the stochastic Lyapunov theory, it is shown that the closed-loop control system trajectories are kept on the integral sliding surface almost surely since the initial time, and moreover, the stochastic stability of the sliding motion can be guaranteed in terms of linear matrix inequalities. Another main contribution is that the results of universal fuzzy integral sliding-mode controllers for two classes of stochastic nonlinear systems, along with constructive procedures to obtain the universal fuzzy integral sliding-mode controllers, are provided, respectively. Simulation results from an inverted pendulum example are presented to illustrate the advantages and effectiveness of the proposed approaches.

Effects of Stochastic Traffic Flow Model on Expected System Performance

DTIC Science & Technology

2012-12-01

NSWC-PCD has made considerable improvements to their pedestrian flow modeling . In addition to the linear paths, the 2011 version now includes...using stochastic paths. 2.2 Linear Paths vs. Stochastic Paths 2.2.1 Linear Paths and Direct Maximum Pd Calculation Modeling pedestrian traffic flow...as a stochastic process begins with the linear path model . Let the detec- tion area be R x C voxels. This creates C 2 total linear paths, path(Cs

Compact and highly efficient laser pump cavity

DOEpatents

Chang, Jim J.; Bass, Isaac L.; Zapata, Luis E.

1999-01-01

A new, compact, side-pumped laser pump cavity design which uses non-conventional optics for injection of laser-diode light into a laser pump chamber includes a plurality of elongated light concentration channels. In one embodiment, the light concentration channels are compound parabolic concentrators (CPC) which have very small exit apertures so that light will not escape from the pumping chamber and will be multiply reflected through the laser rod. This new design effectively traps the pump radiation inside the pump chamber that encloses the laser rod. It enables more uniform laser pumping and highly effective recycle of pump radiation, leading to significantly improved laser performance. This new design also effectively widens the acceptable radiation wavelength of the diodes, resulting in a more reliable laser performance with lower cost.

Data collection strategies for time-resolved X-ray free-electron laser diffraction, and 2-color methods

PubMed Central

Li, Chufeng; Schmidt, Kevin; Spence, John C.

2015-01-01

We compare three schemes for time-resolved X-ray diffraction from protein nanocrystals using an X-ray free-electron laser. We find expressions for the errors in structure factor measurement using the Monte Carlo pump-probe method of data analysis with a liquid jet, the fixed sample pump-probe (goniometer) method (both diffract-and-destroy, and below the safe damage dose), and a proposed two-color method. Here, an optical pump pulse arrives between X-ray pulses of slightly different energies which hit the same nanocrystal, using a weak first X-ray pulse which does not damage the sample. (Radiation damage is outrun in the other cases.) This two-color method, in which separated Bragg spots are impressed on the same detector readout, eliminates stochastic fluctuations in crystal size, shape, and orientation and is found to require two orders of magnitude fewer diffraction patterns than the currently used Monte Carlo liquid jet method, for 1% accuracy. Expressions are given for errors in structure factor measurement for the four approaches, and detailed simulations provided for cathepsin B and IC3 crystals. While the error is independent of the number of shots for the dose-limited goniometer method, it falls off inversely as the square root of the number of shots for the two-color and Monte Carlo methods, with a much smaller pre-factor for the two-color mode, when the first shot is below the damage threshold. PMID:26798813

Stochastic Multi-Timescale Power System Operations With Variable Wind Generation

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

Wu, Hongyu; Krad, Ibrahim; Florita, Anthony

This paper describes a novel set of stochastic unit commitment and economic dispatch models that consider stochastic loads and variable generation at multiple operational timescales. The stochastic model includes four distinct stages: stochastic day-ahead security-constrained unit commitment (SCUC), stochastic real-time SCUC, stochastic real-time security-constrained economic dispatch (SCED), and deterministic automatic generation control (AGC). These sub-models are integrated together such that they are continually updated with decisions passed from one to another. The progressive hedging algorithm (PHA) is applied to solve the stochastic models to maintain the computational tractability of the proposed models. Comparative case studies with deterministic approaches are conductedmore » in low wind and high wind penetration scenarios to highlight the advantages of the proposed methodology, one with perfect forecasts and the other with current state-of-the-art but imperfect deterministic forecasts. The effectiveness of the proposed method is evaluated with sensitivity tests using both economic and reliability metrics to provide a broader view of its impact.« less

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 damage analysis for brittle materials using stochastic micro-structural information

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Identification and stochastic control of helicopter dynamic modes

NASA Technical Reports Server (NTRS)

Molusis, J. A.; Bar-Shalom, Y.

1983-01-01

A general treatment of parameter identification and stochastic control for use on helicopter dynamic systems is presented. Rotor dynamic models, including specific applications to rotor blade flapping and the helicopter ground resonance problem are emphasized. Dynamic systems which are governed by periodic coefficients as well as constant coefficient models are addressed. The dynamic systems are modeled by linear state variable equations which are used in the identification and stochastic control formulation. The pure identification problem as well as the stochastic control problem which includes combined identification and control for dynamic systems is addressed. The stochastic control problem includes the effect of parameter uncertainty on the solution and the concept of learning and how this is affected by the control's duel effect. The identification formulation requires algorithms suitable for on line use and thus recursive identification algorithms are considered. The applications presented use the recursive extended kalman filter for parameter identification which has excellent convergence for systems without process noise.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

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

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient formore » the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.« less

Siphon effects on continuous subcutaneous insulin infusion pump delivery performance.

PubMed

Zisser, Howard C; Bevier, Wendy; Dassau, Eyal; Jovanovic, Lois

2010-01-01

The objective was to quantify hydrostatic effects on continuous subcutaneous insulin infusion (CSII) pumps during basal and bolus insulin delivery. We tested CSII pumps from Medtronic Diabetes (MiniMed 512 and 515), Smiths Medical (Deltec Cozmo 1700), and Insulet (OmniPod) using insulin aspart (Novolog, Novo Nordisk). Pumps were filled and primed per manufacturer's instructions. The fluid level change was measured using an inline graduated glass pipette (100 microl) when the pipette was moved in relation to the pump (80 cm Cosmo and 110 cm Medtronics) and when level. Pumps were compared during 1 and 5 U boluses and basal insulin delivery of 1.0 and 1.5 U/h. Pronounced differences were seen during basal delivery in pumps using 80-100 cm tubing. For the 1 U/h rate, differences ranged from 74.5% of the expected delivery when the pumps were below the pipettes and pumping upward to 123.3% when the pumps were above the pipettes and pumping downward. For the 1.5 U/h rate, differences ranged from 86.7% to 117.0% when the pumps were below or above the pipettes, respectively. Compared to pumps with tubing, OmniPod performed with significantly less variation in insulin delivery. Changing position of a conventional CSII pump in relation to its tubing results in significant changes in insulin delivery. The siphon effect in the tubing may affect the accuracy of insulin delivery, especially during low basal rates. This effect has been reported when syringe pumps were moved in relation to infusion sites but has not been reported with CSII pumps. 2010 Diabetes Technology Society.

A Bayesian approach to model structural error and input variability in groundwater modeling

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

2015-12-01

Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

stochastic estimation of transmissivity fields conditioned to flow connectivity data

NASA Astrophysics Data System (ADS)

Freixas, Genis; Fernàndez-Garcia, Daniel; Sanchez-vila, Xavier

2017-04-01

Most methods for hydraulic parameter interpretation rely on a number of simplifications regarding the homogeneity of the underlying porous media. This way, the actual heterogeneity of any natural parameter, such as transmissivity, is transferred to the estimated in a way heavily dependent on the interpretation method used. An example is a pumping test, in most cases interpreted by means of the Cooper-Jacob method, which implicitly assumes a homogeneous isotropic confined aquifer. It was shown that the estimates obtained from this method when applied to a real site are not local values, but still have a physical meaning; the estimated transmissivity is equal to the effective transmissivity characteristic of the regional scale, while the log-ratio of the estimated storage coefficient with respect to the actual real value (assumed constant), indicated by , is an indicator of flow connectivity, representative of the scale given by the distance between the pumping and the observation wells. In this work we propose a methodology to use together with actual measurements of the log transmissivity at selected points to obtain a map of the best local transmissivity estimates using cokriging. Since the interpolation involves two variables measured at different support scales, a critical point is the estimation of the covariance and crosscovariance matrices, involving some quadratures that are obtained using some simplified approach. The method was applied to a synthetic field displaying statistical anisotropy, showing that the use of connectivity indicators mixed with the local values provide a better representation of the local value map, in particular regarding the enhanced representation of the continuity of structures corresponding to either high or low values.

Impulsive control of stochastic systems with applications in chaos control, chaos synchronization, and neural networks.

PubMed

Li, Chunguang; Chen, Luonan; Aihara, Kazuyuki

2008-06-01

Real systems are often subject to both noise perturbations and impulsive effects. In this paper, we study the stability and stabilization of systems with both noise perturbations and impulsive effects. In other words, we generalize the impulsive control theory from the deterministic case to the stochastic case. The method is based on extending the comparison method to the stochastic case. The method presented in this paper is general and easy to apply. Theoretical results on both stability in the pth mean and stability with disturbance attenuation are derived. To show the effectiveness of the basic theory, we apply it to the impulsive control and synchronization of chaotic systems with noise perturbations, and to the stability of impulsive stochastic neural networks. Several numerical examples are also presented to verify the theoretical results.

Anomalous scaling of stochastic processes and the Moses effect

NASA Astrophysics Data System (ADS)

Chen, Lijian; Bassler, Kevin E.; McCauley, Joseph L.; Gunaratne, Gemunu H.

2017-04-01

The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t1/2. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.

Anomalous scaling of stochastic processes and the Moses effect.

PubMed

Chen, Lijian; Bassler, Kevin E; McCauley, Joseph L; Gunaratne, Gemunu H

2017-04-01

The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t^{1/2}. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.

Application of an NLME-Stochastic Deconvolution Approach to Level A IVIVC Modeling.

PubMed

Kakhi, Maziar; Suarez-Sharp, Sandra; Shepard, Terry; Chittenden, Jason

2017-07-01

Stochastic deconvolution is a parameter estimation method that calculates drug absorption using a nonlinear mixed-effects model in which the random effects associated with absorption represent a Wiener process. The present work compares (1) stochastic deconvolution and (2) numerical deconvolution, using clinical pharmacokinetic (PK) data generated for an in vitro-in vivo correlation (IVIVC) study of extended release (ER) formulations of a Biopharmaceutics Classification System class III drug substance. The preliminary analysis found that numerical and stochastic deconvolution yielded superimposable fraction absorbed (F abs ) versus time profiles when supplied with exactly the same externally determined unit impulse response parameters. In a separate analysis, a full population-PK/stochastic deconvolution was applied to the clinical PK data. Scenarios were considered in which immediate release (IR) data were either retained or excluded to inform parameter estimation. The resulting F abs profiles were then used to model level A IVIVCs. All the considered stochastic deconvolution scenarios, and numerical deconvolution, yielded on average similar results with respect to the IVIVC validation. These results could be achieved with stochastic deconvolution without recourse to IR data. Unlike numerical deconvolution, this also implies that in crossover studies where certain individuals do not receive an IR treatment, their ER data alone can still be included as part of the IVIVC analysis. Published by Elsevier Inc.

Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation.

PubMed

Erban, Radek; Kevrekidis, Ioannis G; Adalsteinsson, David; Elston, Timothy C

2006-02-28

We present computer-assisted methods for analyzing stochastic models of gene regulatory networks. The main idea that underlies this equation-free analysis is the design and execution of appropriately initialized short bursts of stochastic simulations; the results of these are processed to estimate coarse-grained quantities of interest, such as mesoscopic transport coefficients. In particular, using a simple model of a genetic toggle switch, we illustrate the computation of an effective free energy Phi and of a state-dependent effective diffusion coefficient D that characterize an unavailable effective Fokker-Planck equation. Additionally we illustrate the linking of equation-free techniques with continuation methods for performing a form of stochastic "bifurcation analysis"; estimation of mean switching times in the case of a bistable switch is also implemented in this equation-free context. The accuracy of our methods is tested by direct comparison with long-time stochastic simulations. This type of equation-free analysis appears to be a promising approach to computing features of the long-time, coarse-grained behavior of certain classes of complex stochastic models of gene regulatory networks, circumventing the need for long Monte Carlo simulations.

Non-Markovian spin-resolved counting statistics and an anomalous relation between autocorrelations and cross correlations in a three-terminal quantum dot

NASA Astrophysics Data System (ADS)

Luo, JunYan; Yan, Yiying; Huang, Yixiao; Yu, Li; He, Xiao-Ling; Jiao, HuJun

2017-01-01

We investigate the noise correlations of spin and charge currents through an electron spin resonance (ESR)-pumped quantum dot, which is tunnel coupled to three electrodes maintained at an equivalent chemical potential. A recursive scheme is employed with inclusion of the spin degrees of freedom to account for the spin-resolved counting statistics in the presence of non-Markovian effects due to coupling with a dissipative heat bath. For symmetric spin-up and spin-down tunneling rates, an ESR-induced spin flip mechanism generates a pure spin current without an accompanying net charge current. The stochastic tunneling of spin carriers, however, produces universal shot noises of both charge and spin currents, revealing the effective charge and spin units of quasiparticles in transport. In the case of very asymmetric tunneling rates for opposite spins, an anomalous relationship between noise autocorrelations and cross correlations is revealed, where super-Poissonian autocorrelation is observed in spite of a negative cross correlation. Remarkably, with strong dissipation strength, non-Markovian memory effects give rise to a positive cross correlation of the charge current in the absence of a super-Poissonian autocorrelation. These unique noise features may offer essential methods for exploiting internal spin dynamics and various quasiparticle tunneling processes in mesoscopic transport.

Unification theory of optimal life histories and linear demographic models in internal stochasticity.

PubMed

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of "Stochastic Control Theory" in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path-integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models.

Unification Theory of Optimal Life Histories and Linear Demographic Models in Internal Stochasticity

PubMed Central

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of “Stochastic Control Theory” in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path–integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models. PMID:24945258

Multiplicative stochastic processes in nonlinear systems: Noise-induced transition from the overdamped to the inertial regime

NASA Astrophysics Data System (ADS)

Faetti, Sandro; Festa, Crescenzo; Fronzoni, Leone; Grigolini, Paolo; Martano, Paolo

1984-12-01

An experimental apparatus is set up to check, via analog circuits, the recent theoretical predictions of Graham and Schenzle

Stochastic resonance in micro/nano cantilever sensors

NASA Astrophysics Data System (ADS)

Singh, Priyanka; Yadava, R. D. S.

2018-05-01

In this paper we present a comparative study on the stochastic resonance in micro/nano cantilever resonators due to fluctuations in the fundamental frequency or the damping coefficient. Considering DC+AC electrostatic actuation in the presence of zero-mean Gaussian noise with exponential autocorrelation we analyze stochastic resonance behaviors for the frequency and the damping fluctuations separately, and compare the effects of stochastic resonance on Q-factor of the resonators for different levels of damping losses. It is found that even though the stochastic resonance occurs for both types of fluctuations, only the damping fluctuation produces right cooperative influence on the fundamental resonance that improves both the amplitude response and the quality factor of the resonator.

The effect of memory in the stochastic master equation analyzed using the stochastic Liouville equation of motion. Electronic energy migration transfer between reorienting donor-donor, donor-acceptor chromophores

NASA Astrophysics Data System (ADS)

Håkansson, Pär; Westlund, Per-Olof

2005-01-01

This paper discusses the process of energy migration transfer within reorientating chromophores using the stochastic master equation (SME) and the stochastic Liouville equation (SLE) of motion. We have found that the SME over-estimates the rate of the energy migration compared to the SLE solution for a case of weakly interacting chromophores. This discrepancy between SME and SLE is caused by a memory effect occurring when fluctuations in the dipole-dipole Hamiltonian ( H( t)) are on the same timescale as the intrinsic fast transverse relaxation rate characterized by (1/ T2). Thus the timescale critical for energy-transfer experiments is T2≈10 -13 s. An extended SME is constructed, accounting for the memory effect of the dipole-dipole Hamiltonian dynamics. The influence of memory on the interpretation of experiments is discussed.

Delay-induced stochastic bifurcations in a bistable system under white noise

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

Sun, Zhongkui, E-mail: sunzk@nwpu.edu.cn; Fu, Jin; Xu, Wei

2015-08-15

In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochasticmore » P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.« less

Stochastic joint inversion of geoelectrical cross-well data for salt tracer test monitoring to image the hydraulic conductivity field of heterogenous aquifers

NASA Astrophysics Data System (ADS)

Revil, A.; Jardani, A.; Dupont, J.

2012-12-01

The assessment of hydraulic conductivity of heterogeneous aquifers is a difficult task using traditional hydrogeological methods (e.g., steady state or transient pumping tests) due to their low spatial resolution associated with a low density of available piezometers. Geophysical measurements performed at the ground surface and in boreholes provide additional information for increasing the resolution and accuracy of the inverted hydraulic conductivity. We use a stochastic joint inversion of Direct Current (DC) resistivity and Self-Potential (SP) data plus in situ measurement of the salinity in a downstream well during a synthetic salt tracer experiment to reconstruct the hydraulic conductivity field of an heterogeneous aquifer. The pilot point parameterization is used to avoid over-parameterization of the inverse problem. Bounds on the model parameters are used to promote a consistent Markov chain Monte Carlo sampling of the hydrogeological parameters of the model. To evaluate the effectiveness of the inversion process, we compare several scenarios where the geophysical data are coupled or not to the hydrogeological data to map the hydraulic conductivity. We first test the effectiveness of the inversion of each type of data alone, and then we combine the methods two by two. We finally combine all the information together to show the value of each type of geophysical data in the joint inversion process because of their different sensitivity map. The results of the inversion reveal that the self-potential data improve the estimate of hydraulic conductivity especially when the self-potential data are combined to the salt concentration measurement in the second well or to the time-lapse electrical resistivity data. Various tests are also performed to quantify the uncertainty in the inversion when for instance the semi-variogram is not known and its parameters should be inverted as well.

Improved ensemble-mean forecasting of ENSO events by a zero-mean stochastic error model of an intermediate coupled model

NASA Astrophysics Data System (ADS)

Zheng, Fei; Zhu, Jiang

2017-04-01

How to design a reliable ensemble prediction strategy with considering the major uncertainties of a forecasting system is a crucial issue for performing an ensemble forecast. In this study, a new stochastic perturbation technique is developed to improve the prediction skills of El Niño-Southern Oscillation (ENSO) through using an intermediate coupled model. We first estimate and analyze the model uncertainties from the ensemble Kalman filter analysis results through assimilating the observed sea surface temperatures. Then, based on the pre-analyzed properties of model errors, we develop a zero-mean stochastic model-error model to characterize the model uncertainties mainly induced by the missed physical processes of the original model (e.g., stochastic atmospheric forcing, extra-tropical effects, Indian Ocean Dipole). Finally, we perturb each member of an ensemble forecast at each step by the developed stochastic model-error model during the 12-month forecasting process, and add the zero-mean perturbations into the physical fields to mimic the presence of missing processes and high-frequency stochastic noises. The impacts of stochastic model-error perturbations on ENSO deterministic predictions are examined by performing two sets of 21-yr hindcast experiments, which are initialized from the same initial conditions and differentiated by whether they consider the stochastic perturbations. The comparison results show that the stochastic perturbations have a significant effect on improving the ensemble-mean prediction skills during the entire 12-month forecasting process. This improvement occurs mainly because the nonlinear terms in the model can form a positive ensemble-mean from a series of zero-mean perturbations, which reduces the forecasting biases and then corrects the forecast through this nonlinear heating mechanism.

Entropic stochastic resonance of a self-propelled Janus particle

NASA Astrophysics Data System (ADS)

Liu, Zhenzhen; Du, Luchun; Guo, Wei; Mei, Dong-Cheng

2016-10-01

Entropic stochastic resonance is investigated when a self-propelled Janus particle moves in a double-cavity container. Numerical simulation results indicate the entropic stochastic resonance can survive even if there is no symmetry breaking in any direction. This is the essential distinction between the property of a self-propelled Janus particle and that of a passive Brownian particle, for the symmetry breaking is necessary for the entropic stochastic resonance of a passive Brownian particle. With the rotational noise intensity growing at small fixed noise intensity of translational motion, the signal power amplification increases monotonically towards saturation which also can be regarded as a kind of stochastic resonance effect. Besides, the increase in the natural frequency of the periodic driving depresses the degree of the stochastic resonance, whereas the rise in its amplitude enhances and then suppresses the behavior.

Stochastic receding horizon control: application to an octopedal robot

NASA Astrophysics Data System (ADS)

Shah, Shridhar K.; Tanner, Herbert G.

2013-06-01

Miniature autonomous systems are being developed under ARL's Micro Autonomous Systems and Technology (MAST). These systems can only be fitted with a small-size processor, and their motion behavior is inherently uncertain due to manufacturing and platform-ground interactions. One way to capture this uncertainty is through a stochastic model. This paper deals with stochastic motion control design and implementation for MAST- specific eight-legged miniature crawling robots, which have been kinematically modeled as systems exhibiting the behavior of a Dubin's car with stochastic noise. The control design takes the form of stochastic receding horizon control, and is implemented on a Gumstix Overo Fire COM with 720 MHz processor and 512 MB RAM, weighing 5.5 g. The experimental results show the effectiveness of this control law for miniature autonomous systems perturbed by stochastic noise.

Optimality, stochasticity, and variability in motor behavior

PubMed Central

Guigon, Emmanuel; Baraduc, Pierre; Desmurget, Michel

2008-01-01

Recent theories of motor control have proposed that the nervous system acts as a stochastically optimal controller, i.e. it plans and executes motor behaviors taking into account the nature and statistics of noise. Detrimental effects of noise are converted into a principled way of controlling movements. Attractive aspects of such theories are their ability to explain not only characteristic features of single motor acts, but also statistical properties of repeated actions. Here, we present a critical analysis of stochastic optimality in motor control which reveals several difficulties with this hypothesis. We show that stochastic control may not be necessary to explain the stochastic nature of motor behavior, and we propose an alternative framework, based on the action of a deterministic controller coupled with an optimal state estimator, which relieves drawbacks of stochastic optimality and appropriately explains movement variability. PMID:18202922

Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics.

PubMed

Cotter, C J; Gottwald, G A; Holm, D D

2017-09-01

In Holm (Holm 2015 Proc. R. Soc. A 471 , 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow.

Statistical nature of infrared dynamics on de Sitter background

NASA Astrophysics Data System (ADS)

Tokuda, Junsei; Tanaka, Takahiro

2018-02-01

In this study, we formulate a systematic way of deriving an effective equation of motion(EoM) for long wavelength modes of a massless scalar field with a general potential V(phi) on de Sitter background, and investigate whether or not the effective EoM can be described as a classical stochastic process. Our formulation gives an extension of the usual stochastic formalism to including sub-leading secular growth coming from the nonlinearity of short wavelength modes. Applying our formalism to λ phi4 theory, we explicitly derive an effective EoM which correctly recovers the next-to-leading secularly growing part at a late time, and show that this effective EoM can be seen as a classical stochastic process. Our extended stochastic formalism can describe all secularly growing terms which appear in all correlation functions with a specific operator ordering. The restriction of the operator ordering will not be a big drawback because the commutator of a light scalar field becomes negligible at large scales owing to the squeezing.

Recursive stochastic effects in valley hybrid inflation

NASA Astrophysics Data System (ADS)

Levasseur, Laurence Perreault; Vennin, Vincent; Brandenberger, Robert

2013-10-01

Hybrid inflation is a two-field model where inflation ends because of a tachyonic instability, the duration of which is determined by stochastic effects and has important observational implications. Making use of the recursive approach to the stochastic formalism presented in [L. P. Levasseur, preceding article, Phys. Rev. D 88, 083537 (2013)], these effects are consistently computed. Through an analysis of backreaction, this method is shown to converge in the valley but points toward an (expected) instability in the waterfall. It is further shown that the quasistationarity of the auxiliary field distribution breaks down in the case of a short-lived waterfall. We find that the typical dispersion of the waterfall field at the critical point is then diminished, thus increasing the duration of the waterfall phase and jeopardizing the possibility of a short transition. Finally, we find that stochastic effects worsen the blue tilt of the curvature perturbations by an O(1) factor when compared with the usual slow-roll contribution.

Delay-distribution-dependent H∞ state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.

PubMed

Sheng, Li; Wang, Zidong; Tian, Engang; Alsaadi, Fuad E

2016-12-01

This paper deals with the H ∞ state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying stochastic delay takes values on certain intervals with known probability distributions. The system measurement is transmitted through fading channels described by the Rice fading model. The aim of the addressed problem is to design a state estimator such that the estimation performance is guaranteed in the mean-square sense against admissible stochastic time-delays, stochastic noises as well as stochastic fading signals. By employing the stochastic analysis approach combined with the Kronecker product, several delay-distribution-dependent conditions are derived to ensure that the error dynamics of the neuron states is stochastically stable with prescribed H ∞ performance. Finally, a numerical example is provided to illustrate the effectiveness of the obtained results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stochastic volatility of the futures prices of emission allowances: A Bayesian approach

NASA Astrophysics Data System (ADS)

Kim, Jungmu; Park, Yuen Jung; Ryu, Doojin

2017-01-01

Understanding the stochastic nature of the spot volatility of emission allowances is crucial for risk management in emissions markets. In this study, by adopting a stochastic volatility model with or without jumps to represent the dynamics of European Union Allowances (EUA) futures prices, we estimate the daily volatilities and model parameters by using the Markov Chain Monte Carlo method for stochastic volatility (SV), stochastic volatility with return jumps (SVJ) and stochastic volatility with correlated jumps (SVCJ) models. Our empirical results reveal three important features of emissions markets. First, the data presented herein suggest that EUA futures prices exhibit significant stochastic volatility. Second, the leverage effect is noticeable regardless of whether or not jumps are included. Third, the inclusion of jumps has a significant impact on the estimation of the volatility dynamics. Finally, the market becomes very volatile and large jumps occur at the beginning of a new phase. These findings are important for policy makers and regulators.

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem.

PubMed

Schilde, M; Doerner, K F; Hartl, R F

2014-10-01

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches.

Experimental investigation of the effect of pump incoherence on nonlinear pump spectral broadening and continuous-wave supercontinuum generation

NASA Astrophysics Data System (ADS)

Martin-Lopez, S.; Carrasco-Sanz, A.; Corredera, P.; Abrardi, L.; Hernanz, M. L.; Gonzalez-Herraez, M.

2006-12-01

The development of high-power cw fiber lasers has triggered a great interest in the phenomena of nonlinear pump spectral broadening and cw supercontinuum generation. These effects have very convenient applications in Raman amplification, optical fiber metrology, and fiber sensing. In particular, it was recently shown that pump incoherence has a strong impact in these processes. We study experimentally the effect of pump incoherence in nonlinear pump spectral broadening and cw supercontinuum generation in optical fibers. We show that under certain experimental conditions an optimum degree of pump incoherence yields the best performance in the broadening process. We qualitatively explain these results, and we point out that these results may have important implications in cw supercontinuum optimization.

Stochastic mixed-mode oscillations in a three-species predator-prey model

NASA Astrophysics Data System (ADS)

Sadhu, Susmita; Kuehn, Christian

2018-03-01

The effect of demographic stochasticity, in the form of Gaussian white noise, in a predator-prey model with one fast and two slow variables is studied. We derive the stochastic differential equations (SDEs) from a discrete model. For suitable parameter values, the deterministic drift part of the model admits a folded node singularity and exhibits a singular Hopf bifurcation. We focus on the parameter regime near the Hopf bifurcation, where small amplitude oscillations exist as stable dynamics in the absence of noise. In this regime, the stochastic model admits noise-driven mixed-mode oscillations (MMOs), which capture the intermediate dynamics between two cycles of population outbreaks. We perform numerical simulations to calculate the distribution of the random number of small oscillations between successive spikes for varying noise intensities and distance to the Hopf bifurcation. We also study the effect of noise on a suitable Poincaré map. Finally, we prove that the stochastic model can be transformed into a normal form near the folded node, which can be linked to recent results on the interplay between deterministic and stochastic small amplitude oscillations. The normal form can also be used to study the parameter influence on the noise level near folded singularities.

A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

NASA Astrophysics Data System (ADS)

Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

2017-12-01

Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

National Assessment of Energy Storage for Grid Balancing and Arbitrage: Phase 1, WECC

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

Kintner-Meyer, Michael CW; Balducci, Patrick J.; Colella, Whitney G.

2012-06-01

To examine the role that energy storage could play in mitigating the impacts of the stochastic variability of wind generation on regional grid operation, the Pacific Northwest National Laboratory (PNNL) examined a hypothetical 2020 grid scenario in which additional wind generation capacity is built to meet renewable portfolio standard targets in the Western Interconnection. PNNL developed a stochastic model for estimating the balancing requirements using historical wind statistics and forecasting error, a detailed engineering model to analyze the dispatch of energy storage and fast-ramping generation devices for estimating size requirements of energy storage and generation systems for meeting new balancingmore » requirements, and financial models for estimating the life-cycle cost of storage and generation systems in addressing the future balancing requirements for sub-regions in the Western Interconnection. Evaluated technologies include combustion turbines, sodium sulfur (Na-S) batteries, lithium ion batteries, pumped-hydro energy storage, compressed air energy storage, flywheels, redox flow batteries, and demand response. Distinct power and energy capacity requirements were estimated for each technology option, and battery size was optimized to minimize costs. Modeling results indicate that in a future power grid with high-penetration of renewables, the most cost competitive technologies for meeting balancing requirements include Na-S batteries and flywheels.« less

Evolutionary algorithms for the optimization of advective control of contaminated aquifer zones

NASA Astrophysics Data System (ADS)

Bayer, Peter; Finkel, Michael

2004-06-01

Simple genetic algorithms (SGAs) and derandomized evolution strategies (DESs) are employed to adapt well capture zones for the hydraulic optimization of pump-and-treat systems. A hypothetical contaminant site in a heterogeneous aquifer serves as an application template. On the basis of the results from numerical flow modeling, particle tracking is applied to delineate the pathways of the contaminants. The objective is to find the minimum pumping rate of up to eight recharge wells within a downgradient well placement area. Both the well coordinates and the pumping rates are subject to optimization, leading to a mixed discrete-continuous problem. This article discusses the ideal formulation of the objective function for which the number of particles and the total pumping rate are used as decision criteria. Boundary updating is introduced, which enables the reorganization of the decision space limits by the incorporation of experience from previous optimization runs. Throughout the study the algorithms' capabilities are evaluated in terms of the number of model runs which are needed to identify optimal and suboptimal solutions. Despite the complexity of the problem both evolutionary algorithm variants prove to be suitable for finding suboptimal solutions. The DES with weighted recombination reveals to be the ideal algorithm to find optimal solutions. Though it works with real-coded decision parameters, it proves to be suitable for adjusting discrete well positions. Principally, the representation of well positions as binary strings in the SGA is ideal. However, even if the SGA takes advantage of bookkeeping, the vital high discretization of pumping rates results in long binary strings, which escalates the model runs that are needed to find an optimal solution. Since the SGA string lengths increase with the number of wells, the DES gains superiority, particularly for an increasing number of wells. As the DES is a self-adaptive algorithm, it proves to be the more robust optimization method for the selected advective control problem than the SGA variants of this study, exhibiting a less stochastic search which is reflected in the minor variability of the found solutions.

[Insulin pump in type 2 diabetes: B-cell focused treatment].

PubMed

Picková, Klára; Rušavý, Zdeněk

Type 2 diabetes is a disorder characterized by insulin resistance and progressive deterioration of B-cell insulin secretion. B-cell protective strategies for lowering glucolipotoxicity by rapid achievement of normoglycemia using exogenous insulin improve their function and prolong diabetes remission. Insulin pump is an effective treatment method in newly diagnosed diabetes, where even short-term pump therapy is B-cell protective. Combination therapy with insulin pump and antidiabetics targeting the incretin system acts in synergy to protect the B-cell. While the positive effect of insulin pump is apparent even a year after stopping the therapy, the effect of incretins lasts only while on the medication. Short-term insulin treatment, especially delivered by insulin pump, is an effective method of B-cell protection in recent type 2 diabetes.Key words: B-cell function - diabetes mellitus - insulin pump - insulin resistance - type 2 diabetes.

Estimating the effects of 17α-ethinylestradiol on stochastic population growth rate of fathead minnows: a population synthesis of empirically derived vital rates.

PubMed

Schwindt, Adam R; Winkelman, Dana L

2016-09-01

Urban freshwater streams in arid climates are wastewater effluent dominated ecosystems particularly impacted by bioactive chemicals including steroid estrogens that disrupt vertebrate reproduction. However, more understanding of the population and ecological consequences of exposure to wastewater effluent is needed. We used empirically derived vital rate estimates from a mesocosm study to develop a stochastic stage-structured population model and evaluated the effect of 17α-ethinylestradiol (EE2), the estrogen in human contraceptive pills, on fathead minnow Pimephales promelas stochastic population growth rate. Tested EE2 concentrations ranged from 3.2 to 10.9 ng L(-1) and produced stochastic population growth rates (λ S ) below 1 at the lowest concentration, indicating potential for population decline. Declines in λ S compared to controls were evident in treatments that were lethal to adult males despite statistically insignificant effects on egg production and juvenile recruitment. In fact, results indicated that λ S was most sensitive to the survival of juveniles and female egg production. More broadly, our results document that population model results may differ even when empirically derived estimates of vital rates are similar among experimental treatments, and demonstrate how population models integrate and project the effects of stressors throughout the life cycle. Thus, stochastic population models can more effectively evaluate the ecological consequences of experimentally derived vital rates.

Impact of deterministic and stochastic updates on network reciprocity in the prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-08-01

In 2 × 2 prisoner's dilemma games, network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium. This study introduced an intriguing framework for the strategy update rule that allows any combination of a purely deterministic method, imitation max (IM), and a purely probabilistic one, pairwise Fermi (Fermi-PW). A series of simulations covering the whole range from IM to Fermi-PW reveals that, as a general tendency, the larger fractions of stochastic updating reduce network reciprocity, so long as the underlying lattice contains no noise in the degree of distribution. However, a small amount of stochastic flavor added to an otherwise perfectly deterministic update rule was actually found to enhance network reciprocity. This occurs because a subtle stochastic effect in the update rule improves the evolutionary trail in games having more stag-hunt-type dilemmas, although the same stochastic effect degenerates evolutionary trails in games having more chicken-type dilemmas. We explain these effects by dividing evolutionary trails into the enduring and expanding periods defined by Shigaki et al. [Phys. Rev. E 86, 031141 (2012), 10.1103/PhysRevE.86.031141].

Kinking and Torsion Can Significantly Improve the Efficiency of Valveless Pumping in Periodically Compressed Tubular Conduits. Implications for Understanding of the Form-Function Relationship of Embryonic Heart Tubes.

PubMed

Hiermeier, Florian; Männer, Jörg

2017-11-19

Valveless pumping phenomena (peristalsis, Liebau-effect) can generate unidirectional fluid flow in periodically compressed tubular conduits. Early embryonic hearts are tubular conduits acting as valveless pumps. It is unclear whether such hearts work as peristaltic or Liebau-effect pumps. During the initial phase of its pumping activity, the originally straight embryonic heart is subjected to deforming forces that produce bending, twisting, kinking, and coiling. This deformation process is called cardiac looping. Its function is traditionally seen as generating a configuration needed for establishment of correct alignments of pulmonary and systemic flow pathways in the mature heart of lung-breathing vertebrates. This idea conflicts with the fact that cardiac looping occurs in all vertebrates, including gill-breathing fishes. We speculate that looping morphogenesis may improve the efficiency of valveless pumping. To test the physical plausibility of this hypothesis, we analyzed the pumping performance of a Liebau-effect pump in straight and looped (kinked) configurations. Compared to the straight configuration, the looped configuration significantly improved the pumping performance of our pump. This shows that looping can improve the efficiency of valveless pumping driven by the Liebau-effect. Further studies are needed to clarify whether this finding may have implications for understanding of the form-function relationship of embryonic hearts.

Kinking and Torsion Can Significantly Improve the Efficiency of Valveless Pumping in Periodically Compressed Tubular Conduits. Implications for Understanding of the Form-Function Relationship of Embryonic Heart Tubes

PubMed Central

Hiermeier, Florian; Männer, Jörg

2017-01-01

Valveless pumping phenomena (peristalsis, Liebau-effect) can generate unidirectional fluid flow in periodically compressed tubular conduits. Early embryonic hearts are tubular conduits acting as valveless pumps. It is unclear whether such hearts work as peristaltic or Liebau-effect pumps. During the initial phase of its pumping activity, the originally straight embryonic heart is subjected to deforming forces that produce bending, twisting, kinking, and coiling. This deformation process is called cardiac looping. Its function is traditionally seen as generating a configuration needed for establishment of correct alignments of pulmonary and systemic flow pathways in the mature heart of lung-breathing vertebrates. This idea conflicts with the fact that cardiac looping occurs in all vertebrates, including gill-breathing fishes. We speculate that looping morphogenesis may improve the efficiency of valveless pumping. To test the physical plausibility of this hypothesis, we analyzed the pumping performance of a Liebau-effect pump in straight and looped (kinked) configurations. Compared to the straight configuration, the looped configuration significantly improved the pumping performance of our pump. This shows that looping can improve the efficiency of valveless pumping driven by the Liebau-effect. Further studies are needed to clarify whether this finding may have implications for understanding of the form-function relationship of embryonic hearts. PMID:29367548

Stochastic goal-oriented error estimation with memory

NASA Astrophysics Data System (ADS)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

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.

Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics

PubMed Central

Cotter, C. J.

2017-01-01

In Holm (Holm 2015 Proc. R. Soc. A 471, 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow. PMID:28989316

10 CFR Appendix B to Part 20 - Annual Limits on Intake (ALIs) and Derived Air Concentrations (DACs) of Radionuclides for...

Code of Federal Regulations, 2014 CFR

2014-01-01

...) a committed effective dose equivalent of 5 rems (stochastic ALI) or (2) a committed dose equivalent of 50 rems to an organ or tissue (non-stochastic ALI). The stochastic ALIs were derived to result in... equivalent to the whole body of 5 rems. The derivation includes multiplying the committed dose equivalent to...

10 CFR Appendix B to Part 20 - Annual Limits on Intake (ALIs) and Derived Air Concentrations (DACs) of Radionuclides for...

Code of Federal Regulations, 2011 CFR

2011-01-01

...) a committed effective dose equivalent of 5 rems (stochastic ALI) or (2) a committed dose equivalent of 50 rems to an organ or tissue (non-stochastic ALI). The stochastic ALIs were derived to result in... equivalent to the whole body of 5 rems. The derivation includes multiplying the committed dose equivalent to...

10 CFR Appendix B to Part 20 - Annual Limits on Intake (ALIs) and Derived Air Concentrations (DACs) of Radionuclides for...

Code of Federal Regulations, 2012 CFR

2012-01-01

...) a committed effective dose equivalent of 5 rems (stochastic ALI) or (2) a committed dose equivalent of 50 rems to an organ or tissue (non-stochastic ALI). The stochastic ALIs were derived to result in... equivalent to the whole body of 5 rems. The derivation includes multiplying the committed dose equivalent to...

10 CFR Appendix B to Part 20 - Annual Limits on Intake (ALIs) and Derived Air Concentrations (DACs) of Radionuclides for...

Code of Federal Regulations, 2010 CFR

2010-01-01

...) a committed effective dose equivalent of 5 rems (stochastic ALI) or (2) a committed dose equivalent of 50 rems to an organ or tissue (non-stochastic ALI). The stochastic ALIs were derived to result in... equivalent to the whole body of 5 rems. The derivation includes multiplying the committed dose equivalent to...

10 CFR Appendix B to Part 20 - Annual Limits on Intake (ALIs) and Derived Air Concentrations (DACs) of Radionuclides for...

Code of Federal Regulations, 2013 CFR

2013-01-01

...) a committed effective dose equivalent of 5 rems (stochastic ALI) or (2) a committed dose equivalent of 50 rems to an organ or tissue (non-stochastic ALI). The stochastic ALIs were derived to result in... equivalent to the whole body of 5 rems. The derivation includes multiplying the committed dose equivalent to...

Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management

Treesearch

Mo Zhou; Joseph Buongiorno

2011-01-01

Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to...

Nanoparticles as Efflux Pump and Biofilm Inhibitor to Rejuvenate Bactericidal Effect of Conventional Antibiotics

NASA Astrophysics Data System (ADS)

Gupta, Divya; Singh, Ajeet; Khan, Asad U.

2017-07-01

The universal problem of bacterial resistance to antibiotic reflects a serious threat for physicians to control infections. Evolution in bacteria results in the development of various complex resistance mechanisms to neutralize the bactericidal effect of antibiotics, like drug amelioration, target modification, membrane permeability reduction, and drug extrusion through efflux pumps. Efflux pumps acquire a wide range of substrate specificity and also the tremendous efficacy for drug molecule extrusion outside bacterial cells. Hindrance in the functioning of efflux pumps may rejuvenate the bactericidal effect of conventional antibiotics. Efflux pumps also play an important role in the exclusion or inclusion of quorum-sensing biomolecules responsible for biofilm formation in bacterial cells. This transit movement of quorum-sensing biomolecules inside or outside the bacterial cells may get interrupted by impeding the functioning of efflux pumps. Metallic nanoparticles represent a potential candidate to block efflux pumps of bacterial cells. The application of nanoparticles as efflux pump inhibitors will not only help to revive the bactericidal effect of conventional antibiotics but will also assist to reduce biofilm-forming capacity of microbes. This review focuses on a novel and fascinating application of metallic nanoparticles in synergy with conventional antibiotics for efflux pump inhibition.

Detection of pure inverse spin-Hall effect induced by spin pumping at various excitation

NASA Astrophysics Data System (ADS)

Inoue, H. Y.; Harii, K.; Ando, K.; Sasage, K.; Saitoh, E.

2007-10-01

Electric-field generation due to the inverse spin-Hall effect (ISHE) driven by spin pumping was detected and separated experimentally from the extrinsic magnetogalvanic effects in a Ni81Fe19/Pt film. By applying a sample-cavity configuration in which the extrinsic effects are suppressed, the spin pumping using ferromagnetic resonance gives rise to a symmetric spectral shape in the electromotive force spectrum, indicating that the motive force is due entirely to ISHE. This method allows the quantitative analysis of the ISHE and the spin-pumping effect. The microwave-power dependence of the ISHE amplitude is consistent with the prediction of a direct current-spin-pumping scenario.

Stochastic Representations of Seismic Anisotropy: Verification of Effective Media Models and Application to the Continental Crust

NASA Astrophysics Data System (ADS)

Song, X.; Jordan, T. H.

2017-12-01

The seismic anisotropy of the continental crust is dominated by two mechanisms: the local (intrinsic) anisotropy of crustal rocks caused by the lattice-preferred orientation of their constituent minerals, and the geometric (extrinsic) anisotropy caused by the alignment and layering of elastic heterogeneities by sedimentation and deformation. To assess the relative importance of these mechanisms, we have applied Jordan's (GJI, 2015) self-consistent, second-order theory to compute the effective elastic parameters of stochastic media with hexagonal local anisotropy and small-scale 3D heterogeneities that have transversely isotropic (TI) statistics. The theory pertains to stochastic TI media in which the eighth-order covariance tensor of the elastic moduli can be separated into a one-point variance tensor that describes the local anisotropy in terms of a anisotropy orientation ratio (ξ from 0 to ∞), and a two-point correlation function that describes the geometric anisotropy in terms of a heterogeneity aspect ratio (η from 0 to ∞). If there is no local anisotropy, then, in the limiting case of a horizontal stochastic laminate (η→∞), the effective-medium equations reduce to the second-order equations derived by Backus (1962) for a stochastically layered medium. This generalization of the Backus equations to 3D stochastic media, as well as the introduction of local, stochastically rotated anisotropy, provides a powerful theory for interpreting the anisotropic signatures of sedimentation and deformation in continental environments; in particular, the parameterizations that we propose are suitable for tomographic inversions. We have verified this theory through a series high-resolution numerical experiments using both isotropic and anisotropic wave-propagation codes.

Population stochastic modelling (PSM)--an R package for mixed-effects models based on stochastic differential equations.

PubMed

Klim, Søren; Mortensen, Stig Bousgaard; Kristensen, Niels Rode; Overgaard, Rune Viig; Madsen, Henrik

2009-06-01

The extension from ordinary to stochastic differential equations (SDEs) in pharmacokinetic and pharmacodynamic (PK/PD) modelling is an emerging field and has been motivated in a number of articles [N.R. Kristensen, H. Madsen, S.H. Ingwersen, Using stochastic differential equations for PK/PD model development, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 109-141; C.W. Tornøe, R.V. Overgaard, H. Agersø, H.A. Nielsen, H. Madsen, E.N. Jonsson, Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations, Pharm. Res. 22 (August(8)) (2005) 1247-1258; R.V. Overgaard, N. Jonsson, C.W. Tornøe, H. Madsen, Non-linear mixed-effects models with stochastic differential equations: implementation of an estimation algorithm, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 85-107; U. Picchini, S. Ditlevsen, A. De Gaetano, Maximum likelihood estimation of a time-inhomogeneous stochastic differential model of glucose dynamics, Math. Med. Biol. 25 (June(2)) (2008) 141-155]. PK/PD models are traditionally based ordinary differential equations (ODEs) with an observation link that incorporates noise. This state-space formulation only allows for observation noise and not for system noise. Extending to SDEs allows for a Wiener noise component in the system equations. This additional noise component enables handling of autocorrelated residuals originating from natural variation or systematic model error. Autocorrelated residuals are often partly ignored in PK/PD modelling although violating the hypothesis for many standard statistical tests. This article presents a package for the statistical program R that is able to handle SDEs in a mixed-effects setting. The estimation method implemented is the FOCE(1) approximation to the population likelihood which is generated from the individual likelihoods that are approximated using the Extended Kalman Filter's one-step predictions.

Joint  effects of habitat configuration and temporal stochasticity on population dynamics

Treesearch

Jennifer M. Fraterrigo; Scott M. Pearson; Monica G. Turner

2009-01-01

Habitat configuration and temporal stochasticity in the environment are recognized as important drivers of population structure, yet few studies have examined the combined influence of these factors....

Random aspects of beam physics and laser-plasma interactions

NASA Astrophysics Data System (ADS)

Charman, Andrew Emile

Aspects of the dynamics of charged particle and radiation beams, and of the interaction of plasmas with radiation are investigated, informed by concerns of classical and quantum mechanical uncertainty and noise, and related by notions of particle and radiation phase space manipulation, overlap, and control. We begin by studying questions of optimal longitudinal pulse-shaping in laser wakefield accelerators, based on a one-dimensional model with prescribed laser drive and either a linearized or fully nonlinear quasi-static plasma response. After discussing various figures of-merit, we advocate maximizing the peak wake amplitude instead of the transformer ratio. A number of new results are demonstrated, certain conjectures are rigorously proved for the first time, and some erroneous claims corrected. Instead of using short laser pulses to excite plasma waves, one can employ the beat wave between two co-propagating lasers to excite a Langmuir wave with high phase velocity suitable for acceleration of relativistic electrons. A modified version of this plasma beat-wave accelerator scheme is introduced and analyzed, which is based on autoresonant phase-locking of the nonlinear Langmuir wave to the slowly chirped beat frequency of the driving lasers via adiabatic passage through resonance. This new scheme is designed to overcome some of the well-known limitations of previous approaches, such as relativistic detuning and nonlinear modulation of the driven Langmuir wave amplitude, as well as sen sitivity to frequency mismatch due to measurement uncertainties and density fluctuations or inhomogeneities. From radiation exciting plasmas, we turn to issues of plasmas or beams emitting radiation. We develop a Hilbert-space and operator-based approach to electromagnetic radiation, and use this formalism to derive a maximum-power variational principle (MPVP) for spontaneous radiation from prescribed classical harmonic sources. Results are first derived in the paraxial limit, based on well-known analogies between paraxial optics and the Schrodinger equation for a single non-relativistic particle, and then generalized to non-paraxial situations. In essence, the variational principle says that prescribed classical charges radiate "as much as possible," consistent with energy conservation. The techniques are developed to model undulator radiation from relativistic electron beams, for which an example involving high harmonic generation is reviewed. We next study a situation where wiggler radiation is both emitted from particles and reapplied to them. In stochastic cooling, information in the radiation induced from a particle bunch, if suitably amplified and fed back on the beam, can decrease entropy and increase phase space density. Specifically, we analyze and assess possible quantum mechanical effects in optical stochastic cooling. Fast stochastic cooling (i.e., on microsecond time-scales) would be desirable in certain applications, for example, to boost final luminosity in the proposed muon collider, where the short particle lifetimes severely limit the total time available to reduce beam phase space. But fast cooling requires very high-bandwidth amplifiers to limit the incoherent heating effects from neighboring particles. Transit-time optical stochastic cooling employs high-gain, high-bandwidth, solid-state lasers to amplify the spontaneous radiation from the charged particle bunch in a strong-field magnetic wiggler. This amplified light is then fed back onto the same bunch inside a second wiggler, with appropriate phase delay to effect cooling. Prior to amplification, the usable coherent signal from any one particle is quite small, on average much less than one photon for each pass through the wiggler. This fact suggests that the radiation must be treated quantum mechanically, and raises doubts as to whether this weak signal even contains sufficient phase information for cooling and whether it can be reliably amplified to provide cooling on each pass. Further examining the possibility of quantum mechanical effects of charges and their radiation, we turn to quantum treatments of Electromagnetically-Induced-Transparency (EIT) in magnetized plasmas, in which the medium---normally opaque to a resonantly-polarized EM probe field at the cyclotron frequency---can be made transparent by the application of an intense EM pump at a frequency detuned below the cyclotron frequency by the plasma frequency. This raises fundamental questions as to how and to what extent a seemingly classical phenomena in plasma can mimic a quantum mechanical effect in atoms. We address these questions by describing both systems in a common quantum mechanical language, where in the cold, unsaturated limit, the relevant excitations are associated with collective Bosonic modes, or quasi-particles. EIT can be understood in terms of the dressing of these modes via the pump-mediated interaction, leading to a dark-state polariton coherently combining both field and particle excitations that is largely immune to the cyclotron resonance. (Abstract shortened by UMI.)

Subcritical Hopf Bifurcation and Stochastic Resonance of Electrical Activities in Neuron under Electromagnetic Induction

PubMed Central

Fu, Yu-Xuan; Kang, Yan-Mei; Xie, Yong

2018-01-01

The FitzHugh–Nagumo model is improved to consider the effect of the electromagnetic induction on single neuron. On the basis of investigating the Hopf bifurcation behavior of the improved model, stochastic resonance in the stochastic version is captured near the bifurcation point. It is revealed that a weak harmonic oscillation in the electromagnetic disturbance can be amplified through stochastic resonance, and it is the cooperative effect of random transition between the resting state and the large amplitude oscillating state that results in the resonant phenomenon. Using the noise dependence of the mean of interburst intervals, we essentially suggest a biologically feasible clue for detecting weak signal by means of neuron model with subcritical Hopf bifurcation. These observations should be helpful in understanding the influence of the magnetic field to neural electrical activity. PMID:29467642

Subcritical Hopf Bifurcation and Stochastic Resonance of Electrical Activities in Neuron under Electromagnetic Induction.

PubMed

Fu, Yu-Xuan; Kang, Yan-Mei; Xie, Yong

2018-01-01

The FitzHugh-Nagumo model is improved to consider the effect of the electromagnetic induction on single neuron. On the basis of investigating the Hopf bifurcation behavior of the improved model, stochastic resonance in the stochastic version is captured near the bifurcation point. It is revealed that a weak harmonic oscillation in the electromagnetic disturbance can be amplified through stochastic resonance, and it is the cooperative effect of random transition between the resting state and the large amplitude oscillating state that results in the resonant phenomenon. Using the noise dependence of the mean of interburst intervals, we essentially suggest a biologically feasible clue for detecting weak signal by means of neuron model with subcritical Hopf bifurcation. These observations should be helpful in understanding the influence of the magnetic field to neural electrical activity.

Fundamental limitation of a two-dimensional description of magnetic reconnection

NASA Astrophysics Data System (ADS)

Firpo, Marie-Christine

2014-10-01

For magnetic reconnection to be possible, the electrons have at some point to ``get free from magnetic slavery,'' according to von Steiger's formulation. Stochasticity may be considered as one possible ingredient through which this may be realized in the magnetic reconnection process. It will be argued that non-ideal effects may be considered as a ``hidden'' way to introduce stochasticity. Then it will be shown that there exists a generic intrinsic stochasticity of magnetic field lines that does not require the invocation of non-ideal effects but cannot show up in effective two-dimensional models of magnetic reconnection. Possible implications will be discussed in the frame of tokamak sawteeth that form a laboratory prototype of magnetic reconnection.

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem

PubMed Central

Schilde, M.; Doerner, K.F.; Hartl, R.F.

2014-01-01

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches. PMID:25844013

Effects of Pump Pulsation on Hydrodynamic Properties and Dissolution Profiles in Flow-Through Dissolution Systems (USP 4).

PubMed

Yoshida, Hiroyuki; Kuwana, Akemi; Shibata, Hiroko; Izutsu, Ken-Ichi; Goda, Yukihiro

2016-06-01

To clarify the effects of pump pulsation and flow-through cell (FTC) dissolution system settings on the hydrodynamic properties and dissolution profiles of model formulations. Two FTC systems with different cell temperature control mechanisms were used. Particle image velocimetry (PIV) was used to analyze the hydrodynamic properties of test solutions in the flow-through dissolution test cell. Two pulsation pumps (semi-sine, full-sine) and a non-pulsatile pump were used to study the effects of varied flows on the dissolution profiles of United States Pharmacopeia standard tablets. PIV analysis showed periodic changes in the aligned upward fluid flow throughout the dissolution cell that was designed to reduce the temperature gradient during pump pulsation (0.5 s/pulse). The maximum instantaneous flow from the semi-sine pump was higher than that of the full-sine pump under all conditions. The flow from the semi-sine wave pump showed faster dissolution of salicylic acid and prednisone tablets than those from other pumps. The semi-sine wave pump flow showed similar dissolution profiles in the two FTC systems. Variations in instantaneous fluid flow caused by pump pulsation that meets the requirements of pharmacopoeias are a factor that affects the dissolution profiles of tablets in FTC systems.

Forecasting the Relative and Cumulative Effects of Multiple Stressors on At-risk Populations

DTIC Science & Technology

2011-08-01

Vitals (observed vital rates), Movement, Ranges, Barriers (barrier interactions), Stochasticity (a time series of stochasticity indices...Simulation Viewer are themselves stochastic . They can change each time it is run. B. 196 Analysis If multiple Census events are present in the life...30-year period. A monthly time series was generated for the 20th-century using monthly anomalies for temperature, precipitation, and percent

Effect of pump polarization direction on power characteristics in monolithic microchip Nd:YAG dual-frequency laser.

PubMed

Chen, Hao; Zhang, Shulian; Tan, Yidong

2016-04-10

The pump polarization direction can greatly influence the characteristics of the laser diode end-pumped monolithic microchip Nd:YAG dual-frequency laser. We experimentally observe the lasing thresholds and the optical powers of two splitting modes versus the pump polarization direction. The effect of the pump-induced gain anisotropy on the mode oscillation sequence is analyzed. And the effect on the intensities of these modes is also proved with a rate equation model. This study contributes to the improvement of the stability and the reliability of the Nd:YAG dual-frequency laser.

Geographic variation in density-dependent dynamics impacts the synchronizing effect of dispersal and regional stochasticity

Treesearch

Andrew M. Liebhold; Derek M. Johnson; Ottar N. Bj& #248rnstad

2006-01-01

Explanations for the ubiquitous presence of spatially synchronous population dynamics have assumed that density-dependent processes governing the dynamics of local populations are identical among disjunct populations, and low levels of dispersal or small amounts of regionalized stochasticity ("Moran effect") can act to synchronize populations. In this study...

Bird diversity and environmental heterogeneity in North America: A test of the area-heterogeneity trade-off

Treesearch

Rachel Chocron; Curtis H. Flather; Ronen Kadmon

2015-01-01

Aim: Deterministic niche theory predicts that increasing environmental heterogeneity increases species richness. In contrast, a recent stochastic model suggests that heterogeneity has a unimodal effect on species richness since high levels of heterogeneity reduce the effective area available per species, thereby increasing the likelihood of stochastic...

Production and efficiency of large wildland fire suppression effort: A stochastic frontier analysis

Treesearch

Hari Katuwal; Dave Calkin; Michael S. Hand

2016-01-01

This study examines the production and efficiency of wildland fire suppression effort. We estimate the effectiveness of suppression resource inputs to produce controlled fire lines that contain large wildland fires using stochastic frontier analysis. Determinants of inefficiency are identified and the effects of these determinants on the daily production of...

Perception of stochastically undersampled sound waveforms: a model of auditory deafferentation

PubMed Central

Lopez-Poveda, Enrique A.; Barrios, Pablo

2013-01-01

Auditory deafferentation, or permanent loss of auditory nerve afferent terminals, occurs after noise overexposure and aging and may accompany many forms of hearing loss. It could cause significant auditory impairment but is undetected by regular clinical tests and so its effects on perception are poorly understood. Here, we hypothesize and test a neural mechanism by which deafferentation could deteriorate perception. The basic idea is that the spike train produced by each auditory afferent resembles a stochastically digitized version of the sound waveform and that the quality of the waveform representation in the whole nerve depends on the number of aggregated spike trains or auditory afferents. We reason that because spikes occur stochastically in time with a higher probability for high- than for low-intensity sounds, more afferents would be required for the nerve to faithfully encode high-frequency or low-intensity waveform features than low-frequency or high-intensity features. Deafferentation would thus degrade the encoding of these features. We further reason that due to the stochastic nature of nerve firing, the degradation would be greater in noise than in quiet. This hypothesis is tested using a vocoder. Sounds were filtered through ten adjacent frequency bands. For the signal in each band, multiple stochastically subsampled copies were obtained to roughly mimic different stochastic representations of that signal conveyed by different auditory afferents innervating a given cochlear region. These copies were then aggregated to obtain an acoustic stimulus. Tone detection and speech identification tests were performed by young, normal-hearing listeners using different numbers of stochastic samplers per frequency band in the vocoder. Results support the hypothesis that stochastic undersampling of the sound waveform, inspired by deafferentation, impairs speech perception in noise more than in quiet, consistent with auditory aging effects. PMID:23882176

Stochastic simulation of Venice land uplift by seawater injection in deep heterogeneous aquifers

NASA Astrophysics Data System (ADS)

Ferronato, M.; Gambolati, G.; Teatini, P.; Bau, D. A.; Putti, M.

2010-12-01

In recent years, several geo-mechanical modeling studies have indicated that seawater injection into deep formations underneath the city of Venice, Italy, may produce a land uplift sufficient to significantly mitigate the effects of the acqua alta, that is, the exceptional tide peaks that periodically occur in the northern Adriatic Sea. However, of major concern is the differential vertical displacement at the ground surface, which must not exceed prescribed regulatory thresholds to guarantee structural preservation of the city historical buildings. In this work, we focus on the hydraulic conductivity, K, which - due to its inherent spatial heterogeneity - is often one of the most difficult hydrogeological parameters to characterize, and analyze the effects that spatially heterogeneous aquifer K distributions may have on the uniformity of the induced land uplift. This study relies on a series of stochastic geomechanical simulations performed using an uncoupled 3D finite-element model poro-elastic model and refers to a pilot project devised to address the feasibility and sustainability of an actual full-scale injection program. The pilot project considers the recharge of about 3,100 m3/day seawater over three years from three injection wells installed into six aquifers comprised between depths of 600 and 800 meters. The K field is modeled geostatistically according to an unconditional, second-order, stationary random process characterized by an exponential covariance function. The stochastic geomechanical simulations are structured into a sensitivity analysis in order to investigate the impact of the variance, σ2, and the horizontal correlation scale, λ, of the K field on the spatial distributions of the ground surface uplift and its horizontal gradient ρz. The results indicate that, irrespective of the σ2 and λ values, properly selected within the ranges 0.2-1.0 and 20-1000 m, respectively, typical of normally consolidated sedimentary basins, the predicted uplift is substantially regular with negligible differential displacements. Even under the most pessimistic scenario (σ2=1.0 and λ=1000 m) the maximum ρz results from two to three times smaller than that experienced by the city over the 1960’s due to ground water pumping (10×10-5), one order of magnitude less than the maximum limit allowed for masonry buildings (50×10-55), and about 20 times smaller than the values that restricted portions of the city are currently experiencing due to surficial loads and to possible heterogeneities of the upper Holocene deposits upon which the city is founded.

Stochastic resonance effects reveal the neural mechanisms of transcranial magnetic stimulation

PubMed Central

Schwarzkopf, Dietrich Samuel; Silvanto, Juha; Rees, Geraint

2011-01-01

Transcranial magnetic stimulation (TMS) is a popular method for studying causal relationships between neural activity and behavior. However its mode of action remains controversial, and so far there is no framework to explain its wide range of facilitatory and inhibitory behavioral effects. While some theoretical accounts suggests that TMS suppresses neuronal processing, other competing accounts propose that the effects of TMS result from the addition of noise to neuronal processing. Here we exploited the stochastic resonance phenomenon to distinguish these theoretical accounts and determine how TMS affects neuronal processing. Specifically, we showed that online TMS can induce stochastic resonance in the human brain. At low intensity, TMS facilitated the detection of weak motion signals but with higher TMS intensities and stronger motion signals we found only impairment in detection. These findings suggest that TMS acts by adding noise to neuronal processing, at least in an online TMS protocol. Importantly, such stochastic resonance effects may also explain why TMS parameters that under normal circumstances impair behavior, can induce behavioral facilitations when the stimulated area is in an adapted or suppressed state. PMID:21368025

Effect of laser speckle on light from laser diode-pumped phosphor-converted light sources.

PubMed

Aquino, Felipe; Jadwisienczak, Wojciech M; Rahman, Faiz

2017-01-10

Laser diode (LD) pumped white light sources are being developed as an alternative to light-emitting diode-pumped sources for high efficiency and/or high brightness applications. While several performance metrics of laser-pumped phosphor-converted light sources have been investigated, the effect of laser speckle has not been sufficiently explored. This paper describes our experimental studies on how laser speckle affects the behavior of light from laser-excited phosphor lamps. A single LD pumping a phosphor plate was the geometry explored in this work. Overall, our findings are that the down-converted light did not exhibit any speckle, whereas speckle was present in the residual pump light but much reduced from that in direct laser light. Furthermore, a thicker coating of small-grained phosphors served to effectively reduce speckle through static pump light diffusion in the phosphor coating. Our investigations showed that speckle is not of concern in illumination from LD-pumped phosphor-converted light sources.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Disentangling the stochastic behavior of complex time series

NASA Astrophysics Data System (ADS)

Anvari, Mehrnaz; Tabar, M. Reza Rahimi; Peinke, Joachim; Lehnertz, Klaus

2016-10-01

Complex systems involving a large number of degrees of freedom, generally exhibit non-stationary dynamics, which can result in either continuous or discontinuous sample paths of the corresponding time series. The latter sample paths may be caused by discontinuous events - or jumps - with some distributed amplitudes, and disentangling effects caused by such jumps from effects caused by normal diffusion processes is a main problem for a detailed understanding of stochastic dynamics of complex systems. Here we introduce a non-parametric method to address this general problem. By means of a stochastic dynamical jump-diffusion modelling, we separate deterministic drift terms from different stochastic behaviors, namely diffusive and jumpy ones, and show that all of the unknown functions and coefficients of this modelling can be derived directly from measured time series. We demonstrate appli- cability of our method to empirical observations by a data-driven inference of the deterministic drift term and of the diffusive and jumpy behavior in brain dynamics from ten epilepsy patients. Particularly these different stochastic behaviors provide extra information that can be regarded valuable for diagnostic purposes.

Inducing Tropical Cyclones to Undergo Brownian Motion

NASA Astrophysics Data System (ADS)

Hodyss, D.; McLay, J.; Moskaitis, J.; Serra, E.

2014-12-01

Stochastic parameterization has become commonplace in numerical weather prediction (NWP) models used for probabilistic prediction. Here, a specific stochastic parameterization will be related to the theory of stochastic differential equations and shown to be affected strongly by the choice of stochastic calculus. From an NWP perspective our focus will be on ameliorating a common trait of the ensemble distributions of tropical cyclone (TC) tracks (or position), namely that they generally contain a bias and an underestimate of the variance. With this trait in mind we present a stochastic track variance inflation parameterization. This parameterization makes use of a properly constructed stochastic advection term that follows a TC and induces its position to undergo Brownian motion. A central characteristic of Brownian motion is that its variance increases with time, which allows for an effective inflation of an ensemble's TC track variance. Using this stochastic parameterization we present a comparison of the behavior of TCs from the perspective of the stochastic calculi of Itô and Stratonovich within an operational NWP model. The central difference between these two perspectives as pertains to TCs is shown to be properly predicted by the stochastic calculus and the Itô correction. In the cases presented here these differences will manifest as overly intense TCs, which, depending on the strength of the forcing, could lead to problems with numerical stability and physical realism.

Increase of economy of torque flow pump with high specific speed

NASA Astrophysics Data System (ADS)

Gusak, A. G.; Krishtop, I. V.; German, V. F.; Baga, V. N.

2017-08-01

Torque flow pumps are widely spread types of energy machines, which are used in majority of modern branches of industry for pumping of dirty media. The main task of researchers of torque flow pumps is increase of such pumps effectiveness for higher feed. Hydraulic losses for torque flow pumps are caused by working process of such pumps and are inevitable. Decrease of losses can be obtained by means of optimization of hydraulic flow part geometry. Modern approach to design of pump outlet introduces new constructive solutions which can increase economy of torque flow pumps. The aim of this research is increase of economy of torque flow pumps by means of application of spatial outlet and investigation of its geometry on pump characteristics. Analytical and numerical methods of liquid flow research for hydraulic flow part of torque flow pump were used in this paper. Moreover, influence of hydraulic flow part geometry of different designs of “Turo” type torque flow pumps outlets on pump characteristics was investigated. Numerical research enabled to study process of energy transfer of torque flow pump and evaluate influence of geometrical dimensions of spatial spiral outlet on its characteristics. Besides numerical research confirmed introduced regularity of peripheral velocity distribution in outlet. Velocity moment distribution in outlet was obtained during implementation of numerical research. Implemented bench tests of torque flow pump prototypes enabled to obtain real characteristics of pump and confirm effectiveness of spatial geometry of outlet application for such pump.

Estimating the effects of 17α-ethinylestradiol on stochastic population growth rate of fathead minnows: a population synthesis of empirically derived vital rates

USGS Publications Warehouse

Schwindt, Adam R.; Winkelman, Dana L.

2016-01-01

Urban freshwater streams in arid climates are wastewater effluent dominated ecosystems particularly impacted by bioactive chemicals including steroid estrogens that disrupt vertebrate reproduction. However, more understanding of the population and ecological consequences of exposure to wastewater effluent is needed. We used empirically derived vital rate estimates from a mesocosm study to develop a stochastic stage-structured population model and evaluated the effect of 17α-ethinylestradiol (EE2), the estrogen in human contraceptive pills, on fathead minnow Pimephales promelas stochastic population growth rate. Tested EE2 concentrations ranged from 3.2 to 10.9 ng L−1 and produced stochastic population growth rates (λ S ) below 1 at the lowest concentration, indicating potential for population decline. Declines in λ S compared to controls were evident in treatments that were lethal to adult males despite statistically insignificant effects on egg production and juvenile recruitment. In fact, results indicated that λ S was most sensitive to the survival of juveniles and female egg production. More broadly, our results document that population model results may differ even when empirically derived estimates of vital rates are similar among experimental treatments, and demonstrate how population models integrate and project the effects of stressors throughout the life cycle. Thus, stochastic population models can more effectively evaluate the ecological consequences of experimentally derived vital rates.

Radiation risk estimation and its application to human beings in space.

PubMed

Sinclair, W K

1984-01-01

The number of human beings likely to spend time in space will increase as time goes on. While exposures vary according to missions, orbits, shielding, etc., an average space radiation fluence (ignoring solar flares, radiation belts and anomalous regions in space) in locations close to earth is about 10 rad/year with a quality factor of about 5.5. The potential effects of exposure to these fluences include both non-stochastic effects and stochastic effects (cancer and genetic damage). Non-stochastic effects, damage to the lens of the eye, bone marrow or gonads, can be avoided by keeping radiation limits below threshold values. Stochastic effects imply risk at all levels. The magnitude of these risks has been discussed in a number of reports by the UNSCEAR Committee and the BEIR Committee in the USA during 1970-1980. The uncertainties associated with these risks and information which has become available since the last BEIR report is discussed. In considering reasonable limits for exposure in space, acceptable levels for stochastic risks must be based on appropriate comparisons. In view of the limited term of duty of most space workers, a lifetime limit may be appropriate. This lifetime limit might be comparable in terms of risks with limits for radiation workers on the ground but received at a higher annual rate for a shorter time. These and other approaches are expected to be considered by an NCRP Committee currently examining the problem of space radiation hazards.

Cost-utility of laparoscopic Nissen fundoplication versus proton pump inhibitors for chronic and controlled gastroesophageal reflux disease: a 3-year prospective randomized controlled trial and economic evaluation.

PubMed

Goeree, Ron; Hopkins, Rob; Marshall, John K; Armstrong, David; Ungar, Wendy J; Goldsmith, Charles; Allen, Christopher; Anvari, Mehran

2011-01-01

Very few randomized controlled trials (RCTs) have compared laparoscopic Nissen fundoplication (LNF) to proton pump inhibitors (PPI) medical management for patients with chronic gastroesophageal reflux disease (GERD). Larger RCTs have been relatively short in duration, and have reported mixed results regarding symptom control and effect on quality of life (QOL). Economic evaluations have reported conflicting results. To determine the incremental cost-utility of LNF versus PPI for treating patients with chronic and controlled GERD over 3 years from the societal perspective. Economic evaluation was conducted alongside a RCT that enrolled 104 patients from October 2000 to September 2004. Primary study outcome was GERD symptoms (secondary outcomes included QOL and cost-utility). Resource utilization and QOL data collected at regular follow-up intervals determined incremental cost/QALY gained. Stochastic uncertainty was assessed using bootstrapping and methodologic assumptions were assessed using sensitivity analysis. No statistically significant differences in GERD symptom scores, but LNF did result in fewer heartburn days and improved QOL. Costs were higher for LNF patients by $3205/patient over 3 years but QOL was also higher as measured by either QOL instrument. Based on total costs, incremental cost-utility of LNF was $29,404/QALY gained using the Health Utility Index 3. Cost-utility results were sensitive to the utility instrument used ($29,404/QALY for Health Utility Index 3, $31,117/QALY for the Short Form 6D, and $76,310/QALY for EuroQol 5D) and if current lower prices for PPIs were used in the analysis. Results varied depending on resource use/costs included in the analysis, the QOL instrument used, and the cost of PPIs; however, LNF was generally found to be a cost-effective treatment for patients with symptomatic controlled GERD requiring long-term management. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Species Associations in a Species-Rich Subtropical Forest Were Not Well-Explained by Stochastic Geometry of Biodiversity

PubMed Central

Wang, Qinggang; Bao, Dachuan; Guo, Yili; Lu, Junmeng; Lu, Zhijun; Xu, Yaozhan; Zhang, Kuihan; Liu, Haibo; Meng, Hongjie; Jiang, Mingxi; Qiao, Xiujuan; Huang, Handong

2014-01-01

The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1) the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2) The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3) Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47%) of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4) We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66%) than shrub species (18%). We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure. PMID:24824996

Species associations in a species-rich subtropical forest were not well-explained by stochastic geometry of biodiversity.

PubMed

Wang, Qinggang; Bao, Dachuan; Guo, Yili; Lu, Junmeng; Lu, Zhijun; Xu, Yaozhan; Zhang, Kuihan; Liu, Haibo; Meng, Hongjie; Jiang, Mingxi; Qiao, Xiujuan; Huang, Handong

2014-01-01

The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1) the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2) The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3) Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47%) of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4) We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66%) than shrub species (18%). We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure.

Baseline-dependent effect of noise-enhanced insoles on gait variability in healthy elderly walkers.

PubMed

Stephen, Damian G; Wilcox, Bethany J; Niemi, James B; Franz, Jason R; Franz, Jason; Kerrigan, Dr; Kerrigan, D Casey; D'Andrea, Susan E

2012-07-01

The purpose of this study was to determine whether providing subsensory stochastic-resonance mechanical vibration to the foot soles of elderly walkers could decrease gait variability. In a randomized double-blind controlled trial, 29 subjects engaged in treadmill walking while wearing sandals customized with three actuators capable of producing stochastic-resonance mechanical vibration embedded in each sole. For each subject, we determined a subsensory level of vibration stimulation. After a 5-min acclimation period of walking with the footwear, subjects were asked to walk on the treadmill for six trials, each 30s long. Trials were pair-wise random: in three trials, actuators provided subsensory vibration; in the other trials, they did not. Subjects wore reflective markers to track body motion. Stochastic-resonance mechanical stimulation exhibited baseline-dependent effects on spatial stride-to-stride variability in gait, slightly increasing variability in subjects with least baseline variability and providing greater reductions in variability for subjects with greater baseline variability (p<.001). Thus, applying stochastic-resonance mechanical vibrations on the plantar surface of the foot reduces gait variability for subjects with more variable gait. Stochastic-resonance mechanical vibrations may provide an effective intervention for preventing falls in healthy elderly walkers. Published by Elsevier B.V.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids

PubMed Central

Ali, S. M.; Mehmood, C. A; Khan, B.; Jawad, M.; Farid, U; Jadoon, J. K.; Ali, M.; Tareen, N. K.; Usman, S.; Majid, M.; Anwar, S. M.

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion. PMID:27314229

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

PubMed

Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

Effectiveness Testing of a Piezoelectric Energy Harvester for an Automobile Wheel Using Stochastic Resonance

PubMed Central

Zhang, Yunshun; Zheng, Rencheng; Shimono, Keisuke; Kaizuka, Tsutomu; Nakano, Kimihiko

2016-01-01

The collection of clean power from ambient vibrations is considered a promising method for energy harvesting. For the case of wheel rotation, the present study investigates the effectiveness of a piezoelectric energy harvester, with the application of stochastic resonance to optimize the efficiency of energy harvesting. It is hypothesized that when the wheel rotates at variable speeds, the energy harvester is subjected to on-road noise as ambient excitations and a tangentially acting gravity force as a periodic modulation force, which can stimulate stochastic resonance. The energy harvester was miniaturized with a bistable cantilever structure, and the on-road noise was measured for the implementation of a vibrator in an experimental setting. A validation experiment revealed that the harvesting system was optimized to capture power that was approximately 12 times that captured under only on-road noise excitation and 50 times that captured under only the periodic gravity force. Moreover, the investigation of up-sweep excitations with increasing rotational frequency confirmed that stochastic resonance is effective in optimizing the performance of the energy harvester, with a certain bandwidth of vehicle speeds. An actual-vehicle experiment validates that the prototype harvester using stochastic resonance is capable of improving power generation performance for practical tire application. PMID:27763522

Effectiveness Testing of a Piezoelectric Energy Harvester for an Automobile Wheel Using Stochastic Resonance.

PubMed

Zhang, Yunshun; Zheng, Rencheng; Shimono, Keisuke; Kaizuka, Tsutomu; Nakano, Kimihiko

2016-10-17

The collection of clean power from ambient vibrations is considered a promising method for energy harvesting. For the case of wheel rotation, the present study investigates the effectiveness of a piezoelectric energy harvester, with the application of stochastic resonance to optimize the efficiency of energy harvesting. It is hypothesized that when the wheel rotates at variable speeds, the energy harvester is subjected to on-road noise as ambient excitations and a tangentially acting gravity force as a periodic modulation force, which can stimulate stochastic resonance. The energy harvester was miniaturized with a bistable cantilever structure, and the on-road noise was measured for the implementation of a vibrator in an experimental setting. A validation experiment revealed that the harvesting system was optimized to capture power that was approximately 12 times that captured under only on-road noise excitation and 50 times that captured under only the periodic gravity force. Moreover, the investigation of up-sweep excitations with increasing rotational frequency confirmed that stochastic resonance is effective in optimizing the performance of the energy harvester, with a certain bandwidth of vehicle speeds. An actual-vehicle experiment validates that the prototype harvester using stochastic resonance is capable of improving power generation performance for practical tire application.

Off-pump versus on-pump coronary artery bypass surgery: meta-analysis and meta-regression of 13,524 patients from randomized trials.

PubMed

Sá, Michel Pompeu Barros de Oliveira; Ferraz, Paulo Ernando; Escobar, Rodrigo Renda; Martins, Wendell Nunes; Lustosa, Pablo César; Nunes, Eliobas de Oliveira; Vasconcelos, Frederico Pires; Lima, Ricardo Carvalho

2012-12-01

Most recent published meta-analysis of randomized controlled trials (RCTs) showed that off-pump coronary artery bypass graft surgery (CABG) reduces incidence of stroke by 30% compared with on-pump CABG, but showed no difference in other outcomes. New RCTs were published, indicating need of new meta-analysis to investigate pooled results adding these further studies. MEDLINE, EMBASE, CENTRAL/CCTR, SciELO, LILACS, Google Scholar and reference lists of relevant articles were searched for RCTs that compared outcomes (30-day mortality for all-cause, myocardial infarction or stroke) between off-pump versus on-pump CABG until May 2012. The principal summary measures were relative risk (RR) with 95% Confidence Interval (CI) and P values (considered statistically significant when <0.05). The RR's were combined across studies using DerSimonian-Laird random effects weighted model. Meta-analysis and meta-regression were completed using the software Comprehensive Meta-Analysis version 2 (Biostat Inc., Englewood, New Jersey, USA). Forty-seven RCTs were identified and included 13,524 patients (6,758 for off-pump and 6,766 for on-pump CABG). There was no significant difference between off-pump and on-pump CABG groups in RR for 30-day mortality or myocardial infarction, but there was difference about stroke in favor to off-pump CABG (RR 0.793, 95% CI 0.660-0.920, P=0.049). It was observed no important heterogeneity of effects about any outcome, but it was observed publication bias about outcome "stroke". Meta-regression did not demonstrate influence of female gender, number of grafts or age in outcomes. Off-pump CABG reduces the incidence of post-operative stroke by 20.7% and has no substantial effect on mortality or myocardial infarction in comparison to on-pump CABG. Patient gender, number of grafts performed and age do not seem to explain the effect of off-pump CABG on mortality, myocardial infarction or stroke, respectively.

Cost-effectiveness of insulin pumps compared with multiple daily injections both provided with structured education for adults with type 1 diabetes: a health economic analysis of the Relative Effectiveness of Pumps over Structured Education (REPOSE) randomised controlled trial.

PubMed

Pollard, Daniel John; Brennan, Alan; Dixon, Simon; Waugh, Norman; Elliott, Jackie; Heller, Simon; Lee, Ellen; Campbell, Michael; Basarir, Hasan; White, David

2018-04-07

To assess the long-term cost-effectiveness of insulin pumps and Dose Adjustment for Normal Eating (pumps+DAFNE) compared with multiple daily insulin injections and DAFNE (MDI+DAFNE) for adults with type 1 diabetes mellitus (T1DM) in the UK. We undertook a cost-utility analysis using the Sheffield Type 1 Diabetes Policy Model and data from the Relative Effectiveness of Pumps over Structured Education (REPOSE) trial to estimate the lifetime incidence of diabetic complications, intervention-based resource use and associated effects on costs and quality-adjusted life years (QALYs). All economic analyses took a National Health Service and personal social services perspective and discounted costs and QALYs at 3.5% per annum. A probabilistic sensitivity analysis was performed on the base case. Further uncertainties in the cost of pumps and the evidence used to inform the model were explored using scenario analyses. Eight diabetes centres in England and Scotland. Adults with T1DM who were eligible to receive a structured education course and did not have a strong clinical indication or a preference for a pump. Pumps+DAFNE. MDI+DAFNE. Incremental costs, incremental QALYs gained and incremental cost-effectiveness ratios (ICERs). Compared with MDI+DAFNE, pumps+DAFNE was associated with an incremental discounted lifetime cost of +£18 853 (95% CI £6175 to £31 645) and a gain in discounted lifetime QALYs of +0.13 (95% CI -0.70 to +0.96). The base case mean ICER was £142 195 per QALY gained. The probability of pump+DAFNE being cost-effective using a cost-effectiveness threshold of £20 000 per QALY gained was 14.0%. All scenario and subgroup analyses examined indicated that the ICER was unlikely to fall below £30 000 per QALY gained. Our analysis of the REPOSE data suggests that routine use of pumps in adults without an immediate clinical need for a pump, as identified by National Institute for Health and Care Excellence, would not be cost-effective. ISRCTN61215213. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Establishing a beachhead: A stochastic population model with an Allee effect applied to species invasion

USGS Publications Warehouse

Ackleh, A.S.; Allen, L.J.S.; Carter, J.

2007-01-01

We formulated a spatially explicit stochastic population model with an Allee effect in order to explore how invasive species may become established. In our model, we varied the degree of migration between local populations and used an Allee effect with variable birth and death rates. Because of the stochastic component, population sizes below the Allee effect threshold may still have a positive probability for successful invasion. The larger the network of populations, the greater the probability of an invasion occurring when initial population sizes are close to or above the Allee threshold. Furthermore, if migration rates are low, one or more than one patch may be successfully invaded, while if migration rates are high all patches are invaded. ?? 2007 Elsevier Inc. All rights reserved.

Hybrid approaches for multiple-species stochastic reaction–diffusion models

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

Spill, Fabian, E-mail: fspill@bu.edu; Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139; Guerrero, Pilar

2015-10-15

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and smallmore » in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.« less

Genetic Variation in the Nuclear and Organellar Genomes Modulates Stochastic Variation in the Metabolome, Growth, and Defense

PubMed Central

Joseph, Bindu; Corwin, Jason A.; Kliebenstein, Daniel J.

2015-01-01

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype. PMID:25569687

Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense.

PubMed

Joseph, Bindu; Corwin, Jason A; Kliebenstein, Daniel J

2015-01-01

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype.

A Rigorous Temperature-Dependent Stochastic Modelling and Testing for MEMS-Based Inertial Sensor Errors.

PubMed

El-Diasty, Mohammed; Pagiatakis, Spiros

2009-01-01

In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM) models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times). It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF). It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at -40 °C, -20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Memory effects on stochastic resonance

NASA Astrophysics Data System (ADS)

Neiman, Alexander; Sung, Wokyung

1996-02-01

We study the phenomenon of stochastic resonance (SR) in a bistable system with internal colored noise. In this situation the system possesses time-dependent memory friction connected with noise via the fluctuation-dissipation theorem, so that in the absence of periodic driving the system approaches the thermodynamic equilibrium state. For this non-Markovian case we find that memory usually suppresses stochastic resonance. However, for a large memory time SR can be enhanced by the memory.

Chemical event chain model of coupled genetic oscillators.

PubMed

Jörg, David J; Morelli, Luis G; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Stochastic maps, continuous approximation, and stable distribution

NASA Astrophysics Data System (ADS)

Kessler, David A.; Burov, Stanislav

2017-10-01

A continuous approximation framework for general nonlinear stochastic as well as deterministic discrete maps is developed. For the stochastic map with uncorelated Gaussian noise, by successively applying the Itô lemma, we obtain a Langevin type of equation. Specifically, we show how nonlinear maps give rise to a Langevin description that involves multiplicative noise. The multiplicative nature of the noise induces an additional effective force, not present in the absence of noise. We further exploit the continuum description and provide an explicit formula for the stable distribution of the stochastic map and conditions for its existence. Our results are in good agreement with numerical simulations of several maps.

Chemical event chain model of coupled genetic oscillators

NASA Astrophysics Data System (ADS)

Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

On stochastic control and optimal measurement strategies. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Kramer, L. C.

1971-01-01

The control of stochastic dynamic systems is studied with particular emphasis on those which influence the quality or nature of the measurements which are made to effect control. Four main areas are discussed: (1) the meaning of stochastic optimality and the means by which dynamic programming may be applied to solve a combined control/measurement problem; (2) a technique by which it is possible to apply deterministic methods, specifically the minimum principle, to the study of stochastic problems; (3) the methods described are applied to linear systems with Gaussian disturbances to study the structure of the resulting control system; and (4) several applications are considered.

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

PubMed

Lei, Youming; Zheng, Fan

2016-12-01

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

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

Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes

NASA Astrophysics Data System (ADS)

Liyanagedera, Chamika M.; Sengupta, Abhronil; Jaiswal, Akhilesh; Roy, Kaushik

2017-12-01

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-efficient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity of nanoelectronic synaptic or neural components to perform learning or inference. However, there has been limited analysis on the scaling effect of stochastic spin devices and its impact on the operation of such stochastic networks at the system level. This work attempts to explore the design space and analyze the performance of nanomagnet-based stochastic neuromorphic computing architectures for magnets with different barrier heights. We illustrate how the underlying network architecture must be modified to account for the random telegraphic switching behavior displayed by magnets with low barrier heights as they are scaled into the superparamagnetic regime. We perform a device-to-system-level analysis on a deep neural-network architecture for a digit-recognition problem on the MNIST data set.

Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

NASA Technical Reports Server (NTRS)

Williams Colin P.

1999-01-01

Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

Influence of the ac-Stark shift on GPS atomic clock timekeeping

NASA Astrophysics Data System (ADS)

Formichella, V.; Camparo, J.; Tavella, P.

2017-01-01

The ac-Stark shift (or light shift) is a fundamental aspect of the field/atom interaction arising from virtual transitions between atomic states, and as Alfred Kastler noted, it is the real-photon counterpart of the Lamb shift. In the rubidium atomic frequency standards (RAFS) flying on Global Positioning System (GPS) satellites, it plays an important role as one of the major perturbations defining the RAFS' frequency: the rf-discharge lamp in the RAFS creates an atomic signal via optical pumping and simultaneously perturbs the atoms' ground-state hyperfine splitting via the light shift. Though the significance of the light shift has been known for decades, to date there has been no concrete evidence that it limits the performance of the high-quality RAFS flying on GPS satellites. Here, we show that the long-term frequency stability of GPS RAFS is primarily determined by the light shift as a consequence of stochastic jumps in lamplight intensity. Our results suggest three paths forward for improved GPS system timekeeping: (1) reduce the light-shift coefficient of the RAFS by careful control of the lamp's spectrum; (2) operate the lamp under conditions where lamplight jumps are not so pronounced; and (3) employ a light source for optical pumping that does not suffer pronounced light jumps (e.g., a diode laser).

Stationary responses of a Rayleigh viscoelastic system with zero barrier impacts under external random excitation.

PubMed

Wang, Deli; Xu, Wei; Zhao, Xiangrong

2016-03-01

This paper aims to deal with the stationary responses of a Rayleigh viscoelastic system with zero barrier impacts under external random excitation. First, the original stochastic viscoelastic system is converted to an equivalent stochastic system without viscoelastic terms by approximately adding the equivalent stiffness and damping. Relying on the means of non-smooth transformation of state variables, the above system is replaced by a new system without an impact term. Then, the stationary probability density functions of the system are observed analytically through stochastic averaging method. By considering the effects of the biquadratic nonlinear damping coefficient and the noise intensity on the system responses, the effectiveness of the theoretical method is tested by comparing the analytical results with those generated from Monte Carlo simulations. Additionally, it does deserve attention that some system parameters can induce the occurrence of stochastic P-bifurcation.

Relativistic analysis of stochastic kinematics

NASA Astrophysics Data System (ADS)

Giona, Massimiliano

2017-10-01

The relativistic analysis of stochastic kinematics is developed in order to determine the transformation of the effective diffusivity tensor in inertial frames. Poisson-Kac stochastic processes are initially considered. For one-dimensional spatial models, the effective diffusion coefficient measured in a frame Σ moving with velocity w with respect to the rest frame of the stochastic process is inversely proportional to the third power of the Lorentz factor γ (w ) =(1-w2/c2) -1 /2 . Subsequently, higher-dimensional processes are analyzed and it is shown that the diffusivity tensor in a moving frame becomes nonisotropic: The diffusivities parallel and orthogonal to the velocity of the moving frame scale differently with respect to γ (w ) . The analysis of discrete space-time diffusion processes permits one to obtain a general transformation theory of the tensor diffusivity, confirmed by several different simulation experiments. Several implications of the theory are also addressed and discussed.

Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells.

PubMed

Aisopou, Angeliki; Binning, Philip J; Albrechtsen, Hans-Jørgen; Bjerg, Poul L

2015-01-01

This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly affect the pesticide breakthrough time and maximum concentration at the well. The effect of the pumping rate on the pesticide concentration depends on the hydrogeology of the aquifer; in a layered aquifer, a high pumping rate resulted in a considerably different breakthrough than a low pumping rate, while in an aquifer with a stream the effect of the pumping rate was insignificant. Pesticide application history and properties have also a great impact on the effect of the pumping rate on the concentration at the well. The findings of the study show that variable pumping rates can generate temporal variability in the concentration at the well, which helps understanding the results of groundwater monitoring programs. The results are used to provide guidance on the design of pumping and regulatory changes for the long-term supply of safe groundwater. The fate of selected pesticides is examined, for example, if the application of bentazone in a region with a layered aquifer stops today, the concentration at the well can continue to increase for 20 years if a low pumping rate is applied. This study concludes that because of the rapid response of the pesticide concentration at the drinking water well due to changes in pumping, wellhead management is important for managing pesticide concentrations. © 2014, National GroundWater Association.

The Allee effect, stochastic dynamics and the eradication of alien species

Treesearch

Andrew Liebhold; Jordi Bascompte; Jordi Bascompte

2003-01-01

Previous treatments of the population biology of eradication have assumed that eradication can only be achieved via 100% removal of the alien population. However, this assumption appears to be incorrect because stochastic dynamics and the Allee effect typically contribute to the extinction of very low-density populations. We explore a model that incorporates Allee...

Finite-time H∞ filtering for non-linear stochastic systems

NASA Astrophysics Data System (ADS)

Hou, Mingzhe; Deng, Zongquan; Duan, Guangren

2016-09-01

This paper describes the robust H∞ filtering analysis and the synthesis of general non-linear stochastic systems with finite settling time. We assume that the system dynamic is modelled by Itô-type stochastic differential equations of which the state and the measurement are corrupted by state-dependent noises and exogenous disturbances. A sufficient condition for non-linear stochastic systems to have the finite-time H∞ performance with gain less than or equal to a prescribed positive number is established in terms of a certain Hamilton-Jacobi inequality. Based on this result, the existence of a finite-time H∞ filter is given for the general non-linear stochastic system by a second-order non-linear partial differential inequality, and the filter can be obtained by solving this inequality. The effectiveness of the obtained result is illustrated by a numerical example.

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.

Refractory pulse counting processes in stochastic neural computers.

PubMed

McNeill, Dean K; Card, Howard C

2005-03-01

This letter quantitiatively investigates the effect of a temporary refractory period or dead time in the ability of a stochastic Bernoulli processor to record subsequent pulse events, following the arrival of a pulse. These effects can arise in either the input detectors of a stochastic neural network or in subsequent processing. A transient period is observed, which increases with both the dead time and the Bernoulli probability of the dead-time free system, during which the system reaches equilibrium. Unless the Bernoulli probability is small compared to the inverse of the dead time, the mean and variance of the pulse count distributions are both appreciably reduced.

Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects

PubMed Central

Baumann, Hendrik; Sandmann, Werner

2016-01-01

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity. PMID:27010993

Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects.

PubMed

Baumann, Hendrik; Sandmann, Werner

2016-01-01

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity.

Experimental and Numerical Analysis of Performance Discontinuity of a Pump-Turbine under Pumping Mode

NASA Astrophysics Data System (ADS)

Zhang, X.; Burgstaller, R.; Lai, X.; Gehrer, A.; Kefalas, A.; Pang, Y.

2016-11-01

The performance discontinuity of a pump-turbine under pumping mode is harmful to stable operation of units in hydropower station. In this paper, the performance discontinuity phenomenon of the pump-turbine was studied by means of experiment and numerical simulation. In the experiment, characteristics of the pump-turbine with different diffuser vane openings were tested in order to investigate the effect of pumping casing to the performance discontinuity. While other effects such as flow separation and rotating stall are known to have an effect on the discontinuity, the present studied test cases show that prerotation is the dominating effect for the instability, positions of the positive slope of characteristics are almost the same in different diffuser vane opening conditions. The impeller has principal effect to the performance discontinuity. In the numerical simulation, CFD analysis of tested pump-turbine has been done with k-ω and SST turbulence model. It is found that the position of performance curve discontinuity corresponds to flow recirculation at impeller inlet. Flow recirculation at impeller inlet is the cause of the discontinuity of characteristics curve. It is also found that the operating condition of occurrence of flow recirculation at impeller inlet is misestimated with k-ω and SST turbulence model. Furthermore, the original SST model has been modified. We predict the occurrence position of flow recirculation at impeller inlet correctly with the modified SST turbulence model, and it also can improve the prediction accuracy of the pump- turbine performance at the same time.

Operational adaptability evaluation index system of pumped storage in UHV receiving-end grids

NASA Astrophysics Data System (ADS)

Yuan, Bo; Zong, Jin; Feng, Junshu

2017-01-01

Pumped storage is an effective solution to deal with the emergency reserve shortage, renewable energy accommodating and peak-shaving problems in ultra-high voltage (UHV) transmission receiving-end grids. However, governments and public opinion in China tend to evaluate the operational effectiveness of pumped storage using annual utilization hour, which may result in unreasonable and unnecessary dispatch of pumped storage. This paper built an operational adaptability evaluation index system for pumped storage in UHV-receiving end grids from three aspects: security insurance, peak-shaving and renewable energy accommodating, which can provide a comprehensive and objective way to evaluate the operational performance of a pumped storage station.

Stochastic description of quantum Brownian dynamics

NASA Astrophysics Data System (ADS)

Yan, Yun-An; Shao, Jiushu

2016-08-01

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

Stochastic theory of fatigue corrosion

NASA Astrophysics Data System (ADS)

Hu, Haiyun

1999-10-01

A stochastic theory of corrosion has been constructed. The stochastic equations are described giving the transportation corrosion rate and fluctuation corrosion coefficient. In addition the pit diameter distribution function, the average pit diameter and the most probable pit diameter including other related empirical formula have been derived. In order to clarify the effect of stress range on the initiation and growth behaviour of pitting corrosion, round smooth specimen were tested under cyclic loading in 3.5% NaCl solution.

Desynchronization of stochastically synchronized chemical oscillators

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

Snari, Razan; Tinsley, Mark R., E-mail: mark.tinsley@mail.wvu.edu, E-mail: kshowalt@wvu.edu; Faramarzi, Sadegh

Experimental and theoretical studies are presented on the design of perturbations that enhance desynchronization in populations of oscillators that are synchronized by periodic entrainment. A phase reduction approach is used to determine optimal perturbation timing based upon experimentally measured phase response curves. The effectiveness of the perturbation waveforms is tested experimentally in populations of periodically and stochastically synchronized chemical oscillators. The relevance of the approach to therapeutic methods for disrupting phase coherence in groups of stochastically synchronized neuronal oscillators is discussed.

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.

Inverse modeling of hydraulic tests in fractured crystalline rock based on a transition probability geostatistical approach

NASA Astrophysics Data System (ADS)

Blessent, Daniela; Therrien, René; Lemieux, Jean-Michel

2011-12-01

This paper presents numerical simulations of a series of hydraulic interference tests conducted in crystalline bedrock at Olkiluoto (Finland), a potential site for the disposal of the Finnish high-level nuclear waste. The tests are in a block of crystalline bedrock of about 0.03 km3 that contains low-transmissivity fractures. Fracture density, orientation, and fracture transmissivity are estimated from Posiva Flow Log (PFL) measurements in boreholes drilled in the rock block. On the basis of those data, a geostatistical approach relying on a transitional probability and Markov chain models is used to define a conceptual model based on stochastic fractured rock facies. Four facies are defined, from sparsely fractured bedrock to highly fractured bedrock. Using this conceptual model, three-dimensional groundwater flow is then simulated to reproduce interference pumping tests in either open or packed-off boreholes. Hydraulic conductivities of the fracture facies are estimated through automatic calibration using either hydraulic heads or both hydraulic heads and PFL flow rates as targets for calibration. The latter option produces a narrower confidence interval for the calibrated hydraulic conductivities, therefore reducing the associated uncertainty and demonstrating the usefulness of the measured PFL flow rates. Furthermore, the stochastic facies conceptual model is a suitable alternative to discrete fracture network models to simulate fluid flow in fractured geological media.

Internal additive noise effects in stochastic resonance using organic field effect transistor

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

Suzuki, Yoshiharu; Asakawa, Naoki; Matsubara, Kiyohiko

Stochastic resonance phenomenon was observed in organic field effect transistor using poly(3-hexylthiophene), which enhances performance of signal transmission with application of noise. The enhancement of correlation coefficient between the input and output signals was low, and the variation of correlation coefficient was not remarkable with respect to the intensity of external noise, which was due to the existence of internal additive noise following the nonlinear threshold response. In other words, internal additive noise plays a positive role on the capability of approximately constant signal transmission regardless of noise intensity, which can be said “homeostatic” behavior or “noise robustness” against externalmore » noise. Furthermore, internal additive noise causes emergence of the stochastic resonance effect even on the threshold unit without internal additive noise on which the correlation coefficient usually decreases monotonically.« less

[Study on spectral gain characterization of FWM processes with multi-frequency pumps in photonic crystal fiber].

PubMed

Hui, Zhan-Qiang

2011-10-01

Spectral gain induced by four-wave-mixing with multi-frequency pump was investigated by exploiting the data signal and continue lights co-propagation in dispersion flattened high nonlinear photonic crystal fiber (PCF). The effects of wavelength drift of pump lights, polarization state of orthogonal or parallel of pump lights, polarization mismatch of signal light versus orthogonal pump lights, total power of signal and probe light on the spectrum gain were analyzed. The results show that good FWM gain effects with multi-frequency pump can be obtained in 36.4 nm wavelength range when power ratio of pump to probe light is appropriate and with identical polarization. Furthermore, the gain of FWM with multi-frequency pump is very sensitive to polarization fluctuation and the different idle waves obtain different gain with the variation in signal polarization state. Moreover, the impact of pump numbers was investigated. The obtained results would be helpful for further research on ultrahigh-speed all optical signal processing devices exploiting the FWM with multi-frequency pump in PCF for future photonics network.

Slow and fast light via SBS in optical fibers for short pulses and broadband pump

NASA Astrophysics Data System (ADS)

Kalosha, V. P.; Chen, Liang; Bao, Xiaoyi

2006-12-01

Slow-light effect via stimulated Brillouin scattering (SBS) in single-mode optical fibers was considered for short probe pulses of nanosecond duration relevant to Gb/s data streams. Unlike recent estimations of delay versus pump based on steady-state small-signal approximation we have used numerical solution of three-wave equations describing SBS for a realistic fiber length. Both regimes of small signal and pump depletion (gain saturation) were considered. The physical origin of Stokes pulse distortion is revealed which is related to excitation of long-living acoustic field behind the pulse and prevents effective delay control by pump power increase at cw pumping. We have shown different slope of the gain-dependent delay for different pulse durations. Spectrally broadened pumping by multiple cw components, frequency-modulated pump and pulse train were studied for short pulses which allow to obtain large delay and suppress pulse distortion. In the pump-depletion regime of pumping by pulse train, both pulse delay and distortion decrease with increasing pump, and the pulse achieves advancement.

Transient enhancement of magnetization damping in CoFeB film via pulsed laser excitation

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

Liu, Bo; Ruan, Xuezhong, E-mail: xzruan@nju.edu.cn, E-mail: ybxu@nju.edu.cn; Wu, Zhenyao

2016-07-25

Laser-induced spin dynamics of in-plane magnetized CoFeB films has been studied by using time-resolved magneto-optical Kerr effect measurements. While the effective demagnetization field shows little dependence on the pump laser fluence, the intrinsic damping constant has been found to be increased from 0.008 to 0.076 with the increase in the pump fluence from 2 mJ/cm{sup 2} to 20 mJ/cm{sup 2}. This sharp enhancement has been shown to be transient and ascribed to the heating effect induced by the pump laser excitation, as the damping constant is almost unchanged when the pump-probe measurements are performed at a fixed pump fluence ofmore » 5 mJ/cm{sup 2} after irradiation by high power pump pulses.« less

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.

Parameter-induced stochastic resonance with a periodic signal

NASA Astrophysics Data System (ADS)

Li, Jian-Long; Xu, Bo-Hou

2006-12-01

In this paper conventional stochastic resonance (CSR) is realized by adding the noise intensity. This demonstrates that tuning the system parameters with fixed noise can make the noise play a constructive role and realize parameter-induced stochastic resonance (PSR). PSR can be interpreted as changing the intrinsic characteristic of the dynamical system to yield the cooperative effect between the stochastic-subjected nonlinear system and the external periodic force. This can be realized at any noise intensity, which greatly differs from CSR that is realized under the condition of the initial noise intensity not greater than the resonance level. Moreover, it is proved that PSR is different from the optimization of system parameters.

Stochastic optimization for the detection of changes in maternal heart rate kinetics during pregnancy

NASA Astrophysics Data System (ADS)

Zakynthinaki, M. S.; Barakat, R. O.; Cordente Martínez, C. A.; Sampedro Molinuevo, J.

2011-03-01

The stochastic optimization method ALOPEX IV has been successfully applied to the problem of detecting possible changes in the maternal heart rate kinetics during pregnancy. For this reason, maternal heart rate data were recorded before, during and after gestation, during sessions of exercises of constant mild intensity; ALOPEX IV stochastic optimization was used to calculate the parameter values that optimally fit a dynamical systems model to the experimental data. The results not only demonstrate the effectiveness of ALOPEX IV stochastic optimization, but also have important implications in the area of exercise physiology, as they reveal important changes in the maternal cardiovascular dynamics, as a result of pregnancy.

Modeling and Computation of Transboundary Industrial Pollution with Emission Permits Trading by Stochastic Differential Game

PubMed Central

2015-01-01

Transboundary industrial pollution requires international actions to control its formation and effects. In this paper, we present a stochastic differential game to model the transboundary industrial pollution problems with emission permits trading. More generally, the process of emission permits price is assumed to be stochastic and to follow a geometric Brownian motion (GBM). We make use of stochastic optimal control theory to derive the system of Hamilton-Jacobi-Bellman (HJB) equations satisfied by the value functions for the cooperative and the noncooperative games, respectively, and then propose a so-called fitted finite volume method to solve it. The efficiency and the usefulness of this method are illustrated by the numerical experiments. The two regions’ cooperative and noncooperative optimal emission paths, which maximize the regions’ discounted streams of the net revenues, together with the value functions, are obtained. Additionally, we can also obtain the threshold conditions for the two regions to decide whether they cooperate or not in different cases. The effects of parameters in the established model on the results have been also examined. All the results demonstrate that the stochastic emission permits prices can motivate the players to make more flexible strategic decisions in the games. PMID:26402322

Modeling and Computation of Transboundary Industrial Pollution with Emission Permits Trading by Stochastic Differential Game.

PubMed

Chang, Shuhua; Wang, Xinyu; Wang, Zheng

2015-01-01

Transboundary industrial pollution requires international actions to control its formation and effects. In this paper, we present a stochastic differential game to model the transboundary industrial pollution problems with emission permits trading. More generally, the process of emission permits price is assumed to be stochastic and to follow a geometric Brownian motion (GBM). We make use of stochastic optimal control theory to derive the system of Hamilton-Jacobi-Bellman (HJB) equations satisfied by the value functions for the cooperative and the noncooperative games, respectively, and then propose a so-called fitted finite volume method to solve it. The efficiency and the usefulness of this method are illustrated by the numerical experiments. The two regions' cooperative and noncooperative optimal emission paths, which maximize the regions' discounted streams of the net revenues, together with the value functions, are obtained. Additionally, we can also obtain the threshold conditions for the two regions to decide whether they cooperate or not in different cases. The effects of parameters in the established model on the results have been also examined. All the results demonstrate that the stochastic emission permits prices can motivate the players to make more flexible strategic decisions in the games.

Effective long wavelength scalar dynamics in de Sitter

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

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

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

Stochastic effects in a thermochemical system with Newtonian heat exchange.

PubMed

Nowakowski, B; Lemarchand, A

2001-12-01

We develop a mesoscopic description of stochastic effects in the Newtonian heat exchange between a diluted gas system and a thermostat. We explicitly study the homogeneous Semenov model involving a thermochemical reaction and neglecting consumption of reactants. The master equation includes a transition rate for the thermal transfer process, which is derived on the basis of the statistics for inelastic collisions between gas particles and walls of the thermostat. The main assumption is that the perturbation of the Maxwellian particle velocity distribution can be neglected. The transition function for the thermal process admits a continuous spectrum of temperature changes, and consequently, the master equation has a complicated integro-differential form. We perform Monte Carlo simulations based on this equation to study the stochastic effects in the Semenov system in the explosive regime. The dispersion of ignition times is calculated as a function of system size. For sufficiently small systems, the probability distribution of temperature displays transient bimodality during the ignition period. The results of the stochastic description are successfully compared with those of direct simulations of microscopic particle dynamics.

Simulation of groundwater and surface-water interaction and effects of pumping in a complex glacial-sediment aquifer, east central Massachusetts

USGS Publications Warehouse

Eggleston, Jack R.; Carlson, Carl S.; Fairchild, Gillian M.; Zarriello, Phillip J.

2012-01-01

The effects of groundwater pumping on surface-water features were evaluated by use of a numerical groundwater model developed for a complex glacial-sediment aquifer in northeastern Framingham, Massachusetts, and parts of surrounding towns. The aquifer is composed of sand, gravel, silt, and clay glacial-fill sediments up to 270 feet thick over an irregular fractured bedrock surface. Surface-water bodies, including Cochituate Brook, the Sudbury River, Lake Cochituate, Dudley Pond, and adjoining wetlands, are in hydraulic connection with the aquifer and can be affected by groundwater withdrawals. Groundwater and surface-water interaction was simulated with MODFLOW-NWT under current conditions and a variety of hypothetical pumping conditions. Simulations of hypothetical pumping at reactivated water supply wells indicate that captured groundwater would decrease baseflow to the Sudbury River and induce recharge from Lake Cochituate. Under constant (steady-state) pumping, induced groundwater recharge from Lake Cochituate was equal to about 32 percent of the simulated pumping rate, and flow downstream in the Sudbury River decreased at the same rate as pumping. However, surface water responded quickly to pumping stresses. When pumping was simulated for 1 month and then stopped, streamflow depletions decreased by about 80 percent within 2 months and by about 90 percent within about 4 months. The fast surface water response to groundwater pumping offers the potential to substantially reduce streamflow depletions during periods of low flow, which are of greatest concern to the ecological integrity of the river. Results indicate that streamflow depletion during September, typically the month of lowest flow, can be reduced by 29 percent by lowering the maximum pumping rates to near zero during September. Lowering pumping rates for 3 months (July through September) reduces streamflow depletion during September by 79 percent as compared to constant pumping. These results demonstrate that a seasonal or streamflow-based groundwater pumping schedule can reduce the effects of pumping during periods of low flow.

Environmental Effects on Fatigue Crack Growth in High Performance Aluminum Alloys

DTIC Science & Technology

2009-03-13

tested for leaks to a rate of 2x 10൒ cm3/s with helium. All devices connected to the chamber, including pumps , gages and valves, are ultra-high- vacuum ...Pfeiffer TMU-262P), backed by a 5 L/s scroll pump (ULVAC DIS-250). This pump combination eliminates the possibility of contamination by pumping fluid used...both pumps are connected directly to the vacuum chamber to achieve optimum pump -down speeds. Pumping down the chamber is further facilitated by use of

Brownian motion surviving in the unstable cubic potential and the role of Maxwell's demon

NASA Astrophysics Data System (ADS)

Ornigotti, Luca; Ryabov, Artem; Holubec, Viktor; Filip, Radim

2018-03-01

The trajectories of an overdamped particle in a highly unstable potential diverge so rapidly, that the variance of position grows much faster than its mean. A description of the dynamics by moments is therefore not informative. Instead, we propose and analyze local directly measurable characteristics, which overcome this limitation. We discuss the most probable particle position (position of the maximum of the probability density) and the local uncertainty in an unstable cubic potential, V (x ) ˜x3 , both in the transient regime and in the long-time limit. The maximum shifts against the acting force as a function of time and temperature. Simultaneously, the local uncertainty does not increase faster than the observable shift. In the long-time limit, the probability density naturally attains a quasistationary form. We interpret this process as a stabilization via the measurement-feedback mechanism, the Maxwell demon, which works as an entropy pump. The rules for measurement and feedback naturally arise from the basic properties of the unstable dynamics. All reported effects are inherent in any unstable system. Their detailed understanding will stimulate the development of stochastic engines and amplifiers and, later, their quantum counterparts.

Gyro-effect stabilizes unstable permanent maglev centrifugal pump.

PubMed

Qian, Kun-Xi

2007-03-01

According to Earnshaw's Theorem (1839), the passive maglev cannot achieve stable equilibrium and thus an extra coil is needed to make the rotor electrically levitated in a heart pump. The author had developed a permanent maglev centrifugal pump utilizing only passive magnetic bearings, to keep the advantages but to avoid the disadvantages of the electric maglev pumps. The equilibrium stability was achieved by use of so-called "gyro-effect": a rotating body with certain high speed can maintain its rotation stably. This pump consisted of a rotor (driven magnets and an impeller), and a stator with motor coil and pump housing. Two passive magnetic bearings between rotor and stator were devised to counteract the attractive force between the motor coil iron core and the rotor driven magnets. Bench testing with saline demonstrated a levitated rotor under preconditions of higher than 3,250 rpm rotation and more than 1 l/min pumping flow. Rotor levitation was demonstrated by 4 Hall sensors on the stator, with evidence of reduced maximal eccentric distance from 0.15 mm to 0.07 mm. The maximal rotor vibration amplitude was 0.06 mm in a gap of 0.15 mm between rotor and stator. It concluded that Gyro-effect can help passive maglev bearings to achieve stabilization of permanent maglev pump; and that high flow rate indicates good hydraulic property of the pump, which helps also the stability of passive maglev pump.

A Stochastic Tick-Borne Disease Model: Exploring the Probability of Pathogen Persistence.

PubMed

Maliyoni, Milliward; Chirove, Faraimunashe; Gaff, Holly D; Govinder, Keshlan S

2017-09-01

We formulate and analyse a stochastic epidemic model for the transmission dynamics of a tick-borne disease in a single population using a continuous-time Markov chain approach. The stochastic model is based on an existing deterministic metapopulation tick-borne disease model. We compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in tick-borne disease dynamics. The probability of disease extinction and that of a major outbreak are computed and approximated using the multitype Galton-Watson branching process and numerical simulations, respectively. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that a disease outbreak is more likely if the disease is introduced by infected deer as opposed to infected ticks. These insights demonstrate the importance of host movement in the expansion of tick-borne diseases into new geographic areas.

Improved Stability and Stabilization Results for Stochastic Synchronization of Continuous-Time Semi-Markovian Jump Neural Networks With Time-Varying Delay.

PubMed

Wei, Yanling; Park, Ju H; Karimi, Hamid Reza; Tian, Yu-Chu; Jung, Hoyoul; Yanling Wei; Park, Ju H; Karimi, Hamid Reza; Yu-Chu Tian; Hoyoul Jung; Tian, Yu-Chu; Wei, Yanling; Jung, Hoyoul; Karimi, Hamid Reza; Park, Ju H

2018-06-01

Continuous-time semi-Markovian jump neural networks (semi-MJNNs) are those MJNNs whose transition rates are not constant but depend on the random sojourn time. Addressing stochastic synchronization of semi-MJNNs with time-varying delay, an improved stochastic stability criterion is derived in this paper to guarantee stochastic synchronization of the response systems with the drive systems. This is achieved through constructing a semi-Markovian Lyapunov-Krasovskii functional together as well as making use of a novel integral inequality and the characteristics of cumulative distribution functions. Then, with a linearization procedure, controller synthesis is carried out for stochastic synchronization of the drive-response systems. The desired state-feedback controller gains can be determined by solving a linear matrix inequality-based optimization problem. Simulation studies are carried out to demonstrate the effectiveness and less conservatism of the presented approach.

Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

PubMed

Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

2016-08-01

In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.

PubMed

Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir

2018-03-01

This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

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.

STOCHASTIC OPTICS: A SCATTERING MITIGATION FRAMEWORK FOR RADIO INTERFEROMETRIC IMAGING

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

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

2016-12-10

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

Stochastic Simulation Tool for Aerospace Structural Analysis

NASA Technical Reports Server (NTRS)

Knight, Norman F.; Moore, David F.

2006-01-01

Stochastic simulation refers to incorporating the effects of design tolerances and uncertainties into the design analysis model and then determining their influence on the design. A high-level evaluation of one such stochastic simulation tool, the MSC.Robust Design tool by MSC.Software Corporation, has been conducted. This stochastic simulation tool provides structural analysts with a tool to interrogate their structural design based on their mathematical description of the design problem using finite element analysis methods. This tool leverages the analyst's prior investment in finite element model development of a particular design. The original finite element model is treated as the baseline structural analysis model for the stochastic simulations that are to be performed. A Monte Carlo approach is used by MSC.Robust Design to determine the effects of scatter in design input variables on response output parameters. The tool was not designed to provide a probabilistic assessment, but to assist engineers in understanding cause and effect. It is driven by a graphical-user interface and retains the engineer-in-the-loop strategy for design evaluation and improvement. The application problem for the evaluation is chosen to be a two-dimensional shell finite element model of a Space Shuttle wing leading-edge panel under re-entry aerodynamic loading. MSC.Robust Design adds value to the analysis effort by rapidly being able to identify design input variables whose variability causes the most influence in response output parameters.

Simulation of quantum dynamics based on the quantum stochastic differential equation.

PubMed

Li, Ming

2013-01-01

The quantum stochastic differential equation derived from the Lindblad form quantum master equation is investigated. The general formulation in terms of environment operators representing the quantum state diffusion is given. The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. The effectiveness and superiority of the algorithm are verified by the performance analysis of the accuracy and the computational cost in comparison with the classical Runge-Kutta algorithm.

Pricing foreign equity option with stochastic volatility

NASA Astrophysics Data System (ADS)

Sun, Qi; Xu, Weidong

2015-11-01

In this paper we propose a general foreign equity option pricing framework that unifies the vast foreign equity option pricing literature and incorporates the stochastic volatility into foreign equity option pricing. Under our framework, the time-changed Lévy processes are used to model the underlying assets price of foreign equity option and the closed form pricing formula is obtained through the use of characteristic function methodology. Numerical tests indicate that stochastic volatility has a dramatic effect on the foreign equity option prices.

46 CFR 28.820 - Fire pumps, fire mains, fire hydrants, and fire hoses.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 1 2014-10-01 2014-10-01 false Fire pumps, fire mains, fire hydrants, and fire hoses... REQUIREMENTS FOR COMMERCIAL FISHING INDUSTRY VESSELS Aleutian Trade Act Vessels § 28.820 Fire pumps, fire mains... pump connected to a fixed piping system. This pump must be capable of delivering an effective stream of...

46 CFR 28.820 - Fire pumps, fire mains, fire hydrants, and fire hoses.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Fire pumps, fire mains, fire hydrants, and fire hoses... REQUIREMENTS FOR COMMERCIAL FISHING INDUSTRY VESSELS Aleutian Trade Act Vessels § 28.820 Fire pumps, fire mains... pump connected to a fixed piping system. This pump must be capable of delivering an effective stream of...

46 CFR 28.820 - Fire pumps, fire mains, fire hydrants, and fire hoses.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Fire pumps, fire mains, fire hydrants, and fire hoses... REQUIREMENTS FOR COMMERCIAL FISHING INDUSTRY VESSELS Aleutian Trade Act Vessels § 28.820 Fire pumps, fire mains... pump connected to a fixed piping system. This pump must be capable of delivering an effective stream of...

46 CFR 28.820 - Fire pumps, fire mains, fire hydrants, and fire hoses.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 1 2013-10-01 2013-10-01 false Fire pumps, fire mains, fire hydrants, and fire hoses... REQUIREMENTS FOR COMMERCIAL FISHING INDUSTRY VESSELS Aleutian Trade Act Vessels § 28.820 Fire pumps, fire mains... pump connected to a fixed piping system. This pump must be capable of delivering an effective stream of...

Comparative analysis of the effectiveness of three immunization strategies in controlling disease outbreaks in realistic social networks.

PubMed

Xu, Zhijing; Zu, Zhenghu; Zheng, Tao; Zhang, Wendou; Xu, Qing; Liu, Jinjie

2014-01-01

The high incidence of emerging infectious diseases has highlighted the importance of effective immunization strategies, especially the stochastic algorithms based on local available network information. Present stochastic strategies are mainly evaluated based on classical network models, such as scale-free networks and small-world networks, and thus are insufficient. Three frequently referred stochastic immunization strategies-acquaintance immunization, community-bridge immunization, and ring vaccination-were analyzed in this work. The optimal immunization ratios for acquaintance immunization and community-bridge immunization strategies were investigated, and the effectiveness of these three strategies in controlling the spreading of epidemics were analyzed based on realistic social contact networks. The results show all the strategies have decreased the coverage of the epidemics compared to baseline scenario (no control measures). However the effectiveness of acquaintance immunization and community-bridge immunization are very limited, with acquaintance immunization slightly outperforming community-bridge immunization. Ring vaccination significantly outperforms acquaintance immunization and community-bridge immunization, and the sensitivity analysis shows it could be applied to controlling the epidemics with a wide infectivity spectrum. The effectiveness of several classical stochastic immunization strategies was evaluated based on realistic contact networks for the first time in this study. These results could have important significance for epidemic control research and practice.

Amerciamysis bahia Stochastic Matrix Population Model for Laboratory Populations

EPA Science Inventory

The population model described here is a stochastic, density-independent matrix model for integrating the effects of toxicants on survival and reproduction of the marine invertebrate, Americamysis bahia. The model was constructed using Microsoft® Excel 2003. The focus of the mode...

Stochastic model for fatigue crack size and cost effective design decisions. [for aerospace structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1975-01-01

This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

Can a microscopic stochastic model explain the emergence of pain cycles in patients?

NASA Astrophysics Data System (ADS)

Di Patti, Francesca; Fanelli, Duccio

2009-01-01

A stochastic model is introduced here to investigate the molecular mechanisms which trigger the perception of pain. The action of analgesic drug compounds is discussed in a dynamical context, where the competition with inactive species is explicitly accounted for. Finite size effects inevitably perturb the mean-field dynamics: oscillations in the amount of bound receptors are spontaneously manifested, driven by the noise which is intrinsic to the system under scrutiny. These effects are investigated both numerically, via stochastic simulations, and analytically, through a large size expansion. The claim that our findings could provide a consistent interpretative framework for explaining the emergence of cyclic behaviors in response to analgesic treatments is substantiated.

On the impact of a refined stochastic model for airborne LiDAR measurements

NASA Astrophysics Data System (ADS)

Bolkas, Dimitrios; Fotopoulos, Georgia; Glennie, Craig

2016-09-01

Accurate topographic information is critical for a number of applications in science and engineering. In recent years, airborne light detection and ranging (LiDAR) has become a standard tool for acquiring high quality topographic information. The assessment of airborne LiDAR derived DEMs is typically based on (i) independent ground control points and (ii) forward error propagation utilizing the LiDAR geo-referencing equation. The latter approach is dependent on the stochastic model information of the LiDAR observation components. In this paper, the well-known statistical tool of variance component estimation (VCE) is implemented for a dataset in Houston, Texas, in order to refine the initial stochastic information. Simulations demonstrate the impact of stochastic-model refinement for two practical applications, namely coastal inundation mapping and surface displacement estimation. Results highlight scenarios where erroneous stochastic information is detrimental. Furthermore, the refined stochastic information provides insights on the effect of each LiDAR measurement in the airborne LiDAR error budget. The latter is important for targeting future advancements in order to improve point cloud accuracy.

Plasma Equilibria With Stochastic Magnetic Fields

NASA Astrophysics Data System (ADS)

Krommes, J. A.; Reiman, A. H.

2009-05-01

Plasma equilibria that include regions of stochastic magnetic fields are of interest in a variety of applications, including tokamaks with ergodic limiters and high-pressure stellarators. Such equilibria are examined theoretically, and a numerical algorithm for their construction is described.^2,3 % The balance between stochastic diffusion of magnetic lines and small effects^2 omitted from the simplest MHD description can support pressure and current profiles that need not be flattened in stochastic regions. The diffusion can be described analytically by renormalizing stochastic Langevin equations for pressure and parallel current j, with particular attention being paid to the satisfaction of the periodicity constraints in toroidal configurations with sheared magnetic fields. The equilibrium field configuration can then be constructed by coupling the prediction for j to Amp'ere's law, which is solved numerically. A. Reiman et al., Pressure-induced breaking of equilibrium flux surfaces in the W7AS stellarator, Nucl. Fusion 47, 572--8 (2007). J. A. Krommes and A. H. Reiman, Plasma equilibrium in a magnetic field with stochastic regions, submitted to Phys. Plasmas. J. A. Krommes, Fundamental statistical theories of plasma turbulence in magnetic fields, Phys. Reports 360, 1--351.

Effects of plasma flows on particle diffusion in stochastic magnetic fields

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

Vlad, M.; Spineanu, F.; Misguich, J.H.

1996-07-01

The study of collisional test particle diffusion in stochastic magnetic fields is extended to include the effects of the macroscopic flows of the plasma (drifts). We show that a substantial amplification of the diffusion coefficient can be obtained. This effect is produced by the combined action of the parallel collisional velocity and of the average drifts. The perpendicular collisional velocity influences the effective diffusion only in the limit of small average drifts. {copyright} {ital 1996 The American Physical Society.}

Dynamic analysis of a pumped-storage hydropower plant with random power load

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Xu, Beibei; Patelli, Edoardo; Tolo, Silvia

2018-02-01

This paper analyzes the dynamic response of a pumped-storage hydropower plant in generating mode. Considering the elastic water column effects in the penstock, a linearized reduced order dynamic model of the pumped-storage hydropower plant is used in this paper. As the power load is always random, a set of random generator electric power output is introduced to research the dynamic behaviors of the pumped-storage hydropower plant. Then, the influences of the PI gains on the dynamic characteristics of the pumped-storage hydropower plant with the random power load are analyzed. In addition, the effects of initial power load and PI parameters on the stability of the pumped-storage hydropower plant are studied in depth. All of the above results will provide theoretical guidance for the study and analysis of the pumped-storage hydropower plant.

The effect of stochiastic technique on estimates of population viability from transition matrix models

USGS Publications Warehouse

Kaye, T.N.; Pyke, David A.

2003-01-01

Population viability analysis is an important tool for conservation biologists, and matrix models that incorporate stochasticity are commonly used for this purpose. However, stochastic simulations may require assumptions about the distribution of matrix parameters, and modelers often select a statistical distribution that seems reasonable without sufficient data to test its fit. We used data from long-term (5a??10 year) studies with 27 populations of five perennial plant species to compare seven methods of incorporating environmental stochasticity. We estimated stochastic population growth rate (a measure of viability) using a matrix-selection method, in which whole observed matrices were selected at random at each time step of the model. In addition, we drew matrix elements (transition probabilities) at random using various statistical distributions: beta, truncated-gamma, truncated-normal, triangular, uniform, or discontinuous/observed. Recruitment rates were held constant at their observed mean values. Two methods of constraining stage-specific survival to a??100% were also compared. Different methods of incorporating stochasticity and constraining matrix column sums interacted in their effects and resulted in different estimates of stochastic growth rate (differing by up to 16%). Modelers should be aware that when constraining stage-specific survival to 100%, different methods may introduce different levels of bias in transition element means, and when this happens, different distributions for generating random transition elements may result in different viability estimates. There was no species effect on the results and the growth rates derived from all methods were highly correlated with one another. We conclude that the absolute value of population viability estimates is sensitive to model assumptions, but the relative ranking of populations (and management treatments) is robust. Furthermore, these results are applicable to a range of perennial plants and possibly other life histories.

The Validity of Quasi-Steady-State Approximations in Discrete Stochastic Simulations

PubMed Central

Kim, Jae Kyoung; Josić, Krešimir; Bennett, Matthew R.

2014-01-01

In biochemical networks, reactions often occur on disparate timescales and can be characterized as either fast or slow. The quasi-steady-state approximation (QSSA) utilizes timescale separation to project models of biochemical networks onto lower-dimensional slow manifolds. As a result, fast elementary reactions are not modeled explicitly, and their effect is captured by nonelementary reaction-rate functions (e.g., Hill functions). The accuracy of the QSSA applied to deterministic systems depends on how well timescales are separated. Recently, it has been proposed to use the nonelementary rate functions obtained via the deterministic QSSA to define propensity functions in stochastic simulations of biochemical networks. In this approach, termed the stochastic QSSA, fast reactions that are part of nonelementary reactions are not simulated, greatly reducing computation time. However, it is unclear when the stochastic QSSA provides an accurate approximation of the original stochastic simulation. We show that, unlike the deterministic QSSA, the validity of the stochastic QSSA does not follow from timescale separation alone, but also depends on the sensitivity of the nonelementary reaction rate functions to changes in the slow species. The stochastic QSSA becomes more accurate when this sensitivity is small. Different types of QSSAs result in nonelementary functions with different sensitivities, and the total QSSA results in less sensitive functions than the standard or the prefactor QSSA. We prove that, as a result, the stochastic QSSA becomes more accurate when nonelementary reaction functions are obtained using the total QSSA. Our work provides an apparently novel condition for the validity of the QSSA in stochastic simulations of biochemical reaction networks with disparate timescales. PMID:25099817

THE EFFECT OF TWO-MAGNON SCATTERING ON PARALLEL-PUMP INSTABILITY THRESHOLDS.

DTIC Science & Technology

Following a general description of the important properties and symmetries of the parallel-pump coupling and of two- magnon scattering, several...theoretical approaches to the problem of the effect of two- magnon scattering on the parallel-pump instability threshold are explored. A successful approach

Numerical investigation of output beam quality in efficient broadband optical parametric chirped pulse amplification

NASA Astrophysics Data System (ADS)

Liu, Xiao-Di; Xu, Lu; Liang, Xiao-Yan

2017-01-01

We theoretically analyzed output beam quality of broad bandwidth non-collinear optical parametric chirped pulse amplification (NOPCPA) in LiB3O5 (LBO) centered at 800 nm. With a three-dimensional numerical model, the influence of the pump intensity, pump and signal spatial modulations, and the walk-off effect on the OPCPA output beam quality are presented, together with conversion efficiency and the gain spectrum. The pump modulation is a dominant factor that affects the output beam quality. Comparatively, the influence of signal modulation is insignificant. For a low-energy system with small beam sizes, walk-off effect has to be considered. Pump modulation and walk-off effect lead to asymmetric output beam profile with increased modulation. A special pump modulation type is found to optimize output beam quality and efficiency. For a high-energy system with large beam sizes, the walk-off effect can be neglected, certain back conversion is beneficial to reduce the output modulation. A trade-off must be made between the output beam quality and the conversion efficiency, especially when the pump modulation is large since. A relatively high conversion efficiency and a low output modulation are both achievable by controlling the pump modulation and intensity.

LOX/LH2 vane pump for auxiliary propulsion systems

NASA Technical Reports Server (NTRS)

Hemminger, J. A.; Ulbricht, T. E.

1985-01-01

Positive displacement pumps offer potential efficiency advantages over centrifugal pumps for future low thrust space missions. Low flow rate applications, such as space station auxiliary propulsion or dedicated low thrust orbiter transfer vehicles, are typical of missions where low flow and high head rise challenge centrifugal pumps. The positive displacement vane pump for pumping of LOX and LH2 is investigated. This effort has included: (1) a testing program in which pump performance was investigated for differing pump clearances and for differing pump materials while pumping LN2, LOX, and LH2; and (2) an analysis effort, in which a comprehensive pump performance analysis computer code was developed and exercised. An overview of the theoretical framework of the performance analysis computer code is presented, along with a summary of analysis results. Experimental results are presented for pump operating in liquid nitrogen. Included are data on the effects on pump performance of pump clearance, speed, and pressure rise. Pump suction performance is also presented.

Interplay between three RND efflux pumps in doxycycline-selected strains of Burkholderia thailandensis.

PubMed

Biot, Fabrice Vincent; Lopez, Mélanie Monique; Poyot, Thomas; Neulat-Ripoll, Fabienne; Lignon, Sabrina; Caclard, Arnaud; Thibault, François Michel; Peinnequin, Andre; Pagès, Jean-Marie; Valade, Eric

2013-01-01

Efflux systems are involved in multidrug resistance in most Gram-negative non-fermentative bacteria. We have chosen Burkholderia thailandensis to dissect the development of multidrug resistance phenotypes under antibiotic pressure. We used doxycycline selection to obtain several resistant B. thailandensis variants. The minimal inhibitory concentrations of a large panel of structurally unrelated antibiotics were determined ± the efflux pump inhibitor phenylalanine-arginine ß-naphthylamide (PAßN). Membrane proteins were identified by proteomic method and the expressions of major efflux pumps in the doxycycline selected variants were compared to those of the parental strains by a quantitative RT-PCR analysis. Doxycycline selected variants showed a multidrug resistance in two major levels corresponding to the overproduction of two efflux pumps depending on its concentration: AmrAB-OprA and BpeEF-OprC. The study of two mutants, each lacking one of these pumps, indicated that a third pump, BpeAB-OprB, could substitute for the defective pump. Surprisingly, we observed antagonistic effects between PAßN and aminoglycosides or some ß-lactams. PAßN induced the overexpression of AmrAB-OprA and BpeAB-OprB pump genes, generating this unexpected effect. These results may account for the weak activity of PAßN in some Gram-negative species. We clearly demonstrated two antagonistic effects of this molecule on bacterial cells: the blocking of antibiotic efflux and an increase in efflux pump gene expression. Thus, doxycycline is a very efficient RND efflux pump inducer and PAßN may promote the production of some efflux pumps. These results should be taken into account when considering antibiotic treatments and in future studies on efflux pump inhibitors.

Simulation analysis and experimental verification of spiral-tube-type valveless piezoelectric pump with gyroscopic effect

NASA Astrophysics Data System (ADS)

Leng, Xuefei; Zhang, Jianhui; Jiang, Yan; Wang, Shouyin; Zhao, Chunsheng

2014-07-01

The current research of the valveless piezoelectric pump focuses on increasing the flow rate and pressure differential. Compared with the valve piezoelectric pump, the valveless one has excellent performances in simple structure, low cost, and easy miniaturization. So, their important development trend is the mitigation of their weakness, and the multi-function integration. The flow in a spiral tube element is sensitive to the element attitude caused by the Coriolis force, and that a valveless piezoelectric pump is designed by applying this phenomenon. The pump has gyroscopic effect, and has both the actuator function of fluid transfer and the sensor function, which can obtain the angular velocity when its attitude changes. First, the present paper analyzes the flow characteristics in the tube, obtains the calculation formula for the pump flow, and identifies the relationship between pump attitude and flow, which clarifies the impact of flow and driving voltage, frequency, spiral line type and element attitude, and verifies the gyroscopic effect of the pump. Then, the finite element simulation is used to verify the theory. Finally, a pump is fabricated for experimental testing of the relationship between pump attitude and pressure differential. Experimental results show that when Archimedes spiral θ=4π is selected for the tube design, and the rotation speed of the plate is 70 r/min, the pressure differential is 88.2 Pa, which is 1.5 times that of 0 r/min rotation speed. The spiral-tube-type valveless piezoelectric pump proposed can turn the element attitude into a form of pressure output, which is important for the multi-function integration of the valveless piezoelectric pump and for the development of civil gyroscope in the future.

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Wilkins, David C.; Roth, Dan

2010-01-01

For hard computational problems, stochastic local search has proven to be a competitive approach to finding optimal or approximately optimal problem solutions. Two key research questions for stochastic local search algorithms are: Which algorithms are effective for initialization? When should the search process be restarted? In the present work we investigate these research questions in the context of approximate computation of most probable explanations (MPEs) in Bayesian networks (BNs). We introduce a novel approach, based on the Viterbi algorithm, to explanation initialization in BNs. While the Viterbi algorithm works on sequences and trees, our approach works on BNs with arbitrary topologies. We also give a novel formalization of stochastic local search, with focus on initialization and restart, using probability theory and mixture models. Experimentally, we apply our methods to the problem of MPE computation, using a stochastic local search algorithm known as Stochastic Greedy Search. By carefully optimizing both initialization and restart, we reduce the MPE search time for application BNs by several orders of magnitude compared to using uniform at random initialization without restart. On several BNs from applications, the performance of Stochastic Greedy Search is competitive with clique tree clustering, a state-of-the-art exact algorithm used for MPE computation in BNs.

Influence of stochastic sea ice parametrization on climate and the role of atmosphere–sea ice–ocean interaction

PubMed Central

Juricke, Stephan; Jung, Thomas

2014-01-01

The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere–sea ice–ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10–20% after an accumulation period of approximately 20–30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small. PMID:24842027

Pricing real estate index options under stochastic interest rates

NASA Astrophysics Data System (ADS)

Gong, Pu; Dai, Jun

2017-08-01

Real estate derivatives as new financial instruments are not merely risk management tools but also provide a novel way to gain exposure to real estate assets without buying or selling the physical assets. Although real estate derivatives market has exhibited a rapid development in recent years, the valuation challenge of real estate derivatives remains a great obstacle for further development in this market. In this paper, we derive a partial differential equation contingent on a real estate index in a stochastic interest rate environment and propose a modified finite difference method that adopts the non-uniform grids to solve this problem. Numerical results confirm the efficiency of the method and indicate that constant interest rate models lead to the mispricing of options and the effects of stochastic interest rates on option prices depend on whether the term structure of interest rates is rising or falling. Finally, we have investigated and compared the different effects of stochastic interest rates on European and American option prices.

Pricing foreign equity option under stochastic volatility tempered stable Lévy processes

NASA Astrophysics Data System (ADS)

Gong, Xiaoli; Zhuang, Xintian

2017-10-01

Considering that financial assets returns exhibit leptokurtosis, asymmetry properties as well as clustering and heteroskedasticity effect, this paper substitutes the logarithm normal jumps in Heston stochastic volatility model by the classical tempered stable (CTS) distribution and normal tempered stable (NTS) distribution to construct stochastic volatility tempered stable Lévy processes (TSSV) model. The TSSV model framework permits infinite activity jump behaviors of return dynamics and time varying volatility consistently observed in financial markets through subordinating tempered stable process to stochastic volatility process, capturing leptokurtosis, fat tailedness and asymmetry features of returns. By employing the analytical characteristic function and fast Fourier transform (FFT) technique, the formula for probability density function (PDF) of TSSV returns is derived, making the analytical formula for foreign equity option (FEO) pricing available. High frequency financial returns data are employed to verify the effectiveness of proposed models in reflecting the stylized facts of financial markets. Numerical analysis is performed to investigate the relationship between the corresponding parameters and the implied volatility of foreign equity option.

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 resonance enhancement of small-world neural networks by hybrid synapses and time delay

NASA Astrophysics Data System (ADS)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang

2017-01-01

The synergistic effect of hybrid electrical-chemical synapses and information transmission delay on the stochastic response behavior in small-world neuronal networks is investigated. Numerical results show that, the stochastic response behavior can be regulated by moderate noise intensity to track the rhythm of subthreshold pacemaker, indicating the occurrence of stochastic resonance (SR) in the considered neural system. Inheriting the characteristics of two types of synapses-electrical and chemical ones, neural networks with hybrid electrical-chemical synapses are of great improvement in neuron communication. Particularly, chemical synapses are conducive to increase the network detectability by lowering the resonance noise intensity, while the information is better transmitted through the networks via electrical coupling. Moreover, time delay is able to enhance or destroy the periodic stochastic response behavior intermittently. In the time-delayed small-world neuronal networks, the introduction of electrical synapses can significantly improve the signal detection capability by widening the range of optimal noise intensity for the subthreshold signal, and the efficiency of SR is largely amplified in the case of pure chemical couplings. In addition, the stochastic response behavior is also profoundly influenced by the network topology. Increasing the rewiring probability in pure chemically coupled networks can always enhance the effect of SR, which is slightly influenced by information transmission delay. On the other hand, the capacity of information communication is robust to the network topology within the time-delayed neuronal systems including electrical couplings.

Inhibitors of Proton Pumping

PubMed Central

Bisson, Mary A.

1986-01-01

Reported inhibitors of the Characean plasmalemma proton pump were tested for their ability to inhibit the passive H+ conductance which develops in Chara corallina Klein ex Willd. at high pH. Diethylstilbestrol inhibits the proton pump and the passive H+ conductance with about the same time course, at concentrations that have no effect on cytoplasmic streaming. N-Ethylmaleimide, a sulfhydryl reagent which is small and relatively nonpolar, also inhibits both pumping and passive conductance of H+. However, it also inhibits cytoplasmic streaming with about the same time course, and therefore could not be considered a specific ATPase inhibitor. p-Chloromercuribenzene sulfonate (PCMBS), a sulfhydryl reagent which is large and charged and hence less able to penetrate the membrane, does not inhibit pumping or conductance at low concentration. At high concentration, PCMBS sometimes inhibits pumping without affecting H+ conductance, but since streaming is also inhibited, the effect on the pump cannot be said to be specific. 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide, a water soluble carbodiimide, weakly inhibits both pump and conductance, apparently specifically. PMID:16664807

Beam quality improvement by population-dynamic-coupled combined guiding effect in end-pumped Nd:YVO4 laser oscillator

NASA Astrophysics Data System (ADS)

Shen, Yijie; Gong, Mali; Fu, Xing

2018-05-01

Beam quality improvement with pump power increasing in an end-pumped laser oscillator is experimentally realized for the first time, to the best of our knowledge. The phenomenon is caused by the population-dynamic-coupled combined guiding effect, a comprehensive theoretical model of which has been well established, in agreement with the experimental results. Based on an 888 nm in-band dual-end-pumped oscillator using four tandem Nd:YVO4 crystals, the output beam quality of M^2= 1.1/1.1 at the pump power of 25 W is degraded to M^2 = 2.5/1.8 at 75 W pumping and then improved to M^2= 1.8/1.3 at 150 W pumping. The near-TEM_{00} mode is obtained with the highest continuous-wave output power of 72.1 W and the optical-to-optical efficiency of 48.1%. This work demonstrates great potential to further scale the output power of end-pumped laser oscillator while keeping good beam quality.

Artificial emotion triggered stochastic behavior transitions with motivational gain effects for multi-objective robot tasks

NASA Astrophysics Data System (ADS)

Dağlarli, Evren; Temeltaş, Hakan

2007-04-01

This paper presents artificial emotional system based autonomous robot control architecture. Hidden Markov model developed as mathematical background for stochastic emotional and behavior transitions. Motivation module of architecture considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors. Also motivational gain effects of proposed architecture can be observed on the executing behaviors during simulation.

Long-term changes in food availability mediate the effects of temperature on growth, development and survival in striped marsh frog larvae: implications for captive breeding programmes

PubMed Central

Courtney Jones, Stephanie K.; Munn, Adam J.; Penman, Trent D.; Byrne, Phillip G.

2015-01-01

Food availability and temperature are known to trigger phenotypic change, but the interactive effects between these factors are only beginning to be considered. The aim of this study was to examine the independent and interactive effects of long-term stochastic food availability and water temperature on larval survivorship, growth and development of the striped marsh frog, Limnodynastes peronii. Larval L. peronii were reared in conditions of either constant or stochastic food availability and in water at three different temperatures (18, 22 and 26°C), and effects on survival, growth and development were quantified. Over the experimental period, larval growth rate was highest and survivorship lowest at the warmest temperature. However, changes in food availability mediated the effects of temperature, with slower larval growth and higher survivorship in stochastic food availability treatments. Tadpoles in the stochastic food availability treatments did not reach metamorphosis during the experimental period, suggesting that developmental stasis may have been induced by food restriction. Overall, these results demonstrate that changes in food availability alter the effects of water temperature on survival, growth and development. From an applied perspective, understanding how environmental factors interact to cause phenotypic change may assist with amphibian conservation by improving the number of tadpoles generated in captive breeding programmes. PMID:27293714

Elegant anti-disturbance control for discrete-time stochastic systems with nonlinearity and multiple disturbances

NASA Astrophysics Data System (ADS)

Wei, Xinjiang; Sun, Shixiang

2018-03-01

An elegant anti-disturbance control (EADC) strategy for a class of discrete-time stochastic systems with both nonlinearity and multiple disturbances, which include the disturbance with partially known information and a sequence of random vectors, is proposed in this paper. A stochastic disturbance observer is constructed to estimate the disturbance with partially known information, based on which, an EADC scheme is proposed by combining pole placement and linear matrix inequality methods. It is proved that the two different disturbances can be rejected and attenuated, and the corresponding desired performances can be guaranteed for discrete-time stochastic systems with known and unknown nonlinear dynamics, respectively. Simulation examples are given to demonstrate the effectiveness of the proposed schemes compared with some existing results.

Optically pumped isotopic ammonia laser system

DOEpatents

Buchwald, Melvin I.; Jones, Claude R.; Nelson, Leonard Y.

1982-01-01

An optically pumped isotopic ammonia laser system which is capable of producing a plurality of frequencies in the middle infrared spectral region. Two optical pumping mechanisms are disclosed, i.e., pumping on R(J) and lasing on P(J) in response to enhancement of rotational cascade lasing including stimulated Raman effects, and, pumping on R(J) and lasing on P(J+2). The disclosed apparatus for optical pumping include a hole coupled cavity and a grating coupled cavity.

Interaction of external alkali metal ions with the Na-K pump of human erythrocytes: a comparison of their effects on activation of the pump and on the rate of ouabain binding

PubMed Central

1978-01-01

The effects of external alkali metal ions on the rate of ouabain binding and on the rate of the Na-K pump were examined in human red blood cells. In Na-containing solutions, K, Cs, and Li decreased the rate of ouabain binding. For K and Cs, the kinetics of this effect were similar to those for their activation of the pump. In Na-free (choline- substituted) solutions the rate of ouabain binding was decreased by K whereas it was promoted by Cs and Li. External Na increased the rate of ouabain binding whether or not external K was present, and the kinetics of this effect were not the same as those for inhibition of the pump by Na. These findings are interpreted to mean that not only do the cations affect ouabain binding at the external loading sites on the pump from which ions are translocated inward, but that there are additional sites on the external aspect of the pump at which cations can promote ouabain binding, and that these sites can be occupied by Li, Na, and Cs. It is postulated that these latter sites are those from which Na is discharged after outward translocation by the pump. PMID:702113

Temporal Behavior of the Pump Pulses, Residual Pump Pulses, and THz Pulses for D2O Gas Pumped by a TEA CO2 Laser

NASA Astrophysics Data System (ADS)

Geng, Lijie; Zhang, Zhifeng; Zhai, Yusheng; Su, Yuling; Zhou, Fanghua; Qu, Yanchen; Zhao, Weijiang

2016-08-01

Temporal behavior of the pump pulses, residual pump pulses, and THz pulses for optically pumped D2O gas molecules was investigated by using a tunable TEA CO2 laser as the pumping source. The pulse profiles of pump laser pulses, residual pump pulses, and the THz output pulses were measured, simultaneously, at several different gas pressures. For THz pulse, the pulse delay between the THz pulse and the pump pulse was observed and the delay time was observed to increase from 40 to 70 ns with an increase in gas pressure from 500 to 1700 Pa. Both THz pulse broadening and compression were observed, and the pulse broadening effect transformed to the compression effect with increasing the gas pressure. For the residual pump pulse, the full width at half maximum (FWHM) of the main pulse decreased with increasing gas pressure, and the main pulse disappeared at high gas pressures. The secondary pulses were observed at high gas pressure, and the time intervals of about 518 and 435 ns were observed between the THz output pulse and the secondary residual pump pulse at the pressure of 1400 Pa and 1700 Pa, from which the vibrational relaxation time constants of about 5.45 and 5.55 μs Torr were obtained.

Modulation of ouabain binding and potassium pump fluxes by cellular sodium and potassium in human and sheep erythrocytes.

PubMed Central

Joiner, C H; Lauf, P K

1978-01-01

1. Erythrocytes were treated with nystatin to alter internal Na (Nai) and K (Ki) composition. Although the rates of K pumping and [3H]ouabain binding were altered dramatically, the relationship between glycoside binding and K pump inhibition was unaffected. 2. Human cells with high Nai and low Ki exhibited an increased rate of ouabain binding as compared to high Ki, low Nai cells; this paralleled the stimulated K pump activity of high Nai cells. 3. At constant Ki, increasing internal Na stimulated K pump and ouabain binding rates concomitantly. 4. At low Nai, increasing Ki inhibited both K pumping and ouabain binding. However, at high Nai, increasing Ki from 4 to 44 mM stimulated the rate of glycoside binding, parallel to its effect of increasing the rate of active K influx. 5. Anti-L, an isoantibody to low K (LK) sheep red cells, increased the rate of ouabain binding via its stimulation of K pump turnover. Since the latter effect is the result of affinity changes at the internal cation activation site(s) of the pump (Lauf, Rasmusen, Hoffman, Dunham, Cook, Parmelee & Tosteson, 1970), the antibody's effect on ouabain binding reflected the positive correlation between the rates of K pump turnover and glycoside binding. 6. These data provide the first evidence in intact cells for the occurrence of a Nai-induced conformational change in the Na/K pump during its normal operational cycle. PMID:722574

The effect of stochastic modeling of ionospheric effect on the various lengths of baseline determination

NASA Astrophysics Data System (ADS)

Kwon, J.; Yang, H.

2006-12-01

Although GPS provides continuous and accurate position information, there are still some rooms for improvement of its positional accuracy, especially in the medium and long range baseline determination. In general, in case of more than 50 km baseline length, the effect of ionospheric delay is the one causing the largest degradation in positional accuracy. For example, the ionospheric delay in terms of double differenced mode easily reaches 10 cm with baseline length of 101 km. Therefore, many researchers have been tried to mitigate/reduce the effect using various modeling methods. In this paper, the optimal stochastic modeling of the ionospheric delay in terms of baseline length is presented. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. Here, the ionospheric delay is stochastically modeled by well-known Gaussian, 1st and 3rd order Gauss-Markov process. The parameters required in those models such as correlation distance and time is determined by the least-square adjustment using ionosphere-only observables. Mainly the results and analysis from this study show the effect of stochastic models of the ionospheric delay in terms of the baseline length, models, and parameters used. In the above example with 101 km baseline length, it was found that the positional accuracy with appropriate ionospheric modeling (Gaussian) was about ±2 cm whereas it reaches about ±15 cm with no stochastic modeling. It is expected that the approach in this study contributes to improve positional accuracy, especially in medium and long range baseline determination.

The individual tolerance concept is not the sole explanation for the probit dose-effect model

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

Newman, M.C.; McCloskey, J.T.

2000-02-01

Predominant methods for analyzing dose- or concentration-effect data (i.e., probit analysis) are based on the concept of individual tolerance or individual effective dose (IED, the smallest characteristic dose needed to kill an individual). An alternative explanation (stochasticity hypothesis) is that individuals do not have unique tolerances: death results from stochastic processes occurring similarly in all individuals. These opposing hypotheses were tested with two types of experiments. First, time to stupefaction (TTS) was measured for zebra fish (Brachydanio rerio) exposed to benzocaine. The same 40 fish were exposed during five trials to test if the same order for TTS was maintainedmore » among trials. The IED hypothesis was supported with a minor stochastic component being present. Second, eastern mosquitofish (Gambusia holbrooki) were exposed to sublethal or lethal NaCl concentrations until a large portion of the lethally exposed fish died. After sufficient time for recovery, fish sublethally exposed and fish surviving lethal exposure were exposed simultaneously to lethal NaCl concentrations. No statistically significant effect was found of previous exposure on survival time but a large stochastic component to the survival dynamics was obvious. Repetition of this second type of test with pentachlorophenol also provided no support for the IED hypothesis. The authors conclude that neither hypothesis alone was the sole or dominant explanation for the lognormal (probit) model. Determination of the correct explanation (IED or stochastic) or the relative contributions of each is crucial to predicting consequences to populations after repeated or chronic exposures to any particular toxicant.« less

Effectiveness of a heat exchanger in a heat pump clothes dryer

NASA Astrophysics Data System (ADS)

Nasution, A. H.; Sembiring, P. G.; Ambarita, H.

2018-02-01

This paper deals with study on a heat pump clothes dryer coupled with a heat exchanger. The objective is to explore the effects of the heat exchanger on the performance of the heat pump dryer. The heat pump dryer consists of a vapor compression cycle and integrated with a drying room with volume 1 m3. The power of compressor is 800 Watt and the refrigerant of the cycle is R22. The heat exchanger is a flat plate type with dimensions of 400 mm × 400 mm × 400 mm. The results show the present of the heat exchanger increase the performance of the heat pump dryer. In the present experiment the COP, TP and SMER increase 15.11%, 4.81% and 58.62%, respectively. This is because the heat exchanger provides a better drying condition in the drying room with higher temperature and lower relative humidity in comparison with heat pump dryer without heat exchanger. The effectiveness of the heat exchanger is also high, it is above 50%. It is suggested to install a heat exchanger in a heat pump dryer.

A highly reliable cryogenic mixing pump with no mechanical moving parts

NASA Astrophysics Data System (ADS)

Chen, W.; Niblick, A. L.

2017-12-01

This paper presents the design and preliminary test results of a novel cryogenic mixing pump based on magnetocaloric effect. The mixing pump is developed to enable long-term cryogenic propellant storage in space by preventing thermal stratification of cryogens in storage tanks. The mixing pump uses an innovative thermodynamic process to generate fluid jets to promote fluid mixing, eliminating the need for mechanical pumps. Its innovative mechanism uses a solid magnetocaloric material to alternately vaporize and condense the cryogen in the pumping chamber, and thus control the volume of the fluid inside the pumping chamber to produce pumping action. The pump is capable of self-priming and can generate a high-pressure rise. This paper discusses operating mechanism and design consideration of the pump, introduces the configuration of a brassboard cryogenic pump, and presents the preliminary test results of the pump with liquid nitrogen.

Assessment of single-shell tank residual-liquid issues at Hanford Site, Washington

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

Murthy, K.S.; Stout, L.A.; Napier, B.A.

1983-06-01

This report provides an assessment of the overall effectiveness and implications of jet pumping the interstitial liquids (IL) from single-shell tanks at Hanford. The jet-pumping program, currently in progress at Hanford, involves the planned removal of IL contained in 89 of the 149 single-shell tanks and its transfer to double-shell tanks after volume reduction by evaporation. The purpose of this report is to estimate the public and worker doses associated with (1) terminating pumping immediately, (2) pumping to a 100,000-gal limit per tank, (3) pumping to a 50,000-gal limit per tank, and (4) pumping to the maximum practical liquid removalmore » level of 30,000 gal. Assessment of the cost-effectiveness of these various levels of pumping in minimizing any undue health and safety risks to the public or worker is also presented.« less

Pump tank divider plate for sump suction sodium pumps

DOEpatents

George, John A.; Nixon, Donald R.

1977-01-01

A circular plate extends across the diameter of "sump suction" pump, with a close clearance between the edge of the plate and the wall of the pump tank. The plate is located above the pump impeller, inlet and outlet flow nozzles but below the sodium free surface and effectively divides the pump tank into two separate chambers. On change of pump speed, the close fitting flow restriction plate limits the rate of flow into or out of the upper chamber, thereby minimizing the rate of level change in the tank and permitting time for the pump cover gas pressure to be varied to maintain an essentially constant level.

Stochastic Robust Mathematical Programming Model for Power System Optimization

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

Liu, Cong; Changhyeok, Lee; Haoyong, Chen

2016-01-01

This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.

Pumped shot noise in adiabatically modulated graphene-based double-barrier structures.

PubMed

Zhu, Rui; Lai, Maoli

2011-11-16

Quantum pumping processes are accompanied by considerable quantum noise. Based on the scattering approach, we investigated the pumped shot noise properties in adiabatically modulated graphene-based double-barrier structures. It is found that compared with the Poisson processes, the pumped shot noise is dramatically enhanced where the dc pumped current changes flow direction, which demonstrates the effect of the Klein paradox.

Pumped shot noise in adiabatically modulated graphene-based double-barrier structures

NASA Astrophysics Data System (ADS)

Zhu, Rui; Lai, Maoli

2011-11-01

Quantum pumping processes are accompanied by considerable quantum noise. Based on the scattering approach, we investigated the pumped shot noise properties in adiabatically modulated graphene-based double-barrier structures. It is found that compared with the Poisson processes, the pumped shot noise is dramatically enhanced where the dc pumped current changes flow direction, which demonstrates the effect of the Klein paradox.

Head-to-head comparison of H2-receptor antagonists and proton pump inhibitors in the treatment of erosive esophagitis: A meta-analysis

PubMed Central

Wang, Wei-Hong; Huang, Jia-Qing; Zheng, Ge-Fan; Xia, Harry Hua-Xiang; Wong, Wai-Man; Lam, Shiu-Kum; Wong, Benjamin Chun-Yu

2005-01-01

AIM: To systematically evaluate the efficacy of H2-receptor antagonists (H2RAs) and proton pump inhibitors in healing erosive esophagitis (EE). METHODS: A meta-analysis was performed. A literature search was conducted in PubMed, Medline, Embase, and Cochrane databases to include randomized controlled head-to-head comparative trials evaluating the efficacy of H2RAs or proton pump inhibitors in healing EE. Relative risk (RR) and 95% confidence interval (CI) were calculated under a random-effects model. RESULTS: RRs of cumulative healing rates for each comparison at 8 wk were: high dose vs standard dose H2RAs, 1.17 (95%CI, 1.02-1.33); standard dose proton pump inhibitors vs standard dose H2RAs, 1.59 (95%CI, 1.44-1.75); standard dose other proton pump inhibitors vs standard dose omeprazole, 1.06 (95%CI, 0.98-1.06). Proton pump inhibitors produced consistently greater healing rates than H2RAs of all doses across all grades of esophagitis, including patients refractory to H2RAs. Healing rates achieved with standard dose omeprazole were similar to those with other proton pump inhibitors in all grades of esophagitis. CONCLUSION: H2RAs are less effective for treating patients with erosive esophagitis, especially in those with severe forms of esophagitis. Standard dose proton pump inhibitors are significantly more effective than H2RAs in healing esophagitis of all grades. Proton pump inhibitors given at the recommended dose are equally effective for healing esophagitis. PMID:15996033

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth.

PubMed

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

NASA Astrophysics Data System (ADS)

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Floaters may buffer the extinction risk of small populations: an empirical assessment

PubMed Central

2017-01-01

The high extinction risk of small populations is commonly explained by reductions in fecundity and breeder survival associated with demographic and environmental stochasticity. However, ecological theory suggests that population extinctions may also arise from reductions in the number of floaters able to replace the lost breeders. This can be particularly plausible under harsh fragmentation scenarios, where species must survive as small populations subjected to severe effects of stochasticity. Using a woodpecker study in fragmented habitats (2004–2016), we provide here empirical support for the largely neglected hypothesis that floaters buffer population extirpation risks. After controlling for population size, patch size and the intrinsic quality of habitat, populations in patches with floaters had a lower extinction probability than populations in patches without floaters (0.013 versus 0.131). Floaters, which often replace the lost breeders, were less likely to occur in small and low-quality patches, showing that population extirpations may arise from unnoticed reductions in floater numbers in poor-quality habitats. We argue that adequate pools of the typically overlooked floaters may buffer extirpation risks by reducing the detrimental impacts of demographic and environmental stochasticity. However, unravelling the influence of floaters in buffering stochastic effects and promoting population stability require additional studies in an ample array of species and stochastic scenarios. PMID:28424345

Floaters may buffer the extinction risk of small populations: an empirical assessment.

PubMed

Robles, Hugo; Ciudad, Carlos

2017-04-26

The high extinction risk of small populations is commonly explained by reductions in fecundity and breeder survival associated with demographic and environmental stochasticity. However, ecological theory suggests that population extinctions may also arise from reductions in the number of floaters able to replace the lost breeders. This can be particularly plausible under harsh fragmentation scenarios, where species must survive as small populations subjected to severe effects of stochasticity. Using a woodpecker study in fragmented habitats (2004-2016), we provide here empirical support for the largely neglected hypothesis that floaters buffer population extirpation risks. After controlling for population size, patch size and the intrinsic quality of habitat, populations in patches with floaters had a lower extinction probability than populations in patches without floaters (0.013 versus 0.131). Floaters, which often replace the lost breeders, were less likely to occur in small and low-quality patches, showing that population extirpations may arise from unnoticed reductions in floater numbers in poor-quality habitats. We argue that adequate pools of the typically overlooked floaters may buffer extirpation risks by reducing the detrimental impacts of demographic and environmental stochasticity. However, unravelling the influence of floaters in buffering stochastic effects and promoting population stability require additional studies in an ample array of species and stochastic scenarios. © 2017 The Author(s).

Autapse-induced multiple stochastic resonances in a modular neuronal network

NASA Astrophysics Data System (ADS)

Yang, XiaoLi; Yu, YanHu; Sun, ZhongKui

2017-08-01

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

Noise Enhances Action Potential Generation in Mouse Sensory Neurons via Stochastic Resonance.

PubMed

Onorato, Irene; D'Alessandro, Giuseppina; Di Castro, Maria Amalia; Renzi, Massimiliano; Dobrowolny, Gabriella; Musarò, Antonio; Salvetti, Marco; Limatola, Cristina; Crisanti, Andrea; Grassi, Francesca

2016-01-01

Noise can enhance perception of tactile and proprioceptive stimuli by stochastic resonance processes. However, the mechanisms underlying this general phenomenon remain to be characterized. Here we studied how externally applied noise influences action potential firing in mouse primary sensory neurons of dorsal root ganglia, modelling a basic process in sensory perception. Since noisy mechanical stimuli may cause stochastic fluctuations in receptor potential, we examined the effects of sub-threshold depolarizing current steps with superimposed random fluctuations. We performed whole cell patch clamp recordings in cultured neurons of mouse dorsal root ganglia. Noise was added either before and during the step, or during the depolarizing step only, to focus onto the specific effects of external noise on action potential generation. In both cases, step + noise stimuli triggered significantly more action potentials than steps alone. The normalized power norm had a clear peak at intermediate noise levels, demonstrating that the phenomenon is driven by stochastic resonance. Spikes evoked in step + noise trials occur earlier and show faster rise time as compared to the occasional ones elicited by steps alone. These data suggest that external noise enhances, via stochastic resonance, the recruitment of transient voltage-gated Na channels, responsible for action potential firing in response to rapid step-wise depolarizing currents.

Noise Enhances Action Potential Generation in Mouse Sensory Neurons via Stochastic Resonance

PubMed Central

Onorato, Irene; D'Alessandro, Giuseppina; Di Castro, Maria Amalia; Renzi, Massimiliano; Dobrowolny, Gabriella; Musarò, Antonio; Salvetti, Marco; Limatola, Cristina; Crisanti, Andrea; Grassi, Francesca

2016-01-01

Noise can enhance perception of tactile and proprioceptive stimuli by stochastic resonance processes. However, the mechanisms underlying this general phenomenon remain to be characterized. Here we studied how externally applied noise influences action potential firing in mouse primary sensory neurons of dorsal root ganglia, modelling a basic process in sensory perception. Since noisy mechanical stimuli may cause stochastic fluctuations in receptor potential, we examined the effects of sub-threshold depolarizing current steps with superimposed random fluctuations. We performed whole cell patch clamp recordings in cultured neurons of mouse dorsal root ganglia. Noise was added either before and during the step, or during the depolarizing step only, to focus onto the specific effects of external noise on action potential generation. In both cases, step + noise stimuli triggered significantly more action potentials than steps alone. The normalized power norm had a clear peak at intermediate noise levels, demonstrating that the phenomenon is driven by stochastic resonance. Spikes evoked in step + noise trials occur earlier and show faster rise time as compared to the occasional ones elicited by steps alone. These data suggest that external noise enhances, via stochastic resonance, the recruitment of transient voltage-gated Na channels, responsible for action potential firing in response to rapid step-wise depolarizing currents. PMID:27525414

Sparse Learning with Stochastic Composite Optimization.

PubMed

Zhang, Weizhong; Zhang, Lijun; Jin, Zhongming; Jin, Rong; Cai, Deng; Li, Xuelong; Liang, Ronghua; He, Xiaofei

2017-06-01

In this paper, we study Stochastic Composite Optimization (SCO) for sparse learning that aims to learn a sparse solution from a composite function. Most of the recent SCO algorithms have already reached the optimal expected convergence rate O(1/λT), but they often fail to deliver sparse solutions at the end either due to the limited sparsity regularization during stochastic optimization (SO) or due to the limitation in online-to-batch conversion. Even when the objective function is strongly convex, their high probability bounds can only attain O(√{log(1/δ)/T}) with δ is the failure probability, which is much worse than the expected convergence rate. To address these limitations, we propose a simple yet effective two-phase Stochastic Composite Optimization scheme by adding a novel powerful sparse online-to-batch conversion to the general Stochastic Optimization algorithms. We further develop three concrete algorithms, OptimalSL, LastSL and AverageSL, directly under our scheme to prove the effectiveness of the proposed scheme. Both the theoretical analysis and the experiment results show that our methods can really outperform the existing methods at the ability of sparse learning and at the meantime we can improve the high probability bound to approximately O(log(log(T)/δ)/λT).

Demographic noise can reverse the direction of deterministic selection

PubMed Central

Constable, George W. A.; Rogers, Tim; McKane, Alan J.; Tarnita, Corina E.

2016-01-01

Deterministic evolutionary theory robustly predicts that populations displaying altruistic behaviors will be driven to extinction by mutant cheats that absorb common benefits but do not themselves contribute. Here we show that when demographic stochasticity is accounted for, selection can in fact act in the reverse direction to that predicted deterministically, instead favoring cooperative behaviors that appreciably increase the carrying capacity of the population. Populations that exist in larger numbers experience a selective advantage by being more stochastically robust to invasions than smaller populations, and this advantage can persist even in the presence of reproductive costs. We investigate this general effect in the specific context of public goods production and find conditions for stochastic selection reversal leading to the success of public good producers. This insight, developed here analytically, is missed by the deterministic analysis as well as by standard game theoretic models that enforce a fixed population size. The effect is found to be amplified by space; in this scenario we find that selection reversal occurs within biologically reasonable parameter regimes for microbial populations. Beyond the public good problem, we formulate a general mathematical framework for models that may exhibit stochastic selection reversal. In this context, we describe a stochastic analog to r−K theory, by which small populations can evolve to higher densities in the absence of disturbance. PMID:27450085

Effects of Elongation on Stochastic Layer and Magnetic Footprint in Divertor Tokamaks

NASA Astrophysics Data System (ADS)

Wadi, Hasina; Jones, Morgin; Ali, Halima; Punjabi, Alkesh

2007-11-01

An area-preserving map is constructed to calculate effects of elongation on the stochastic layer and magnetic footprint in divertor tokamaks. The generating function for the map is S(x,y) = -(1/2)α^2y^2 (1-y^2/2a^2)+(1/2)β^2x^2. Method of maps developed by Punjabi and Boozer [1,2] is used to construct the map and to calculate the stochastic layer and the magnetic footprints. The poloidal magnetic flux inside the ideal separatrix and the safety factor profile are held constant, and elongation is varied by (1) varying the width of separatrix surface in the midplane keeping the height fixed, and (2) varying the height keeping the width of separatrix surface fixed. As the width is increased, the stochastic layer and the footprint become narrower. As the height is increased, the width of stochastic layer and the footprint become narrower. Detailed results of this study will be presented. This work is supported by US DOE OFES DE-FG02-01ER54624 and DE-FG02-04ER54793. [1] A. Punjabi, A. Verma, and A. Boozer, Phys Rev Lett, 69, 3322-3325 (1992). [2] A. Punjabi, H. Ali, T. Evans, and A. Boozer, Phys Lett A 364 140--145 (2007).

? filtering for stochastic systems driven by Poisson processes

NASA Astrophysics Data System (ADS)

Song, Bo; Wu, Zheng-Guang; Park, Ju H.; Shi, Guodong; Zhang, Ya

2015-01-01

This paper investigates the ? filtering problem for stochastic systems driven by Poisson processes. By utilising the martingale theory such as the predictable projection operator and the dual predictable projection operator, this paper transforms the expectation of stochastic integral with respect to the Poisson process into the expectation of Lebesgue integral. Then, based on this, this paper designs an ? filter such that the filtering error system is mean-square asymptotically stable and satisfies a prescribed ? performance level. Finally, a simulation example is given to illustrate the effectiveness of the proposed filtering scheme.

The threshold of a stochastic delayed SIR epidemic model with vaccination

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing

2016-11-01

In this paper, we study the threshold dynamics of a stochastic delayed SIR epidemic model with vaccination. We obtain sufficient conditions for extinction and persistence in the mean of the epidemic. The threshold between persistence in the mean and extinction of the stochastic system is also obtained. Compared with the corresponding deterministic model, the threshold affected by the white noise is smaller than the basic reproduction number Rbar0 of the deterministic system. Results show that time delay has important effects on the persistence and extinction of the epidemic.

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards

PubMed Central

Nyflot, Matthew J.; Yang, Fei; Byrd, Darrin; Bowen, Stephen R.; Sandison, George A.; Kinahan, Paul E.

2015-01-01

Abstract. Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes. PMID:26251842

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards.

PubMed

Nyflot, Matthew J; Yang, Fei; Byrd, Darrin; Bowen, Stephen R; Sandison, George A; Kinahan, Paul E

2015-10-01

Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes.

Characterization of Nonlinear Effects in Optically Pumped Vertical Cavity Surface Emitting Lasers

DTIC Science & Technology

1993-12-01

Vertical Cavity Surface Emitting Lasers ( VCSELs ) are an exciting...lines A-3 X AFIT/GEOiENP/93 D-01 Abstract The nonlinear characteristics of optically pumped Vertical Cavity Surface Emitting Lasers ( VCSELs ) are...uniformity of the VCSEL fabrication. xi Characterization of Nonlinear Effects in Optically Pumped Vertical Cavity Surface Emitting Lasers

Dynamics of a prey-predator system under Poisson white noise excitation

NASA Astrophysics Data System (ADS)

Pan, Shan-Shan; Zhu, Wei-Qiu

2014-10-01

The classical Lotka-Volterra (LV) model is a well-known mathematical model for prey-predator ecosystems. In the present paper, the pulse-type version of stochastic LV model, in which the effect of a random natural environment has been modeled as Poisson white noise, is investigated by using the stochastic averaging method. The averaged generalized Itô stochastic differential equation and Fokker-Planck-Kolmogorov (FPK) equation are derived for prey-predator ecosystem driven by Poisson white noise. Approximate stationary solution for the averaged generalized FPK equation is obtained by using the perturbation method. The effect of prey self-competition parameter ɛ2 s on ecosystem behavior is evaluated. The analytical result is confirmed by corresponding Monte Carlo (MC) simulation.

Resources alter the structure and increase stochasticity in bromeliad microfauna communities.

PubMed

Petermann, Jana S; Kratina, Pavel; Marino, Nicholas A C; MacDonald, A Andrew M; Srivastava, Diane S

2015-01-01

Although stochastic and deterministic processes have been found to jointly shape structure of natural communities, the relative importance of both forces may vary across different environmental conditions and across levels of biological organization. We tested the effects of abiotic environmental conditions, altered trophic interactions and dispersal limitation on the structure of aquatic microfauna communities in Costa Rican tank bromeliads. Our approach combined natural gradients in environmental conditions with experimental manipulations of bottom-up interactions (resources), top-down interactions (predators) and dispersal at two spatial scales in the field. We found that resource addition strongly increased the abundance and reduced the richness of microfauna communities. Community composition shifted in a predictable way towards assemblages dominated by flagellates and ciliates but with lower abundance and richness of algae and amoebae. While all functional groups responded strongly and predictably to resource addition, similarity among communities at the species level decreased, suggesting a role of stochasticity in species-level assembly processes. Dispersal limitation did not affect the communities. Since our design excluded potential priority effects we can attribute the differences in community similarity to increased demographic stochasticity of resource-enriched communities related to erratic changes in population sizes of some species. In contrast to resources, predators and environmental conditions had negligible effects on community structure. Our results demonstrate that bromeliad microfauna communities are strongly controlled by bottom-up forces. They further suggest that the relative importance of stochasticity may change with productivity and with the organizational level at which communities are examined.

Resources Alter the Structure and Increase Stochasticity in Bromeliad Microfauna Communities

PubMed Central

Petermann, Jana S.; Kratina, Pavel; Marino, Nicholas A. C.; MacDonald, A. Andrew M.; Srivastava, Diane S.

2015-01-01

Although stochastic and deterministic processes have been found to jointly shape structure of natural communities, the relative importance of both forces may vary across different environmental conditions and across levels of biological organization. We tested the effects of abiotic environmental conditions, altered trophic interactions and dispersal limitation on the structure of aquatic microfauna communities in Costa Rican tank bromeliads. Our approach combined natural gradients in environmental conditions with experimental manipulations of bottom-up interactions (resources), top-down interactions (predators) and dispersal at two spatial scales in the field. We found that resource addition strongly increased the abundance and reduced the richness of microfauna communities. Community composition shifted in a predictable way towards assemblages dominated by flagellates and ciliates but with lower abundance and richness of algae and amoebae. While all functional groups responded strongly and predictably to resource addition, similarity among communities at the species level decreased, suggesting a role of stochasticity in species-level assembly processes. Dispersal limitation did not affect the communities. Since our design excluded potential priority effects we can attribute the differences in community similarity to increased demographic stochasticity of resource-enriched communities related to erratic changes in population sizes of some species. In contrast to resources, predators and environmental conditions had negligible effects on community structure. Our results demonstrate that bromeliad microfauna communities are strongly controlled by bottom-up forces. They further suggest that the relative importance of stochasticity may change with productivity and with the organizational level at which communities are examined. PMID:25775464

A stochastic model for the probability of malaria extinction by mass drug administration.

PubMed

Pemberton-Ross, Peter; Chitnis, Nakul; Pothin, Emilie; Smith, Thomas A

2017-09-18

Mass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, R c . A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically. The results indicate that mass drug administration (Firstly, R c must be sustained at R c  < 1.2 to avoid the rapid re-establishment of infections in the population. Secondly, the MDA must produce effective cure rates of >95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level. There are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.

[The temperature factor and magnetic noise under the conditions of stochastic resonance of magnetosomes].

PubMed

Bingi, V N; Chernavskiĭ, D S; Rubin, A B

2006-01-01

The influence of magnetic noise on the dynamics of magnetic nanoparticles under the conditions of stochastic resonance is considered. The effect of the magnetic noise is shown to be equivalent to the growth of the effective thermostat temperature for the particles at the permanent actual temperature of the medium. This regularity may be used for testing the hypothesis on the involvement of magnetic nanoparticles in the formation of biological effects of weak magnetic fields.

Field experiment and numerical simulation of coupling non-Darcy flow caused by curtain and pumping well in foundation pit dewatering

NASA Astrophysics Data System (ADS)

Wang, Jianxiu; Liu, Xiaotian; Wu, Yuanbin; Liu, Shaoli; Wu, Lingao; Lou, Rongxiang; Lu, Jiansheng; Yin, Yao

2017-06-01

High-velocity non-Darcy flow produced larger drawdown than Darcy flow under the same pumping rate. When the non-Darcy flow caused by curtain met non-Darcy flow caused by pumping wells, superposition and amplification effect occurred in the coupling area, the non-Darcy flow was defined as coupling non-Darcy flow. The coupling non-Darcy flow can be produced and controlled using different combination of curtain and pumping wells in foundation pit dewatering to obtain the maximum drawdown using the minimum pumping rate. The Qianjiang Century City Station foundation pit of Hangzhou subway, China, was selected as background. Field experiments were performed to observe the coupling non-Darcy flow in round gravel. A generalized conceptual model was established to study the coupling effect under different combination of curtain and pumping wells. Numerical simulations of the coupling non-Darcy flow in foundation pit dewatering were carried out based on the Forchheimer equation. The non-Darcy flow area and flow velocity were influenced by the coupling effect. Short filter tube, large pumping rate, small horizontal distance between filter tube and diaphragm wall, and small vertical distance between the filter tube and confined aquifer roof effectively strengthened the coupling effect and obtained a large drawdown. The pumping wells installed close to a curtain was an intentional choice designed to create coupling non-Darcy flow and obtain the maximize drawdown. It can be used in the dewatering of a long and narrow foundation pit, such as a subway foundation pit.

Field, laboratory, and modeling investigation of the skin effect at wells with slotted casing, Boise Hydrogeophysical Research Site

NASA Astrophysics Data System (ADS)

Barrash, Warren; Clemo, Tom; Fox, Jessica J.; Johnson, Timothy C.

2006-07-01

Understanding and quantification of wellbore skin improves our ability to accurately measure or estimate hydrologic parameters with tests at wells such as pumping tests, flowmeter tests, and slug tests. This paper presents observations and results from a series of field, laboratory, and modeling tests which, together, explain the source of wellbore skin at wells at a research wellfield and which support estimation of skin thickness ( ds) and skin hydraulic conductivity ( Ks). Positive wellbore skin effects were recognized at wells in the shallow, unconfined, coarse-grained fluvial aquifer at the Boise Hydrogeophysical Research Site (BHRS). Well development efforts at the BHRS removed residual drilling fines but only marginally reduced the skin effect. Likely causes for the remaining wellbore skin effect were examined; partial clogging of screen slots with sand is consistent with field observations and can account for the magnitude of wellbore skin effect observed. We then use the WTAQ code ( Barlow and Moench, 1999) with a redefinition of the term for delayed observation well response to include skin effects at observation wells (in addition to pumping wells) in order to analyze aquifer tests at the BHRS for average Ks values at individual wells. Systematic differences in Ks values are recognized in results at pumping ( Ks_Q) and observation ( Ks_obs) wells: larger values are seen at observation wells (average Ks_obs=0.0023 cm/s) than pumping wells. Two possible causes are recognized for the occurrence of higher Ks values at observation wells than pumping wells: (1) flow diversion between aquifer layers on approach to a pumping well with positive skin; and (2) larger portion of flow passing through lower-K zones in the heterogeneous aquifer near the pumping well than the observation wells due to strongly radially convergent flow near the pumping well. For the well-aquifer system at the BHRS, modeling analyses of drawdown vs time at observation wells provide better Ks estimates than those from pumping wells.

Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon

NASA Astrophysics Data System (ADS)

Wu, Jiang; Liao, Fucheng; Tomizuka, Masayoshi

2017-01-01

This paper discusses the design of the optimal preview controller for a linear continuous-time stochastic control system in finite-time horizon, using the method of augmented error system. First, an assistant system is introduced for state shifting. Then, in order to overcome the difficulty of the state equation of the stochastic control system being unable to be differentiated because of Brownian motion, the integrator is introduced. Thus, the augmented error system which contains the integrator vector, control input, reference signal, error vector and state of the system is reconstructed. This leads to the tracking problem of the optimal preview control of the linear stochastic control system being transformed into the optimal output tracking problem of the augmented error system. With the method of dynamic programming in the theory of stochastic control, the optimal controller with previewable signals of the augmented error system being equal to the controller of the original system is obtained. Finally, numerical simulations show the effectiveness of the controller.

Distinct Sources of Deterministic and Stochastic Components of Action Timing Decisions in Rodent Frontal Cortex.

PubMed

Murakami, Masayoshi; Shteingart, Hanan; Loewenstein, Yonatan; Mainen, Zachary F

2017-05-17

The selection and timing of actions are subject to determinate influences such as sensory cues and internal state as well as to effectively stochastic variability. Although stochastic choice mechanisms are assumed by many theoretical models, their origin and mechanisms remain poorly understood. Here we investigated this issue by studying how neural circuits in the frontal cortex determine action timing in rats performing a waiting task. Electrophysiological recordings from two regions necessary for this behavior, medial prefrontal cortex (mPFC) and secondary motor cortex (M2), revealed an unexpected functional dissociation. Both areas encoded deterministic biases in action timing, but only M2 neurons reflected stochastic trial-by-trial fluctuations. This differential coding was reflected in distinct timescales of neural dynamics in the two frontal cortical areas. These results suggest a two-stage model in which stochastic components of action timing decisions are injected by circuits downstream of those carrying deterministic bias signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Uncertainty Reduction for Stochastic Processes on Complex Networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Castellano, Claudio

2018-05-01

Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.

Stochastic modification of the Schrödinger-Newton equation

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Modeling of stochastic motion of bacteria propelled spherical microbeads

NASA Astrophysics Data System (ADS)

Arabagi, Veaceslav; Behkam, Bahareh; Cheung, Eugene; Sitti, Metin

2011-06-01

This work proposes a stochastic dynamic model of bacteria propelled spherical microbeads as potential swimming microrobotic bodies. Small numbers of S. marcescens bacteria are attached with their bodies to surfaces of spherical microbeads. Average-behavior stochastic models that are normally adopted when studying such biological systems are generally not effective for cases in which a small number of agents are interacting in a complex manner, hence a stochastic model is proposed to simulate the behavior of 8-41 bacteria assembled on a curved surface. Flexibility of the flagellar hook is studied via comparing simulated and experimental results for scenarios of increasing bead size and the number of attached bacteria on a bead. Although requiring more experimental data to yield an exact, certain flagellar hook stiffness value, the examined results favor a stiffer flagella. The stochastic model is intended to be used as a design and simulation tool for future potential targeted drug delivery and disease diagnosis applications of bacteria propelled microrobots.

Transition of Femtosecond-Filament-Solid Interactions from Single to Multiple Filament Regime

DOE PAGES

Skrodzki, P. J.; Burger, M.; Jovanovic, I.

2017-10-06

High-peak-power fs-laser filaments offer unique characteristics attractive to remote sensing via techniques such as remote laser-induced breakdown spectroscopy (R-LIBS). The dynamics of several ablation mechanisms following the interaction between a filament and a solid determines the emission strength and reproducibility of target plasma, which is of relevance for R-LIBS applications. Here, we investigate the space- and time-resolved dynamics of ionic and atomic emission from copper as well as the surrounding atmosphere in order to understand limitations of fs-filament-ablation for standoff energy delivery. Furthermore, we probe the shock front produced from filament-target interaction using time-resolved shadowgraphy and infer laser-material coupling efficienciesmore » for both single and multiple filament regimes through analysis of shock expansion with the Sedov model for point detonation. The results provide insight into plasma structure for the range of peak powers up to 30 times the critical power for filamentation P cr. Despite the stochastic nucleation of multiple filaments at peak-powers greater than 16 P cr, emission of ionic and neutral species increases with pump beam intensity, and short-lived nitrogen emission originating from the ambient is consistently observed. Ultimately, results suggest favorable scaling of emission intensity from target species on the laser pump energy, furthering the prospects for use of filament-solid interactions for remote sensing.« less

Transition of Femtosecond-Filament-Solid Interactions from Single to Multiple Filament Regime

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

Skrodzki, P. J.; Burger, M.; Jovanovic, I.

High-peak-power fs-laser filaments offer unique characteristics attractive to remote sensing via techniques such as remote laser-induced breakdown spectroscopy (R-LIBS). The dynamics of several ablation mechanisms following the interaction between a filament and a solid determines the emission strength and reproducibility of target plasma, which is of relevance for R-LIBS applications. Here, we investigate the space- and time-resolved dynamics of ionic and atomic emission from copper as well as the surrounding atmosphere in order to understand limitations of fs-filament-ablation for standoff energy delivery. Furthermore, we probe the shock front produced from filament-target interaction using time-resolved shadowgraphy and infer laser-material coupling efficienciesmore » for both single and multiple filament regimes through analysis of shock expansion with the Sedov model for point detonation. The results provide insight into plasma structure for the range of peak powers up to 30 times the critical power for filamentation P cr. Despite the stochastic nucleation of multiple filaments at peak-powers greater than 16 P cr, emission of ionic and neutral species increases with pump beam intensity, and short-lived nitrogen emission originating from the ambient is consistently observed. Ultimately, results suggest favorable scaling of emission intensity from target species on the laser pump energy, furthering the prospects for use of filament-solid interactions for remote sensing.« less

Pump-probe surface photovoltage spectroscopy measurements on semiconductor epitaxial layers.

PubMed

Jana, Dipankar; Porwal, S; Sharma, T K; Kumar, Shailendra; Oak, S M

2014-04-01

Pump-probe Surface Photovoltage Spectroscopy (SPS) measurements are performed on semiconductor epitaxial layers. Here, an additional sub-bandgap cw pump laser beam is used in a conventional chopped light geometry SPS setup under the pump-probe configuration. The main role of pump laser beam is to saturate the sub-bandgap localized states whose contribution otherwise swamp the information related to the bandgap of material. It also affects the magnitude of Dember voltage in case of semi-insulating (SI) semiconductor substrates. Pump-probe SPS technique enables an accurate determination of the bandgap of semiconductor epitaxial layers even under the strong influence of localized sub-bandgap states. The pump beam is found to be very effective in suppressing the effect of surface/interface and bulk trap states. The overall magnitude of SPV signal is decided by the dependence of charge separation mechanisms on the intensity of the pump beam. On the contrary, an above bandgap cw pump laser can be used to distinguish the signatures of sub-bandgap states by suppressing the band edge related feature. Usefulness of the pump-probe SPS technique is established by unambiguously determining the bandgap of p-GaAs epitaxial layers grown on SI-GaAs substrates, SI-InP wafers, and p-GaN epilayers grown on Sapphire substrates.

Habitat connectivity and in-stream vegetation control temporal variability of benthic invertebrate communities.

PubMed

Huttunen, K-L; Mykrä, H; Oksanen, J; Astorga, A; Paavola, R; Muotka, T

2017-05-03

One of the key challenges to understanding patterns of β diversity is to disentangle deterministic patterns from stochastic ones. Stochastic processes may mask the influence of deterministic factors on community dynamics, hindering identification of the mechanisms causing variation in community composition. We studied temporal β diversity (among-year dissimilarity) of macroinvertebrate communities in near-pristine boreal streams across 14 years. To assess whether the observed β diversity deviates from that expected by chance, and to identify processes (deterministic vs. stochastic) through which different explanatory factors affect community variability, we used a null model approach. We observed that at the majority of sites temporal β diversity was low indicating high community stability. When stochastic variation was unaccounted for, connectivity was the only variable explaining temporal β diversity, with weakly connected sites exhibiting higher community variability through time. After accounting for stochastic effects, connectivity lost importance, suggesting that it was related to temporal β diversity via random colonization processes. Instead, β diversity was best explained by in-stream vegetation, community variability decreasing with increasing bryophyte cover. These results highlight the potential of stochastic factors to dampen the influence of deterministic processes, affecting our ability to understand and predict changes in biological communities through time.

Predicting evolutionary rescue via evolving plasticity in stochastic environments

PubMed Central

Baskett, Marissa L.

2016-01-01

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

Spatially heterogeneous stochasticity and the adaptive diversification of dormancy.

PubMed

Rajon, E; Venner, S; Menu, F

2009-10-01

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

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

NASA Astrophysics Data System (ADS)

Lacroix, Denis

2005-06-01

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

Engineering approach for cost effective operation of industrial pump systems

NASA Astrophysics Data System (ADS)

Krickis, O.; Oleksijs, R.

2017-10-01

Power plants operators are persuaded to operate the main equipment such as centrifugal pumps in economically effective way. The operation of pump sets of district heating network at power plants should be done according to prescriptions of the original equipment manufacturer with further implementation of these requirements to distributed control system of the plant. In order to operate industrial pump sets with a small number of malfunctions is necessary to control the duty point of pump sets in H-Q coordinates, which could be complex task in some installations. Alternatively, pump operation control could be organized in H-n (head vs rpm) coordinates, utilizing pressure transmitters in pressure pipeline and value of rpm from variable speed driver. Safe operation range of the pump has to be limited with system parabolas, which prevents the duty point location outside of the predefined operation area. The particular study demonstrates the engineering approach for pump’s safe operation control development in MATLAB/Simulink environment, which allows to simulate the operation of the pump at different capacities in hydraulic system with variable characteristic and to predefine the conditions for efficient simultaneous pump operation in parallel connection.

Study on the threshold of a stochastic SIR epidemic model and its extensions

NASA Astrophysics Data System (ADS)

Zhao, Dianli

2016-09-01

This paper provides a simple but effective method for estimating the threshold of a class of the stochastic epidemic models by use of the nonnegative semimartingale convergence theorem. Firstly, the threshold R0SIR is obtained for the stochastic SIR model with a saturated incidence rate, whose value is below 1 or above 1 will completely determine the disease to go extinct or prevail for any size of the white noise. Besides, when R0SIR > 1 , the system is proved to be convergent in time mean. Then, the threshold of the stochastic SIVS models with or without saturated incidence rate are also established by the same method. Comparing with the previously-known literatures, the related results are improved, and the method is simpler than before.

Response analysis of a class of quasi-linear systems with fractional derivative excited by Poisson white noise

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

Yang, Yongge; Xu, Wei, E-mail: weixu@nwpu.edu.cn; Yang, Guidong

The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractionalmore » order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.« less

A new design of robust H∞ sliding mode control for uncertain stochastic T-S fuzzy time-delay systems.

PubMed

Gao, Qing; Feng, Gang; Xi, Zhiyu; Wang, Yong; Qiu, Jianbin

2014-09-01

In this paper, a novel dynamic sliding mode control scheme is proposed for a class of uncertain stochastic nonlinear time-delay systems represented by Takagi-Sugeno fuzzy models. The key advantage of the proposed scheme is that two very restrictive assumptions in most existing sliding mode control approaches for stochastic fuzzy systems have been removed. It is shown that the closed-loop control system trajectories can be driven onto the sliding surface in finite time almost certainly. It is also shown that the stochastic stability of the resulting sliding motion can be guaranteed in terms of linear matrix inequalities; moreover, the sliding-mode controller can be obtained simultaneously. Simulation results illustrating the advantages and effectiveness of the proposed approaches are also provided.

Uncertainty-accounting environmental policy and management of water systems.

PubMed

Baresel, Christian; Destouni, Georgia

2007-05-15

Environmental policies for water quality and ecosystem management do not commonly require explicit stochastic accounts of uncertainty and risk associated with the quantification and prediction of waterborne pollutant loads and abatement effects. In this study, we formulate and investigate a possible environmental policy that does require an explicit stochastic uncertainty account. We compare both the environmental and economic resource allocation performance of such an uncertainty-accounting environmental policy with that of deterministic, risk-prone and risk-averse environmental policies under a range of different hypothetical, yet still possible, scenarios. The comparison indicates that a stochastic uncertainty-accounting policy may perform better than deterministic policies over a range of different scenarios. Even in the absence of reliable site-specific data, reported literature values appear to be useful for such a stochastic account of uncertainty.

Mechanisms of Stochastic Diffusion of Energetic Ions in Spherical Tori

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

Ya.I. Kolesnichenko; R.B. White; Yu.V. Yakovenko

Stochastic diffusion of the energetic ions in spherical tori is considered. The following issues are addressed: (I) Goldston-White-Boozer diffusion in a rippled field; (ii) cyclotron-resonance-induced diffusion caused by the ripple; (iii) effects of non-conservation of the magnetic moment in an axisymmetric field. It is found that the stochastic diffusion in spherical tori with a weak magnetic field has a number of peculiarities in comparison with conventional tokamaks; in particular, it is characterized by an increased role of mechanisms associated with non-conservation of the particle magnetic moment. It is concluded that in current experiments on National Spherical Torus eXperiment (NSTX) themore » stochastic diffusion does not have a considerable influence on the confinement of energetic ions.« less

Simulated effects of ground-water management scenarios on the Santa Fe group aquifer system, Middle Rio Grande Basin, New Mexico, 2001-40

USGS Publications Warehouse

Bexfield, Laura M.; McAda, Douglas P.

2003-01-01

Future conditions in the Santa Fe Group aquifer system through 2040 were simulated using the most recent revision of the U.S. Geological Survey groundwater- flow model for the Middle Rio Grande Basin. Three simulations were performed to investigate the likely effects of different scenarios of future groundwater pumping by the City of Albuquerque on the ground-water system. For simulation I, pumping was held constant at known year-2000 rates. For simulation II, pumping was increased to simulate the use of pumping to meet all projected city water demand through 2040. For simulation III, pumpingwas reduced in accordance with a plan by the City of Albuquerque to use surfacewater to meet most of the projectedwater demand. The simulations indicate that for each of the three pumping scenarios, substantial additional watertable declines would occur in some areas of the basin through 2040. However, the reduced pumping scenario of simulation III also results in water-table rise over a broad area of the city. All three scenarios indicate that the contributions of aquifer storage and river leakage to the ground-water system would change between 2000 and 2040. Comparisons among the results for simulations I, II, and III indicate that the various pumping scenarios have substantially different effects on water-level declines in the Albuquerque area and on the contribution of each water-budget component to the total budget for the ground-water system. Between 2000 and 2040, water-level declines for continued pumping at year-2000 rates are as much as 120 feet greater than for reduced pumping; water-level declines for increased pumping to meet all projected city demand are as much as 160 feet greater. Over the same time period, reduced pumping results in retention in aquifer storage of about 1,536,000 acre-feet of ground water as compared with continued pumping at year- 2000 rates and of about 2,257,000 acre-feet as compared with increased pumping. The quantity of water retained in the Rio Grande as a result of reduced pumping and the associated decrease in induced recharge from the river is about 731,000 acre-feet as compared with continued pumping at year-2000 rates and about 872,000 acre-feet as compared with increased pumping. Reduced pumping results in slight increases in the quantity of water lost from the groundwater system to evapotranspiration and agriculturaldrain flow compared with the other pumping scenarios.

An approach to assessing stochastic radiogenic risk in medical imaging

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

Wolbarst, Anthony B.; Hendee, William R.; Department of Radiology, Mayo Clinic, Rochester, Minnesota 55901

2011-12-15

Purpose: This letter suggests a formalism, the medical effective dose (MED), that is suitable for assessing stochastic radiogenic risks in diagnostic medical procedures. Methods: The MED is derived from radiobiological and probabilistic first principals, including: (1) The independence of radiation-induced biological effects in neighboring voxels at low doses; (2) the linear no-threshold assumption for stochastic radiation injury (although other dose-response relationships could be incorporated, instead); (3) the best human radiation dose-response data currently available; and (4) the built-in possibility that the carcinogenic risk to an irradiated organ may depend on its volume. The MED involves a dose-risk summation over irradiatedmore » voxels at high spatial resolution; it reduces to the traditional effective dose when every organ is irradiated uniformly and when the dependence of risk on organ volumes is ignored. Standard relative-risk tissue weighting factors can be used with the MED approach until more refined data become available. Results: The MED is intended for clinical and phantom dosimetry, and it provides an estimate of overall relative radiogenic stochastic risk for any given dose distribution. A result of the MED derivation is that the stochastic risk may increase with the volume of tissue (i.e., the number of cells) irradiated, a feature that can be activated when forthcoming radiobiological research warrants it. In this regard, the MED resembles neither the standard effective dose (E) nor the CT dose index (CTDI), but it is somewhat like the CT dose-length product (DLP). Conclusions: The MED is a novel, probabilistically and biologically based means of estimating stochastic-risk-weighted doses associated with medical imaging. Built in, ab initio, is the ability to link radiogenic risk to organ volume and other clinical factors. It is straightforward to implement when medical dose distributions are available, provided that one is content, for the time being, to accept the relative tissue weighting factors published by the International Commission of Radiological Protection (ICRP). It requires no new radiobiological data and avoids major problems encountered by the E, CTDI, and CT-E formalisms. It makes possible relative inter-patient dosimetry, and also realistic intercomparisons of stochastic risks from different protocols that yield images of comparable quality.« less

Assessment of BTEX-induced health risk under multiple uncertainties at a petroleum-contaminated site: An integrated fuzzy stochastic approach

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Huang, Guo H.

2011-12-01

Groundwater pollution has gathered more and more attention in the past decades. Conducting an assessment of groundwater contamination risk is desired to provide sound bases for supporting risk-based management decisions. Therefore, the objective of this study is to develop an integrated fuzzy stochastic approach to evaluate risks of BTEX-contaminated groundwater under multiple uncertainties. It consists of an integrated interval fuzzy subsurface modeling system (IIFMS) and an integrated fuzzy second-order stochastic risk assessment (IFSOSRA) model. The IIFMS is developed based on factorial design, interval analysis, and fuzzy sets approach to predict contaminant concentrations under hybrid uncertainties. Two input parameters (longitudinal dispersivity and porosity) are considered to be uncertain with known fuzzy membership functions, and intrinsic permeability is considered to be an interval number with unknown distribution information. A factorial design is conducted to evaluate interactive effects of the three uncertain factors on the modeling outputs through the developed IIFMS. The IFSOSRA model can systematically quantify variability and uncertainty, as well as their hybrids, presented as fuzzy, stochastic and second-order stochastic parameters in health risk assessment. The developed approach haw been applied to the management of a real-world petroleum-contaminated site within a western Canada context. The results indicate that multiple uncertainties, under a combination of information with various data-quality levels, can be effectively addressed to provide supports in identifying proper remedial efforts. A unique contribution of this research is the development of an integrated fuzzy stochastic approach for handling various forms of uncertainties associated with simulation and risk assessment efforts.

Impact of pumping configuration on all-fibered femtosecond chirped pulse amplification

NASA Astrophysics Data System (ADS)

Lecourt, Jean-Bernard; Duterte, Charles; Bertrand, Anthony; Liégeois, Flavien; Hernandez, Yves; Giannone, Domenico

2008-04-01

We experimentally compared the co- and counter-propagative pumping scheme for the amplification of ultra-short optical pulses. According to pumping direction we show that optical pulses with a duration of 75 fs and 100mW of average output power can be obtained for co-propagative pumping, while pulse duration is never shorter than 400 fs for the counter-propagative case. We show that the impact of non-linear effects on pulse propagation is different for the two pumping configurations. We assume that Self Phase Modulation (SPM) is the main effect in the copropagative case, whereas the impact of Stimulated Raman Scattering is bigger for the counter-propagative case.

Stochastic demography and the neutral substitution rate in class-structured populations.

PubMed

Lehmann, Laurent

2014-05-01

The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

The effect of surface wettability on the performance of a piezoelectric membrane pump

NASA Astrophysics Data System (ADS)

Wang, Jiantao; Yang, Zhigang; Liu, Yong; Shen, Yanhu; Chen, Song; Yu, Jianqun

2018-04-01

In this paper, we studied the effect of surface wettability on the bubble tolerance of a piezoelectric membrane pump, by applying the super-hydrophilic or super-hydrophobic surface to the key elements on the pump. Wettability for the flow passage surface has a direct influence on the air bubbles flowing in the fluid. Based on the existing research results, we first analyzed the relationship between the flow passage surface of the piezoelectric pump and the bubbles in the fluid. Then we made three prototypes where pump chamber walls and valve plate surfaces were given different wettability treatments. After the output performance test, results demonstrate that giving super-hydrophilic treatment on the surface of key elements can improve the bubble tolerance of piezoelectric pump; in contrast, giving super-hydrophobic treatment will reduce the bubble tolerance.

Methods and apparatus of entangled photon generation using four-wave mixing

DOEpatents

Camacho, Ryan

2016-02-23

A non-linear optical device is provided. The device comprises an optical disk or ring microresonator fabricated from a material that exhibits an optical nonlinearity able to produce degenerate four-wave mixing (FWM) in response to a pump beam having a pump frequency in a specified effective range. The microresonator is conformed to exhibit an angular group velocity minimum at a pump frequency within the specified effective range such that there is zero angular group velocity dispersion at the pump frequency. We refer to such a pump frequency as the "zero dispersion frequency". In embodiments, excitation of the resonator by a pump beam of sufficient intensity at the zero-dispersion frequency causes the resonator to emit a frequency comb of entangled photon pairs wherein the respective frequencies in each pair are symmetrically placed about the zero-dispersion frequency.

Stochastic sensitivity measure for mistuned high-performance turbines

NASA Technical Reports Server (NTRS)

Murthy, Durbha V.; Pierre, Christophe

1992-01-01

A stochastic measure of sensitivity is developed in order to predict the effects of small random blade mistuning on the dynamic aeroelastic response of turbomachinery blade assemblies. This sensitivity measure is based solely on the nominal system design (i.e., on tuned system information), which makes it extremely easy and inexpensive to calculate. The measure has the potential to become a valuable design tool that will enable designers to evaluate mistuning effects at a preliminary design stage and thus assess the need for a full mistuned rotor analysis. The predictive capability of the sensitivity measure is illustrated by examining the effects of mistuning on the aeroelastic modes of the first stage of the oxidizer turbopump in the Space Shuttle Main Engine. Results from a full analysis mistuned systems confirm that the simple stochastic sensitivity measure predicts consistently the drastic changes due to misturning and the localization of aeroelastic vibration to a few blades.

Interplay between social debate and propaganda in an opinion formation model

NASA Astrophysics Data System (ADS)

Gimenez, M. C.; Revelli, J. A.; Lama, M. S. de la; Lopez, J. M.; Wio, H. S.

2013-01-01

We introduce a simple model of opinion dynamics in which a two-state agent modified Sznajd model evolves due to the simultaneous action of stochastic driving and a periodic signal. The stochastic effect mimics a social temperature, so the agents may adopt decisions in support for or against some opinion or position, according to a modified Sznajd rule with a varying probability. The external force represents a simplified picture by which society feels the influence of the external effects of propaganda. By means of Monte Carlo simulations we have shown the dynamical interplay between the social condition or mood and the external influence, finding a stochastic resonance-like phenomenon when we depict the noise-to-signal ratio as a function of the social temperature. In addition, we have also studied the effects of the system size and the external signal strength on the opinion formation dynamics.

Stochastic resonance in underdamped periodic potential systems with alpha stable Lévy noise

NASA Astrophysics Data System (ADS)

Liu, Ruo-Nan; Kang, Yan-Mei

2018-06-01

In this paper, we investigate the effect of alpha stable Lévy noise with alpha stability index α (0 < α ≤ 2) on stochastic resonance (SR) in underdamped periodic potential systems by the non-perturbative expansion moment method and stochastic simulation. Using the spectral amplification factor as a quantifying index, we find that SR can occur in both sinusoidal potentials and ratchet potentials when α is close to 2, while the resonant effect becomes weaker as the stability index decreases. By means of massive numerical statistics, we ascribe this trend to the typical jumps of non-Gaussian Lévy noise (0 < α < 2), which play a destructive role on the periodicity of the long time mean response. We also disclose that the skewness parameter of Lévy noise has a more notable impact on the resonant effect of the asymmetric ratchet potential than that of the symmetric sinusoidal potential because of symmetry breaking.

Inhibition of the active lymph pump by flow in rat mesenteric lymphatics and thoracic duct

NASA Technical Reports Server (NTRS)

Gashev, Anatoliy A.; Davis, Michael J.; Zawieja, David C.; Delp, M. D. (Principal Investigator)

2002-01-01

There are only a few reports of the influence of imposed flow on an active lymph pump under conditions of controlled intraluminal pressure. Thus, the mechanisms are not clearly defined. Rat mesenteric lymphatics and thoracic ducts were isolated, cannulated and pressurized. Input and output pressures were adjusted to impose various flows. Lymphatic systolic and diastolic diameters were measured and used to determine contraction frequency and pump flow indices. Imposed flow inhibited the active lymph pump in both mesenteric lymphatics and in the thoracic duct. The active pump of the thoracic duct appeared more sensitive to flow than did the active pump of the mesenteric lymphatics. Imposed flow reduced the frequency and amplitude of the contractions and accordingly the active pump flow. Flow-induced inhibition of the active lymph pump followed two temporal patterns. The first pattern was a rapidly developing inhibition of contraction frequency. Upon imposition of flow, the contraction frequency immediately fell and then partially recovered over time during continued flow. This effect was dependent on the magnitude of imposed flow, but did not depend on the direction of flow. The effect also depended upon the rate of change in the direction of flow. The second pattern was a slowly developing reduction of the amplitude of the lymphatic contractions, which increased over time during continued flow. The inhibition of contraction amplitude was dependent on the direction of the imposed flow, but independent of the magnitude of flow. Nitric oxide was partly but not completely responsible for the influence of flow on the mesenteric lymph pump. Exposure to NO mimicked the effects of flow, and inhibition of the NO synthase by N (G)-monomethyl-L-arginine attenuated but did not completely abolish the effects of flow.

Effectiveness of Additives in Improving Fuel Lubricity and Preventing Pump Failure at High Temperature

DTIC Science & Technology

2013-01-01

after pump calibrations , transfer pump blade measurements, injector nozzle tests, pump parts evaluation, and parts conditions photographs are also... Injectors –0 0.53 5,500 0.257 1 2-15293089 DF2 As Purchased 105 (40) 1,000 1,000 Calibration off spec areas–4 Pump Rating–1.04 Failed Injectors –0 0.53...5,500 0.257 2 1-15382732 DF2 As Purchased 135 (57) 1,000 1,000 Calibration off spec areas–4 Pump Rating–1.13 Failed Injectors –0 0.55

Use of randomised controlled trials for producing cost-effectiveness evidence: potential impact of design choices on sample size and study duration.

PubMed

Backhouse, Martin E

2002-01-01

A number of approaches to conducting economic evaluations could be adopted. However, some decision makers have a preference for wholly stochastic cost-effectiveness analyses, particularly if the sampled data are derived from randomised controlled trials (RCTs). Formal requirements for cost-effectiveness evidence have heightened concerns in the pharmaceutical industry that development costs and times might be increased if formal requirements increase the number, duration or costs of RCTs. Whether this proves to be the case or not will depend upon the timing, nature and extent of the cost-effectiveness evidence required. To illustrate how different requirements for wholly stochastic cost-effectiveness evidence could have a significant impact on two of the major determinants of new drug development costs and times, namely RCT sample size and study duration. Using data collected prospectively in a clinical evaluation, sample sizes were calculated for a number of hypothetical cost-effectiveness study design scenarios. The results were compared with a baseline clinical trial design. The sample sizes required for the cost-effectiveness study scenarios were mostly larger than those for the baseline clinical trial design. Circumstances can be such that a wholly stochastic cost-effectiveness analysis might not be a practical proposition even though its clinical counterpart is. In such situations, alternative research methodologies would be required. For wholly stochastic cost-effectiveness analyses, the importance of prior specification of the different components of study design is emphasised. However, it is doubtful whether all the information necessary for doing this will typically be available when product registration trials are being designed. Formal requirements for wholly stochastic cost-effectiveness evidence based on the standard frequentist paradigm have the potential to increase the size, duration and number of RCTs significantly and hence the costs and timelines associated with new product development. Moreover, it is possible to envisage situations where such an approach would be impossible to adopt. Clearly, further research is required into the issue of how to appraise the economic consequences of alternative economic evaluation research strategies.

Estimating Hydraulic Parameters When Poroelastic Effects Are Significant

USGS Publications Warehouse

Berg, S.J.; Hsieh, P.A.; Illman, W.A.

2011-01-01

For almost 80 years, deformation-induced head changes caused by poroelastic effects have been observed during pumping tests in multilayered aquifer-aquitard systems. As water in the aquifer is released from compressive storage during pumping, the aquifer is deformed both in the horizontal and vertical directions. This deformation in the pumped aquifer causes deformation in the adjacent layers, resulting in changes in pore pressure that may produce drawdown curves that differ significantly from those predicted by traditional groundwater theory. Although these deformation-induced head changes have been analyzed in several studies by poroelasticity theory, there are at present no practical guidelines for the interpretation of pumping test data influenced by these effects. To investigate the impact that poroelastic effects during pumping tests have on the estimation of hydraulic parameters, we generate synthetic data for three different aquifer-aquitard settings using a poroelasticity model, and then analyze the synthetic data using type curves and parameter estimation techniques, both of which are based on traditional groundwater theory and do not account for poroelastic effects. Results show that even when poroelastic effects result in significant deformation-induced head changes, it is possible to obtain reasonable estimates of hydraulic parameters using methods based on traditional groundwater theory, as long as pumping is sufficiently long so that deformation-induced effects have largely dissipated. ?? 2011 The Author(s). Journal compilation ?? 2011 National Ground Water Association.

Heat pump evaluation for Space Station ATCS evolution

NASA Technical Reports Server (NTRS)

Ames, Brian E.; Petete, Patricia A.

1991-01-01

A preliminary feasibility assessment of the application of a vapor compression heat pump to the Active Thermal Control System (ATCS) of SSF is presented. This paper focuses on the methodology of raising the surface temperature of the radiators for improved heat rejection. Some of the effects of the vapor compression cycle on SSF examined include heat pump integration into ATCS, constraints on the heat pump operating parameters, and heat pump performance enhancements.

New Discrete Fibonacci Charge Pump Design, Evaluation and Measurement

NASA Astrophysics Data System (ADS)

Matoušek, David; Hospodka, Jiří; Šubrt, Ondřej

2017-06-01

This paper focuses on the practical aspects of the realisation of Dickson and Fibonacci charge pumps. Standard Dickson charge pump circuit solution and new Fibonacci charge pump implementation are compared. Both charge pumps were designed and then evaluated by LTspice XVII simulations and realised in a discrete form on printed circuit board (PCB). Finally, the key parameters as the output voltage, efficiency, rise time, variable power supply and clock frequency effects were measured.

Terahertz Optical Gain Based on Intersubband Transitions in Optically-Pumped Semiconductor Quantum Wells: Coherent Pumped-Probe Interactions

NASA Technical Reports Server (NTRS)

Liu, Ansheng; Ning, Cun-Zheng

1999-01-01

Terahertz optical gain due to intersubband transitions in optically-pumped semiconductor quantum wells (QW's) is calculated nonperturbatively. We solve the pump- field-induced nonequilibrium distribution function for each subband of the QW system from a set of rate equations that include both intrasubband and intersubband relaxation processes. The gain arising from population inversion and stimulated Raman processes is calculated in a unified manner. We show that the coherent pump and signal wave interactions contribute significantly to the THz gain. Because of the optical Stark effect and pump-induced population redistribution, optical gain saturation at larger pump intensities is predicted.

Representing pump-capacity relations in groundwater simulation models

USGS Publications Warehouse

Konikow, Leonard F.

2010-01-01

The yield (or discharge) of constant-speed pumps varies with the total dynamic head (or lift) against which the pump is discharging. The variation in yield over the operating range of the pump may be substantial. In groundwater simulations that are used for management evaluations or other purposes, where predictive accuracy depends on the reliability of future discharge estimates, model reliability may be enhanced by including the effects of head-capacity (or pump-capacity) relations on the discharge from the well. A relatively simple algorithm has been incorporated into the widely used MODFLOW groundwater flow model that allows a model user to specify head-capacity curves. The algorithm causes the model to automatically adjust the pumping rate each time step to account for the effect of drawdown in the cell and changing lift, and will shut the pump off if lift exceeds a critical value. The algorithm is available as part of a new multinode well package (MNW2) for MODFLOW.

Representing pump-capacity relations in groundwater simulati on models

USGS Publications Warehouse

Konikow, Leonard F.

2010-01-01

The yield (or discharge) of constant-speed pumps varies with the total dynamic head (or lift) against which the pump is discharging. The variation in yield over the operating range of the pump may be substantial. In groundwater simulations that are used for management evaluations or other purposes, where predictive accuracy depends on the reliability of future discharge estimates, model reliability may be enhanced by including the effects of head-capacity (or pump-capacity) relations on the discharge from the well. A relatively simple algorithm has been incorporated into the widely used MODFLOW groundwater flow model that allows a model user to specify head-capacity curves. The algorithm causes the model to automatically adjust the pumping rate each time step to account for the effect of drawdown in the cell and changing lift, and will shut the pump off if lift exceeds a critical value. The algorithm is available as part of a new multinode well package (MNW2) for MODFLOW. ?? 2009 National Ground Water Association.

Effect of wetting-layer density of states on the gain and phase recovery dynamics of quantum-dot semiconductor optical amplifiers

NASA Astrophysics Data System (ADS)

Kim, Jungho; Yu, Bong-Ahn

2015-03-01

We numerically investigate the effect of the wetting-layer (WL) density of states on the gain and phase recovery dynamics of quantum-dot semiconductor optical amplifiers in both electrical and optical pumping schemes by solving 1088 coupled rate equations. The temporal variations of the ultrafast gain and phase recovery responses at the ground state (GS) are calculated as a function of the WL density of states. The ultrafast gain recovery responses do not significantly depend on the WL density of states in the electrical pumping scheme and the three optical pumping schemes such as the optical pumping to the WL, the optical pumping to the excited state ensemble, and the optical pumping to the GS ensemble. The ultrafast phase recovery responses are also not significantly affected by the WL density of states except the optical pumping to the WL, where the phase recovery component caused by the WL becomes slowed down as the WL density of states increases.

Dual-channel current valve in a three terminal zigzag graphene nanoribbon junction

NASA Astrophysics Data System (ADS)

Zhang, L.

2017-02-01

We theoretically propose a dual-channel current valve based on a three terminal zigzag graphene nanoribbon (ZGNR) junction driven by three asymmetric time-dependent pumping potentials. By means of the Keldysh Green’s function method, we show that two asymmetric charge currents can be pumped in the different left-right terminals of the device at a zero bias, which mainly stems from the single photon-assisted pumping approximation and the valley valve effect in a ZGNR p-n junction. The ON and OFF states of pumped charge currents are crucially dependent on the even-odd chain widths of the three electrodes, the pumping frequency, the lattice potential and the Fermi level. Two-tunneling spin valves are also considered to spatially separate and detect 100% polarized spin currents owing to the combined spin pump effect and the valley selective transport in a three terminal ZGNR ferromagnetic junction. Our investigations might be helpful to control the spatial and spin degrees of freedom of electrons in graphene pumping devices.

Free energy dissipation of the spontaneous gating of a single voltage-gated potassium channel.

PubMed

Wang, Jia-Zeng; Wang, Rui-Zhen

2018-02-01

Potassium channels mainly contribute to the resting potential and re-polarizations, with the potassium electrochemical gradient being maintained by the pump Na + /K + -ATPase. In this paper, we construct a stochastic model mimicking the kinetics of a potassium channel, which integrates temporal evolving of the membrane voltage and the spontaneous gating of the channel. Its stationary probability density functions (PDFs) are found to be singular at the boundaries, which result from the fact that the evolving rates of voltage are greater than the gating rates of the channel. We apply PDFs to calculate the power dissipations of the potassium current, the leakage, and the gating currents. On a physical perspective, the essential role of the system is the K + -battery charging the leakage (L-)battery. A part of power will inevitably be dissipated among the process. So, the efficiency of energy transference is calculated.

Free energy dissipation of the spontaneous gating of a single voltage-gated potassium channel

NASA Astrophysics Data System (ADS)

Wang, Jia-Zeng; Wang, Rui-Zhen

2018-02-01

Potassium channels mainly contribute to the resting potential and re-polarizations, with the potassium electrochemical gradient being maintained by the pump Na+/K+-ATPase. In this paper, we construct a stochastic model mimicking the kinetics of a potassium channel, which integrates temporal evolving of the membrane voltage and the spontaneous gating of the channel. Its stationary probability density functions (PDFs) are found to be singular at the boundaries, which result from the fact that the evolving rates of voltage are greater than the gating rates of the channel. We apply PDFs to calculate the power dissipations of the potassium current, the leakage, and the gating currents. On a physical perspective, the essential role of the system is the K+-battery charging the leakage (L-)battery. A part of power will inevitably be dissipated among the process. So, the efficiency of energy transference is calculated.

Multi-pulse pumping for far-field super-resolution imaging

NASA Astrophysics Data System (ADS)

Requena, Sebastian; Raut, Sangram; Doan, Hung; Kimball, Joe; Fudala, Rafal; Borejdo, Julian; Gryczynski, Ignacy; Strzhemechny, Yuri; Gryczynski, Zygmunt

2016-02-01

Recently, far-field optical imaging with a resolution significantly beyond diffraction limit has attracted tremendous attention allowing for high resolution imaging in living objects. Various methods have been proposed that are divided in to two basic approaches; deterministic super-resolution like STED or RESOLFT and stochastic super-resolution like PALM or STORM. We propose to achieve super-resolution in far-field fluorescence imaging by the use of controllable (on-demand) bursts of pulses that can change the fluorescence signal of long-lived component over one order of magnitude. We demonstrate that two beads, one labeled with a long-lived dye and another with a short-lived dye, separated by a distance lower than 100 nm can be easily resolved in a single experiment. The proposed method can be used to separate two biological structures in a cell by targeting them with two antibodies labeled with long-lived and short-lived fluorophores.

Biopolymer dynamics driven by helical flagella

NASA Astrophysics Data System (ADS)

Balin, Andrew K.; Zöttl, Andreas; Yeomans, Julia M.; Shendruk, Tyler N.

2017-11-01

Microbial flagellates typically inhabit complex suspensions of polymeric material which can impact the swimming speed of motile microbes, filter feeding of sessile cells, and the generation of biofilms. There is currently a need to better understand how the fundamental dynamics of polymers near active cells or flagella impacts these various phenomena, in particular, the hydrodynamic and steric influence of a rotating helical filament on suspended polymers. Our Stokesian dynamics simulations show that as a stationary rotating helix pumps fluid along its long axis, polymers migrate radially inward while being elongated. We observe that the actuation of the helix tends to increase the probability of finding polymeric material within its pervaded volume. This accumulation of polymers within the vicinity of the helix is stronger for longer polymers. We further analyze the stochastic work performed by the helix on the polymers and show that this quantity is positive on average and increases with polymer contour length.

Turbulence hierarchy in a random fibre laser

PubMed Central

González, Iván R. Roa; Lima, Bismarck C.; Pincheira, Pablo I. R.; Brum, Arthur A.; Macêdo, Antônio M. S.; Vasconcelos, Giovani L.; de S. Menezes, Leonardo; Raposo, Ernesto P.; Gomes, Anderson S. L.; Kashyap, Raman

2017-01-01

Turbulence is a challenging feature common to a wide range of complex phenomena. Random fibre lasers are a special class of lasers in which the feedback arises from multiple scattering in a one-dimensional disordered cavity-less medium. Here we report on statistical signatures of turbulence in the distribution of intensity fluctuations in a continuous-wave-pumped erbium-based random fibre laser, with random Bragg grating scatterers. The distribution of intensity fluctuations in an extensive data set exhibits three qualitatively distinct behaviours: a Gaussian regime below threshold, a mixture of two distributions with exponentially decaying tails near the threshold and a mixture of distributions with stretched-exponential tails above threshold. All distributions are well described by a hierarchical stochastic model that incorporates Kolmogorov’s theory of turbulence, which includes energy cascade and the intermittence phenomenon. Our findings have implications for explaining the remarkably challenging turbulent behaviour in photonics, using a random fibre laser as the experimental platform. PMID:28561064

Random attractor of non-autonomous stochastic Boussinesq lattice system

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

Zhao, Min, E-mail: zhaomin1223@126.com; Zhou, Shengfan, E-mail: zhoushengfan@yahoo.com

2015-09-15

In this paper, we first consider the existence of tempered random attractor for second-order non-autonomous stochastic lattice dynamical system of nonlinear Boussinesq equations effected by time-dependent coupled coefficients and deterministic forces and multiplicative white noise. Then, we establish the upper semicontinuity of random attractors as the intensity of noise approaches zero.

Parameter-based stochastic simulation of selection and breeding for multiple traits

Treesearch

Jennifer Myszewski; Thomas Byram; Floyd Bridgwater

2006-01-01

To increase the adaptability and economic value of plantations, tree improvement professionals often manage multiple traits in their breeding programs. When these traits are unfavorably correlated, breeders must weigh the economic importance of each trait and select for a desirable aggregate phenotype. Stochastic simulation allows breeders to test the effects of...

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models.

PubMed

Butler, T; Graham, L; Estep, D; Dawson, C; Westerink, J J

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

NASA Astrophysics Data System (ADS)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Fluctuations and Noise in Stochastic Spread of Respiratory Infection Epidemics in Social Networks

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Emelyanova, Natalya; Demin, Sergey; Gafarov, Fail; Hänggi, Peter; Yulmetyeva, Dinara

2003-05-01

For the analysis of epidemic and disease dynamics complexity, it is necessary to understand the basic principles and notions of its spreading in long-time memory media. Here we considering the problem from a theoretical and practical viewpoint, presenting the quantitative evidence confirming the existence of stochastic long-range memory and robust chaos in a real time series of respiratory infections of human upper respiratory track. In this work we present a new statistical method of analyzing the spread of grippe and acute respiratory track infections epidemic process of human upper respiratory track by means of the theory of discrete non-Markov stochastic processes. We use the results of our recent theory (Phys. Rev. E 65, 046107 (2002)) for the study of statistical effects of memory in real data series, describing the epidemic dynamics of human acute respiratory track infections and grippe. The obtained results testify to an opportunity of the strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks with a view to time discreteness and effects of statistical memory.

Stochastic resonance on a modular neuronal network of small-world subnetworks with a subthreshold pacemaker

NASA Astrophysics Data System (ADS)

Yu, Haitao; Wang, Jiang; Liu, Chen; Deng, Bin; Wei, Xile

2011-12-01

We study the phenomenon of stochastic resonance on a modular neuronal network consisting of several small-world subnetworks with a subthreshold periodic pacemaker. Numerical results show that the correlation between the pacemaker frequency and the dynamical response of the network is resonantly dependent on the intensity of additive spatiotemporal noise. This effect of pacemaker-driven stochastic resonance of the system depends extensively on the local and the global network structure, such as the intra- and inter-coupling strengths, rewiring probability of individual small-world subnetwork, the number of links between different subnetworks, and the number of subnetworks. All these parameters play a key role in determining the ability of the network to enhance the noise-induced outreach of the localized subthreshold pacemaker, and only they bounded to a rather sharp interval of values warrant the emergence of the pronounced stochastic resonance phenomenon. Considering the rather important role of pacemakers in real-life, the presented results could have important implications for many biological processes that rely on an effective pacemaker for their proper functioning.

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

NASA Technical Reports Server (NTRS)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation

NASA Astrophysics Data System (ADS)

Sakellariou, J. S.; Fassois, S. D.

2006-11-01

A stochastic output error (OE) vibration-based methodology for damage detection and assessment (localization and quantification) in structures under earthquake excitation is introduced. The methodology is intended for assessing the state of a structure following potential damage occurrence by exploiting vibration signal measurements produced by low-level earthquake excitations. It is based upon (a) stochastic OE model identification, (b) statistical hypothesis testing procedures for damage detection, and (c) a geometric method (GM) for damage assessment. The methodology's advantages include the effective use of the non-stationary and limited duration earthquake excitation, the handling of stochastic uncertainties, the tackling of the damage localization and quantification subproblems, the use of "small" size, simple and partial (in both the spatial and frequency bandwidth senses) identified OE-type models, and the use of a minimal number of measured vibration signals. Its feasibility and effectiveness are assessed via Monte Carlo experiments employing a simple simulation model of a 6 storey building. It is demonstrated that damage levels of 5% and 20% reduction in a storey's stiffness characteristics may be properly detected and assessed using noise-corrupted vibration signals.

46 CFR 185.512 - Recommended emergency instructions format.

Code of Federal Regulations, 2011 CFR

2011-10-01

... in bilges. Use power driven bilge pump, hand pump, and buckets to dewater. (iii) Align fire pumps to... fixed extinguishing system if installed. (v) Maneuver vessel to minimize effect of wind on fire. (vi) If...

Stochastic stability of parametrically excited random systems

NASA Astrophysics Data System (ADS)

Labou, M.

2004-01-01

Multidegree-of-freedom dynamic systems subjected to parametric excitation are analyzed for stochastic stability. The variation of excitation intensity with time is described by the sum of a harmonic function and a stationary random process. The stability boundaries are determined by the stochastic averaging method. The effect of random parametric excitation on the stability of trivial solutions of systems of differential equations for the moments of phase variables is studied. It is assumed that the frequency of harmonic component falls within the region of combination resonances. Stability conditions for the first and second moments are obtained. It turns out that additional parametric excitation may have a stabilizing or destabilizing effect, depending on the values of certain parameters of random excitation. As an example, the stability of a beam in plane bending is analyzed.

Enhancement of ohmic and stochastic heating by resonance effects in capacitive radio frequency discharges: a theoretical approach.

PubMed

Mussenbrock, T; Brinkmann, R P; Lieberman, M A; Lichtenberg, A J; Kawamura, E

2008-08-22

In low-pressure capacitive radio frequency discharges, two mechanisms of electron heating are dominant: (i) Ohmic heating due to collisions of electrons with neutrals of the background gas and (ii) stochastic heating due to momentum transfer from the oscillating boundary sheath. In this work we show by means of a nonlinear global model that the self-excitation of the plasma series resonance which arises in asymmetric capacitive discharges due to nonlinear interaction of plasma bulk and sheath significantly affects both Ohmic heating and stochastic heating. We observe that the series resonance effect increases the dissipation by factors of 2-5. We conclude that the nonlinear plasma dynamics should be taken into account in order to describe quantitatively correct electron heating in asymmetric capacitive radio frequency discharges.

Examples of oil cavitation erosion in positive displacement pumps

NASA Technical Reports Server (NTRS)

Halat, J. A.; Ellis, G. O.

1974-01-01

The effects of cavitation flow on piston type, positive displacement, hydraulic pumps are discussed. The operating principles of the pump and the components which are most subject to erosion effects are described. The mechanisms of cavitation phenomena are identified from photographic records. Curves are developed to show the solubility of air in water, oil-water emulsion, and industrial hydraulic oil.

Possible involvement of membrane lipids peroxidation and oxidation of catalytically essential thiols of the cerebral transmembrane sodium pump as component mechanisms of iron-mediated oxidative stress-linked dysfunction of the pump's activity

PubMed Central

Omotayo, T.I.; Akinyemi, G.S.; Omololu, P.A.; Ajayi, B.O.; Akindahunsi, A.A.; Rocha, J.B.T.; Kade, I.J.

2014-01-01

The precise molecular events defining the complex role of oxidative stress in the inactivation of the cerebral sodium pump in radical-induced neurodegenerative diseases is yet to be fully clarified and thus still open. Herein we investigated the modulation of the activity of the cerebral transmembrane electrogenic enzyme in Fe2+-mediated in vitro oxidative stress model. The results show that Fe2+ inhibited the transmembrane enzyme in a concentration dependent manner and this effect was accompanied by a biphasic generation of aldehydic product of lipid peroxidation. While dithiothreitol prevented both Fe2+ inhibitory effect on the pump and lipid peroxidation, vitamin E prevented only lipid peroxidation but not inhibition of the pump. Besides, malondialdehyde (MDA) inhibited the pump by a mechanism not related to oxidation of its critical thiols. Apparently, the low activity of the pump in degenerative diseases mediated by Fe2+ may involve complex multi-component mechanisms which may partly involve an initial oxidation of the critical thiols of the enzyme directly mediated by Fe2+ and during severe progression of such diseases; aldehydic products of lipid peroxidation such as MDA may further exacerbate this inhibitory effect by a mechanism that is likely not related to the oxidation of the catalytically essential thiols of the ouabain-sensitive cerebral electrogenic pump. PMID:25618580

On the Kolmogorov constant in stochastic turbulence models

NASA Astrophysics Data System (ADS)

Heinz, Stefan

2002-11-01

The Kolmogorov constant is fundamental in stochastic models of turbulence. To explain the reasons for observed variations of this quantity, it is calculated for two flows by various methods and data. Velocity fluctuations are considered as the sum of contributions due to anisotropy, acceleration fluctuations and stochastic forcing that is controlled by the Kolmogorov constant. It is shown that the effects of anisotropy and acceleration fluctuations are responsible for significant variations of the Kolmogorov constant. It is found near 2 for flows where anisotropy and acceleration fluctuations contribute to the energy budget, and near 6 if such contributions disappear.

Role of demographic stochasticity in a speciation model with sexual reproduction

NASA Astrophysics Data System (ADS)

Lafuerza, Luis F.; McKane, Alan J.

2016-03-01

Recent theoretical studies have shown that demographic stochasticity can greatly increase the tendency of asexually reproducing phenotypically diverse organisms to spontaneously evolve into localized clusters, suggesting a simple mechanism for sympatric speciation. Here we study the role of demographic stochasticity in a model of competing organisms subject to assortative mating. We find that in models with sexual reproduction, noise can also lead to the formation of phenotypic clusters in parameter ranges where deterministic models would lead to a homogeneous distribution. In some cases, noise can have a sizable effect, rendering the deterministic modeling insufficient to understand the phenotypic distribution.

Gryphon: A Hybrid Agent-Based Modeling and Simulation Platform for Infectious Diseases

NASA Astrophysics Data System (ADS)

Yu, Bin; Wang, Jijun; McGowan, Michael; Vaidyanathan, Ganesh; Younger, Kristofer

In this paper we present Gryphon, a hybrid agent-based stochastic modeling and simulation platform developed for characterizing the geographic spread of infectious diseases and the effects of interventions. We study both local and non-local transmission dynamics of stochastic simulations based on the published parameters and data for SARS. The results suggest that the expected numbers of infections and the timeline of control strategies predicted by our stochastic model are in reasonably good agreement with previous studies. These preliminary results indicate that Gryphon is able to characterize other future infectious diseases and identify endangered regions in advance.

Effects of Cone-Shaped Bend Inlet Cannulas of an Axial Blood Pump on Thrombus Formation: An Experiment and Simulation Study.

PubMed

Liu, Guangmao; Zhou, Jianye; Sun, Hansong; Zhang, Yan; Chen, Haibo; Hu, Shengshou

2017-04-05

BACKGROUND Cannula shape and connection style influence the risk of thrombus formation in the blood pump by varying the blood flow characteristics inside the pump. Inlet cannulas should be designed based on the need for anatomical fit and reducing the risk of thrombus generation in the blood pump. The effects on thrombus formation of the cone-shaped bend inlet cannulas of axial blood pumps should be studied. MATERIAL AND METHODS The cannulas were designed as cone-shaped, with 1 bent section connecting 2 straight sections. Both the silicone tube and novel cone-shaped cannula were simulated for comparison. The flow fields of a blood pump with inlet cannula were simulated by computational fluid dynamics (CFD) at flows of 2.0, 2.5, and 3.0 liters per minute (lpm), with pump rotational speeds of 7500, 8000, and 8500 rpm, respectively. Then, 6 two-dimensional (2D) particle image velocimetry (PIV) tests were conducted and the velocity distributions were analyzed. RESULTS A low-velocity region was located inside the pump entrance when a soft silicone tube was used. At 8500 rpm and 3.0 lpm working condition, the minimum velocity inside the pump with cone-shaped cannulas was 2.5×10^-1 m/s. The cone-shaped cannulas eliminated the low-velocity region inside the pump. Both CFD and PIV results showed that the low-velocity region did not spread to the entrance of the blood pump within the flow range from 2.0 lpm to 7.0 lpm. CONCLUSIONS The designed cone-shaped bent cannulas can eliminate the low-velocity region inside the blood pump and reduce the risk of thrombus formation in the blood pump.

Electroosmotic pump performance is affected by concentration polarizations of both electrodes and pump

PubMed Central

Suss, Matthew E.; Mani, Ali; Zangle, Thomas A.; Santiago, Juan G.

2010-01-01

Current methods of optimizing electroosmotic (EO) pump performance include reducing pore diameter and reducing ionic strength of the pumped electrolyte. However, these approaches each increase the fraction of total ionic current carried by diffuse electric double layer (EDL) counterions. When this fraction becomes significant, concentration polarization (CP) effects become important, and traditional EO pump models are no longer valid. We here report on the first simultaneous concentration field measurements, pH visualizations, flow rate, and voltage measurements on such systems. Together, these measurements elucidate key parameters affecting EO pump performance in the CP dominated regime. Concentration field visualizations show propagating CP enrichment and depletion fronts sourced by our pump substrate and traveling at order mm/min velocities through millimeter-scale channels connected serially to our pump. The observed propagation in millimeter-scale channels is not explained by current propagating CP models. Additionally, visualizations show that CP fronts are sourced by and propagate from the electrodes of our system, and then interact with the EO pump-generated CP zones. With pH visualizations, we directly detect that electrolyte properties vary sharply across the anode enrichment front interface. Our observations lead us to hypothesize possible mechanisms for the propagation of both pump- and electrode-sourced CP zones. Lastly, our experiments show the dynamics associated with the interaction of electrode and membrane CP fronts, and we describe the effect of these phenomena on EO pump flow rates and applied voltages under galvanostatic conditions. PMID:21516230

Deformation-induced changes in hydraulic head during ground-water withdrawal

USGS Publications Warehouse

Hsieh, Paul A.

1996-01-01

Ground-water withdrawal from a confined or semiconfined aquifer causes three-dimensional deformation in the pumped aquifer and in adjacent layers (overlying and underlying aquifers and aquitards). In response to the deformation, hydraulic head in the adjacent layers could rise or fall almost immediately after the start of pumping. This deformation-induced effect suggest that an adjacent layer undergoes horizontal compression and vertical extension when pumping begins. Hydraulic head initially drops in a region near the well and close to the pumped aquifer, but rises outside this region. Magnitude of head change varies from a few centimeters to more than 10 centimeters. Factors that influence the development of deformation-induced effects includes matrix rigidity (shear modulus), the arrangement of aquifer and aquitards, their thicknesses, and proximity to land surface. Induced rise in hydraulic head is prominent in an aquitard that extends from land surface to a shallow pumped aquifer. Induced drop in hydraulic head is likely observed close to the well in an aquifer that is separated from the pumped aquifer by a relatively thin aquitard. Induced effects might last for hours in an aquifer, but could persist for many days in an aquitard. Induced effects are eventually dissipated by fluid flow from regions of higher head to regions of lower head, and by propagation of drawdown from the pumped aquifer into adjacent layers.

Using failure mode and effects analysis to plan implementation of smart i.v. pump technology.

PubMed

Wetterneck, Tosha B; Skibinski, Kathleen A; Roberts, Tanita L; Kleppin, Susan M; Schroeder, Mark E; Enloe, Myra; Rough, Steven S; Hundt, Ann Schoofs; Carayon, Pascale

2006-08-15

Failure mode and effects analysis (FMEA) was used to evaluate a smart i.v. pump as it was implemented into a redesigned medication-use process. A multidisciplinary team conducted a FMEA to guide the implementation of a smart i.v. pump that was designed to prevent pump programming errors. The smart i.v. pump was equipped with a dose-error reduction system that included a pre-defined drug library in which dosage limits were set for each medication. Monitoring for potential failures and errors occurred for three months postimplementation of FMEA. Specific measures were used to determine the success of the actions that were implemented as a result of the FMEA. The FMEA process at the hospital identified key failure modes in the medication process with the use of the old and new pumps, and actions were taken to avoid errors and adverse events. I.V. pump software and hardware design changes were also recommended. Thirteen of the 18 failure modes reported in practice after pump implementation had been identified by the team. A beneficial outcome of FMEA was the development of a multidisciplinary team that provided the infrastructure for safe technology implementation and effective event investigation after implementation. With the continual updating of i.v. pump software and hardware after implementation, FMEA can be an important starting place for safe technology choice and implementation and can produce site experts to follow technology and process changes over time. FMEA was useful in identifying potential problems in the medication-use process with the implementation of new smart i.v. pumps. Monitoring for system failures and errors after implementation remains necessary.

Interplay between intrinsic noise and the stochasticity of the cell cycle in bacterial colonies.

PubMed

Canela-Xandri, Oriol; Sagués, Francesc; Buceta, Javier

2010-06-02

Herein we report on the effects that different stochastic contributions induce in bacterial colonies in terms of protein concentration and production. In particular, we consider for what we believe to be the first time cell-to-cell diversity due to the unavoidable randomness of the cell-cycle duration and its interplay with other noise sources. To that end, we model a recent experimental setup that implements a protein dilution protocol by means of division events to characterize the gene regulatory function at the single cell level. This approach allows us to investigate the effect of different stochastic terms upon the total randomness experimentally reported for the gene regulatory function. In addition, we show that the interplay between intrinsic fluctuations and the stochasticity of the cell-cycle duration leads to different constructive roles. On the one hand, we show that there is an optimal value of protein concentration (alternatively an optimal value of the cell cycle phase) such that the noise in protein concentration attains a minimum. On the other hand, we reveal that there is an optimal value of the stochasticity of the cell cycle duration such that the coherence of the protein production with respect to the colony average production is maximized. The latter can be considered as a novel example of the recently reported phenomenon of diversity induced resonance. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Magnetohydrodynamic stability of stochastically driven accretion flows.

PubMed

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

2013-07-01

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

Development and validation of a stochastic model for potential growth of Listeria monocytogenes in naturally contaminated lightly preserved seafood.

PubMed

Mejlholm, Ole; Bøknæs, Niels; Dalgaard, Paw

2015-02-01

A new stochastic model for the simultaneous growth of Listeria monocytogenes and lactic acid bacteria (LAB) was developed and validated on data from naturally contaminated samples of cold-smoked Greenland halibut (CSGH) and cold-smoked salmon (CSS). During industrial processing these samples were added acetic and/or lactic acids. The stochastic model was developed from an existing deterministic model including the effect of 12 environmental parameters and microbial interaction (O. Mejlholm and P. Dalgaard, Food Microbiology, submitted for publication). Observed maximum population density (MPD) values of L. monocytogenes in naturally contaminated samples of CSGH and CSS were accurately predicted by the stochastic model based on measured variability in product characteristics and storage conditions. Results comparable to those from the stochastic model were obtained, when product characteristics of the least and most preserved sample of CSGH and CSS were used as input for the existing deterministic model. For both modelling approaches, it was shown that lag time and the effect of microbial interaction needs to be included to accurately predict MPD values of L. monocytogenes. Addition of organic acids to CSGH and CSS was confirmed as a suitable mitigation strategy against the risk of growth by L. monocytogenes as both types of products were in compliance with the EU regulation on ready-to-eat foods. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Quantum pump effect induced by a linearly polarized microwave in a two-dimensional electron gas.

PubMed

Song, Juntao; Liu, Haiwen; Jiang, Hua

2012-05-30

A quantum pump effect is predicted in an ideal homogeneous two-dimensional electron gas (2DEG) that is normally irradiated by linearly polarized microwaves (MW). Without considering effects from spin-orbital coupling or the magnetic field, it is found that a polarized MW can continuously pump electrons from the longitudinal to the transverse direction, or from the transverse to the longitudinal direction, in the central irradiated region. The large pump current is obtained for both the low frequency limit and the high frequency case. Its magnitude depends on sample properties such as the size of the radiated region, the power and frequency of the MW, etc. Through the calculated results, the pump current should be attributed to the dominant photon-assisted tunneling processes as well as the asymmetry of the electron density of states with respect to the Fermi energy.

Engineering: Liquid metal pumped at a record temperature

NASA Astrophysics Data System (ADS)

Lambrinou, Konstantina

2017-10-01

Although liquid metals are effective fluids for heat transfer, pumping them at high temperatures is limited by their corrosiveness to solid metals. A clever pump design addresses this challenge using only ceramics. See Article p.199

pth moment exponential stability of stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays.

PubMed

Wang, Fen; Chen, Yuanlong; Liu, Meichun

2018-02-01

Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues of the pth moment exponential stability of stochastic memristor-based BAM neural networks are investigated. By using the stochastic stability theory, Itô's differential formula and Young inequality, the criteria are derived. Meanwhile, with Lyapunov approach and Cauchy-Schwarz inequality, we derive some sufficient conditions for the mean square exponential stability of the above systems. The obtained results improve and extend previous works on memristor-based or usual neural networks dynamical systems. Four numerical examples are provided to illustrate the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Event-triggered resilient filtering with stochastic uncertainties and successive packet dropouts via variance-constrained approach

NASA Astrophysics Data System (ADS)

Jia, Chaoqing; Hu, Jun; Chen, Dongyan; Liu, Yurong; Alsaadi, Fuad E.

2018-07-01

In this paper, we discuss the event-triggered resilient filtering problem for a class of time-varying systems subject to stochastic uncertainties and successive packet dropouts. The event-triggered mechanism is employed with hope to reduce the communication burden and save network resources. The stochastic uncertainties are considered to describe the modelling errors and the phenomenon of successive packet dropouts is characterized by a random variable obeying the Bernoulli distribution. The aim of the paper is to provide a resilient event-based filtering approach for addressed time-varying systems such that, for all stochastic uncertainties, successive packet dropouts and filter gain perturbation, an optimized upper bound of the filtering error covariance is obtained by designing the filter gain. Finally, simulations are provided to demonstrate the effectiveness of the proposed robust optimal filtering strategy.

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

2016-11-14

In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

Stochastic resonance in a fractional oscillator driven by multiplicative quadratic noise

NASA Astrophysics Data System (ADS)

Ren, Ruibin; Luo, Maokang; Deng, Ke

2017-02-01

Stochastic resonance of a fractional oscillator subject to an external periodic field as well as to multiplicative and additive noise is investigated. The fluctuations of the eigenfrequency are modeled as the quadratic function of the trichotomous noise. Applying the moment equation method and Shapiro-Loginov formula, we obtain the exact expression of the complex susceptibility and related stability criteria. Theoretical analysis and numerical simulations indicate that the spectral amplification (SPA) depends non-monotonicly both on the external driving frequency and the parameters of the quadratic noise. In addition, the investigations into fractional stochastic systems have suggested that both the noise parameters and the memory effect can induce the phenomenon of stochastic multi-resonance (SMR), which is previously reported and believed to be absent in the case of the multiplicative noise with only a linear term.

H∞ state estimation for discrete-time memristive recurrent neural networks with stochastic time-delays

NASA Astrophysics Data System (ADS)

Liu, Hongjian; Wang, Zidong; Shen, Bo; Alsaadi, Fuad E.

2016-07-01

This paper deals with the robust H∞ state estimation problem for a class of memristive recurrent neural networks with stochastic time-delays. The stochastic time-delays under consideration are governed by a Bernoulli-distributed stochastic sequence. The purpose of the addressed problem is to design the robust state estimator such that the dynamics of the estimation error is exponentially stable in the mean square, and the prescribed ? performance constraint is met. By utilizing the difference inclusion theory and choosing a proper Lyapunov-Krasovskii functional, the existence condition of the desired estimator is derived. Based on it, the explicit expression of the estimator gain is given in terms of the solution to a linear matrix inequality. Finally, a numerical example is employed to demonstrate the effectiveness and applicability of the proposed estimation approach.

Stochastic inversion of cross-borehole radar data from metalliferous vein detection

NASA Astrophysics Data System (ADS)

Zeng, Zhaofa; Huai, Nan; Li, Jing; Zhao, Xueyu; Liu, Cai; Hu, Yingsa; Zhang, Ling; Hu, Zuzhi; Yang, Hui

2017-12-01

In the exploration and evaluation of the metalliferous veins with a cross-borehole radar system, traditional linear inversion methods (least squares inversion, LSQR) only get indirect parameters (permittivity, resistivity, or velocity) to estimate the target structure. They cannot accurately reflect the geological parameters of the metalliferous veins’ media properties. In order to get the intrinsic geological parameters and internal distribution, in this paper, we build a metalliferous veins model based on the stochastic effective medium theory, and carry out stochastic inversion and parameter estimation based on the Monte Carlo sampling algorithm. Compared with conventional LSQR, the stochastic inversion can get higher resolution inversion permittivity and velocity of the target body. We can estimate more accurately the distribution characteristics of abnormality and target internal parameters. It provides a new research idea to evaluate the properties of complex target media.

Attempts at a numerical realisation of stochastic differential equations containing Preisach operator

NASA Astrophysics Data System (ADS)

McCarthy, S.; Rachinskii, D.

2011-01-01

We describe two Euler type numerical schemes obtained by discretisation of a stochastic differential equation which contains the Preisach memory operator. Equations of this type are of interest in areas such as macroeconomics and terrestrial hydrology where deterministic models containing the Preisach operator have been developed but do not fully encapsulate stochastic aspects of the area. A simple price dynamics model is presented as one motivating example for our studies. Some numerical evidence is given that the two numerical schemes converge to the same limit as the time step decreases. We show that the Preisach term introduces a damping effect which increases on the parts of the trajectory demonstrating a stronger upwards or downwards trend. The results are preliminary to a broader programme of research of stochastic differential equations with the Preisach hysteresis operator.

A new state evaluation method of oil pump unit based on AHP and FCE

NASA Astrophysics Data System (ADS)

Lin, Yang; Liang, Wei; Qiu, Zeyang; Zhang, Meng; Lu, Wenqing

2017-05-01

In order to make an accurate state evaluation of oil pump unit, a comprehensive evaluation index should be established. A multi-parameters state evaluation method of oil pump unit is proposed in this paper. The oil pump unit is analyzed by Failure Mode and Effect Analysis (FMEA), so evaluation index can be obtained based on FMEA conclusions. The weights of different parameters in evaluation index are discussed using Analytic Hierarchy Process (AHP) with expert experience. According to the evaluation index and the weight of each parameter, the state evaluation is carried out by Fuzzy Comprehensive Evaluation (FCE) and the state is divided into five levels depending on status value, which is inspired by human body health. In order to verify the effectiveness and feasibility of the proposed method, a state evaluation of oil pump used in a pump station is taken as an example.

Estimating mechanical blood trauma in a centrifugal blood pump: laser Doppler anemometer measurements of the mean velocity field.

PubMed

Pinotti, M; Paone, N

1996-06-01

A laser Doppler anemometer (LDA) was used to obtain the mean velocity and the Reynolds stress fields in the inner channels of a well-known centrifugal vaneless pump (Bio-pump). Effects of the excessive flow resistance against which an occlusive pump operates in some surgical situations, such as cardiopulmonary bypass, are illustrated. The velocity vector field obtained from LDA measurements reveals that the constraint-forced vortex provides pumping action in a restricted area in the core of the pump. In such situations, recirculating zones dominate the flow and consequently increase the damage to blood cells and raise the risk of thrombus formation in the device. Reynolds normal and shear stress fields were obtained in the entry flow for the channel formed by two rotating cones to illustrate the effects of flow disturbances on the potential for blood cell damage.

Estimating Mechanical Blood Trauma in a Centrifugal Blood Pump: Laser Doppler Anemometer Measurements of the Mean Velocity Field.

PubMed

Pinotti, Marcos; Paone, Nicola

1996-05-01

A laser Doppler anemometer (LDA) was used to obtain the mean velocity and the Reynolds stress fields in the inner channels of a well-known centrifugal vaneless pump (Bio-pump). Effects of the excessive flow resistance against which an occlusive pump operates in some surgical situations, such as cardiopulmonary bypass, are illustrated. The velocity vector field obtained from LDA measurements reveals that the constraint-forced vortex provides pumping action in a restricted area in the core of the pump. In such situations, recirculating zones dominate the flow and consequently increase the damage to blood cells and raise the risk of thrombus formation in the device. Reynolds normal and shear stress fields were obtained in the entry flow for the channel formed by two rotating cones to illustrate the effects of flow disturbances on the potential for blood cell damage. © 1996 International Society for Artificial Organs.

Demonstration of slow light propagation in an optical fiber under dual pump light with co-propagation and counter-propagation

NASA Astrophysics Data System (ADS)

Qiu, Wei; Liu, Jianjun; Wang, Yuda; Yang, Yujing; Gao, Yuan; Lv, Pin; Jiang, Qiuli

2018-04-01

In this paper, a general theory of coherent population oscillation effect in an Er3+ -doped fiber under the dual-frequency pumping laser with counter-propagation and co-propagation at room temperature is presented. Using the numerical simulation, in case of dual frequency light waves (1480 nm and 980 nm) with co-propagation and counter-propagation, we analyze the effect of the pump optical power ratio (M) on the group speed of light. The group velocity of light can be varied with the change of M. We research the time delay and fractional delay in an Er3+-doped fiber under the dual-frequency pumping laser with counter-propagation and co-propagation. Compared to the methods of the single pumping, the larger time delay can be got by using the technique of dual-frequency laser pumped fiber with co-propagation and counter-propagation.

Possible effects of groundwater pumping on surface water in the Verde Valley, Arizona

USGS Publications Warehouse

Leake, Stanley A.; Haney, Jeanmarie

2010-01-01

The U.S. Geological Survey (USGS), in cooperation with The Nature Conservancy, has applied a groundwater model to simulate effects of groundwater pumping and artificial recharge on surface water in the Verde Valley sub-basin of Arizona. Results are in two sets of maps that show effects of locations of pumping or recharge on streamflow. These maps will help managers make decisions that will meet water needs and minimize environmental impacts.

Stochastic Resonance in Signal Detection and Human Perception

DTIC Science & Technology

2006-07-05

learning scheme performing a stochastic gradient ascent on the SNR to determine the optimal noise level based on the samples from the process. Rather than...produce some SR effect in threshold neurons and a new statistically robust learning law was proposed to find the optimal noise level. [McDonnell...Ultimately, we know that it is the brain that responds to a visual stimulus causing neurons to fire. Conceivably if we understood the effect of the noise PDF

Radiation induced leakage due to stochastic charge trapping in isolation layers of nanoscale MOSFETs

NASA Astrophysics Data System (ADS)

Zebrev, G. I.; Gorbunov, M. S.; Pershenkov, V. S.

2008-03-01

The sensitivity of sub-100 nm devices to microdose effects, which can be considered as intermediate case between cumulative total dose and single event errors, is investigated. A detailed study of radiation-induced leakage due to stochastic charge trapping in irradiated planar and nonplanar devices is developed. The influence of High-K insulators on nanoscale ICs reliability is discussed. Low critical values of trapped charge demonstrate a high sensitivity to single event effect.

Fractional Brownian motors and stochastic resonance

NASA Astrophysics Data System (ADS)

Goychuk, Igor; Kharchenko, Vasyl

2012-05-01

We study fluctuating tilt Brownian ratchets based on fractional subdiffusion in sticky viscoelastic media characterized by a power law memory kernel. Unlike the normal diffusion case, the rectification effect vanishes in the adiabatically slow modulation limit and optimizes in a driving frequency range. It is shown also that the anomalous rectification effect is maximal (stochastic resonance effect) at optimal temperature and can be of surprisingly good quality. Moreover, subdiffusive current can flow in the counterintuitive direction upon a change of temperature or driving frequency. The dependence of anomalous transport on load exhibits a remarkably simple universality.

Methods of milk expression for lactating women.

PubMed

Becker, Genevieve E; Smith, Hazel A; Cooney, Fionnuala

2016-09-29

Breastfeeding is important, however not all infants can feed at the breast and methods of expressing milk need evaluation. To assess acceptability, effectiveness, safety, effect on milk composition, contamination and costs of methods of milk expression. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (21 March 2016), handsearched relevant journals and conference proceedings, and contacted experts in the field to seek additional published or unpublished studies. We also examined reference lists of all relevant retrieved papers. Randomised and quasi-randomised trials comparing methods at any time after birth. Three review authors independently assessed trials for inclusion and risk of bias, extracted data and checked them for accuracy. This updated review includes 41 trials involving 2293 participants, with 22 trials involving 1339 participants contributing data for analysis. Twenty-six of the trials referred to mothers of infants in neonatal units (n = 1547) and 14 to mothers of healthy infants at home (n = 730), with one trial containing mothers of both neonatal and healthy older infants (n = 16). Eleven trials compared one or more types of pump versus hand expression and 14 studies compared one type of pump versus another type of pump, with three of these studies comparing both hand expression and pump types. Twenty studies compared a specific protocol or adjunct behaviour including sequential versus simultaneous pumping protocols, pumping frequency, provision of an education and support intervention, relaxation, breast massage, combining hand expression with pumping and a breast cleansing protocol.Due to heterogeneity in participants, interventions, and outcomes measured or reported, we were unable to pool findings for most of the specified outcomes. It was not possible therefore to produce a 'Summary of findings' table in this update. Most of the included results were derived from single studies. Trials took place in 14 countries under a variety of circumstances and were published from 1982 to 2015. Sixteen of the 30 trials that evaluated pumps or products had support from the manufacturers. The risk of bias of the included studies was variable. Primary outcomesOnly one of the 17 studies examining maternal satisfaction/acceptability with the method or adjunct behaviour provided data suitable for analysis. In this study, self-efficacy was assessed by asking mothers if they agreed or disagreed with the following statement: 'I don't want anyone to see me (hand expressing/pumping)'. The study found that mothers who were using the electric pump were more likely to agree with the statement compared to mothers hand expressing, (mean difference (MD) 0.70, 95% confidence interval (CI) 0.15 to 1.25; P = 0.01, participants = 68). Mothers who were hand expressing reported that the instructions for expression were clearer compared to the electric pump, (MD -0.40, 95% CI -0.75 to -0.05; P = 0.02, participants = 68). Descriptive reporting of satisfaction in the other studies varied in the measures used, did not indicate a clear preference for one pump type, although there was satisfaction with some relaxation and support interventions.We found no clinically significant differences between methods related to contamination of the milk that compared any type of pump to hand expression (risk ratio (RR) 1.13, 95% CI 0.79 to 1.61; P = 0.51, participants = 28), manual pump compared to hand expression, (MD 0.20, 95% CI -0.18 to 0.58; P = 0.30, participants = 142) a large electric pump compared to hand expression (MD 0.10, 95% CI -0.29 to 0.49; P = 0.61, participants = 123), or a large electric pump compared to a manual pump (MD -0.10, 95% CI -0.46 to 0.26; P = 0.59, participants = 141).The level of maternal breast or nipple pain or damage was similar in comparisons of a large electric pump to hand expression (MD 0.02, 95% CI -0.67 to 0.71; P = 0.96, participants = 68). A study comparing a manual and large electric pump, reported sore nipples in 7% for both groups and engorgement in 4% using a manual pump versus 6% using an electric pump; and in one study no nipple damage was reported in the hand-expression group, and one case of nipple damage in each of the manual pump and the large electric pump groups.One study examined adverse effects on infants, however as the infants did not all receive their mothers' expressed milk, we have not included the results. Secondary outcomesThe quantity of expressed milk obtained was increased, in some studies by a clinically significant amount, in interventions involving relaxation, music, warmth, massage, initiation of pumping, increased frequency of pumping and suitable breast shield size. Support programmes and simultaneous compared to sequential pumping did not show a difference in milk obtained. No pump consistently increased the milk volume obtained significantly.In relation to nutrient quality, hand expression or a large electric pump were found to provide higher protein than a manual pump, and hand expression provided higher sodium and lower potassium compared to a large electric pump or a manual pump. Fat content was higher with breast massage when pumping; no evidence of difference was found for energy content between methods.No consistent effect was found related to prolactin change or effect on oxytocin release with pump type or method. Economic aspects were not reported. The most suitable method for milk expression may depend on the time since birth, purpose of expression and the individual mother and infant. Low-cost interventions including initiation of milk expression sooner after birth when not feeding at the breast, relaxation, massage, warming the breasts, hand expression and lower cost pumps may be as effective, or more effective, than large electric pumps for some outcomes. Variation in nutrient content across methods may be relevant to some infants. Small sample sizes, large standard deviations, and the diversity of the interventions argue caution in applying these results beyond the specific method tested in the specific settings. Independently funded research is needed for more trials on hand expression, relaxation and other techniques that do not have a commercial potential.

Long-term influence of asteroids on planet longitudes and chaotic dynamics of the solar system

NASA Astrophysics Data System (ADS)

Woillez, E.; Bouchet, F.

2017-11-01

Over timescales much longer than an orbital period, the solar system exhibits large-scale chaotic behavior and can thus be viewed as a stochastic dynamical system. The aim of the present paper is to compare different sources of stochasticity in the solar system. More precisely we studied the importance of the long term influence of asteroids on the chaotic dynamics of the solar system. We show that the effects of asteroids on planets is similar to a white noise process, when those effects are considered on a timescale much larger than the correlation time τϕ ≃ 104 yr of asteroid trajectories. We computed the timescale τe after which the effects of the stochastic evolution of the asteroids lead to a loss of information for the initial conditions of the perturbed Laplace-Lagrange secular dynamics. The order of magnitude of this timescale is precisely determined by theoretical argument, and we find that τe ≃ 104 Myr. Although comparable to the full main-sequence lifetime of the sun, this timescale is considerably longer than the Lyapunov time τI ≃ 10 Myr of the solar system without asteroids. This shows that the external sources of chaos arise as a small perturbation in the stochastic secular behavior of the solar system, rather due to intrinsic chaos.

Path durations for use in the stochastic‐method simulation of ground motions

USGS Publications Warehouse

Boore, David M.; Thompson, Eric M.

2014-01-01

The stochastic method of ground‐motion simulation assumes that the energy in a target spectrum is spread over a duration DT. DT is generally decomposed into the duration due to source effects (DS) and to path effects (DP). For the most commonly used source, seismological theory directly relates DS to the source corner frequency, accounting for the magnitude scaling of DT. In contrast, DP is related to propagation effects that are more difficult to represent by analytic equations based on the physics of the process. We are primarily motivated to revisit DT because the function currently employed by many implementations of the stochastic method for active tectonic regions underpredicts observed durations, leading to an overprediction of ground motions for a given target spectrum. Further, there is some inconsistency in the literature regarding which empirical duration corresponds to DT. Thus, we begin by clarifying the relationship between empirical durations and DT as used in the first author’s implementation of the stochastic method, and then we develop a new DP relationship. The new DP function gives significantly longer durations than in the previous DP function, but the relative contribution of DP to DT still diminishes with increasing magnitude. Thus, this correction is more important for small events or subfaults of larger events modeled with the stochastic finite‐fault method.

Stochastic Threshold Microdose Model for Cell Killing by Insoluble Metallic Nanomaterial Particles

PubMed Central

Scott, Bobby R.

2010-01-01

This paper introduces a novel microdosimetric model for metallic nanomaterial-particles (MENAP)-induced cytotoxicity. The focus is on the engineered insoluble MENAP which represent a significant breakthrough in the design and development of new products for consumers, industry, and medicine. Increased production is rapidly occurring and may cause currently unrecognized health effects (e.g., nervous system dysfunction, heart disease, cancer); thus, dose-response models for MENAP-induced biological effects are needed to facilitate health risk assessment. The stochastic threshold microdose (STM) model presented introduces novel stochastic microdose metrics for use in constructing dose-response relationships for the frequency of specific cellular (e.g., cell killing, mutations, neoplastic transformation) or subcellular (e.g., mitochondria dysfunction) effects. A key metric is the exposure-time-dependent, specific burden (MENAP count) for a given critical target (e.g., mitochondria, nucleus). Exceeding a stochastic threshold specific burden triggers cell death. For critical targets in the cytoplasm, the autophagic mode of death is triggered. For the nuclear target, the apoptotic mode of death is triggered. Overall cell survival is evaluated for the indicated competing modes of death when both apply. The STM model can be applied to cytotoxicity data using Bayesian methods implemented via Markov chain Monte Carlo. PMID:21191483

Stochasticity in staged models of epidemics: quantifying the dynamics of whooping cough

PubMed Central

Black, Andrew J.; McKane, Alan J.

2010-01-01

Although many stochastic models can accurately capture the qualitative epidemic patterns of many childhood diseases, there is still considerable discussion concerning the basic mechanisms generating these patterns; much of this stems from the use of deterministic models to try to understand stochastic simulations. We argue that a systematic method of analysing models of the spread of childhood diseases is required in order to consistently separate out the effects of demographic stochasticity, external forcing and modelling choices. Such a technique is provided by formulating the models as master equations and using the van Kampen system-size expansion to provide analytical expressions for quantities of interest. We apply this method to the susceptible–exposed–infected–recovered (SEIR) model with distributed exposed and infectious periods and calculate the form that stochastic oscillations take on in terms of the model parameters. With the use of a suitable approximation, we apply the formalism to analyse a model of whooping cough which includes seasonal forcing. This allows us to more accurately interpret the results of simulations and to make a more quantitative assessment of the predictions of the model. We show that the observed dynamics are a result of a macroscopic limit cycle induced by the external forcing and resonant stochastic oscillations about this cycle. PMID:20164086

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

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

Wang, Hong; Aziz, H M Abdul; Young, Stan

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less

Model selection for integrated pest management with stochasticity.

PubMed

Akman, Olcay; Comar, Timothy D; Hrozencik, Daniel

2018-04-07

In Song and Xiang (2006), an integrated pest management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an integrated pest management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulated water sources and effects of pumping on surface and ground water, Sagamore and Monomoy flow lenses, Cape Cod, Massachusetts

USGS Publications Warehouse

Walter, Donald A.; Whealan, Ann T.

2005-01-01

The sandy sediments underlying Cape Cod, Massachusetts, compose an important aquifer that is the sole source of water for a region undergoing rapid development. Population increases and urbanization on Cape Cod lead to two primary environmental effects that relate directly to water supply: (1) adverse effects of land use on the quality of water in the aquifer and (2) increases in pumping that can adversely affect environmentally sensitive surface waters, such as ponds and streams. These considerations are particularly important on the Sagamore and Monomoy flow lenses, which underlie the largest and most populous areas on Cape Cod. Numerical models of the two flow lenses were developed to simulate ground-water-flow conditions in the aquifer and to (1) delineate areas at the water table contributing water to wells and (2) estimate the effects of pumping and natural changes in recharge on surface waters. About 350 million gallons per day (Mgal/d) of water recharges the aquifer at the water table in this area; most water (about 65 percent) discharges at the coast and most of the remaining water (about 28 percent) discharges into streams. A total of about 24.9 Mgal/d, or about 7 percent, of water in the aquifer is withdrawn for water supply; most pumped water is returned to the hydrologic system as return flow creating a state of near mass balance in the aquifer. Areas at the water table that contribute water directly to production wells total about 17 square miles; some water (about 10 percent) pumped from the wells flows through ponds prior to reaching the wells. Current (2003) steady-state pumping reduces simulated ground-water levels in some areas by more than 4 feet; projected (2020) pumping may reduce water levels by an additional 3 feet or more in these same areas. Current (2003) and future (2020) pumping reduces total streamflow by about 4 and 9 cubic feet per second (ft3/s), corresponding to about 5 percent and 9 percent, respectively, of total streamflow. Natural recharge varies with time, over both monthly and multiyear time scales. Monthly changes in recharge cause pond levels to vary between 1 and 2 feet in an average year; annual changes in recharge, which can be much larger than monthly variations, can cause pond levels to vary by more than 10 feet in some areas over a period of years. Streamflow, which also changes in response to changes in recharge, varies by a factor of two over an average year and can vary more over multiyear periods. On average, monthly pumping ranges from 15.8 Mgal/d in March to 45.3 Mgal/d in August. Pumping and the distribution of return flow can seasonally affect the hydrologic system by lowering ground-water and pond levels and by depleting streamflows, particularly in the summer months. Maximum drawdowns in March and August exceed 3 feet and 6 feet, respectively, for current (2003) pumping. Simulated drawdowns from projected (2020) pumping, relative to water levels representing 2003 pumping conditions, exceed 2 feet in March and 5 feet in August. Current (2003) and future (2020) pumping can decrease pond levels in some areas by more than 3 feet; drawdown generally is largest during the month of August of an average year. Over multiyear periods, seasonal pumping can lower pond levels in some areas by more than 4 feet; the effects of seasonal pumping are largest during periods of reduced recharge. Monthly streamflow depletion varies in individual streams but can exceed 2 ft3/s in some streams. The combined effects of seasonal pumping and drought can reduce pond levels by more than 10 feet below average levels. Water levels in Mary Dunn Pond, which is in an area of large current and projected pumping, are predicted (2020) to decline during drought conditions by about 10.6 feet: about 6.9 feet from lower recharge, about 2.3 feet from current (2003) pumping, and about 1.4 feet from additional future (2020) pumping. The results indicate that pumping generally does not cause substantial

Effects of Proposed Additional Ground-Water Withdrawals from the Mississippi River Valley Alluvial Aquifer on Water Levels in Lonoke County, Arkansas

USGS Publications Warehouse

Czarnecki, John B.

2006-01-01

The Grand Prairie Water Users Association, located in Lonoke County, Arkansas, plans to increase ground-water withdrawals from the Mississippi River Valley alluvial aquifer from their current (2005) rate of about 400 gallons per minute to 1,400 gallons per minute (2,016,000 gallons per day). The effect of pumping from a proposed well was simulated using a digital model of ground-water flow. The proposed additional withdrawals were added to an existing pumping cell specified in the model, with increased pumping beginning in 2005, and specified to pump at a total combined rate of 2,016,000 gallons per day for a period of 46 years. In addition, pumping from wells owned by Cabot Water Works, located about 2 miles from the proposed pumping, was added to the model beginning in 2001 and continuing through to the end of 2049. Simulated pumping causes a cone of depression to occur in the alluvial aquifer with a maximum decline in water level of about 8.5 feet in 46 years in the model cell of the proposed well compared to 1998 withdrawals. However, three new dry model cells occur south of the withdrawal well after 46 years. This total water-level decline takes into account the cumulative effect of all wells pumping in the vicinity, although the specified pumping rate from all other model cells in 2005 is less than for actual conditions in 2005. After 46 years with the additional pumping, the water-level altitude in the pumped model cell was about 177.4 feet, which is 41.7 feet higher than 135.7 feet, the altitude corresponding to half of the original saturated thickness of the alluvial aquifer (a metric used to determine if the aquifer should be designated as a Critical Ground-Water Area (Arkansas Natural Resources Commission, 2006)).

Description and comparison of selected models for hydrologic analysis of ground-water flow, St Joseph River basin, Indiana

USGS Publications Warehouse

Peters, J.G.

1987-01-01

The Indiana Department of Natural Resources (IDNR) is developing water-management policies designed to assess the effects of irrigation and other water uses on water supply in the basin. In support of this effort, the USGS, in cooperation with IDNR, began a study to evaluate appropriate methods for analyzing the effects of pumping on ground-water levels and streamflow in the basin 's glacial aquifer systems. Four analytical models describe drawdown for a nonleaky, confined aquifer and fully penetrating well; a leaky, confined aquifer and fully penetrating well; a leaky, confined aquifer and partially penetrating well; and an unconfined aquifer and partially penetrating well. Analytical equations, simplifying assumptions, and methods of application are described for each model. In addition to these four models, several other analytical models were used to predict the effects of ground-water pumping on water levels in the aquifer and on streamflow in local areas with up to two pumping wells. Analytical models for a variety of other hydrogeologic conditions are cited. A digital ground-water flow model was used to describe how a numerical model can be applied to a glacial aquifer system. The numerical model was used to predict the effects of six pumping plans in 46.5 sq mi area with as many as 150 wells. Water budgets for the six pumping plans were used to estimate the effect of pumping on streamflow reduction. Results of the analytical and numerical models indicate that, in general, the glacial aquifers in the basin are highly permeable. Radial hydraulic conductivity calculated by the analytical models ranged from 280 to 600 ft/day, compared to 210 and 360 ft/day used in the numerical model. Maximum seasonal pumping for irrigation produced maximum calculated drawdown of only one-fourth of available drawdown and reduced streamflow by as much as 21%. Analytical models are useful in estimating aquifer properties and predicting local effects of pumping in areas with simple lithology and boundary conditions and with few pumping wells. Numerical models are useful in regional areas with complex hydrogeology with many pumping wells and provide detailed water budgets useful for estimating the sources of water in pumping simulations. Numerical models are useful in constructing flow nets. The choice of which type of model to use is also based on the nature and scope of questions to be answered and on the degree of accuracy required. (Author 's abstract)

Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2016-04-01

In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.

Stochastic analysis of uncertain thermal parameters for random thermal regime of frozen soil around a single freezing pipe

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhou, Lei

2018-03-01

The artificial ground freezing method (AGF) is widely used in civil and mining engineering, and the thermal regime of frozen soil around the freezing pipe affects the safety of design and construction. The thermal parameters can be truly random due to heterogeneity of the soil properties, which lead to the randomness of thermal regime of frozen soil around the freezing pipe. The purpose of this paper is to study the one-dimensional (1D) random thermal regime problem on the basis of a stochastic analysis model and the Monte Carlo (MC) method. Considering the uncertain thermal parameters of frozen soil as random variables, stochastic processes and random fields, the corresponding stochastic thermal regime of frozen soil around a single freezing pipe are obtained and analyzed. Taking the variability of each stochastic parameter into account individually, the influences of each stochastic thermal parameter on stochastic thermal regime are investigated. The results show that the mean temperatures of frozen soil around the single freezing pipe with three analogy method are the same while the standard deviations are different. The distributions of standard deviation have a great difference at different radial coordinate location and the larger standard deviations are mainly at the phase change area. The computed data with random variable method and stochastic process method have a great difference from the measured data while the computed data with random field method well agree with the measured data. Each uncertain thermal parameter has a different effect on the standard deviation of frozen soil temperature around the single freezing pipe. These results can provide a theoretical basis for the design and construction of AGF.

Quantifying Stochastic Noise in Cultured Circadian Reporter Cells

DOE PAGES

John, Peter C.; Doyle, III, Francis J.

2015-11-20

We report that stochastic noise at the cellular level has been shown to play a fundamental role in circadian oscillations, influencing how groups of cells entrain to external cues and likely serving as the mechanism by which cell-autonomous rhythms are generated. Despite this importance, few studies have investigated how clock perturbations affect stochastic noise—even as increasing numbers of high-throughput screens categorize how gene knockdowns or small molecules can change clock period and amplitude. This absence is likely due to the difficulty associated with measuring cell-autonomous stochastic noise directly, which currently requires the careful collection and processing of single-cell data. Inmore » this study, we show that the damping rate of population-level bioluminescence recordings can serve as an accurate measure of overall stochastic noise, and one that can be applied to future and existing high-throughput circadian screens. Using cell-autonomous fibroblast data, we first show directly that higher noise at the single-cell results in faster damping at the population level. Next, we show that the damping rate of cultured cells can be changed in a dose-dependent fashion by small molecule modulators, and confirm that such a change can be explained by single-cell noise using a mathematical model. We further demonstrate the insights that can be gained by applying our method to a genome-wide siRNA screen, revealing that stochastic noise is altered independently from period, amplitude, and phase. Finally, we hypothesize that the unperturbed clock is highly optimized for robust rhythms, as very few gene perturbations are capable of simultaneously increasing amplitude and lowering stochastic noise. Ultimately, this study demonstrates the importance of considering the effect of circadian perturbations on stochastic noise, particularly with regard to the development of small-molecule circadian therapeutics.« less

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

Groundwater and surface-water interaction and effects of pumping in a complex glacial-sediment aquifer, phase 2, east-central Massachusetts

USGS Publications Warehouse

Eggleston, Jack R.; Zarriello, Phillip J.; Carlson, Carl S.

2015-12-31

Model simulations indicate that under average base-flow conditions, the Birch Road wells have a small effect on flow in the Sudbury River during most months, even at the maximum pumping rate of 4.9 ft3/s (3.17 Mgal/d). Maximum percent streamflow depletion in the Sudbury River caused by simulated pumping takes place during simulated drought conditions, when streamflow decreased by as much as 21 percent under maximum continuous pumping. Simulations also indicate that groundwater withdrawals at the Birch Road site could be managed so that adverse streamflow impacts are substantially ameliorated. Under the most ecologically conservative simulated drought conditions, simulated streamflow depletion was reduced from 21 percent to 3 percent by pumping at the maximum rate for 6 months rather than for 12 months. Simulations that return 10 percent of the Birch Road well withdrawals to Pod Meadow Pond indicate a modest reduction in the Sudbury River streamflow depletion and provide a larger percentage increase to streamflow just downstream of the pond. The groundwater model also indicates that well locations can have a large effect on the sustainable pumping rate and so should be chosen carefully. The model provides a tool for evaluating alternative pumping rates and schedules not included in this analysis.

The Cost Efficiency Impact of the University Operation Fund on Public Universities in Taiwan

ERIC Educational Resources Information Center

Kuo, Jenn-Shyong; Ho, Yi-Cheng

2008-01-01

This study uses the stochastic frontier multiple-product cost function that is modeled after Battese and Coelli [Battese, G. E., & Coelli, T. J. (1995). "A model for technical inefficiency effects in a stochastic frontier production for panel data." "Empirical Economics" 20(2), 325-332.] in order to empirically measure the…

Stochastic responses of Van der Pol vibro-impact system with fractional derivative damping excited by Gaussian white noise.

PubMed

Xiao, Yanwen; Xu, Wei; Wang, Liang

2016-03-01

This paper focuses on the study of the stochastic Van der Pol vibro-impact system with fractional derivative damping under Gaussian white noise excitation. The equations of the original system are simplified by non-smooth transformation. For the simplified equation, the stochastic averaging approach is applied to solve it. Then, the fractional derivative damping term is facilitated by a numerical scheme, therewith the fourth-order Runge-Kutta method is used to obtain the numerical results. And the numerical simulation results fit the analytical solutions. Therefore, the proposed analytical means to study this system are proved to be feasible. In this context, the effects on the response stationary probability density functions (PDFs) caused by noise excitation, restitution condition, and fractional derivative damping are considered, in addition the stochastic P-bifurcation is also explored in this paper through varying the value of the coefficient of fractional derivative damping and the restitution coefficient. These system parameters not only influence the response PDFs of this system but also can cause the stochastic P-bifurcation.

Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes.

PubMed

Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V

2013-04-01

Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes

NASA Astrophysics Data System (ADS)

Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V.

2013-04-01

Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

Characterizing the dynamics of rubella relative to measles: the role of stochasticity

PubMed Central

Rozhnova, Ganna; Metcalf, C. Jessica E.; Grenfell, Bryan T.

2013-01-01

Rubella is a completely immunizing and mild infection in children. Understanding its behaviour is of considerable public health importance because of congenital rubella syndrome, which results from infection with rubella during early pregnancy and may entail a variety of birth defects. The recurrent dynamics of rubella are relatively poorly resolved, and appear to show considerable diversity globally. Here, we investigate the behaviour of a stochastic seasonally forced susceptible–infected–recovered model to characterize the determinants of these dynamics and illustrate patterns by comparison with measles. We perform a systematic analysis of spectra of stochastic fluctuations around stable attractors of the corresponding deterministic model and compare them with spectra from full stochastic simulations in large populations. This approach allows us to quantify the effects of demographic stochasticity and to give a coherent picture of measles and rubella dynamics, explaining essential differences in the recurrent patterns exhibited by these diseases. We discuss the implications of our findings in the context of vaccination and changing birth rates as well as the persistence of these two childhood infections. PMID:24026472

A New Methodology for Open Pit Slope Design in Karst-Prone Ground Conditions Based on Integrated Stochastic-Limit Equilibrium Analysis

NASA Astrophysics Data System (ADS)

Zhang, Ke; Cao, Ping; Ma, Guowei; Fan, Wenchen; Meng, Jingjing; Li, Kaihui

2016-07-01

Using the Chengmenshan Copper Mine as a case study, a new methodology for open pit slope design in karst-prone ground conditions is presented based on integrated stochastic-limit equilibrium analysis. The numerical modeling and optimization design procedure contain a collection of drill core data, karst cave stochastic model generation, SLIDE simulation and bisection method optimization. Borehole investigations are performed, and the statistical result shows that the length of the karst cave fits a negative exponential distribution model, but the length of carbonatite does not exactly follow any standard distribution. The inverse transform method and acceptance-rejection method are used to reproduce the length of the karst cave and carbonatite, respectively. A code for karst cave stochastic model generation, named KCSMG, is developed. The stability of the rock slope with the karst cave stochastic model is analyzed by combining the KCSMG code and the SLIDE program. This approach is then applied to study the effect of the karst cave on the stability of the open pit slope, and a procedure to optimize the open pit slope angle is presented.

An inexact mixed risk-aversion two-stage stochastic programming model for water resources management under uncertainty.

PubMed

Li, W; Wang, B; Xie, Y L; Huang, G H; Liu, L

2015-02-01

Uncertainties exist in the water resources system, while traditional two-stage stochastic programming is risk-neutral and compares the random variables (e.g., total benefit) to identify the best decisions. To deal with the risk issues, a risk-aversion inexact two-stage stochastic programming model is developed for water resources management under uncertainty. The model was a hybrid methodology of interval-parameter programming, conditional value-at-risk measure, and a general two-stage stochastic programming framework. The method extends on the traditional two-stage stochastic programming method by enabling uncertainties presented as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. It could not only provide information on the benefits of the allocation plan to the decision makers but also measure the extreme expected loss on the second-stage penalty cost. The developed model was applied to a hypothetical case of water resources management. Results showed that that could help managers generate feasible and balanced risk-aversion allocation plans, and analyze the trade-offs between system stability and economy.

Stochastic responses of Van der Pol vibro-impact system with fractional derivative damping excited by Gaussian white noise

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

Xiao, Yanwen; Xu, Wei, E-mail: weixu@nwpu.edu.cn; Wang, Liang

2016-03-15

This paper focuses on the study of the stochastic Van der Pol vibro-impact system with fractional derivative damping under Gaussian white noise excitation. The equations of the original system are simplified by non-smooth transformation. For the simplified equation, the stochastic averaging approach is applied to solve it. Then, the fractional derivative damping term is facilitated by a numerical scheme, therewith the fourth-order Runge-Kutta method is used to obtain the numerical results. And the numerical simulation results fit the analytical solutions. Therefore, the proposed analytical means to study this system are proved to be feasible. In this context, the effects onmore » the response stationary probability density functions (PDFs) caused by noise excitation, restitution condition, and fractional derivative damping are considered, in addition the stochastic P-bifurcation is also explored in this paper through varying the value of the coefficient of fractional derivative damping and the restitution coefficient. These system parameters not only influence the response PDFs of this system but also can cause the stochastic P-bifurcation.« less

Front propagation and effect of memory in stochastic desertification models with an absorbing state

NASA Astrophysics Data System (ADS)

Herman, Dor; Shnerb, Nadav M.

2017-08-01

Desertification in dryland ecosystems is considered to be a major environmental threat that may lead to devastating consequences. The concern increases when the system admits two alternative steady states and the transition is abrupt and irreversible (catastrophic shift). However, recent studies show that the inherent stochasticity of the birth-death process, when superimposed on the presence of an absorbing state, may lead to a continuous (second order) transition even if the deterministic dynamics supports a catastrophic transition. Following these works we present here a numerical study of a one-dimensional stochastic desertification model, where the deterministic predictions are confronted with the observed dynamics. Our results suggest that a stochastic spatial system allows for a propagating front only when its active phase invades the inactive (desert) one. In the extinction phase one observes transient front propagation followed by a global collapse. In the presence of a seed bank the vegetation state is shown to be more robust against demographic stochasticity, but the transition in that case still belongs to the directed percolation equivalence class.

Analysis of stochastic model for non-linear volcanic dynamics

NASA Astrophysics Data System (ADS)

Alexandrov, D.; Bashkirtseva, I.; Ryashko, L.

2014-12-01

Motivated by important geophysical applications we consider a dynamic model of the magma-plug system previously derived by Iverson et al. (2006) under the influence of stochastic forcing. Due to strong nonlinearity of the friction force for solid plug along its margins, the initial deterministic system exhibits impulsive oscillations. Two types of dynamic behavior of the system under the influence of the parametric stochastic forcing have been found: random trajectories are scattered on both sides of the deterministic cycle or grouped on its internal side only. It is shown that dispersions are highly inhomogeneous along cycles in the presence of noises. The effects of noise-induced shifts, pressure stabilization and localization of random trajectories have been revealed with increasing the noise intensity. The plug velocity, pressure and displacement are highly dependent of noise intensity as well. These new stochastic phenomena are related with the nonlinear peculiarities of the deterministic phase portrait. It is demonstrated that the repetitive stick-slip motions of the magma-plug system in the case of stochastic forcing can be connected with drumbeat earthquakes.

Optical pumping of electron and nuclear spin in a negatively-charged quantum dot

NASA Astrophysics Data System (ADS)

Bracker, Allan; Gershoni, David; Korenev, Vladimir

2005-03-01

We report optical pumping of electron and nuclear spins in an individual negatively-charged quantum dot. With a bias-controlled heterostructure, we inject one electron into the quantum dot. Intense laser excitation produces negative photoluminescence polarization, which is easily erased by the Hanle effect, demonstrating optical pumping of a long-lived resident electron. The electron spin lifetime is consistent with the influence of nuclear spin fluctuations. Measuring the Overhauser effect in high magnetic fields, we observe a high degree of nuclear spin polarization, which is closely correlated to electron spin pumping.

Optical pumping of the electronic and nuclear spin of single charge-tunable quantum dots.

PubMed

Bracker, A S; Stinaff, E A; Gammon, D; Ware, M E; Tischler, J G; Shabaev, A; Efros, Al L; Park, D; Gershoni, D; Korenev, V L; Merkulov, I A

2005-02-04

We present a comprehensive examination of optical pumping of spins in individual GaAs quantum dots as we change the net charge from positive to neutral to negative with a charge-tunable heterostructure. Negative photoluminescence polarization memory is enhanced by optical pumping of ground state electron spins, which we prove with the first measurements of the Hanle effect on an individual quantum dot. We use the Overhauser effect in a high longitudinal magnetic field to demonstrate efficient optical pumping of nuclear spins for all three charge states of the quantum dot.

Optical Pumping of the Electronic and Nuclear Spin of Single Charge-Tunable Quantum Dots

NASA Astrophysics Data System (ADS)

Bracker, A. S.; Stinaff, E. A.; Gammon, D.; Ware, M. E.; Tischler, J. G.; Shabaev, A.; Efros, Al. L.; Park, D.; Gershoni, D.; Korenev, V. L.; Merkulov, I. A.

2005-02-01

We present a comprehensive examination of optical pumping of spins in individual GaAs quantum dots as we change the net charge from positive to neutral to negative with a charge-tunable heterostructure. Negative photoluminescence polarization memory is enhanced by optical pumping of ground state electron spins, which we prove with the first measurements of the Hanle effect on an individual quantum dot. We use the Overhauser effect in a high longitudinal magnetic field to demonstrate efficient optical pumping of nuclear spins for all three charge states of the quantum dot.

Effect of additional optical pumping injection into the ground-state ensemble on the gain and the phase recovery acceleration of quantum-dot semiconductor optical amplifiers

NASA Astrophysics Data System (ADS)

Kim, Jungho

2014-02-01

The effect of additional optical pumping injection into the ground-state ensemble on the ultrafast gain and the phase recovery dynamics of electrically-driven quantum-dot semiconductor optical amplifiers is numerically investigated by solving 1088 coupled rate equations. The ultrafast gain and the phase recovery responses are calculated with respect to the additional optical pumping power. Increasing the additional optical pumping power can significantly accelerate the ultrafast phase recovery, which cannot be done by increasing the injection current density.

Liquid metal enabled pump

PubMed Central

Tang, Shi-Yang; Khoshmanesh, Khashayar; Sivan, Vijay; Petersen, Phred; O’Mullane, Anthony P.; Abbott, Derek; Mitchell, Arnan; Kalantar-zadeh, Kourosh

2014-01-01

Small-scale pumps will be the heartbeat of many future micro/nanoscale platforms. However, the integration of small-scale pumps is presently hampered by limited flow rate with respect to the input power, and their rather complicated fabrication processes. These issues arise as many conventional pumping effects require intricate moving elements. Here, we demonstrate a system that we call the liquid metal enabled pump, for driving a range of liquids without mechanical moving parts, upon the application of modest electric field. This pump incorporates a droplet of liquid metal, which induces liquid flow at high flow rates, yet with exceptionally low power consumption by electrowetting/deelectrowetting at the metal surface. We present theory explaining this pumping mechanism and show that the operation is fundamentally different from other existing pumps. The presented liquid metal enabled pump is both efficient and simple, and thus has the potential to fundamentally advance the field of microfluidics. PMID:24550485

Synchronization of spin-transfer torque oscillators by spin pumping, inverse spin Hall, and spin Hall effects

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

Elyasi, Mehrdad; Bhatia, Charanjit S.; Yang, Hyunsoo, E-mail: eleyang@nus.edu.sg

2015-02-14

We have proposed a method to synchronize multiple spin-transfer torque oscillators based on spin pumping, inverse spin Hall, and spin Hall effects. The proposed oscillator system consists of a series of nano-magnets in junction with a normal metal with high spin-orbit coupling, and an accumulative feedback loop. We conduct simulations to demonstrate the effect of modulated charge currents in the normal metal due to spin pumping from each nano-magnet. We show that the interplay between the spin Hall effect and inverse spin Hall effect results in synchronization of the nano-magnets.

An Examination of a Pumping Rotor Blade Design for Brownout Mitigation

DTIC Science & Technology

2015-05-18

and 60° above the horizontal axis. All blade designs were tested in a hovering state in ground effect at a blade loading coefficient of 0.08...were tested in a hovering state in ground effect at a blade loading coefficient, CT/σ, of 0.08. Additional measurements were performed on the baseline...comparison to the 0◦ pumping blade due to a negative thrust effect that resulted from mass flow through the pumping slots. When operating at the higher

Stepwise pumping approach to improve free phase light hydrocarbon recovery from unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

1995-04-01

A stepwise, time-varying pumping approach is developed to improve free phase oil recovery of light non-aqueous phase liquids (LNAPL) from a homogeneous, unconfined aquifer. Stepwise pumping is used to contain the floating oil plume and obtain efficient free oil recovery. The graphical plots. The approach uses ARMOS ©, an areal two-dimensional multiphase flow, finite-element simulation model. Systematic simulations of free oil area changes to pumping rates are analyzed. Pumping rates are determined that achieve LNAPL plume containment at different times (i.e. 90, 180 and 360 days) for a planning period of 360 days. These pumping rates are used in reverse order as a stepwise (monotonically increasing) pumping strategy. This stepwise pumping strategy is analyzed further by performing additional simulations at different pumping rates for the last pumping period. The final stepwise pumping strategy is varied by factors of -25% and +30% to evaluate sensitivity in the free oil recovery process. Stepwise pumping is compared to steady pumping rates to determine the best free oil recovery strategy. Stepwise pumping is shown to improve oil recovery by increasing recoveredoil volume (11%) and decreasing residual oil (15%) when compared with traditional steady pumping strategies. The best stepwise pumping strategy recovers more free oil by reducing the amount of residual oil left in the system due to pumping drawdown. This stepwise pumping pproach can be used to enhance free oil recovery and provide for cost-effective design and management of LNAPL cleanup.

Low-dose or standard-dose proton pump inhibitors for maintenance therapy of gastro-oesophageal reflux disease: a cost-effectiveness analysis.

PubMed

You, J H S; Lee, A C M; Wong, S C Y; Chan, F K L

2003-03-15

Studies on the use of low-dose proton pump inhibitor for the maintenance therapy of gastro-oesophageal reflux disease have shown that it might be comparable with standard-dose proton pump inhibitor treatment and superior to standard-dose histamine-2 receptor antagonist therapy. To compare the impact of standard-dose histamine-2 receptor antagonist, low-dose proton pump inhibitor and standard-dose proton pump inhibitor treatment for the maintenance therapy of gastro-oesophageal reflux disease on symptom control and health care resource utilization from the perspective of a public health organization in Hong Kong. A Markov model was designed to simulate, over 12 months, the economic and clinical outcomes of gastro-oesophageal reflux disease patients treated with standard-dose histamine-2 receptor antagonist, low-dose proton pump inhibitor and standard-dose proton pump inhibitor. The transition probabilities were derived from the literature. Resource utilization was retrieved from a group of gastro-oesophageal reflux disease patients in Hong Kong. Sensitivity analysis was conducted to examine the robustness of the model. The standard-dose proton pump inhibitor strategy was associated with the highest numbers of symptom-free patient-years (0.954 years) and quality-adjusted life-years gained (0.999 years), followed by low-dose proton pump inhibitor and standard-dose histamine-2 receptor antagonist. The direct medical cost per patient in the standard-dose proton pump inhibitor group (904 US dollars) was lower than those of the low-dose proton pump inhibitor and standard-dose histamine-2 receptor antagonist groups. The standard-dose proton pump inhibitor strategy appears to be the most effective and least costly for the maintenance management of patients with gastro-oesophageal reflux disease in Hong Kong.

Simulated effects of groundwater pumping and artificial recharge on surface-water resources and riparian vegetation in the Verde Valley sub-basin, Central Arizona

USGS Publications Warehouse

Leake, Stanley A.; Pool, Donald R.

2010-01-01

In the Verde Valley sub-basin, groundwater use has increased in recent decades. Residents and stakeholders in the area have established several groups to help in planning for sustainability of water and other resources of the area. One of the issues of concern is the effect of groundwater pumping in the sub-basin on surface water and on groundwater-dependent riparian vegetation. The Northern Arizona Regional Groundwater-Flow Model by Pool and others (in press) is the most comprehensive and up-to-date tool available to understand the effects of groundwater pumping in the sub-basin. Using a procedure by Leake and others (2008), this model was modified and used to calculate effects of groundwater pumping on surface-water flow and evapotranspiration for areas in the sub-basin. This report presents results for the upper two model layers for pumping durations of 10 and 50 years. Results are in the form of maps that indicate the fraction of the well pumping rate that can be accounted for as the combined effect of reduced surface-water flow and evapotranspiration. In general, the highest and most rapid responses to pumping were computed to occur near surface-water features simulated in the modified model, but results are not uniform along these features. The results are intended to indicate general patterns of model-computed response over large areas. For site-specific projects, improved results may require detailed studies of the local hydrologic conditions and a refinement of the modified model in the area of interest.

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

DOE PAGES

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

2016-11-14

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

Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series

PubMed Central

Ferguson, Jake M; Ponciano, José M

2014-01-01

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. PMID:24304946

Centrifugal and Axial Pump Design and Off-Design Performance Prediction

NASA Technical Reports Server (NTRS)

Veres, Joseph P.

1995-01-01

A meanline pump-flow modeling method has been developed to provide a fast capability for modeling pumps of cryogenic rocket engines. Based on this method, a meanline pump-flow code PUMPA was written that can predict the performance of pumps at off-design operating conditions, given the loss of the diffusion system at the design point. The design-point rotor efficiency and slip factors are obtained from empirical correlations to rotor-specific speed and geometry. The pump code can model axial, inducer, mixed-flow, and centrifugal pumps and can model multistage pumps in series. The rapid input setup and computer run time for this meanline pump flow code make it an effective analysis and conceptual design tool. The map-generation capabilities of the code provide the information needed for interfacing with a rocket engine system modeling code. The off-design and multistage modeling capabilities of PUMPA permit the user to do parametric design space exploration of candidate pump configurations and to provide head-flow maps for engine system evaluation.

A quantum-classical theory with nonlinear and stochastic dynamics

NASA Astrophysics Data System (ADS)

Burić, N.; Popović, D. B.; Radonjić, M.; Prvanović, S.

2014-12-01

The method of constrained dynamical systems on the quantum-classical phase space is utilized to develop a theory of quantum-classical hybrid systems. Effects of the classical degrees of freedom on the quantum part are modeled using an appropriate constraint, and the interaction also includes the effects of neglected degrees of freedom. Dynamical law of the theory is given in terms of nonlinear stochastic differential equations with Hamiltonian and gradient terms. The theory provides a successful dynamical description of the collapse during quantum measurement.

Stochastic dynamic modeling of regular and slow earthquakes

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Radiance limits of ceramic phosphors under high excitation fluxes

NASA Astrophysics Data System (ADS)

Lenef, Alan; Kelso, John; Zheng, Yi; Tchoul, Maxim

2013-09-01

Ceramic phosphors, excited by high radiance pump sources, offer considerable potential for high radiance conversion. Interestingly, thermodynamic arguments suggest that the radiance of the luminescent spot can even exceed that of the incoming light source. In practice, however, thermal quenching and (non-thermal) optical saturation limit the maximum attainable radiance of the luminescent source. We present experimental data for Ce:YAG and Ce:GdYAG ceramics in which these limits have been investigated. High excitation fluxes are achieved using laser pumping. Optical pumping intensities exceeding 100W/mm2 have been shown to produce only modest efficiency depreciation at low overall pump powers because of the short Ce3+ lifetime, although additional limitations exist. When pump powers are higher, heat-transfer bottlenecks within the ceramic and heat-sink interfaces limit maximum pump intensities. We find that surface temperatures of these laser-pumped ceramics can reach well over 150°C, causing thermal-quenching losses. We also find that in some cases, the loss of quantum efficiency with increasing temperature can cause a thermal run-away effect, resulting in a rapid loss in converted light, possibly over-heating the sample or surrounding structures. While one can still obtain radiances on the order of many W/mm2/sr, temperature quenching effects ultimately limit converted light radiance. Finally, we use the diffusion-approximation radiation transport models and rate equation models to simulate some of these nonlinear optical pumping and heating effects in high-scattering ceramics.

A "place n play" modular pump for portable microfluidic applications.

PubMed

Li, Gang; Luo, Yahui; Chen, Qiang; Liao, Lingying; Zhao, Jianlong

2012-03-01

This paper presents an easy-to-use, power-free, and modular pump for portable microfluidic applications. The pump module is a degassed particle desorption polydimethylsiloxane (PDMS) slab with an integrated mesh-shaped chamber, which can be attached on the outlet port of microfluidic device to absorb the air in the microfluidic system and then to create a negative pressure for driving fluid. Different from the existing monolithic degassed PDMS pumps that are generally restricted to limited pumping capacity and are only compatible with PDMS-based microfluidic devices, this pump can offer various possible configures of pumping power by varying the geometries of the pump or by combining different pump modules and can also be employed in any material microfluidic devices. The key advantage of this pump is that its operation only requires the user to place the degassed PDMS slab on the outlet ports of microfluidic devices. To help design pumps with a suitable pumping performance, the effect of pump module geometry on its pumping capacity is also investigated. The results indicate that the performance of the degassed PDMS pump is strongly dependent on the surface area of the pump chamber, the exposure area and the volume of the PDMS pump slab. In addition, the initial volume of air in the closed microfluidic system and the cross-linking degree of PDMS also affect the performance of the degassed PDMS pump. Finally, we demonstrated the utility of this modular pumping method by applying it to a glass-based microfluidic device and a PDMS-based protein crystallization microfluidic device.

A “place n play” modular pump for portable microfluidic applications

PubMed Central

Li, Gang; Luo, Yahui; Chen, Qiang; Liao, Lingying; Zhao, Jianlong

2012-01-01

This paper presents an easy-to-use, power-free, and modular pump for portable microfluidic applications. The pump module is a degassed particle desorption polydimethylsiloxane (PDMS) slab with an integrated mesh-shaped chamber, which can be attached on the outlet port of microfluidic device to absorb the air in the microfluidic system and then to create a negative pressure for driving fluid. Different from the existing monolithic degassed PDMS pumps that are generally restricted to limited pumping capacity and are only compatible with PDMS-based microfluidic devices, this pump can offer various possible configures of pumping power by varying the geometries of the pump or by combining different pump modules and can also be employed in any material microfluidic devices. The key advantage of this pump is that its operation only requires the user to place the degassed PDMS slab on the outlet ports of microfluidic devices. To help design pumps with a suitable pumping performance, the effect of pump module geometry on its pumping capacity is also investigated. The results indicate that the performance of the degassed PDMS pump is strongly dependent on the surface area of the pump chamber, the exposure area and the volume of the PDMS pump slab. In addition, the initial volume of air in the closed microfluidic system and the cross-linking degree of PDMS also affect the performance of the degassed PDMS pump. Finally, we demonstrated the utility of this modular pumping method by applying it to a glass-based microfluidic device and a PDMS-based protein crystallization microfluidic device. PMID:22685507

Pump instability phenomena generated by fluid forces

NASA Technical Reports Server (NTRS)

Gopalakrishnan, S.

1985-01-01

Rotor dynamic behavior of high energy centrifugal pumps is significantly affected by two types of fluid forces; one due to the hydraulic interaction of the impeller with the surrounding volute or diffuser and the other due to the effect of the wear rings. The available data on these forces is first reviewed. A simple one degree-of-freedom system containing these forces is analytically solved to exhibit the rotor dynamic effects. To illustrate the relative magnitude of these phenomena, an example of a multistage boiler feed pump is worked out. It is shown that the wear ring effects tend to suppress critical speed and postpone instability onset. But the volute-impeller forces tend to lower the critical speed and the instability onset speed. However, for typical boiler feed pumps under normal running clearances, the wear ring effects are much more significant than the destabilizing hydraulic interaction effects.

Cladding pumped Yb-doped HOM power amplifier with high gain

NASA Astrophysics Data System (ADS)

Abedin, Kazi S.; Ahmad, Raja; DeSantolo, Anthony M.; Nicholson, Jeffrey W.; Westbrook, Paul S.; Headley, Clifford; DiGiovanni, David J.

2018-02-01

Higher-order mode (HOM) fibers have been engineered to allow propagation of linearly polarized symmetric modes LP0,N in a robust way. Compared with the fundamental mode LP(0,1), HOMs exhibits an effective area that can be larger by over two order magnitude, and thus propagating light in these modes could greatly suppress the effect of nonlinear effects. HOM fibers could also be doped with rare earth ions in order to amplify light propagating in these modes, which offers the enormous potential for generating high-intensity pulses. Excitation of HOM gain fiber using cladding pumping with multimode pump source is attractive for ytterbium based amplifiers, because of the availability of low-cost multimode pump diodes in the 975nm wavelength range. One problem associated with cladding pumping which leads to excitation of the large doped core (over 100 μm diameter) is that it could result in a large amount of amplifiedspontaneous- emission (ASE) noise, particularly when the input signal is weak. Optimization of amplifier design is critical in order to suppress ASE and achieve high gain and pump-to-signal conversion efficiency. We conducted numerical modeling of a cladding pumped HOM-amplifier, which revealed that this problem could be mitigated by using a relatively long gain-fiber that allowed reabsorption of the forward propagating ASE resulting in a further amplification of the signal. We demonstrate efficient amplification of a LP0,10 mode with an effective area 3140μm2 in an Yb-doped HOM amplifier cladding pumped at 975nm. We have successfully obtained a 20.2dB gain for 0.95 W 1064 nm input seed signal to more than 105W.

Review article: relationship between the metabolism and efficacy of proton pump inhibitors--focus on rabeprazole.

PubMed

Horn, J

2004-11-01

Proton pump inhibitors are now considered the mainstay of treatment for acid-related disease. Although all proton pump inhibitors are highly effective, the antisecretory effects of different drugs in this class are not completely consistent across patients. One reason for this is the acid-suppressing effect of Helicobacter pylori infection, which may augment the actions of proton pump inhibitors. A second important reason for interpatient variability of the effects of proton pump inhibitors on acid secretion involves genetically determined differences in the metabolism of these drugs. This article focuses on the impact of genetic polymorphism of cytochrome P450 (CYP)2C19 on the pharmacokinetics and pharmacodynamics of proton pump inhibitors, particularly rabeprazole. Results reviewed indicate that the metabolism and pharmacokinetics of rabeprazole differ significantly from those of other proton pump inhibitors. Most importantly, the clearance of rabeprazole is largely nonenzymatic and less dependent on CYP2C19 than other drugs in its class. This results in greater consistency of pharmacokinetics for rabeprazole across a wide range of patients with acid-related disease, particularly those with different CYP2C19 genotypes. The pharmacodynamic profile for rabeprazole is also characterized by more rapid suppression of gastric acid secretion than with other proton pump inhibitors, which is also independent of CYP2C19 genotype. The favourable pharmacokinetic/pharmacodynamic profile for rabeprazole has been shown to result in high eradication rates for H. pylori in both normal and poor metabolizers. Pharmacodynamic results have also suggested that rabeprazole may be better suited than omeprazole as on-demand therapy for symptomatic gastro-oesophageal reflux disease. Finally, the use of rabeprazole is not complicated by clinically significant drug-drug interactions of the type that have been reported for omeprazole.

Role of interbranch pumping on the quantum-statistical behavior of multi-mode magnons in ferromagnetic nanowires

NASA Astrophysics Data System (ADS)

Haghshenasfard, Zahra; Cottam, M. G.

2018-01-01

Theoretical studies are reported for the quantum-statistical properties of microwave-driven multi-mode magnon systems as represented by ferromagnetic nanowires with a stripe geometry. Effects of both the exchange and the dipole-dipole interactions, as well as a Zeeman term for an external applied field, are included in the magnetic Hamiltonian. The model also contains the time-dependent nonlinear effects due to parallel pumping with an electromagnetic field. Using a coherent magnon state representation in terms of creation and annihilation operators, we investigate the effects of parallel pumping on the temporal evolution of various nonclassical properties of the system. A focus is on the interbranch mixing produced by the pumping field when there are three or more modes. In particular, the occupation magnon number and the multi-mode cross correlations between magnon modes are studied. Manipulation of the collapse and revival phenomena of the average magnon occupation number and the control of the cross correlation between the magnon modes are demonstrated through tuning of the parallel pumping field amplitude and appropriate choices for the coherent magnon states. The cross correlations are a direct consequence of the interbranch pumping effects and do not appear in the corresponding one- or two-mode magnon systems.

The response analysis of fractional-order stochastic system via generalized cell mapping method.

PubMed

Wang, Liang; Xue, Lili; Sun, Chunyan; Yue, Xiaole; Xu, Wei

2018-01-01

This paper is concerned with the response of a fractional-order stochastic system. The short memory principle is introduced to ensure that the response of the system is a Markov process. The generalized cell mapping method is applied to display the global dynamics of the noise-free system, such as attractors, basins of attraction, basin boundary, saddle, and invariant manifolds. The stochastic generalized cell mapping method is employed to obtain the evolutionary process of probability density functions of the response. The fractional-order ϕ 6 oscillator and the fractional-order smooth and discontinuous oscillator are taken as examples to give the implementations of our strategies. Studies have shown that the evolutionary direction of the probability density function of the fractional-order stochastic system is consistent with the unstable manifold. The effectiveness of the method is confirmed using Monte Carlo results.

An application of information theory to stochastic classical gravitational fields

NASA Astrophysics Data System (ADS)

Angulo, J.; Angulo, J. C.; Angulo, J. M.

2018-06-01

The objective of this study lies on the incorporation of the concepts developed in the Information Theory (entropy, complexity, etc.) with the aim of quantifying the variation of the uncertainty associated with a stochastic physical system resident in a spatiotemporal region. As an example of application, a relativistic classical gravitational field has been considered, with a stochastic behavior resulting from the effect induced by one or several external perturbation sources. One of the key concepts of the study is the covariance kernel between two points within the chosen region. Using this concept and the appropriate criteria, a methodology is proposed to evaluate the change of uncertainty at a given spatiotemporal point, based on available information and efficiently applying the diverse methods that Information Theory provides. For illustration, a stochastic version of the Einstein equation with an added Gaussian Langevin term is analyzed.

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.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

The global dynamics for a stochastic SIS epidemic model with isolation

NASA Astrophysics Data System (ADS)

Chen, Yiliang; Wen, Buyu; Teng, Zhidong

2018-02-01

In this paper, we investigate the dynamical behavior for a stochastic SIS epidemic model with isolation which is as an important strategy for the elimination of infectious diseases. It is assumed that the stochastic effects manifest themselves mainly as fluctuation in the transmission coefficient, the death rate and the proportional coefficient of the isolation of infective. It is shown that the extinction and persistence in the mean of the model are determined by a threshold value R0S . That is, if R0S < 1, then disease dies out with probability one, and if R0S > 1, then the disease is stochastic persistent in the means with probability one. Furthermore, the existence of a unique stationary distribution is discussed, and the sufficient conditions are established by using the Lyapunov function method. Finally, some numerical examples are carried out to confirm the analytical results.

Synthetic Sediments and Stochastic Groundwater Hydrology

NASA Astrophysics Data System (ADS)

Wilson, J. L.

2002-12-01

For over twenty years the groundwater community has pursued the somewhat elusive goal of describing the effects of aquifer heterogeneity on subsurface flow and chemical transport. While small perturbation stochastic moment methods have significantly advanced theoretical understanding, why is it that stochastic applications use instead simulations of flow and transport through multiple realizations of synthetic geology? Allan Gutjahr was a principle proponent of the Fast Fourier Transform method for the synthetic generation of aquifer properties and recently explored new, more geologically sound, synthetic methods based on multi-scale Markov random fields. Focusing on sedimentary aquifers, how has the state-of-the-art of synthetic generation changed and what new developments can be expected, for example, to deal with issues like conceptual model uncertainty, the differences between measurement and modeling scales, and subgrid scale variability? What will it take to get stochastic methods, whether based on moments, multiple realizations, or some other approach, into widespread application?

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Effect of mechanical tactile noise on amplitude of visual evoked potentials: multisensory stochastic resonance.

PubMed

Méndez-Balbuena, Ignacio; Huidobro, Nayeli; Silva, Mayte; Flores, Amira; Trenado, Carlos; Quintanar, Luis; Arias-Carrión, Oscar; Kristeva, Rumyana; Manjarrez, Elias

2015-10-01

The present investigation documents the electrophysiological occurrence of multisensory stochastic resonance in the human visual pathway elicited by tactile noise. We define multisensory stochastic resonance of brain evoked potentials as the phenomenon in which an intermediate level of input noise of one sensory modality enhances the brain evoked response of another sensory modality. Here we examined this phenomenon in visual evoked potentials (VEPs) modulated by the addition of tactile noise. Specifically, we examined whether a particular level of mechanical Gaussian noise applied to the index finger can improve the amplitude of the VEP. We compared the amplitude of the positive P100 VEP component between zero noise (ZN), optimal noise (ON), and high mechanical noise (HN). The data disclosed an inverted U-like graph for all the subjects, thus demonstrating the occurrence of a multisensory stochastic resonance in the P100 VEP. Copyright © 2015 the American Physiological Society.

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

PubMed

Wang, Bo; Qi, Qianqian

2018-06-01

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

Low-complexity stochastic modeling of wall-bounded shear flows

NASA Astrophysics Data System (ADS)

Zare, Armin

Turbulent flows are ubiquitous in nature and they appear in many engineering applications. Transition to turbulence, in general, increases skin-friction drag in air/water vehicles compromising their fuel-efficiency and reduces the efficiency and longevity of wind turbines. While traditional flow control techniques combine physical intuition with costly experiments, their effectiveness can be significantly enhanced by control design based on low-complexity models and optimization. In this dissertation, we develop a theoretical and computational framework for the low-complexity stochastic modeling of wall-bounded shear flows. Part I of the dissertation is devoted to the development of a modeling framework which incorporates data-driven techniques to refine physics-based models. We consider the problem of completing partially known sample statistics in a way that is consistent with underlying stochastically driven linear dynamics. Neither the statistics nor the dynamics are precisely known. Thus, our objective is to reconcile the two in a parsimonious manner. To this end, we formulate optimization problems to identify the dynamics and directionality of input excitation in order to explain and complete available covariance data. For problem sizes that general-purpose solvers cannot handle, we develop customized optimization algorithms based on alternating direction methods. The solution to the optimization problem provides information about critical directions that have maximal effect in bringing model and statistics in agreement. In Part II, we employ our modeling framework to account for statistical signatures of turbulent channel flow using low-complexity stochastic dynamical models. We demonstrate that white-in-time stochastic forcing is not sufficient to explain turbulent flow statistics and develop models for colored-in-time forcing of the linearized Navier-Stokes equations. We also examine the efficacy of stochastically forced linearized NS equations and their parabolized equivalents in the receptivity analysis of velocity fluctuations to external sources of excitation as well as capturing the effect of the slowly-varying base flow on streamwise streaks and Tollmien-Schlichting waves. In Part III, we develop a model-based approach to design surface actuation of turbulent channel flow in the form of streamwise traveling waves. This approach is capable of identifying the drag reducing trends of traveling waves in a simulation-free manner. We also use the stochastically forced linearized NS equations to examine the Reynolds number independent effects of spanwise wall oscillations on drag reduction in turbulent channel flows. This allows us to extend the predictive capability of our simulation-free approach to high Reynolds numbers.

Evaluation of Ti-Zr-V (NEG) Thin Films for their pumping speed and pumping Capacity

NASA Astrophysics Data System (ADS)

Bansod, Tripti; Sindal, B. K.; Kumar, K. V. A. N. P. S.; Shukla, S. K.

2012-11-01

Deposition of NEG thin films onto the interior walls of the vacuum chambers is an advanced technique to convert a vacuum chamber from a gas source to an effective pump. These films offer considerably large pumping speed for reactive gases like CO, H2 etc. A UHV compatible pumping speed measurement system was developed in-house to measure the pumping speed of NEG coated chambers. To inject the fixed quantity of CO and H2 gas in pumping speed measurement set-up a calibrated leak was also developed. Stainless steel chambers were sputter coated with thin film of Ti-Zr-V getter material using varied parameters for different compositions and thickness. Pumping capacity which is a function of sorbed gas quantities was also studied at various activation temperatures. In order to optimize the activation temperature for maximum pumping speed for CO and H2, pumping speeds were measured at room temperature after activation at different temperatures. The experimental system detail, pumping performance of the NEG film at various activation temperatures and RGA analysis are presented.

On the contribution of a stochastic background of gravitational radiation to the timing noise of pulsars

NASA Technical Reports Server (NTRS)

Mashhoon, B.

1982-01-01

The influence of a stochastic and isotropic background of gravitational radiation on timing measurements of pulsars is investigated, and it is shown that pulsar timing noise may be used to establish a significant upper limit of about 10 to the -10th on the total energy density of very long-wavelength stochastic gravitational waves. This places restriction on the strength of very long wavelength gravitational waves in the Friedmann model, and such a background is expected to have no significant effect on the approximately 3 K electromagnetic background radiation or on the dynamics of a cluster of galaxies.

Stochastic resonance based on modulation instability in spatiotemporal chaos.

PubMed

Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu

2017-04-03

A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.

Graph Theory-Based Pinning Synchronization of Stochastic Complex Dynamical Networks.

PubMed

Li, Xiao-Jian; Yang, Guang-Hong

2017-02-01

This paper is concerned with the adaptive pinning synchronization problem of stochastic complex dynamical networks (CDNs). Based on algebraic graph theory and Lyapunov theory, pinning controller design conditions are derived, and the rigorous convergence analysis of synchronization errors in the probability sense is also conducted. Compared with the existing results, the topology structures of stochastic CDN are allowed to be unknown due to the use of graph theory. In particular, it is shown that the selection of nodes for pinning depends on the unknown lower bounds of coupling strengths. Finally, an example on a Chua's circuit network is given to validate the effectiveness of the theoretical results.

Use of suprathreshold stochastic resonance in cochlear implant coding

NASA Astrophysics Data System (ADS)

Allingham, David; Stocks, Nigel G.; Morse, Robert P.

2003-05-01

In this article we discuss the possible use of a novel form of stochastic resonance, termed suprathreshold stochastic resonance (SSR), to improve signal encoding/transmission in cochlear implants. A model, based on the leaky-integrate-and-fire (LIF) neuron, has been developed from physiological data and use to model information flow in a population of cochlear nerve fibers. It is demonstrated that information flow can, in principle, be enhanced by the SSR effect. Furthermore, SSR was found to enhance information transmission for signal parameters that are commonly encountered in cochlear implants. This, therefore, gives hope that SSR may be implemented in cochlear implants to improve speech comprehension.

Laboratory testing of a supercritical helium pump for a magnetic refrigerator

NASA Technical Reports Server (NTRS)

Wang, Pao-Lien

1988-01-01

A supercritical helium testing system for a magnetic refrigerator has been built. Details of the supercritical helium pump, the test system, and the test instrumentation are given. Actual pump tests were not run during this ASEE term because of delivery problems associated with the required pump flow meter. Consequently, efforts were directed on preliminary design of the magnetic refrigeration system for the pump. The first concern with the magnetic refrigerator design was determining how to effectively make use of the pump. A method to incorporate the supercritical helium pump into a magnetic refrigerator was determined by using a computer model. An illustrated example of this procedure is given to provide a tool for sizing the magnetic refrigerator system as a function of the pump size. The function of the computer model and its operation are also outlined and discussed.

Accounting for Aquifer Heterogeneity in Analysis of the Skin Effect

NASA Astrophysics Data System (ADS)

Barrash, W.; Clemo, T.; Fox, J. J.; Johnson, T. C.

2005-12-01

Because results of hydraulic tests in boreholes can be influenced by wellbore skin, understanding and quantification of wellbore skin improves our ability to estimate hydraulic conductivity (K) with such tests. We have investigated positive skin at 10-cm ID PVC wells with slotted casing that were emplaced in a 15-m thick coarse fluvial aquifer at the Boise Hydrogeophysical Research Site (BHRS), and we have concluded that the skin effect derives from sand grains partially clogging the slotted casing. We use the WTAQ code (Moench, 1997; Barlow and Moench, 1999) with a redefinition of the term for delayed observation well response to include skin effects at observation wells (in addition to pumping wells) in order to analyze aquifer tests for average skin conductivity (Ks) values at individual wells at the BHRS. Systematic differences in Ks values are recognized in results at pumping (Ks Q) and observation (Ks obs) wells: larger values are seen at observation wells (average Ks obs = 0.0023 cm/s) than pumping wells. Two possible causes are recognized for the occurrence of higher Ks values at observation wells than pumping wells: (1) flow diversion between aquifer layers on approach to a pumping well with a positive skin; and (2) larger portion of flow passing through lower-K zones in the heterogeneous aquifer near the pumping well than the observation wells due to strongly radially convergent flow near the pumping well. Because of the increased drawdown at a pumping well compared with an observation well due to heterogeneity in the aquifer, observation wells provide better Ks estimates than those from pumping wells for the well-aquifer system at the BHRS.

Stochastic population dynamics of a montane ground-dwelling squirrel.

PubMed

Hostetler, Jeffrey A; Kneip, Eva; Van Vuren, Dirk H; Oli, Madan K

2012-01-01

Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990-2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λ<1) for 9 out of 18 years. The stochastic population growth rate λ(s) was 0.92, suggesting a declining population; however, the 95% CI on λ(s) included 1.0 (0.52-1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in λ. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration.

Stochastic Population Dynamics of a Montane Ground-Dwelling Squirrel

PubMed Central

Hostetler, Jeffrey A.; Kneip, Eva; Van Vuren, Dirk H.; Oli, Madan K.

2012-01-01

Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990–2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λ<1) for 9 out of 18 years. The stochastic population growth rate λs was 0.92, suggesting a declining population; however, the 95% CI on λs included 1.0 (0.52–1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in λ. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration. PMID:22479616

Stochastic modular analysis for gene circuits: interplay among retroactivity, nonlinearity, and stochasticity.

PubMed

Kim, Kyung Hyuk; Sauro, Herbert M

2015-01-01

This chapter introduces a computational analysis method for analyzing gene circuit dynamics in terms of modules while taking into account stochasticity, system nonlinearity, and retroactivity. (1) ANALOG ELECTRICAL CIRCUIT REPRESENTATION FOR GENE CIRCUITS: A connection between two gene circuit components is often mediated by a transcription factor (TF) and the connection signal is described by the TF concentration. The TF is sequestered to its specific binding site (promoter region) and regulates downstream transcription. This sequestration has been known to affect the dynamics of the TF by increasing its response time. The downstream effect-retroactivity-has been shown to be explicitly described in an electrical circuit representation, as an input capacitance increase. We provide a brief review on this topic. (2) MODULAR DESCRIPTION OF NOISE PROPAGATION: Gene circuit signals are noisy due to the random nature of biological reactions. The noisy fluctuations in TF concentrations affect downstream regulation. Thus, noise can propagate throughout the connected system components. This can cause different circuit components to behave in a statistically dependent manner, hampering a modular analysis. Here, we show that the modular analysis is still possible at the linear noise approximation level. (3) NOISE EFFECT ON MODULE INPUT-OUTPUT RESPONSE: We investigate how to deal with a module input-output response and its noise dependency. Noise-induced phenotypes are described as an interplay between system nonlinearity and signal noise. Lastly, we provide the comprehensive approach incorporating the above three analysis methods, which we call "stochastic modular analysis." This method can provide an analysis framework for gene circuit dynamics when the nontrivial effects of retroactivity, stochasticity, and nonlinearity need to be taken into account.

Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction

NASA Astrophysics Data System (ADS)

Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan

2017-04-01

Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

The simulation of the non-Markovian behaviour of a two-level system

NASA Astrophysics Data System (ADS)

Semina, I.; Petruccione, F.

2016-05-01

Non-Markovian relaxation dynamics of a two-level system is studied with the help of the non-linear stochastic Schrödinger equation with coloured Ornstein-Uhlenbeck noise. This stochastic Schrödinger equation is investigated numerically with an adapted Platen scheme. It is shown, that the memory effects have a significant impact to the dynamics of the system.

Stochastic and superharmonic stochastic resonances of a confined overdamped harmonic oscillator

NASA Astrophysics Data System (ADS)

Zhang, Lu; Lai, Li; Peng, Hao; Tu, Zhe; Zhong, Suchuan

2018-01-01

The dynamics of many soft condensed matter and biological systems is affected by space limitations, which produce some peculiar effects on the systems' stochastic resonance (SR) behavior. In this study, we propose a model where SR can be observed: a confined overdamped harmonic oscillator that is subjected to a sinusoidal driving force and is under the influence of a multiplicative white noise. The output response of the system is a periodic signal with harmonic frequencies that are odd multiples of the driving frequency. We verify the amplitude resonances at the driving frequencies and superharmonic frequencies that are equal to three, five, and seven times the driving frequency, using a numerical method based on the stochastic Taylor expansion. The synergistic effect of the multiplicative white noise, constant boundaries, and periodic driving force that can induce a SR in the output amplitude at the driving and superharmonic frequencies is found. The SR phenomenon found in this paper is sensitive to the driving amplitude and frequency, inherent potential parameter, and boundary width, thus leading to various resonance conditions. Therefore, the mechanism found could be beneficial for the characterization of these confined systems and could constitute an important tool for controlling their basic properties.

Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models

DOE PAGES

Butler, Troy; Graham, L.; Estep, D.; ...

2015-02-03

The uncertainty in spatially heterogeneous Manning’s n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented in this paper. Technical details that arise in practice by applying the framework to determine the Manning’s n parameter field in amore » shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of “condition” for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. Finally, this notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning’s n parameter and the effect on model predictions is analyzed.« less

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

PubMed

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

2017-04-01

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

Stochastic model of transcription factor-regulated gene expression

NASA Astrophysics Data System (ADS)

Karmakar, Rajesh; Bose, Indrani

2006-09-01

We consider a stochastic model of transcription factor (TF)-regulated gene expression. The model describes two genes, gene A and gene B, which synthesize the TFs and the target gene proteins, respectively. We show through analytic calculations that the TF fluctuations have a significant effect on the distribution of the target gene protein levels when the mean TF level falls in the highest sensitive region of the dose-response curve. We further study the effect of reducing the copy number of gene A from two to one. The enhanced TF fluctuations yield results different from those in the deterministic case. The probability that the target gene protein level exceeds a threshold value is calculated with the knowledge of the probability density functions associated with the TF and target gene protein levels. Numerical simulation results for a more detailed stochastic model are shown to be in agreement with those obtained through analytic calculations. The relevance of these results in the context of the genetic disorder haploinsufficiency is pointed out. Some experimental observations on the haploinsufficiency of the tumour suppressor gene, Nkx 3.1, are explained with the help of the stochastic model of TF-regulated gene expression.

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.

Preliminary design of a Primary Loop Pump Assembly (PLPA), using electromagnetic pumps

NASA Technical Reports Server (NTRS)

Moss, T. A.; Matlin, G.; Donelan, L.; Johnson, J. L.; Rowe, I.

1972-01-01

A preliminary design study of flight-type dc conduction-permanent magnetic, ac helical induction, and ac linear induction pumps for circulating 883 K (1130 F) NaK at 9.1 kg/sec (20 lb/sec) is described. Various electromagnetic pump geometrics are evaluated against hydraulic performance, and the effects of multiple windings and numbers of pumps per assembly on overall reliability were determined. The methods used in the electrical-hydraulic, stress, and thermal analysis are discussed, and the high temperature electrical materials selected for the application are listed.

A polynomial-chaos-expansion-based building block approach for stochastic analysis of photonic circuits

NASA Astrophysics Data System (ADS)

Waqas, Abi; Melati, Daniele; Manfredi, Paolo; Grassi, Flavia; Melloni, Andrea

2018-02-01

The Building Block (BB) approach has recently emerged in photonic as a suitable strategy for the analysis and design of complex circuits. Each BB can be foundry related and contains a mathematical macro-model of its functionality. As well known, statistical variations in fabrication processes can have a strong effect on their functionality and ultimately affect the yield. In order to predict the statistical behavior of the circuit, proper analysis of the uncertainties effects is crucial. This paper presents a method to build a novel class of Stochastic Process Design Kits for the analysis of photonic circuits. The proposed design kits directly store the information on the stochastic behavior of each building block in the form of a generalized-polynomial-chaos-based augmented macro-model obtained by properly exploiting stochastic collocation and Galerkin methods. Using this approach, we demonstrate that the augmented macro-models of the BBs can be calculated once and stored in a BB (foundry dependent) library and then used for the analysis of any desired circuit. The main advantage of this approach, shown here for the first time in photonics, is that the stochastic moments of an arbitrary photonic circuit can be evaluated by a single simulation only, without the need for repeated simulations. The accuracy and the significant speed-up with respect to the classical Monte Carlo analysis are verified by means of classical photonic circuit example with multiple uncertain variables.

Na/K pump inactivation, subsarcolemmal Na measurements, and cytoplasmic ion turnover kinetics contradict restricted Na spaces in murine cardiac myocytes

PubMed Central

Lu, Fang-Min

2017-01-01

Decades ago, it was proposed that Na transport in cardiac myocytes is modulated by large changes in cytoplasmic Na concentration within restricted subsarcolemmal spaces. Here, we probe this hypothesis for Na/K pumps by generating constitutive transsarcolemmal Na flux with the Na channel opener veratridine in whole-cell patch-clamp recordings. Using 25 mM Na in the patch pipette, pump currents decay strongly during continuous activation by extracellular K (τ, ∼2 s). In contradiction to depletion hypotheses, the decay becomes stronger when pump currents are decreased by hyperpolarization. Na channel currents are nearly unchanged by pump activity in these conditions, and conversely, continuous Na currents up to 0.5 nA in magnitude have negligible effects on pump currents. These outcomes are even more pronounced using 50 mM Li as a cytoplasmic Na congener. Thus, the Na/K pump current decay reflects mostly an inactivation mechanism that immobilizes Na/K pump charge movements, not cytoplasmic Na depletion. When channel currents are increased beyond 1 nA, models with unrestricted subsarcolemmal diffusion accurately predict current decay (τ ∼15 s) and reversal potential shifts observed for Na, Li, and K currents through Na channels opened by veratridine, as well as for Na, K, Cs, Li, and Cl currents recorded in nystatin-permeabilized myocytes. Ion concentrations in the pipette tip (i.e., access conductance) track without appreciable delay the current changes caused by sarcolemmal ion flux. Importantly, cytoplasmic mixing volumes, calculated from current decay kinetics, increase and decrease as expected with osmolarity changes (τ >30 s). Na/K pump current run-down over 20 min reflects a failure of pumps to recover from inactivation. Simulations reveal that pump inactivation coupled with Na-activated recovery enhances the rapidity and effectivity of Na homeostasis in cardiac myocytes. In conclusion, an autoregulatory mechanism enhances cardiac Na/K pump activity when cytoplasmic Na rises and suppresses pump activity when cytoplasmic Na declines. PMID:28606910

Effect of crystal length on the thermal characteristic in Nd: YLF laser with 20W diode pumped

NASA Astrophysics Data System (ADS)

Yahya, K. A.; Hussein, O. A.; Mustafa, O. H.

2016-03-01

Theoretical results are reported on thermal effects along the π- 1047nm and σ- 1053nm polarizations in a cut Nd: YLF rod crystal by using 20W Diode -End-pumped. The crystal length effects on the fraction of absorbed pump radiation converted into heat, radial temperature distribution, and the change in a radial refractive index. The result from this study has shown that a maximum fraction converted into heat is calculated to be around 24% and thermal effects of π-polarized 1047 nm stronger than σ-polarized 1053 nm.

Exciton Absorption in Semiconductor Quantum Wells Driven by a Strong Intersubband Pump Field

NASA Technical Reports Server (NTRS)

Liu, Ansheng; Ning, Cun-Zheng

1999-01-01

Optical interband excitonic absorption of semiconductor quantum wells (QW's) driven by a coherent pump field is investigated based on semiconductor Bloch equations. The pump field has a photon energy close to the intersubband spacing between the first two conduction subbands in the QW's. An external weak optical field probes the interband transition. The excitonic effects and pump-induced population redistribution within the conduction subbands in the QW system are included. When the density of the electron-hole pairs in the QW structure is low, the pump field induces an Autler-Townes splitting of the exciton absorption spectrum. The split size and the peak positions of the absorption doublet depend not only on the pump frequency and intensity but also on the carrier density. As the density of the electron-hole pairs is increased, the split contrast (the ratio between the maximum and minimum values) is decreased because the exciton effect is suppressed at higher densities due to the many-body screening.

Pump beam waist-dependent pulse energy generation in Nd:YAG/Cr4+:YAG passively Q-switched microchip laser

NASA Astrophysics Data System (ADS)

Li, Chao-yu; Dong, Jun

2016-08-01

The incident pump beam waist-dependent pulse energy generation in Nd:YAG/Cr4+:YAG composite crystal passively Q-switched microchip laser has been investigated experimentally and theoretically by moving the Nd:YAG/Cr4+:YAG composite crystal along the pump beam direction. Highest pulse energy of 0.4 mJ has been generated when the Nd:YAG/Cr4+:YAG composite crystal is moved about 6 mm away from the focused pump beam waist. Laser pulses with pulse width of 1.7 ns and peak power of over 235 kW have been achieved. The theoretically calculated effective laser beam area at different positions of Nd:YAG/Cr4+:YAG composite crystal along the pump beam direction is in good agreement with the experimental results. The highest peak power can be generated by adjusting the pump beam waist incident on the Nd:YAG/Cr4+:YAG composite crystal to optimize the effective laser beam area in passively Q-switched microchip laser.

Pump absorption in coiled and twisted double-clad hexagonal fiber: effect of launching conditions and core location

NASA Astrophysics Data System (ADS)

Dalidet, Romain; Peterka, Pavel; Doya, Valérie; Aubrecht, Jan; Koška, Pavel

2018-02-01

Ever extending applications of fiber lasers require energy efficient, high-power, small footprint and reliable fiber lasers and laser wavelength versatility. To meet these demands, next generation of active fibers for high-power fiber lasers is coming out that will eventually offer tailored spectroscopic properties, high robustness and reduced cooling requirements and improved efficiency through tailored pump absorption. We report on numerical modelling of the efficiency of the pump absorption in double clad active fibers with hexagonal shape of the inner cladding cross section and rare-earth-doped core. We analyze both the effect of different radii of the spool on which the fiber is coiled and different fiber twisting rates. Two different launching conditions were investigated: the Gaussian input pump beam and a speckle pattern that mimics the output of the pump laser diode pigtail. We have found that by asymmetric position of the rare-earth-doped core we can significantly improve the pump absorption.

Elementary theory of synchronous arterio-arterial blood pumps

NASA Technical Reports Server (NTRS)

Jones, R. T.; Petscheck, H. E.; Kantrowitz, A. R.

1976-01-01

In the technique of arterio-arterial pumping, a volume of fluid is withdrawn from the aorta during systole and reinjected during diastole, thereby reducing the systolic pressure of the heart and adding energy to the systemic circulation. It is found that an upper bound for the effectiveness of such devices is given by a formula that considers stroke output of the unaided heart and the increment caused by the pump with a stroke. The division of effort of the pump between the reduction of pressure and the increase of flow depends on the physiological mechanical impedance of the heart. The total effect is, however, independent of the impedance.