Directory of Open Access Journals (Sweden)
Michelle Hawkins
2013-11-01
Full Text Available Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.
Fundamentals of stochastic nature sciences
Klyatskin, Valery I
2017-01-01
This book addresses the processes of stochastic structure formation in two-dimensional geophysical fluid dynamics based on statistical analysis of Gaussian random fields, as well as stochastic structure formation in dynamic systems with parametric excitation of positive random fields f(r,t) described by partial differential equations. Further, the book considers two examples of stochastic structure formation in dynamic systems with parametric excitation in the presence of Gaussian pumping. In dynamic systems with parametric excitation in space and time, this type of structure formation either happens – or doesn’t! However, if it occurs in space, then this almost always happens (exponentially quickly) in individual realizations with a unit probability. In the case considered, clustering of the field f(r,t) of any nature is a general feature of dynamic fields, and one may claim that structure formation is the Law of Nature for arbitrary random fields of such type. The study clarifies the conditions under wh...
International Nuclear Information System (INIS)
Martinez, Eduardo
2012-01-01
The domain wall dynamics along thin ferromagnetic strips with high perpendicular magnetocrystalline anisotropy driven by either magnetic fields or spin-polarized currents is theoretically analyzed by means of full micromagnetic simulations and a one-dimensional model, including both surface roughness and thermal effects. At finite temperature, the results show a field dependence of the domain wall velocity in good qualitative agreement with available experimental measurements, indicating a low field, low velocity creep regime, and a high field, linear regime separated by a smeared depinning region. Similar behaviors were also observed under applied currents. In the low current creep regime the velocity-current characteristic does not depend significantly on the non-adiabaticity. At high currents, where the domain wall velocity becomes insensitive to surface pinning, the domain wall shows a precessional behavior even when the non-adiabatic parameter is equal to the Gilbert damping. These analyses confirm the relevance of both thermal fluctuations and surface roughness for the domain wall dynamics, and that complete micromagnetic modeling and one-dimensional studies taking into account these effects are required to interpret the experimental measurements in order to get a better understanding of the origin, the role and the magnitude of the non-adiabaticity. (paper)
Stochastic nature of series of waiting times
Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi
2013-06-01
Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2
Diaz-Ruelas, Alvaro; Jeldtoft Jensen, Henrik; Piovani, Duccio; Robledo, Alberto
2016-12-01
It is well known that low-dimensional nonlinear deterministic maps close to a tangent bifurcation exhibit intermittency and this circumstance has been exploited, e.g., by Procaccia and Schuster [Phys. Rev. A 28, 1210 (1983)], to develop a general theory of 1/f spectra. This suggests it is interesting to study the extent to which the behavior of a high-dimensional stochastic system can be described by such tangent maps. The Tangled Nature (TaNa) Model of evolutionary ecology is an ideal candidate for such a study, a significant model as it is capable of reproducing a broad range of the phenomenology of macroevolution and ecosystems. The TaNa model exhibits strong intermittency reminiscent of punctuated equilibrium and, like the fossil record of mass extinction, the intermittency in the model is found to be non-stationary, a feature typical of many complex systems. We derive a mean-field version for the evolution of the likelihood function controlling the reproduction of species and find a local map close to tangency. This mean-field map, by our own local approximation, is able to describe qualitatively only one episode of the intermittent dynamics of the full TaNa model. To complement this result, we construct a complete nonlinear dynamical system model consisting of successive tangent bifurcations that generates time evolution patterns resembling those of the full TaNa model in macroscopic scales. The switch from one tangent bifurcation to the next in the sequences produced in this model is stochastic in nature, based on criteria obtained from the local mean-field approximation, and capable of imitating the changing set of types of species and total population in the TaNa model. The model combines full deterministic dynamics with instantaneous parameter random jumps at stochastically drawn times. In spite of the limitations of our approach, which entails a drastic collapse of degrees of freedom, the description of a high-dimensional model system in terms of a low
A complementarity model for solving stochastic natural gas market equilibria
International Nuclear Information System (INIS)
Zhuang Jifang; Gabriel, Steven A.
2008-01-01
This paper presents a stochastic equilibrium model for deregulated natural gas markets. Each market participant (pipeline operators, producers, etc.) solves a stochastic optimization problem whose optimality conditions, when combined with market-clearing conditions give rise to a certain mixed complementarity problem (MiCP). The stochastic aspects are depicted by a recourse problem for each player in which the first-stage decisions relate to long-term contracts and the second-stage decisions relate to spot market activities for three seasons. Besides showing that such a market model is an instance of a MiCP, we provide theoretical results concerning long-term and spot market prices and solve the resulting MiCP for a small yet representative market. We also note an interesting observation for the value of the stochastic solution for non-optimization problems
A complementarity model for solving stochastic natural gas market equilibria
International Nuclear Information System (INIS)
Jifang Zhuang; Gabriel, S.A.
2008-01-01
This paper presents a stochastic equilibrium model for deregulated natural gas markets. Each market participant (pipeline operators, producers, etc.) solves a stochastic optimization problem whose optimality conditions, when combined with market-clearing conditions give rise to a certain mixed complementarity problem (MiCP). The stochastic aspects are depicted by a recourse problem for each player in which the first-stage decisions relate to long-term contracts and the second-stage decisions relate to spot market activities for three seasons. Besides showing that such a market model is an instance of a MiCP, we provide theoretical results concerning long-term and spot market prices and solve the resulting MiCP for a small yet representative market. We also note an interesting observation for the value of the stochastic solution for non-optimization problems. (author)
Constraining Stochastic Parametrisation Schemes Using High-Resolution Model Simulations
Christensen, H. M.; Dawson, A.; Palmer, T.
2017-12-01
Stochastic parametrisations are used in weather and climate models as a physically motivated way to represent model error due to unresolved processes. Designing new stochastic schemes has been the target of much innovative research over the last decade. While a focus has been on developing physically motivated approaches, many successful stochastic parametrisation schemes are very simple, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) multiplicative scheme `Stochastically Perturbed Parametrisation Tendencies' (SPPT). The SPPT scheme improves the skill of probabilistic weather and seasonal forecasts, and so is widely used. However, little work has focused on assessing the physical basis of the SPPT scheme. We address this matter by using high-resolution model simulations to explicitly measure the `error' in the parametrised tendency that SPPT seeks to represent. The high resolution simulations are first coarse-grained to the desired forecast model resolution before they are used to produce initial conditions and forcing data needed to drive the ECMWF Single Column Model (SCM). By comparing SCM forecast tendencies with the evolution of the high resolution model, we can measure the `error' in the forecast tendencies. In this way, we provide justification for the multiplicative nature of SPPT, and for the temporal and spatial scales of the stochastic perturbations. However, we also identify issues with the SPPT scheme. It is therefore hoped these measurements will improve both holistic and process based approaches to stochastic parametrisation. Figure caption: Instantaneous snapshot of the optimal SPPT stochastic perturbation, derived by comparing high-resolution simulations with a low resolution forecast model.
A Stochastic Grammar for Natural Shapes
Felzenszwalb, Pedro F.
2013-01-01
We consider object detection using a generic model for natural shapes. A common approach for object recognition involves matching object models directly to images. Another approach involves building intermediate representations via a generic grouping processes. We argue that these two processes (model-based recognition and grouping) may use similar computational mechanisms. By defining a generic model for shapes we can use model-based techniques to implement a mid-level vision grouping process.
Patrick C. Tobin; Ottar N. Bjornstad
2005-01-01
Natural enemy-victim systems may exhibit a range of dynamic space-time patterns. We used a theoretical framework to study spatiotemporal structuring in a transient natural enemy-victim system subject to differential rates of dispersal, stochastic forcing, and nonlinear dynamics. Highly mobile natural enemies that attacked less mobile victims were locally spatially...
High-speed Stochastic Fatigue Testing
DEFF Research Database (Denmark)
Brincker, Rune; Sørensen, John Dalsgaard
1990-01-01
Good stochastic fatigue tests are difficult to perform. One of the major reasons is that ordinary servohydraulic loading systems realize the prescribed load history accurately at very low testing speeds only. If the speeds used for constant amplitude testing are applied to stochastic fatigue...
Rackauckas, Christopher; Nie, Qing
2017-01-01
Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs.
International Nuclear Information System (INIS)
Gutierrez, R.; Nafidi, A.; Gutierrez Sanchez, R.
2005-01-01
The principal objective of the present study is to examine the possibilities of using a Gompertz-type innovation diffusion process as a stochastic growth model of natural-gas consumption in Spain, and to compare our results with those obtained, on the one hand, by stochastic logistic innovation modelling and, on the other, by using a stochastic lognormal growth model based on a non-innovation diffusion process. Such a comparison is carried out taking into account the macroeconomic characteristics and natural-gas consumption patterns in Spain, both of which reflect the current expansive situation characterizing the Spanish economy. From the technical standpoint a contribution is also made to the theory of the stochastic Gompertz Innovation diffusion process (SGIDP), as applied to the case in question. (author)
Stochastic Approaches Within a High Resolution Rapid Refresh Ensemble
Jankov, I.
2017-12-01
It is well known that global and regional numerical weather prediction (NWP) ensemble systems are under-dispersive, producing unreliable and overconfident ensemble forecasts. Typical approaches to alleviate this problem include the use of multiple dynamic cores, multiple physics suite configurations, or a combination of the two. While these approaches may produce desirable results, they have practical and theoretical deficiencies and are more difficult and costly to maintain. An active area of research that promotes a more unified and sustainable system is the use of stochastic physics. Stochastic approaches include Stochastic Parameter Perturbations (SPP), Stochastic Kinetic Energy Backscatter (SKEB), and Stochastic Perturbation of Physics Tendencies (SPPT). The focus of this study is to assess model performance within a convection-permitting ensemble at 3-km grid spacing across the Contiguous United States (CONUS) using a variety of stochastic approaches. A single physics suite configuration based on the operational High-Resolution Rapid Refresh (HRRR) model was utilized and ensemble members produced by employing stochastic methods. Parameter perturbations (using SPP) for select fields were employed in the Rapid Update Cycle (RUC) land surface model (LSM) and Mellor-Yamada-Nakanishi-Niino (MYNN) Planetary Boundary Layer (PBL) schemes. Within MYNN, SPP was applied to sub-grid cloud fraction, mixing length, roughness length, mass fluxes and Prandtl number. In the RUC LSM, SPP was applied to hydraulic conductivity and tested perturbing soil moisture at initial time. First iterative testing was conducted to assess the initial performance of several configuration settings (e.g. variety of spatial and temporal de-correlation lengths). Upon selection of the most promising candidate configurations using SPP, a 10-day time period was run and more robust statistics were gathered. SKEB and SPPT were included in additional retrospective tests to assess the impact of using
Stochastic evolutions and hadronization of highly excited hadronic matter
International Nuclear Information System (INIS)
Carruthers, P.
1984-01-01
Stochastic ingredients of high energy hadronic collisions are analyzed, with emphasis on multiplicity distributions. The conceptual simplicity of the k-cell negative binomial distribution is related to the evolution of probability distributions via the Fokker-Planck and related equations. The connection to underlying field theory ideas is sketched. 17 references
Natural tracer test simulation by stochastic particle tracking method
International Nuclear Information System (INIS)
Ackerer, P.; Mose, R.; Semra, K.
1990-01-01
Stochastic particle tracking methods are well adapted to 3D transport simulations where discretization requirements of other methods usually cannot be satisfied. They do need a very accurate approximation of the velocity field. The described code is based on the mixed hybrid finite element method (MHFEM) to calculated the piezometric and velocity field. The random-walk method is used to simulate mass transport. The main advantages of the MHFEM over FD or FE are the simultaneous calculation of pressure and velocity, which are considered as unknowns; the possibility of interpolating velocities everywhere; and the continuity of the normal component of the velocity vector from one element to another. For these reasons, the MHFEM is well adapted for particle tracking methods. After a general description of the numerical methods, the model is used to simulate the observations made during the Twin Lake Tracer Test in 1983. A good match is found between observed and simulated heads and concentrations. (Author) (12 refs., 4 figs.)
Collective, stochastic and nonequilibrium behavior of highly excited hadronic matter
Energy Technology Data Exchange (ETDEWEB)
Carruthers, P [Los Alamos National Lab., NM (USA). Theoretical Div.
1984-04-23
We discuss selected problems concerning the dynamics and stochastic behavior of highly excited matter, particularly the QCD plasma. For the latter we consider the equation of state, kinetics, quasiparticles, flow properties and possible chaos and turbulence. The promise of phase space distribution functions for covariant transport and kinetic theory is stressed. The possibility and implications of a stochastic bag are spelled out. A simplified space-time model of hadronic collisions is pursued, with applications to A-A collisions and other matters. The domain wall between hadronic and plasma phase is of potential importance: its thickness and relation to surface tension is noticed. Finally, we review the recently developed stochastic cell model of multiparticle distributions and KNO scaling. This topic leads to the notion that fractional dimensions are involved in a rather general dynamical context. We speculate that various scaling phenomena are independent of the full dynamical structure, depending only on a general stochastic framework having to do with simple maps and strange attractors. 42 refs.
Chen, Bor-Sen; Yeh, Chin-Hsun
2017-12-01
We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.
Stochastic Model for the Vocabulary Growth in Natural Languages
Directory of Open Access Journals (Sweden)
Martin Gerlach
2013-05-01
Full Text Available We propose a stochastic model for the number of different words in a given database which incorporates the dependence on the database size and historical changes. The main feature of our model is the existence of two different classes of words: (i a finite number of core words, which have higher frequency and do not affect the probability of a new word to be used, and (ii the remaining virtually infinite number of noncore words, which have lower frequency and, once used, reduce the probability of a new word to be used in the future. Our model relies on a careful analysis of the Google Ngram database of books published in the last centuries, and its main consequence is the generalization of Zipf’s and Heaps’ law to two-scaling regimes. We confirm that these generalizations yield the best simple description of the data among generic descriptive models and that the two free parameters depend only on the language but not on the database. From the point of view of our model, the main change on historical time scales is the composition of the specific words included in the finite list of core words, which we observe to decay exponentially in time with a rate of approximately 30 words per year for English.
Stochastic models of solute transport in highly heterogeneous geologic media
Energy Technology Data Exchange (ETDEWEB)
Semenov, V.N.; Korotkin, I.A.; Pruess, K.; Goloviznin, V.M.; Sorokovikova, O.S.
2009-09-15
A stochastic model of anomalous diffusion was developed in which transport occurs by random motion of Brownian particles, described by distribution functions of random displacements with heavy (power-law) tails. One variant of an effective algorithm for random function generation with a power-law asymptotic and arbitrary factor of asymmetry is proposed that is based on the Gnedenko-Levy limit theorem and makes it possible to reproduce all known Levy {alpha}-stable fractal processes. A two-dimensional stochastic random walk algorithm has been developed that approximates anomalous diffusion with streamline-dependent and space-dependent parameters. The motivation for introducing such a type of dispersion model is the observed fact that tracers in natural aquifers spread at different super-Fickian rates in different directions. For this and other important cases, stochastic random walk models are the only known way to solve the so-called multiscaling fractional order diffusion equation with space-dependent parameters. Some comparisons of model results and field experiments are presented.
Collective, stochastic and nonequilibrium behavior of highly excited hadronic matter
International Nuclear Information System (INIS)
Carruthers, P.
1983-01-01
We discuss selected problems concerning the dynamic and stochasticc behavior of highly excited matter, particularly the QCD plasma. For the latter we consider the equation of state, kinetics, quasiparticles, flow properties and possible chaos and turbulence. The promise of phase space distribution functions for covariant transport and kinetic theory is stressed. The possibility and implications of a stochastic bag are spelled out. A simplified space-time model of hadronic collisions is pursued, with applications to A-A collisions and other matters. The domain wall between hadronic and plasma phase is of potential importance: its thickness and relation to surface tension are noticed. Finally we reviewed the recently developed stochastic cell model of multiparticle distributions and KNO scaling. This topic leads to the notion that fractal dimensions are involved in a rather general dynamical context. We speculate that various scaling phenomena are independent of the full dynamical structure, depending only on a general stochastic framework having to do with simple maps and strange attractors. 42 references
Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.
2016-02-24
-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.
Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches
Egging, Rudolf Gerardus
This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. 1 The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in
International Nuclear Information System (INIS)
Egging, R.G.
2010-11-01
This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in
Strelkov, S. A.; Sushkevich, T. A.; Maksakova, S. V.
2017-11-01
We are talking about russian achievements of the world level in the theory of radiation transfer, taking into account its polarization in natural media and the current scientific potential developing in Russia, which adequately provides the methodological basis for theoretically-calculated research of radiation processes and radiation fields in natural media using supercomputers and mass parallelism. A new version of the matrix transfer operator is proposed for solving problems of polarized radiation transfer in heterogeneous media by the method of influence functions, when deterministic and stochastic methods can be combined.
Patterns of Stochastic Behavior in Dynamically Unstable High-Dimensional Biochemical Networks
Directory of Open Access Journals (Sweden)
Simon Rosenfeld
2009-01-01
Full Text Available The question of dynamical stability and stochastic behavior of large biochemical networks is discussed. It is argued that stringent conditions of asymptotic stability have very little chance to materialize in a multidimensional system described by the differential equations of chemical kinetics. The reason is that the criteria of asymptotic stability (Routh- Hurwitz, Lyapunov criteria, Feinberg’s Deficiency Zero theorem would impose the limitations of very high algebraic order on the kinetic rates and stoichiometric coefficients, and there are no natural laws that would guarantee their unconditional validity. Highly nonlinear, dynamically unstable systems, however, are not necessarily doomed to collapse, as a simple Jacobian analysis would suggest. It is possible that their dynamics may assume the form of pseudo-random fluctuations quite similar to a shot noise, and, therefore, their behavior may be described in terms of Langevin and Fokker-Plank equations. We have shown by simulation that the resulting pseudo-stochastic processes obey the heavy-tailed Generalized Pareto Distribution with temporal sequence of pulses forming the set of constituent-specific Poisson processes. Being applied to intracellular dynamics, these properties are naturally associated with burstiness, a well documented phenomenon in the biology of gene expression.
Gragg, Jared; Klose, Ellison; Yang, James
2017-07-01
The available coefficient of friction (ACOF) is a measure of the friction available between two surfaces, which for human gait would be the footwear-floor interface. It is often compared to the required coefficient of friction (RCOF) to determine the likelihood of a slip in gait. Both the ACOF and RCOF are stochastic by nature meaning that neither should be represented by a deterministic value, such as the sample mean. Previous research has determined that the RCOF can be modelled well by either the normal or lognormal distributions, but previous research aimed at determining an appropriate distribution for the ACOF was inconclusive. This study focuses on modelling the stochastic nature of the ACOF by fitting eight continuous probability distributions to ACOF data for six scenarios. In addition, the data were used to study the effect that a simple housekeeping action such as sweeping could have on the ACOF. Practitioner Summary: Previous research aimed at determining an appropriate distribution for the ACOF was inconclusive. The study addresses this issue as well as looking at the effect that an act such as sweeping has on the ACOF.
Reddy, L Ram Gopal; Kuntamalla, Srinivas
2011-01-01
Heart rate variability analysis is fast gaining acceptance as a potential non-invasive means of autonomic nervous system assessment in research as well as clinical domains. In this study, a new nonlinear analysis method is used to detect the degree of nonlinearity and stochastic nature of heart rate variability signals during two forms of meditation (Chi and Kundalini). The data obtained from an online and widely used public database (i.e., MIT/BIH physionet database), is used in this study. The method used is the delay vector variance (DVV) method, which is a unified method for detecting the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. From the results it is clear that there is a significant change in the nonlinearity and stochastic nature of the signal before and during the meditation (p value > 0.01). During Chi meditation there is a increase in stochastic nature and decrease in nonlinear nature of the signal. There is a significant decrease in the degree of nonlinearity and stochastic nature during Kundalini meditation.
Crisan, Dan
2011-01-01
"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa
A Sparse Stochastic Collocation Technique for High-Frequency Wave Propagation with Uncertainty
Malenova, G.; Motamed, M.; Runborg, O.; Tempone, Raul
2016-01-01
We consider the wave equation with highly oscillatory initial data, where there is uncertainty in the wave speed, initial phase, and/or initial amplitude. To estimate quantities of interest related to the solution and their statistics, we combine a high-frequency method based on Gaussian beams with sparse stochastic collocation. Although the wave solution, uϵ, is highly oscillatory in both physical and stochastic spaces, we provide theoretical arguments for simplified problems and numerical evidence that quantities of interest based on local averages of |uϵ|2 are smooth, with derivatives in the stochastic space uniformly bounded in ϵ, where ϵ denotes the short wavelength. This observable related regularity makes the sparse stochastic collocation approach more efficient than Monte Carlo methods. We present numerical tests that demonstrate this advantage.
A Sparse Stochastic Collocation Technique for High-Frequency Wave Propagation with Uncertainty
Malenova, G.
2016-09-08
We consider the wave equation with highly oscillatory initial data, where there is uncertainty in the wave speed, initial phase, and/or initial amplitude. To estimate quantities of interest related to the solution and their statistics, we combine a high-frequency method based on Gaussian beams with sparse stochastic collocation. Although the wave solution, uϵ, is highly oscillatory in both physical and stochastic spaces, we provide theoretical arguments for simplified problems and numerical evidence that quantities of interest based on local averages of |uϵ|2 are smooth, with derivatives in the stochastic space uniformly bounded in ϵ, where ϵ denotes the short wavelength. This observable related regularity makes the sparse stochastic collocation approach more efficient than Monte Carlo methods. We present numerical tests that demonstrate this advantage.
High Weak Order Methods for Stochastic Differential Equations Based on Modified Equations
Abdulle, Assyr
2012-01-01
© 2012 Society for Industrial and Applied Mathematics. Inspired by recent advances in the theory of modified differential equations, we propose a new methodology for constructing numerical integrators with high weak order for the time integration of stochastic differential equations. This approach is illustrated with the constructions of new methods of weak order two, in particular, semi-implicit integrators well suited for stiff (meansquare stable) stochastic problems, and implicit integrators that exactly conserve all quadratic first integrals of a stochastic dynamical system. Numerical examples confirm the theoretical results and show the versatility of our methodology.
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Arampatzis, Georgios; Katsoulakis, Markos A; Pantazis, Yannis
2015-01-01
Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Directory of Open Access Journals (Sweden)
Georgios Arampatzis
Full Text Available Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of
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.
International Nuclear Information System (INIS)
Takata, Takashi; Yamaguchi, Akira
2009-01-01
Since various uncertainties of input variables are involved and nonlinearly-correlated in the Best Estimate (BE) plant dynamics code, it is of importance to evaluate the importance of input uncertainty to the computational results and to estimate the accuracy of the confidence level of the results. In order to estimate the importance and the accuracy, the authors have applied the stochastic safety analysis procedure using the Latin Hypercube sampling method to Liquid Metal Reactor (LMR) natural circulation Decay Heat Removal (DHR) phenomenon in the present paper. 17 input variables are chosen for the analyses and 5 influential variables, which affect the maximum coolant temperature at the core in a short period of time (several tens seconds), are selected to investigate the importance by comparing with the full-scope parametric analysis. As a result, it has been demonstrated that a comparative small number of samples is sufficient enough to estimate the dominant input variable and the confidence level. Furthermore, the influence of the sampling method on the accuracy of the upper tolerance limit (confidence level of 95%) has been examined based on the Wilks' formula. (author)
International Nuclear Information System (INIS)
Hasegawa, Keita; Komiyama, Ryoichi; Fujii, Yasumasa
2016-01-01
The paper presents an economic rationality analysis of power generation mix by stochastic dynamic programming considering fuel price uncertainties and supply disruption risks such as import disruption and nuclear power plant shutdown risk. The situation revolving around Japan's energy security adopted the past statistics, it cannot be applied to a quantitative analysis of future uncertainties. Further objective and quantitative evaluation methods are required in order to analyze Japan's energy system and make it more resilient in sight of long time scale. In this paper, the authors firstly develop the cost minimization model considering oil and natural gas price respectively by stochastic dynamic programming. Then, the authors show several premises of model and an example of result with related to crude oil stockpile, liquefied natural gas stockpile and nuclear power plant capacity. (author)
Scalable domain decomposition solvers for stochastic PDEs in high performance computing
International Nuclear Information System (INIS)
Desai, Ajit; Pettit, Chris; Poirel, Dominique; Sarkar, Abhijit
2017-01-01
Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.
Directory of Open Access Journals (Sweden)
A. W. Wernik
1996-01-01
Full Text Available Four data sets of density fluctuations measured in-situ by the Dynamics Explorer (DE 2 were analyzed in an attempt to study chaotic nature of the high-latitude turbulence and, in this way to complement the conventional spectral analysis. It has been found that the probability distribution function of density differences is far from Gaussian and similar to that observed in the intermittent fluid or MBD turbulence. This indicates that ionospheric density fluctuations are not stochastic but coherent to some extent. Wayland's and surrogate data tests for determinism in a time series of density data allowed us to differentiate between regions of intense shear and moderate shear. We observe that in the region of strong field aligned currents (FAC and intense shear, or along the convection in the collisional regime, ionospheric turbulence behaves like a random noise with non-Gaussian statistics implying that the underlying physical process is nondeterministic. On the other hand, when FACs are weak, and shear is moderate or observations made in the inertial regime the turbulence is chaotic. The attractor dimension is lowest (1.9 for 'old' convected irregularities. The dimension 3.2 is found for turbulence in the inertial regime and considerably smaller (2.4 in the collisional regime. It is suggested that a high dimension in the inertial regime may be caused by a complicated velocity structure in the shear instability region.
PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling
Directory of Open Access Journals (Sweden)
Emilio J. Palacios-Garcia
2017-09-01
Full Text Available Reduction of CO2 emissions is a main target in the future smart grid. This goal is boosting the installation of renewable energy resources (RES, as well as a major consumer engagement that seeks for a more efficient utilization of these resources toward the figure of ‘prosumers’. Nevertheless, these resources present an intermittent nature, which requires the presence of an energy storage system and an energy management system (EMS to ensure an uninterrupted power supply. Moreover, network-related issues might arise due to the increasing power of renewable resources installed in the grid, the storage systems also being capable of contributing to the network stability. However, to assess these future scenarios and test the control strategies, a simulation system is needed. The aim of this paper is to analyze the interaction between residential consumers with high penetration of PV generation and distributed storage and the grid by means of a high temporal resolution simulation scenario based on a stochastic residential load model and PV production records. Results of the model are presented for different PV power rates and storage capacities, as well as a two-level charging strategy as a mechanism for increasing the hosting capacity (HC of the network.
Zhang, Kemei; Zhao, Cong-Ran; Xie, Xue-Jun
2015-12-01
This paper considers the problem of output feedback stabilisation for stochastic high-order feedforward nonlinear systems with time-varying delay. By using the homogeneous domination theory and solving several troublesome obstacles in the design and analysis, an output feedback controller is constructed to drive the closed-loop system globally asymptotically stable in probability.
Stochastic clustering of material surface under high-heat plasma load
Budaev, Viacheslav P.
2017-11-01
The results of a study of a surface formed by high-temperature plasma loads on various materials such as tungsten, carbon and stainless steel are presented. High-temperature plasma irradiation leads to an inhomogeneous stochastic clustering of the surface with self-similar granularity - fractality on the scale from nanoscale to macroscales. Cauliflower-like structure of tungsten and carbon materials are formed under high heat plasma load in fusion devices. The statistical characteristics of hierarchical granularity and scale invariance are estimated. They differ qualitatively from the roughness of the ordinary Brownian surface, which is possibly due to the universal mechanisms of stochastic clustering of material surface under the influence of high-temperature plasma.
Global stability of stochastic high-order neural networks with discrete and distributed delays
International Nuclear Information System (INIS)
Wang Zidong; Fang Jianan; Liu Xiaohui
2008-01-01
High-order neural networks can be considered as an expansion of Hopfield neural networks, and have stronger approximation property, faster convergence rate, greater storage capacity, and higher fault tolerance than lower-order neural networks. In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with discrete and distributed time-delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived, which guarantee the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the stochastic high-order delayed neural networks under consideration are globally asymptotically stable in the mean square if two linear matrix inequalities (LMIs) are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also shown that the main results in this paper cover some recently published works. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria
Ogawa, Shigeyoshi
2017-01-01
This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...
International Nuclear Information System (INIS)
EVANS, TE; MOYER, RA; THOMAS, PR; WATKINS, JG; OSBORNE, TH; BOEDO, JA; FENSTERMACHER, ME; FINKEN, KH; GROEBNER, RJ; GROTH, M; HARRIS, JH; LAHAYE, RJ; LASNIER, CJ; MASUZAKI, S; OHYABU, N; PRETTY, D; RHODES, TL; REIMERDES, H; RUDAKOV, DL; SCHAFFER, MJ; WANG, G; ZENG, L.
2003-01-01
OAK-B135 A stochastic magnetic boundary, produced by an externally applied edge resonant magnetic perturbation, is used to suppress large edge localized modes (ELMs) in high confinement (H-mode) plasmas. The resulting H-mode displays rapid, small oscillations with a bursty character modulated by a coherent 130 Hz envelope. The H-mode transport barrier is unaffected by the stochastic boundary. The core confinement of these discharges is unaffected, despite a three-fold drop in the toroidal rotation in the plasma core. These results demonstrate that stochastic boundaries are compatible with H-modes and may be attractive for ELM control in next-step burning fusion tokamaks
Evans, T E; Moyer, R A; Thomas, P R; Watkins, J G; Osborne, T H; Boedo, J A; Doyle, E J; Fenstermacher, M E; Finken, K H; Groebner, R J; Groth, M; Harris, J H; La Haye, R J; Lasnier, C J; Masuzaki, S; Ohyabu, N; Pretty, D G; Rhodes, T L; Reimerdes, H; Rudakov, D L; Schaffer, M J; Wang, G; Zeng, L
2004-06-11
A stochastic magnetic boundary, produced by an applied edge resonant magnetic perturbation, is used to suppress most large edge-localized modes (ELMs) in high confinement (H-mode) plasmas. The resulting H mode displays rapid, small oscillations with a bursty character modulated by a coherent 130 Hz envelope. The H mode transport barrier and core confinement are unaffected by the stochastic boundary, despite a threefold drop in the toroidal rotation. These results demonstrate that stochastic boundaries are compatible with H modes and may be attractive for ELM control in next-step fusion tokamaks.
International Nuclear Information System (INIS)
Kotake, Kei; Iwakami, Wakana; Ohnishi, Naofumi; Yamada, Shoichi
2009-01-01
We study the properties of gravitational waves (GWs) based on three-dimensional (3D) simulations, which demonstrate neutrino-driven explosions aided by standing accretion shock instability (SASI). Pushed by evidence supporting slow rotation prior to core collapse, we focus on the asphericities in neutrino emissions and matter motions outside the protoneutron star. By performing a ray-tracing calculation in 3D, we estimate accurately the gravitational waveforms from anisotropic neutrino emissions. In contrast to the previous work assuming axisymmetry, we find that the gravitational waveforms vary much more stochastically because the explosion anisotropies depend sensitively on the growth of SASI which develops chaotically in all directions. Our results show that the GW spectrum has its peak near ∼100 Hz, reflecting SASI-induced matter overturns of ∼O(10) ms. We point out that the detection of such signals, possibly visible to the LIGO-class detectors for a Galactic supernova, could be an important probe into the long-veiled explosion mechanism.
Chang, Mou-Hsiung
2015-01-01
The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...
Inverse stochastic-dynamic models for high-resolution Greenland ice core records
DEFF Research Database (Denmark)
Boers, Niklas; Chekroun, Mickael D.; Liu, Honghu
2017-01-01
as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the 18O and dust......Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic-dynamic models from 18O and dust records of unprecedented, subdecadal...
Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo
2016-04-01
Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.
Fatigue in Welded High-Strength Steel Plate Elements under Stochastic Loading
DEFF Research Database (Denmark)
Agerskov, Henning; Petersen, R.I.; Martinez, L. Lopez
1999-01-01
The present project is a part of an investigation on fatigue in offshore structures in high-strength steel. The fatigue life of plate elements with welded attachments is studied. The material used has a yield stress of ~ 810-840 MPa, and high weldability and toughness properties. Fatigue test...... series with constant amplitude loading and with various types of stochastic loading have been carried through on test specimens in high-strength steel, and - for a comparison - on test specimens in conventional offshore structural steel with a yield stress of ~ 400-410 MPa.A comparison between constant...... amplitude and variable amplitude fatigue test results shows shorter fatigue lives in variable amplitude loading than should be expected from the linear fatigue damage accumulation formula. Furthermore, in general longer fatigue lives were obtained for the test specimens in high-strength steel than those...
International Nuclear Information System (INIS)
Langrene, Nicolas
2014-01-01
This thesis deals with the numerical solution of general stochastic control problems, with notable applications for electricity markets. We first propose a structural model for the price of electricity, allowing for price spikes well above the marginal fuel price under strained market conditions. This model allows to price and partially hedge electricity derivatives, using fuel forwards as hedging instruments. Then, we propose an algorithm, which combines Monte-Carlo simulations with local basis regressions, to solve general optimal switching problems. A comprehensive rate of convergence of the method is provided. Moreover, we manage to make the algorithm parsimonious in memory (and hence suitable for high dimensional problems) by generalizing to this framework a memory reduction method that avoids the storage of the sample paths. We illustrate this on the problem of investments in new power plants (our structural power price model allowing the new plants to impact the price of electricity). Finally, we study more general stochastic control problems (the control can be continuous and impact the drift and volatility of the state process), the solutions of which belong to the class of fully nonlinear Hamilton-Jacobi-Bellman equations, and can be handled via constrained Backward Stochastic Differential Equations, for which we develop a backward algorithm based on control randomization and parametric optimizations. A rate of convergence between the constraPned BSDE and its discrete version is provided, as well as an estimate of the optimal control. This algorithm is then applied to the problem of super replication of options under uncertain volatilities (and correlations). (author)
Calibration of semi-stochastic procedure for simulating high-frequency ground motions
Seyhan, Emel; Stewart, Jonathan P.; Graves, Robert
2013-01-01
Broadband ground motion simulation procedures typically utilize physics-based modeling at low frequencies, coupled with semi-stochastic procedures at high frequencies. The high-frequency procedure considered here combines deterministic Fourier amplitude spectra (dependent on source, path, and site models) with random phase. Previous work showed that high-frequency intensity measures from this simulation methodology attenuate faster with distance and have lower intra-event dispersion than in empirical equations. We address these issues by increasing crustal damping (Q) to reduce distance attenuation bias and by introducing random site-to-site variations to Fourier amplitudes using a lognormal standard deviation ranging from 0.45 for Mw 100 km).
Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output
Energy Technology Data Exchange (ETDEWEB)
Melin, Alexander M. [ORNL; Olama, Mohammed M. [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M. [ORNL; Zhang, Yichen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science
2017-09-01
The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.
Analysis of natural circulation BWR dynamics with stochastic and deterministic methods
International Nuclear Information System (INIS)
VanderHagen, T.H.; Van Dam, H.; Hoogenboom, J.E.; Kleiss, E.B.J.; Nissen, W.H.M.; Oosterkamp, W.J.
1986-01-01
Reactor kinetic, thermal hydraulic and total plant stability of a natural convection cooled BWR was studied using noise analysis and by evaluation of process responses to control rod steps and to steamflow control valve steps. An estimate of the fuel thermal time constant and an impression of the recirculation flow response to power variations was obtained. A sophisticated noise analysis method resulted in more insight into the fluctuations of the coolant velocity
Ivanova, Violeta M.; Sousa, Rita; Murrihy, Brian; Einstein, Herbert H.
2014-06-01
This paper presents results from research conducted at MIT during 2010-2012 on modeling of natural rock fracture systems with the GEOFRAC three-dimensional stochastic model. Following a background summary of discrete fracture network models and a brief introduction of GEOFRAC, the paper provides a thorough description of the newly developed mathematical and computer algorithms for fracture intensity, aperture, and intersection representation, which have been implemented in MATLAB. The new methods optimize, in particular, the representation of fracture intensity in terms of cumulative fracture area per unit volume, P32, via the Poisson-Voronoi Tessellation of planes into polygonal fracture shapes. In addition, fracture apertures now can be represented probabilistically or deterministically whereas the newly implemented intersection algorithms allow for computing discrete pathways of interconnected fractures. In conclusion, results from a statistical parametric study, which was conducted with the enhanced GEOFRAC model and the new MATLAB-based Monte Carlo simulation program FRACSIM, demonstrate how fracture intensity, size, and orientations influence fracture connectivity.
Natural gas : a highly lucrative commodity
International Nuclear Information System (INIS)
Anon.
2000-01-01
Exploration and production of natural gas has become highly profitable as natural gas is becoming a leading future commodity. With new technology, high demand and environmental benefits, natural gas is the preferred choice over petroleum as the leading source of energy to heat home and businesses. Canada is the world's third largest producer of natural gas with its Sable Offshore Energy Project being the fourth largest producing natural gas basin in North America. The basin will produce high quality sweet natural gas from 28 production wells over the course of the next 20 to 25 years. The gas will be transported to markets through Nova Scotia, New Brunswick and into the Northeastern United States via the Maritimes and Northeast Pipeline. The 1051 kilometer underground gas pipeline is currently running laterals to Halifax, Nova Scotia and Saint John, New Brunswick. Market studies are being conducted to determine if additional lines are needed to serve Cape Breton, Prince Edward Island and northern New Brunswick. A recent survey identified the following 5 reasons to convert to natural gas: (1) it is safe, (2) it is reliable, (3) it is easy to use, (4) it is cleaner burning and environmentally friendly compared to other energy sources, and (5) it saves the consumer money
Solution of stochastic nonlinear PDEs using Wiener-Hermite expansion of high orders
El Beltagy, Mohamed
2016-01-06
In this work, the Wiener-Hermite Expansion (WHE) is used to solve stochastic nonlinear PDEs excited with noise. The generation of the equivalent set of deterministic integro-differential equations is automated and hence allows for high order terms of WHE. The automation difficulties are discussed, solved and implemented to output the final system to be solved. A numerical Pikard-like algorithm is suggested to solve the resulting deterministic system. The automated WHE is applied to the 1D diffusion equation and to the heat equation. The results are compared with previous solutions obtained with WHEP (WHE with perturbation) technique. The solution obtained using the suggested WHE technique is shown to be the limit of the WHEP solutions with infinite number of corrections. The automation is extended easily to account for white-noise of higher dimension and for general nonlinear PDEs.
Solution of stochastic nonlinear PDEs using Wiener-Hermite expansion of high orders
El Beltagy, Mohamed
2016-01-01
In this work, the Wiener-Hermite Expansion (WHE) is used to solve stochastic nonlinear PDEs excited with noise. The generation of the equivalent set of deterministic integro-differential equations is automated and hence allows for high order terms of WHE. The automation difficulties are discussed, solved and implemented to output the final system to be solved. A numerical Pikard-like algorithm is suggested to solve the resulting deterministic system. The automated WHE is applied to the 1D diffusion equation and to the heat equation. The results are compared with previous solutions obtained with WHEP (WHE with perturbation) technique. The solution obtained using the suggested WHE technique is shown to be the limit of the WHEP solutions with infinite number of corrections. The automation is extended easily to account for white-noise of higher dimension and for general nonlinear PDEs.
Stochastic Analysis of Natural Convection in Vertical Channels with Random Wall Temperature
Directory of Open Access Journals (Sweden)
Ryoichi Chiba
2017-01-01
Full Text Available This study attempts to derive the statistics of temperature and velocity fields of laminar natural convection in a heated vertical channel with random wall temperature. The wall temperature is expressed as a random function with respect to time, or a random process. First, analytical solutions of the transient temperature and flow velocity fields for an arbitrary temporal variation in the channel wall temperature are obtained by the integral transform and convolution theorem. Second, the autocorrelations of the temperature and velocity are formed from the solutions, assuming a stationarity in time. The mean square values of temperature and velocity are computed under the condition that the fluctuation in the channel wall temperature can be considered as white noise or a stationary Markov process. Numerical results demonstrate that a decrease in the Prandtl number or an increase in the correlation time of the random process increases the level of mean square velocity but does not change its spatial distribution tendency, which is a bell-shaped profile with a peak at a certain horizontal distance from the channel wall. The peak position is not substantially affected by the Prandtl number or the correlation time.
Directory of Open Access Journals (Sweden)
Romanu Ekaterini
2006-01-01
Full Text Available This article shows the similarities between Claude Debussy’s and Iannis Xenakis’ philosophy of music and work, in particular the formers Jeux and the latter’s Metastasis and the stochastic works succeeding it, which seem to proceed parallel (with no personal contact to what is perceived as the evolution of 20th century Western music. Those two composers observed the dominant (German tradition as outsiders, and negated some of its elements considered as constant or natural by "traditional" innovators (i.e. serialists: the linearity of musical texture, its form and rhythm.
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...
A high-resolution stochastic model of domestic activity patterns and electricity demand
International Nuclear Information System (INIS)
Widen, Joakim; Waeckelgard, Ewa
2010-01-01
Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings' indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.
Energy Technology Data Exchange (ETDEWEB)
Henshall, G.A.; Halsey, W.G.; Clarke, W.L.; McCright, R.D.
1993-01-01
Recent efforts to identify methods of modeling pitting corrosion damage of high-level radioactive-waste containers are described. The need to develop models that can provide information useful to higher level system performance assessment models is emphasized, and examples of how this could be accomplished are described. Work to date has focused upon physically-based phenomenological stochastic models of pit initiation and growth. These models may provide a way to distill information from mechanistic theories in a way that provides the necessary information to the less detailed performance assessment models. Monte Carlo implementations of the stochastic theory have resulted in simulations that are, at least qualitatively, consistent with a wide variety of experimental data. The effects of environment on pitting corrosion have been included in the model using a set of simple phenomenological equations relating the parameters of the stochastic model to key environmental variables. The results suggest that stochastic models might be useful for extrapolating accelerated test data and for predicting the effects of changes in the environment on pit initiation and growth. Preliminary ideas for integrating pitting models with performance assessment models are discussed. These ideas include improving the concept of container ``failure``, and the use of ``rules-of-thumb`` to take information from the detailed process models and provide it to the higher level system and subsystem models. Finally, directions for future work are described, with emphasis on additional experimental work since it is an integral part of the modeling process.
International Nuclear Information System (INIS)
Henshall, G.A.; Halsey, W.G.; Clarke, W.L.; McCright, R.D.
1993-01-01
Recent efforts to identify methods of modeling pitting corrosion damage of high-level radioactive-waste containers are described. The need to develop models that can provide information useful to higher level system performance assessment models is emphasized, and examples of how this could be accomplished are described. Work to date has focused upon physically-based phenomenological stochastic models of pit initiation and growth. These models may provide a way to distill information from mechanistic theories in a way that provides the necessary information to the less detailed performance assessment models. Monte Carlo implementations of the stochastic theory have resulted in simulations that are, at least qualitatively, consistent with a wide variety of experimental data. The effects of environment on pitting corrosion have been included in the model using a set of simple phenomenological equations relating the parameters of the stochastic model to key environmental variables. The results suggest that stochastic models might be useful for extrapolating accelerated test data and for predicting the effects of changes in the environment on pit initiation and growth. Preliminary ideas for integrating pitting models with performance assessment models are discussed. These ideas include improving the concept of container ''failure'', and the use of ''rules-of-thumb'' to take information from the detailed process models and provide it to the higher level system and subsystem models. Finally, directions for future work are described, with emphasis on additional experimental work since it is an integral part of the modeling process
International Nuclear Information System (INIS)
Tabatabaee, Sajad; Mortazavi, Seyed Saeedallah; Niknam, Taher
2017-01-01
This paper investigates the optimal scheduling of electric power units in the renewable based local distribution systems considering plug-in electric vehicles (PEVs). The appearance of PEVs in the electric grid can create new challenges for the operation of distributed generations and power units inside the network. In order to deal with this issue, a new stochastic optimization method is devised to let the central controll manage the power units and charging behavior of PEVs. The problem formulation aims to minimize the total cost of the network including the cost of power supply for loads and PEVs as well as the cost of energy not supplied (ENS) as the reliability costs. In order to make PEVs as opportunity for the grid, the vehicle-2-grid (V2G) technology is employed to reduce the operational costs. To model the high uncertain behavior of wind turbine, photovoltaics and the charging and discharging pattern of PEVs, a new stochastic power flow based on unscented transform is proposed. Finally, a new optimization algorithm based on bat algorithm (BA) is proposed to solve the problem optimally. The satisfying performance of the proposed stochastic method is tested on a grid-connected local distribution system. - Highlights: • Introduction of stochastic method to assess Plug-in Electric Vehicles effects on the microgrid. • Assessing the role of V2G technology on battery aging and degradation costs. • Use of BA for solving the proposed problem. • Introduction of a new modification method for the BA.
Stochastic model of the near-to-injector spray formation assisted by a high-speed coaxial gas jet
Energy Technology Data Exchange (ETDEWEB)
Gorokhovski, M [Laboratoire de Mecanique des Fluides et d' Acoustique, CNRS-Ecole Centrale de Lyon-INSA Lyon-Universite Claude Bernard Lyon 1, 36 Avenue Guy de Collongue, 69131 Ecully Cedex (France); Jouanguy, J [Laboratoire de Mecanique de Lille, Ecole Centrale de Lille, Blvd Paul Langevin, 59655 Villeneuve d' Ascq Cedex (France); Chtab-Desportes, A [CD-adapco, 31 rue Delizy 93698 Pantin Cedex (France)], E-mail: mikhael.gorokhovski@ec-lyon.fr
2009-06-01
The stochastic model of spray formation in the vicinity of the air-blast atomizer has been described and assessed by comparison with measurements. In this model, the 3D configuration of a continuous liquid core is simulated by spatial trajectories of specifically introduced stochastic particles. The stochastic process is based on the assumption that due to a high Weber number, the exiting continuous liquid jet is depleted in the framework of statistical universalities of a cascade fragmentation under scaling symmetry. The parameters of the stochastic process have been determined according to observations from Lasheras's, Hopfinger's and Villermaux's scientific groups. The spray formation model, based on the computation of spatial distribution of the probability of finding the non-fragmented liquid jet in the near-to-injector region, is combined with the large-eddy simulation (LES) in the coaxial gas jet. Comparison with measurements reported in the literature for different values of the gas-to-liquid dynamic pressure ratio showed that the model predicts correctly the distribution of liquid in the close-to-injector region, the mean length of the liquid core, the spray angle and the typical size of droplets in the far field of spray.
Inverse stochastic-dynamic models for high-resolution Greenland ice core records
Boers, Niklas; Chekroun, Mickael D.; Liu, Honghu; Kondrashov, Dmitri; Rousseau, Denis-Didier; Svensson, Anders; Bigler, Matthias; Ghil, Michael
2017-12-01
Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic-dynamic models from δ18O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP), and we focus on the time interval 59-22 ka b2k. Our model reproduces the dynamical characteristics of both the δ18O and dust proxy records, including the millennial-scale Dansgaard-Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the δ18O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects.
High-energy hadron dynamics based on a stochastic-field multieikonal theory
International Nuclear Information System (INIS)
Arnold, R.C.
1977-01-01
Multieikonal theory, using a stochastic-field representation for collective long-range rapidity correlations, is developed and applied to the calculation of Regge-pole parameters, high-transverse-momentum enhancements, and fluctuation patterns in rapidity densities. If a short-range-order model, such as the one-dimensional planar bootstrap, with only leading t-channel meson poles, is utilized as input to the multieikonal method, the pole spectrum is modified in three ways: promotion and renormalization of leading trajectories (suggesting an effective Pomeron above unity at intermediate energies), and a proliferation of dynamical secondary trajectories, reminiscent of dual models. When transverse dimensions are included, the collective effects produce a growth with energy of large-P/sub T/ inclusive cross sections. Typical-event rapidity distributions, at energies of a few TeV, can be estimated by suitable approximations; the fluctuations give rise to ''domain'' patterns, which have the appearance of clusters separated by rapidity gaps. The relations between this approach to strong-interaction dynamics and a possible unification of weak, electromagnetic, and strong interactions are outlined
American option pricing with stochastic volatility processes
Directory of Open Access Journals (Sweden)
Ping LI
2017-12-01
Full Text Available In order to solve the problem of option pricing more perfectly, the option pricing problem with Heston stochastic volatility model is considered. The optimal implementation boundary of American option and the conditions for its early execution are analyzed and discussed. In view of the fact that there is no analytical American option pricing formula, through the space discretization parameters, the stochastic partial differential equation satisfied by American options with Heston stochastic volatility is transformed into the corresponding differential equations, and then using high order compact finite difference method, numerical solutions are obtained for the option price. The numerical experiments are carried out to verify the theoretical results and simulation. The two kinds of optimal exercise boundaries under the conditions of the constant volatility and the stochastic volatility are compared, and the results show that the optimal exercise boundary also has stochastic volatility. Under the setting of parameters, the behavior and the nature of volatility are analyzed, the volatility curve is simulated, the calculation results of high order compact difference method are compared, and the numerical option solution is obtained, so that the method is verified. The research result provides reference for solving the problems of option pricing under stochastic volatility such as multiple underlying asset option pricing and barrier option pricing.
International Nuclear Information System (INIS)
Rax, J.M.
1992-04-01
The dynamics of electrons in two-dimensional, linearly or circularly polarized, ultra-high intensity (above 10 18 W/cm 2 ) laser waves, is investigated. The Compton harmonic resonances are identified as the source of various stochastic instabilities. Both Arnold diffusion and resonance overlap are considered. The quasilinear kinetic equation, describing the evolution of the electron distribution function, is derived, and the associated collisionless damping coefficient is calculated. The implications of these new processes are considered and discussed
Stochastic Optimization Model to STudy the Operational Impacts of High Wind Penetrations in Ireland
DEFF Research Database (Denmark)
Meibom, Peter; Barth, R.; Hasche, B.
2011-01-01
A stochastic mixed integer linear optimization scheduling model minimizing system operation costs and treating load and wind power production as stochastic inputs is presented. The schedules are updated in a rolling manner as more up-to-date information becomes available. This is a fundamental...... change relative to day-ahead unit commitment approaches. The need for reserves dependent on forecast horizon and share of wind power has been estimated with a statistical model combining load and wind power forecast errors with scenarios of forced outages. The model is used to study operational impacts...
Stochastic quantisation: theme and variation
International Nuclear Information System (INIS)
Klauder, J.R.; Kyoto Univ.
1987-01-01
The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)
Zhao, Michael; Punjabi, Alkesh; Ali, Halima
2009-11-01
The equilibrium EFIT data for the DIII-D shot 115467 is used to construct the equilibrium generating function for magnetic field line trajectories in the DIII-D tokamak in natural canonical coordinates [A. Punjabi, and H. Ali, Phys. Plasmas 15, 122502 (2008)]. A canonical transformation is used to construct an area-preserving map for field line trajectories in the natural canonical coordinates in the DIII-D. Maps in natural canonical coordinates have the advantage that natural canonical coordinates can be inverted to calculate real space coordinates (R,Z,φ), and there is no problem in crossing the separatrix. This is not possible for magnetic coordinates [O. Kerwin, A. Punjabi, and H. Ali, Phys. Plasmas 15, 072504 (2008)]. This map is applied to calculate stochastic broadening from the low mn (m,n)=(1,1)+(1,-1); high mn (m,n)=(4,1)+(3,1); and the peeling-ballooning (m,n)=(40,10)+(30,10) magnetic perturbations. In all three cases, the scaling of the widths of stochastic layer near the X-point in the principal plane of the DIII-D deviates at most by 6% from the .5ex1 -.1em/ -.15em.25ex2 power Boozer-Rechester scaling [A. Boozer, and A. Rechester, Phys. Fluids 21, 682 (1978)]. This work is supported by US Department of Energy grants DE-FG02-07ER54937, DE-FG02-01ER54624 and DE-FG02-04ER54793.
Brantson, Eric Thompson; Ju, Binshan; Wu, Dan; Gyan, Patricia Semwaah
2018-04-01
This paper proposes stochastic petroleum porous media modeling for immiscible fluid flow simulation using Dykstra-Parson coefficient (V DP) and autocorrelation lengths to generate 2D stochastic permeability values which were also used to generate porosity fields through a linear interpolation technique based on Carman-Kozeny equation. The proposed method of permeability field generation in this study was compared to turning bands method (TBM) and uniform sampling randomization method (USRM). On the other hand, many studies have also reported that, upstream mobility weighting schemes, commonly used in conventional numerical reservoir simulators do not accurately capture immiscible displacement shocks and discontinuities through stochastically generated porous media. This can be attributed to high level of numerical smearing in first-order schemes, oftentimes misinterpreted as subsurface geological features. Therefore, this work employs high-resolution schemes of SUPERBEE flux limiter, weighted essentially non-oscillatory scheme (WENO), and monotone upstream-centered schemes for conservation laws (MUSCL) to accurately capture immiscible fluid flow transport in stochastic porous media. The high-order schemes results match well with Buckley Leverett (BL) analytical solution without any non-oscillatory solutions. The governing fluid flow equations were solved numerically using simultaneous solution (SS) technique, sequential solution (SEQ) technique and iterative implicit pressure and explicit saturation (IMPES) technique which produce acceptable numerical stability and convergence rate. A comparative and numerical examples study of flow transport through the proposed method, TBM and USRM permeability fields revealed detailed subsurface instabilities with their corresponding ultimate recovery factors. Also, the impact of autocorrelation lengths on immiscible fluid flow transport were analyzed and quantified. A finite number of lines used in the TBM resulted into visual
International Nuclear Information System (INIS)
Higgs, Helen; Worthington, Andrew
2008-01-01
It is commonly known that wholesale spot electricity markets exhibit high price volatility, strong mean-reversion and frequent extreme price spikes. This paper employs a basic stochastic model, a mean-reverting model and a regime-switching model to capture these features in the Australian national electricity market (NEM), comprising the interconnected markets of New South Wales, Queensland, South Australia and Victoria. Daily spot prices from 1 January 1999 to 31 December 2004 are employed. The results show that the regime-switching model outperforms the basic stochastic and mean-reverting models. Electricity prices are also found to exhibit stronger mean-reversion after a price spike than in the normal period, and price volatility is more than fourteen times higher in spike periods than in normal periods. The probability of a spike on any given day ranges between 5.16% in NSW and 9.44% in Victoria
Huang, Haiying; Du, Qiaosheng; Kang, Xibing
2013-11-01
In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results. © 2013 ISA. Published by ISA. All rights reserved.
Daskalou, Olympia; Karanastasi, Maria; Markonis, Yannis; Dimitriadis, Panayiotis; Koukouvinos, Antonis; Efstratiadis, Andreas; Koutsoyiannis, Demetris
2016-04-01
Following the legislative EU targets and taking advantage of its high renewable energy potential, Greece can obtain significant benefits from developing its water, solar and wind energy resources. In this context we present a GIS-based methodology for the optimal sizing and siting of solar and wind energy systems at the regional scale, which is tested in the Prefecture of Thessaly. First, we assess the wind and solar potential, taking into account the stochastic nature of the associated meteorological processes (i.e. wind speed and solar radiation, respectively), which is essential component for both planning (i.e., type selection and sizing of photovoltaic panels and wind turbines) and management purposes (i.e., real-time operation of the system). For the optimal siting, we assess the efficiency and economic performance of the energy system, also accounting for a number of constraints, associated with topographic limitations (e.g., terrain slope, proximity to road and electricity grid network, etc.), the environmental legislation and other land use constraints. Based on this analysis, we investigate favorable alternatives using technical, environmental as well as financial criteria. The final outcome is GIS maps that depict the available energy potential and the optimal layout for photovoltaic panels and wind turbines over the study area. We also consider a hypothetical scenario of future development of the study area, in which we assume the combined operation of the above renewables with major hydroelectric dams and pumped-storage facilities, thus providing a unique hybrid renewable system, extended at the regional scale.
International Nuclear Information System (INIS)
Pless, Jacquelyn; Arent, Douglas J.; Logan, Jeffrey; Cochran, Jaquelin; Zinaman, Owen
2016-01-01
One energy policy objective in the United States is to promote the adoption of technologies that provide consumers with stable, secure, and clean energy. Recent work provides anecdotal evidence of natural gas (NG) and renewable electricity (RE) synergies in the power sector, however few studies quantify the value of investing in NG and RE systems together as complements. This paper uses discounted cash flow analysis and real options analysis to value hybrid NG-RE systems in distributed applications, focusing on residential and commercial projects assumed to be located in the states of New York and Texas. Technology performance and operational risk profiles are modeled at the hourly level to capture variable RE output and NG prices are modeled stochastically as geometric Ornstein-Uhlenbeck (OU) stochastic processes to capture NG price uncertainty. The findings consistently suggest that NG-RE hybrid distributed systems are more favorable investments in the applications studied relative to their single-technology alternatives when incentives for renewables are available. In some cases, NG-only systems are the favorable investments. Understanding the value of investing in NG-RE hybrid systems provides insights into one avenue towards reducing greenhouse gas emissions, given the important role of NG and RE in the power sector. - Highlights: • Natural gas and renewable electricity can be viewed as complements. • We model hybrid natural gas and renewable electricity systems at the hourly level. • We incorporate variable renewable power output and uncertain natural gas prices. • Hybrid natural gas and renewable electricity systems can be valuable investments.
A stochastic six-degree-of-freedom flight simulator for passively controlled high power rockets
Box, Simon; Bishop, Christopher M.; Hunt, Hugh
2011-01-01
This paper presents a method for simulating the flight of a passively controlled rocket in six degrees of freedom, and the descent under parachute in three degrees of freedom, Also presented is a method for modelling the uncertainty in both the rocket dynamics and the atmospheric conditions using stochastic parameters and the Monte-Carlo method. Included within this we present a method for quantifying the uncertainty in the atmospheric conditions using historical atmospheric data. The core si...
Nan, Hanqing; Liang, Long; Chen, Guo; Liu, Liyu; Liu, Ruchuan; Jiao, Yang
2018-03-01
Three-dimensional (3D) collective cell migration in a collagen-based extracellular matrix (ECM) is among one of the most significant topics in developmental biology, cancer progression, tissue regeneration, and immune response. Recent studies have suggested that collagen-fiber mediated force transmission in cellularized ECM plays an important role in stress homeostasis and regulation of collective cellular behaviors. Motivated by the recent in vitro observation that oriented collagen can significantly enhance the penetration of migrating breast cancer cells into dense Matrigel which mimics the intravasation process in vivo [Han et al. Proc. Natl. Acad. Sci. USA 113, 11208 (2016), 10.1073/pnas.1610347113], we devise a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization. Specifically, a collagen network is represented via the graph (node-bond) model and the microstructural statistics considered include the cross-link (node) density, valence distribution, fiber (bond) length distribution, as well as fiber orientation distribution. An optimization problem is formulated in which the objective function is defined as the squared difference between a set of target microstructural statistics and the corresponding statistics for the simulated network. Simulated annealing is employed to solve the optimization problem by evolving an initial network via random perturbations to generate realizations of homogeneous networks with randomly oriented fibers, homogeneous networks with aligned fibers, heterogeneous networks with a continuous variation of fiber orientation along a prescribed direction, as well as a binary system containing a collagen region with aligned fibers and a dense Matrigel region with randomly oriented fibers. The generation and propagation of active forces in the simulated networks due to polarized contraction of an embedded ellipsoidal cell and a small group
High-pressure-high-temperature treatment of natural diamonds
Royen, J V
2002-01-01
The results are reported of high-pressure-high-temperature (HPHT) treatment experiments on natural diamonds of different origins and with different impurity contents. The diamonds are annealed in a temperature range up to 2000 sup o C at stabilizing pressures up to 7 GPa. The evolution is studied of different defects in the diamond crystal lattice. The influence of substitutional nitrogen atoms, plastic deformation and the combination of these is discussed. Diamonds are characterized at room and liquid nitrogen temperature using UV-visible spectrophotometry, Fourier transform infrared spectrophotometry and photoluminescence spectrometry. The economic implications of diamond HPHT treatments are discussed.
DEFF Research Database (Denmark)
Mejlholm, Ole; Bøknæs, Niels; Dalgaard, Paw
2015-01-01
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...... 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....
Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale
Energy Technology Data Exchange (ETDEWEB)
Zabaras, Nicolas J. [Cornell Univ., Ithaca, NY (United States)
2016-11-08
Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.
Si, Wenjie; Dong, Xunde; Yang, Feifei
2018-03-01
This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.
Stochastic substitute for coupled rate equations in the modeling of highly ionized transient plasmas
International Nuclear Information System (INIS)
Eliezer, S.; Falquina, R.; Minguez, E.
1994-01-01
Plasmas produced by intense laser pulses incident on solid targets often do not satisfy the conditions for local thermodynamic equilibrium, and so cannot be modeled by transport equations relying on equations of state. A proper description involves an excessively large number of coupled rate equations connecting many quantum states of numerous species having different degrees of ionization. Here we pursue a recent suggestion to model the plasma by a few dominant states perturbed by a stochastic driving force. The driving force is taken to be a Poisson impulse process, giving a Langevin equation which is equivalent to a Fokker-Planck equation for the probability density governing the distribution of electron density. An approximate solution to the Langevin equation permits calculation of the characteristic relaxation rate. An exact stationary solution to the Fokker-Planck equation is given as a function of the strength of the stochastic driving force. This stationary solution is used, along with a Laplace transform, to convert the Fokker-Planck equation to one of Schroedinger type. We consider using the classical Hamiltonian formalism and the WKB method to obtain the time-dependent solution
Parzen, Emanuel
1962-01-01
Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine
International Nuclear Information System (INIS)
Hlaing Myat Thu; Lowry, Kym; Jiang Limin; Thaung Hlaing; Holmes, Edward C.; Aaskov, John
2005-01-01
Between 1996 and 1998, two clades (B and C; genotype I) of dengue virus type 1 (DENV-1) appeared in Myanmar (Burma) that were new to that location. Between 1998 and 2000, a third clade (A; genotype III) of DENV-1, which had been circulating at that locality for at least 25 years, became extinct. These changes preceded the largest outbreak of dengue recorded in Myanmar, in 2001, in which more than 95% of viruses recovered from patients were DENV-1, but where the incidence of severe disease was much less than in previous years. Phylogenetic analyses of viral genomes indicated that the two new clades of DENV-1 did not arise from the, now extinct, clade A viruses nor was the extinction of this clade due to differences in the fitness of the viral populations. Since the extinction occurred during an inter-epidemic period, we suggest that it was due to a stochastic event attributable to the low rate of virus transmission in this interval
Stochastic resonance for exploration geophysics
Omerbashich, Mensur
2008-01-01
Stochastic resonance (SR) is a phenomenon in which signal to noise (SN) ratio gets improved by noise addition rather than removal as envisaged classically. SR was first claimed in climatology a few decades ago and then in other disciplines as well. The same as it is observed in natural systems, SR is used also for allowable SN enhancements at will. Here I report a proof of principle that SR can be useful in exploration geophysics. For this I perform high frequency GaussVanicek variance spectr...
International Nuclear Information System (INIS)
Klauder, J.R.
1983-01-01
The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)
Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Ioannis [Princeton Univ., NJ (United States)
2017-03-22
The thrust of the proposal was to exploit modern data-mining tools in a way that will create a systematic, computer-assisted approach to the representation of random media -- and also to the representation of the solutions of an array of important physicochemical processes that take place in/on such media. A parsimonious representation/parametrization of the random media links directly (via uncertainty quantification tools) to good sampling of the distribution of random media realizations. It also links directly to modern multiscale computational algorithms (like the equation-free approach that has been developed in our group) and plays a crucial role in accelerating the scientific computation of solutions of nonlinear PDE models (deterministic or stochastic) in such media – both solutions in particular realizations of the random media, and estimation of the statistics of the solutions over multiple realizations (e.g. expectations).
International Nuclear Information System (INIS)
Dong Bing; Ren Deqing; Zhang Xi
2011-01-01
An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of any pattern. A circular stepped pattern is used in our preliminary experiment and the image contrast shows improvement from 10 -3 to 10 -4.5 at an angular distance of 2λ/D after being corrected by SPGD based AO.
Energy Technology Data Exchange (ETDEWEB)
Kirillin, I.V. [Akhiezer Institute for Theoretical Physics, National Science Center ' ' Kharkov Institute of Physics and Technology' ' , Kharkov (Ukraine); Shul' ga, N.F. [Akhiezer Institute for Theoretical Physics, National Science Center ' ' Kharkov Institute of Physics and Technology' ' , Kharkov (Ukraine); V.N. Karazin Kharkov National University, Kharkov (Ukraine); Bandiera, L. [INFN Sezione di Ferrara, Ferrara (Italy); Guidi, V.; Mazzolari, A. [INFN Sezione di Ferrara, Ferrara (Italy); Universita degli Studi di Ferrara, Dipartimento di Fisica e Scienze della Terra, Ferrara (Italy)
2017-02-15
An investigation on stochastic deflection of high-energy negatively charged particles in a bent crystal was carried out. On the basis of analytical calculation and numerical simulation it was shown that there is a maximum angle at which most of the beam is deflected. The existence of a maximum, which is taken in the correspondence of the optimal radius of curvature, is a novelty with respect to the case of positively charged particles, for which the deflection angle can be freely increased by increasing the crystal length. This difference has to be ascribed to the stronger contribution of incoherent scattering affecting the dynamics of negative particles that move closer to atomic nuclei and electrons. We therefore identified the ideal parameters for the exploitation of axial confinement for negatively charged particle beam manipulation in future high-energy accelerators, e.g., ILC or muon colliders. (orig.)
STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...
African Journals Online (AJOL)
eobe
STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.
International Nuclear Information System (INIS)
Wellens, Thomas; Shatokhin, Vyacheslav; Buchleitner, Andreas
2004-01-01
We are taught by conventional wisdom that the transmission and detection of signals is hindered by noise. However, during the last two decades, the paradigm of stochastic resonance (SR) proved this assertion wrong: indeed, addition of the appropriate amount of noise can boost a signal and hence facilitate its detection in a noisy environment. Due to its simplicity and robustness, SR has been implemented by mother nature on almost every scale, thus attracting interdisciplinary interest from physicists, geologists, engineers, biologists and medical doctors, who nowadays use it as an instrument for their specific purposes. At the present time, there exist a lot of diversified models of SR. Taking into account the progress achieved in both theoretical understanding and practical application of this phenomenon, we put the focus of the present review not on discussing in depth technical details of different models and approaches but rather on presenting a general and clear physical picture of SR on a pedagogical level. Particular emphasis will be given to the implementation of SR in generic quantum systems-an issue that has received limited attention in earlier review papers on the topic. The major part of our presentation relies on the two-state model of SR (or on simple variants thereof), which is general enough to exhibit the main features of SR and, in fact, covers many (if not most) of the examples of SR published so far. In order to highlight the diversity of the two-state model, we shall discuss several examples from such different fields as condensed matter, nonlinear and quantum optics and biophysics. Finally, we also discuss some situations that go beyond the generic SR scenario but are still characterized by a constructive role of noise
International Nuclear Information System (INIS)
Rumpf, H.
1987-01-01
We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)
International Nuclear Information System (INIS)
Karvountzis-Kontakiotis, A.; Dimaratos, A.; Ntziachristos, L.; Samaras, Z.
2017-01-01
This study contributes to the understanding of cycle-to-cycle emissions variability (CEV) in premixed spark-ignition combustion engines. A number of experimental investigations of cycle-to-cycle combustion variability (CCV) exist in published literature; however only a handful of studies deal with CEV. This study experimentally investigates the impact of CCV on CEV of NO and CO, utilizing experimental results from a high-speed spark-ignition engine. Both CEV and CCV are shown to comprise a deterministic and a stochastic component. Results show that at maximum break torque (MBT) operation, the indicated mean effective pressure (IMEP) maximizes and its coefficient of variation (COV_I_M_E_P) minimizes, leading to minimum variation of NO. NO variability and hence mean NO levels can be reduced by more than 50% and 30%, respectively, at advanced ignition timing, by controlling the deterministic CCV using cycle resolved combustion control. The deterministic component of CEV increases at lean combustion (lambda = 1.12) and this overall increases NO variability. CEV was also found to decrease with engine load. At steady speed, increasing throttle position from 20% to 80%, decreased COV_I_M_E_P, COV_N_O and COV_C_O by 59%, 46%, and 6% respectively. Highly resolved engine control, by means of cycle-to-cycle combustion control, appears as key to limit the deterministic feature of cyclic variability and by that to overall reduce emission levels. - Highlights: • Engine emissions variability comprise both stochastic and deterministic components. • Lean and diluted combustion conditions increase emissions variability. • Advanced ignition timing enhances the deterministic component of variability. • Load increase decreases the deterministic component of variability. • The deterministic component can be reduced by highly resolved combustion control.
A Dynamical System Exhibits High Signal-to-noise Ratio Gain by Stochastic Resonance
Makra, Peter; Gingl, Zoltan
2003-05-01
On the basis of mixed-signal simulations, we demonstrate that signal-to-noise ratio (SNR) gains much greater than unity can be obtained in the double-well potential through stochastic resonance (SR) with a symmetric periodic pulse train as deterministic and Gaussian white noise as random excitation. We also show that significant SNR improvement is possible in this system even for a sub-threshold sinusoid input if, instead of the commonly used narrow-band SNR, we apply an equally simple but much more realistic wide-band SNR definition. Using the latter result as an argument, we draw attention to the fact that the choice of the measure to reflect signal quality is critical with regard to the extent of signal improvement observed, and urge reconsideration of the practice prevalent in SR studies that most often the narrow-band SNR is used to characterise SR. Finally, we pose some questions concerning the possibilities of applying SNR improvement in practical set-ups.
Measure Guideline. High Efficiency Natural Gas Furnaces
Energy Technology Data Exchange (ETDEWEB)
Brand, L. [Partnership for Advanced Residential Retrofit (PARR), Des Plaines, IL (United States); Rose, W. [Partnership for Advanced Residential Retrofit (PARR), Des Plaines, IL (United States)
2012-10-01
This measure guideline covers installation of high-efficiency gas furnaces, including: when to install a high-efficiency gas furnace as a retrofit measure; how to identify and address risks; and the steps to be used in the selection and installation process. The guideline is written for Building America practitioners and HVAC contractors and installers. It includes a compilation of information provided by manufacturers, researchers, and the Department of Energy as well as recent research results from the Partnership for Advanced Residential Retrofit (PARR) Building America team.
Measure Guideline: High Efficiency Natural Gas Furnaces
Energy Technology Data Exchange (ETDEWEB)
Brand, L.; Rose, W.
2012-10-01
This Measure Guideline covers installation of high-efficiency gas furnaces. Topics covered include when to install a high-efficiency gas furnace as a retrofit measure, how to identify and address risks, and the steps to be used in the selection and installation process. The guideline is written for Building America practitioners and HVAC contractors and installers. It includes a compilation of information provided by manufacturers, researchers, and the Department of Energy as well as recent research results from the Partnership for Advanced Residential Retrofit (PARR) Building America team.
Collagen Fibrils: Nature's Highly Tunable Nonlinear Springs.
Andriotis, Orestis G; Desissaire, Sylvia; Thurner, Philipp J
2018-03-21
Tissue hydration is well known to influence tissue mechanics and can be tuned via osmotic pressure. Collagen fibrils are nature's nanoscale building blocks to achieve biomechanical function in a broad range of biological tissues and across many species. Intrafibrillar covalent cross-links have long been thought to play a pivotal role in collagen fibril elasticity, but predominantly at large, far from physiological, strains. Performing nanotensile experiments of collagen fibrils at varying hydration levels by adjusting osmotic pressure in situ during atomic force microscopy experiments, we show the power the intrafibrillar noncovalent interactions have for defining collagen fibril tensile elasticity at low fibril strains. Nanomechanical tensile tests reveal that osmotic pressure increases collagen fibril stiffness up to 24-fold in transverse (nanoindentation) and up to 6-fold in the longitudinal direction (tension), compared to physiological saline in a reversible fashion. We attribute the stiffening to the density and strength of weak intermolecular forces tuned by hydration and hence collagen packing density. This reversible mechanism may be employed by cells to alter their mechanical microenvironment in a reversible manner. The mechanism could also be translated to tissue engineering approaches for customizing scaffold mechanics in spatially resolved fashion, and it may help explain local mechanical changes during development of diseases and inflammation.
Komianos, James E.; Papoian, Garegin A.
2018-04-01
Current understanding of how contractility emerges in disordered actomyosin networks of nonmuscle cells is still largely based on the intuition derived from earlier works on muscle contractility. In addition, in disordered networks, passive cross-linkers have been hypothesized to percolate force chains in the network, hence, establishing large-scale connectivity between local contractile clusters. This view, however, largely overlooks the free energy of cross-linker binding at the microscale, which, even in the absence of active fluctuations, provides a thermodynamic drive towards highly overlapping filamentous states. In this work, we use stochastic simulations and mean-field theory to shed light on the dynamics of a single actomyosin force dipole—a pair of antiparallel actin filaments interacting with active myosin II motors and passive cross-linkers. We first show that while passive cross-linking without motor activity can produce significant contraction between a pair of actin filaments, driven by thermodynamic favorability of cross-linker binding, a sharp onset of kinetic arrest exists at large cross-link binding energies, greatly diminishing the effectiveness of this contractility mechanism. Then, when considering an active force dipole containing nonmuscle myosin II, we find that cross-linkers can also serve as a structural ratchet when the motor dissociates stochastically from the actin filaments, resulting in significant force amplification when both molecules are present. Our results provide predictions of how actomyosin force dipoles behave at the molecular level with respect to filament boundary conditions, passive cross-linking, and motor activity, which can explicitly be tested using an optical trapping experiment.
Directory of Open Access Journals (Sweden)
James E. Komianos
2018-04-01
Full Text Available Current understanding of how contractility emerges in disordered actomyosin networks of nonmuscle cells is still largely based on the intuition derived from earlier works on muscle contractility. In addition, in disordered networks, passive cross-linkers have been hypothesized to percolate force chains in the network, hence, establishing large-scale connectivity between local contractile clusters. This view, however, largely overlooks the free energy of cross-linker binding at the microscale, which, even in the absence of active fluctuations, provides a thermodynamic drive towards highly overlapping filamentous states. In this work, we use stochastic simulations and mean-field theory to shed light on the dynamics of a single actomyosin force dipole—a pair of antiparallel actin filaments interacting with active myosin II motors and passive cross-linkers. We first show that while passive cross-linking without motor activity can produce significant contraction between a pair of actin filaments, driven by thermodynamic favorability of cross-linker binding, a sharp onset of kinetic arrest exists at large cross-link binding energies, greatly diminishing the effectiveness of this contractility mechanism. Then, when considering an active force dipole containing nonmuscle myosin II, we find that cross-linkers can also serve as a structural ratchet when the motor dissociates stochastically from the actin filaments, resulting in significant force amplification when both molecules are present. Our results provide predictions of how actomyosin force dipoles behave at the molecular level with respect to filament boundary conditions, passive cross-linking, and motor activity, which can explicitly be tested using an optical trapping experiment.
The effect of stochasticity on the lac operon: an evolutionary perspective.
Directory of Open Access Journals (Sweden)
Milan van Hoek
2007-06-01
Full Text Available The role of stochasticity on gene expression is widely discussed. Both potential advantages and disadvantages have been revealed. In some systems, noise in gene expression has been quantified, in among others the lac operon of Escherichia coli. Whether stochastic gene expression in this system is detrimental or beneficial for the cells is, however, still unclear. We are interested in the effects of stochasticity from an evolutionary point of view. We study this question in the lac operon, taking a computational approach: using a detailed, quantitative, spatial model, we evolve through a mutation-selection process the shape of the promoter function and therewith the effective amount of stochasticity. We find that noise values for lactose, the natural inducer, are much lower than for artificial, nonmetabolizable inducers, because these artificial inducers experience a stronger positive feedback. In the evolved promoter functions, noise due to stochasticity in gene expression, when induced by lactose, only plays a very minor role in short-term physiological adaptation, because other sources of population heterogeneity dominate. Finally, promoter functions evolved in the stochastic model evolve to higher repressed transcription rates than those evolved in a deterministic version of the model. This causes these promoter functions to experience less stochasticity in gene expression. We show that a high repression rate and hence high stochasticity increases the delay in lactose uptake in a variable environment. We conclude that the lac operon evolved such that the impact of stochastic gene expression is minor in its natural environment, but happens to respond with much stronger stochasticity when confronted with artificial inducers. In this particular system, we have shown that stochasticity is detrimental. Moreover, we demonstrate that in silico evolution in a quantitative model, by mutating the parameters of interest, is a promising way to unravel
International Nuclear Information System (INIS)
Bisognano, J.; Leemann, C.
1982-03-01
Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron
Tournaire, O.; Paparoditis, N.
Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve road databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...). In this paper, we propose a new robust and accurate top-down approach for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications. Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm's; coupled with a simulated annealing to find its minimum. Results from aerial images at various resolutions are presented showing that our
International Nuclear Information System (INIS)
Xie Shaofei; Xiang Bingren; Deng Haishan; Xiang Suyun; Lu Jun
2007-01-01
Based on the theory of stochastic resonance, an improved stochastic resonance algorithm with a new criterion for optimizing system parameters to enhance signal-to-noise ratio (SNR) of HPLC/UV chromatographic signal for trace analysis was presented in this study. Compared with the conventional criterion in stochastic resonance, the proposed one can ensure satisfactory SNR as well as good peak shape of chromatographic peak in output signal. Application of the criterion to experimental weak signals of HPLC/UV was investigated and the results showed an excellent quantitative relationship between different concentrations and responses
Stochastic cooling at Fermilab
International Nuclear Information System (INIS)
Marriner, J.
1986-08-01
The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system
Eichhorn, Ralf; Aurell, Erik
2014-04-01
'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response
International Nuclear Information System (INIS)
Azadeh, A.; Asadzadeh, S.M.; Saberi, M.; Nadimi, V.; Tajvidi, A.; Sheikalishahi, M.
2011-01-01
Highlights: → This paper presents a unique approach for long-term natural gas consumption estimation. → It is applied to selected Arab countries to show its superiority and applicability. → It may be used for other real cases for optimum gas consumption estimation. → It is compared with current studies to show its advantages. → It is capable of dealing with complexity, ambiguity, fuzziness, and randomness. -- Abstract: This paper presents an adaptive network-based fuzzy inference system-stochastic frontier analysis (ANFIS-SFA) approach for long-term natural gas (NG) consumption prediction and analysis of the behavior of NG consumption. The proposed models consist of input variables of Gross Domestic Product (GDP) and population (POP). Six distinct models based on different inputs are defined. All of trained ANFIS are then compared with respect to mean absolute percentage error (MAPE). To meet the best performance of the intelligent based approaches, data are pre-processed (scaled) and finally the outputs are post-processed (returned to its original scale). To show the applicability and superiority of the integrated ANFIS-SFA approach, gas consumption in four Middle Eastern countries i.e. Bahrain, Saudi Arabia, Syria, and United Arab Emirates is forecasted and analyzed based on the data of the time period 1980-2007. With the aid of autoregressive model, GDP and population are projected for the period 2008-2015. These projected data are used as the input of ANFIS model to predict the gas consumption in the selected countries for 2008-2015. SFA is then used to examine the behavior of gas consumption in the past and also to make insights for the forthcoming years. The ANFIS-SFA approach is capable of dealing with complexity, uncertainty, and randomness as well as several other unique features discussed in this paper.
Energy Technology Data Exchange (ETDEWEB)
Cabaniss, Stephen E. [Department of Chemistry, University of New Mexico, Albuquerque, NM 87131 (United States)], E-mail: cabaniss@unm.edu; Maurice, Patricia A. [Department of Geology and Civil Engineering, University of Notre Dame (United States); Madey, Greg [Department of Computer Science, University of Notre Dame (United States)
2007-08-15
An agent-based biogeochemical model has been developed which begins with biochemical precursor molecules and simulates the transformation and degradation of natural organic matter (NOM). This manuscript presents an empirical quantitative structure activity relationship (QSAR) which uses the numbers of ligand groups, charge density and heteroatom density of a molecule to estimate Cu-binding affinity (K{sub Cu}{sup '}) at pH 7.0 and ionic strength 0.10 for the molecules in this model. Calibration of this QSAR on a set of 41 model compounds gives a root mean square error of 0.88 log units and r{sup 2} 0.93. Two simulated NOM assemblages, one beginning with small molecules (tannins, terpenoids, flavonoids) and one with biopolymers (protein, lignin), give markedly different distributions of logK{sub Cu}{sup '}. However, calculations based on these logK{sub Cu}{sup '} distributions agree qualitatively with published experimental Cu(II) titration data from river and lake NOM samples.
Numerical Simulation of the Heston Model under Stochastic Correlation
Directory of Open Access Journals (Sweden)
Long Teng
2017-12-01
Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.
Borodin, Andrei N
2017-01-01
This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.
Directory of Open Access Journals (Sweden)
Phillip G. Bell
2014-02-01
Full Text Available This investigation examined the impact of Montmorency tart cherry concentrate (MC on physiological indices of oxidative stress, inflammation and muscle damage across 3 days simulated road cycle racing. Trained cyclists (n = 16 were divided into equal groups and consumed 30 mL of MC or placebo (PLA, twice per day for seven consecutive days. A simulated, high-intensity, stochastic road cycling trial, lasting 109 min, was completed on days 5, 6 and 7. Oxidative stress and inflammation were measured from blood samples collected at baseline and immediately pre- and post-trial on days 5, 6 and 7. Analyses for lipid hydroperoxides (LOOH, interleukin-6 (IL-6, tumor necrosis factor-alpha (TNF-α, interleukin-8 (IL-8, interleukin-1-beta (IL-1-β, high-sensitivity C-reactive protein (hsCRP and creatine kinase (CK were conducted. LOOH (p < 0.01, IL-6 (p < 0.05 and hsCRP (p < 0.05 responses to trials were lower in the MC group versus PLA. No group or interaction effects were found for the other markers. The attenuated oxidative and inflammatory responses suggest MC may be efficacious in combating post-exercise oxidative and inflammatory cascades that can contribute to cellular disruption. Additionally, we demonstrate direct application for MC in repeated days cycling and conceivably other sporting scenario’s where back-to-back performances are required.
The impact of high oil prices on natural gas
International Nuclear Information System (INIS)
Koevoet, H.
2003-01-01
The principle of gas-to-oil (oil prices determine the price of natural gas) in the Netherlands and several other developments elsewhere (war in Iraq and a cold winter in the USA) has caused high natural gas prices. The question is whether the liberalization of the energy market can change this principle [nl
Bos, Charles S.
2008-01-01
When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on realised or bipower variation are applied. This article instead starts from a continuous time diffusion model and derives a parametric analog at high frequency for it, allowing
PC analysis of stochastic differential equations driven by Wiener noise
Le Maitre, Olivier; Knio, Omar
2015-01-01
A polynomial chaos (PC) analysis with stochastic expansion coefficients is proposed for stochastic differential equations driven by additive or multiplicative Wiener noise. It is shown that for this setting, a Galerkin formalism naturally leads
High Weak Order Methods for Stochastic Differential Equations Based on Modified Equations
Abdulle, Assyr; Cohen, David; Vilmart, Gilles; Zygalakis, Konstantinos C.
2012-01-01
© 2012 Society for Industrial and Applied Mathematics. Inspired by recent advances in the theory of modified differential equations, we propose a new methodology for constructing numerical integrators with high weak order for the time integration
The Robustness of Stochastic Switching Networks
Loh, Po-Ling; Zhou, Hongchao; Bruck, Jehoshua
2009-01-01
Many natural systems, including chemical and biological systems, can be modeled using stochastic switching circuits. These circuits consist of stochastic switches, called pswitches, which operate with a fixed probability of being open or closed. We study the effect caused by introducing an error of size ∈ to each pswitch in a stochastic circuit. We analyze two constructions – simple series-parallel and general series-parallel circuits – and prove that simple series-parallel circuits are robus...
Dynamic stochastic optimization
Ermoliev, Yuri; Pflug, Georg
2004-01-01
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective an...
Dynamics of stochastic systems
Klyatskin, Valery I
2005-01-01
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''''oil slicks''''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of ...
Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids
International Nuclear Information System (INIS)
Jakeman, John D.; Archibald, Richard; Xiu Dongbin
2011-01-01
In this paper we present a set of efficient algorithms for detection and identification of discontinuities in high dimensional space. The method is based on extension of polynomial annihilation for discontinuity detection in low dimensions. Compared to the earlier work, the present method poses significant improvements for high dimensional problems. The core of the algorithms relies on adaptive refinement of sparse grids. It is demonstrated that in the commonly encountered cases where a discontinuity resides on a small subset of the dimensions, the present method becomes 'optimal', in the sense that the total number of points required for function evaluations depends linearly on the dimensionality of the space. The details of the algorithms will be presented and various numerical examples are utilized to demonstrate the efficacy of the method.
Non-intrusive low-rank separated approximation of high-dimensional stochastic models
Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca
2013-01-01
This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.
Non-intrusive low-rank separated approximation of high-dimensional stochastic models
Doostan, Alireza
2013-08-01
This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.
International Nuclear Information System (INIS)
Colombino, A.; Mosiello, R.; Norelli, F.; Jorio, V.M.; Pacilio, N.
1975-01-01
A nuclear system kinetics is formulated according to a stochastic approach. The detailed probability balance equations are written for the probability of finding the mixed population of neutrons and detected neutrons, i.e. detectrons, at a given level for a given instant of time. Equations are integrated in search of a probability profile: a series of cases is analyzed through a progressive criterium. It tends to take into account an increasing number of physical processes within the chosen model. The most important contribution is that solutions interpret analytically experimental conditions of equilibrium (moise analysis) and non equilibrium (pulsed neutron measurements, source drop technique, start up procedures)
Energy Technology Data Exchange (ETDEWEB)
Zakova, Jitka [Department of Nuclear and Reactor Physics, Royal Institute of Technology, KTH, Roslagstullsbacken 21, S-10691 Stockholm (Sweden)], E-mail: jitka.zakova@neutron.kth.se; Talamo, Alberto [Nuclear Engineering Division, Argonne National Laboratory, ANL, 9700 South Cass Avenue, Argonne, IL 60439 (United States)], E-mail: alby@anl.gov
2008-05-15
Modeling of prismatic high temperature reactors requires a high precision description due to the triple heterogeneity of the core and also to the random distribution of fuel particles inside the fuel pins. On the latter issue, even with the most advanced Monte Carlo techniques, some approximation often arises while assessing the criticality level: first, a regular lattice of TRISO particles inside the fuel pins and, second, the cutting of TRISO particles by the fuel boundaries. We utilized two of the most accurate Monte Codes: MONK and MCNP, which are both used for licensing nuclear power plants in United Kingdom and in the USA, respectively, to evaluate the influence of the two previous approximations on estimating the criticality level of the Gas Turbine Modular Helium Reactor. The two codes exactly shared the same geometry and nuclear data library, ENDF/B, and only modeled different lattices of TRISO particles inside the fuel pins. More precisely, we investigated the difference between a regular lattice that cuts TRISO particles and a random lattice that axially repeats a region containing over 3000 non-cut particles. We have found that both Monte Carlo codes provide similar excesses of reactivity, provided that they share the same approximations.
High-resolution stochastic integrated thermal–electrical domestic demand model
International Nuclear Information System (INIS)
McKenna, Eoghan; Thomson, Murray
2016-01-01
Highlights: • A major new version of CREST’s demand model is presented. • Simulates electrical and thermal domestic demands at high-resolution. • Integrated structure captures appropriate time-coincidence of variables. • Suitable for low-voltage network and urban energy analyses. • Open-source development in Excel VBA freely available for download. - Abstract: This paper describes the extension of CREST’s existing electrical domestic demand model into an integrated thermal–electrical demand model. The principle novelty of the model is its integrated structure such that the timing of thermal and electrical output variables are appropriately correlated. The model has been developed primarily for low-voltage network analysis and the model’s ability to account for demand diversity is of critical importance for this application. The model, however, can also serve as a basis for modelling domestic energy demands within the broader field of urban energy systems analysis. The new model includes the previously published components associated with electrical demand and generation (appliances, lighting, and photovoltaics) and integrates these with an updated occupancy model, a solar thermal collector model, and new thermal models including a low-order building thermal model, domestic hot water consumption, thermostat and timer controls and gas boilers. The paper reviews the state-of-the-art in high-resolution domestic demand modelling, describes the model, and compares its output with three independent validation datasets. The integrated model remains an open-source development in Excel VBA and is freely available to download for users to configure and extend, or to incorporate into other models.
High energy hadron dynamics based on a Stochastic-field multi-eikonal theory
International Nuclear Information System (INIS)
Arnold, R.C.
1977-06-01
Multi-eikonal theory, using a stoichastic-field representation for collective long range rapidity correlations, is developed and applied to the calculation of Regge pole parameters, high transverse momentum enhancements, and fluctuation patterns in rapidity densities. If a short-range-order model, such as the one-dimensional planar bootstrap, with only leading t-channel meson poles, is utilized as input to the multi-eikonal method, the pole spectrum is modified in three ways; promotion and renormalization of leading trajectories (suggesting an effective pomeron above unity at intermediate energies), and a proliferation of dynamical secondary trajectories, reminiscent of dual models. When transverse dimensions are included, the collective effects produce a growth with energy of large-P/sub tau/ inclusive cross-sections. Typical-event rapidity distributions, at energies of a few TeV, can be estimated by suitable approximations; the fluctuations give rise to ''domain'' patterns, which have the appearance of clusters separated by rapidity gaps. The relations between this approach to strong-interaction dynamics and a possible unification of weak, electromagnetic, and strong interactions are outlined
International Nuclear Information System (INIS)
Shapoval, A.; Le Mouël, J.-L.; Courtillot, V.; Shnirman, M.
2015-01-01
The irregularity index λ is applied to the high-frequency content of daily sunspot numbers ISSN. This λ is a modification of the standard maximal Lyapunov exponent. It is computed here as a function of embedding dimension m, within four-year time windows centered at the maxima of Schwabe cycles. The λ(m) curves form separate clusters (pre-1923 and post-1933). This supports a regime transition and narrows its occurrence to cycle 16, preceding the growth of activity leading to the Modern Maximum. The two regimes are reproduced by a simple autoregressive process AR(1), with the mean of Poisson noise undergoing 11 yr modulation. The autocorrelation a of the process (linked to sunspot lifetime) is a ≈ 0.8 for 1850-1923 and ≈0.95 for 1933-2013. The AR(1) model suggests that groups of spots appear with a Poisson rate and disappear at a constant rate. We further applied the irregularity index to the daily sunspot group number series for the northern and southern hemispheres, provided by the Greenwich Royal Observatory (RGO), in order to study a possible desynchronization. Correlations between the north and south λ(m) curves vary quite strongly with time and indeed show desynchronization. This may reflect a slow change in the dimension of an underlying dynamical system. The ISSN and RGO series of group numbers do not imply an identical mechanism, but both uncover a regime change at a similar time. Computation of the irregularity index near the maximum of cycle 24 will help in checking whether yet another regime change is under way
RES: Regularized Stochastic BFGS Algorithm
Mokhtari, Aryan; Ribeiro, Alejandro
2014-12-01
RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.
Lanchier, Nicolas
2017-01-01
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the ...
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.
Stochastic Averaging and Stochastic Extremum Seeking
Liu, Shu-Jun
2012-01-01
Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering and analysis of bacterial convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...
Performance of Naturally Aspirating IC Engines Operating at High ...
African Journals Online (AJOL)
The loss of power and the increase of fuel consumption of naturally aspirating IC engines operating with low atmospheric pressure at high altitude as well as changes in the mixture quality with non adapting mixture formation systems are principally known. Other effects like the additional advance of ignition timing in petrol ...
On the nature of highly vibrationally excited states of thiophosgene
Indian Academy of Sciences (India)
Understanding the nature of the highly excited molecu- lar eigenstates is equivalent to deciphering the mecha- nism of intramolecular vibrational energy redistribution. (IVR) occurring in the molecule.1 However, the assign- ment of eigenstates is far from simple. The existence of and interplay of several strong anharmonic ...
Nigsch, Annette; Costard, Solenne; Jones, Bryony A; Pfeiffer, Dirk U; Wieland, Barbara
2013-03-01
African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS during that period would most likely contribute to ASF spread ("super-spreaders") or MS that would most likely receive cases from other MS ("super-receivers"). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10-60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1-2 infected premises per outbreak (95% IQR: 1-4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified
Stochastic stacking without filters
International Nuclear Information System (INIS)
Johnson, R.P.; Marriner, J.
1982-12-01
The rate of accumulation of antiprotons is a critical factor in the design of p anti p colliders. A design of a system to accumulate higher anti p fluxes is presented here which is an alternative to the schemes used at the CERN AA and in the Fermilab Tevatron I design. Contrary to these stacking schemes, which use a system of notch filters to protect the dense core of antiprotons from the high power of the stack tail stochastic cooling, an eddy current shutter is used to protect the core in the region of the stack tail cooling kicker. Without filters one can have larger cooling bandwidths, better mixing for stochastic cooling, and easier operational criteria for the power amplifiers. In the case considered here a flux of 1.4 x 10 8 per sec is achieved with a 4 to 8 GHz bandwidth
International Nuclear Information System (INIS)
Braumann, Andreas; Kraft, Markus; Wagner, Wolfgang
2010-01-01
This paper is concerned with computational aspects of a multidimensional population balance model of a wet granulation process. Wet granulation is a manufacturing method to form composite particles, granules, from small particles and binders. A detailed numerical study of a stochastic particle algorithm for the solution of a five-dimensional population balance model for wet granulation is presented. Each particle consists of two types of solids (containing pores) and of external and internal liquid (located in the pores). Several transformations of particles are considered, including coalescence, compaction and breakage. A convergence study is performed with respect to the parameter that determines the number of numerical particles. Averaged properties of the system are computed. In addition, the ensemble is subdivided into practically relevant size classes and analysed with respect to the amount of mass and the particle porosity in each class. These results illustrate the importance of the multidimensional approach. Finally, the kinetic equation corresponding to the stochastic model is discussed.
Detecting change in stochastic sound sequences.
Directory of Open Access Journals (Sweden)
Benjamin Skerritt-Davis
2018-05-01
Full Text Available Our ability to parse our acoustic environment relies on the brain's capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance. In this work, we investigate the brain's sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects' behavior indicates an important role of perceptual constraints in listeners' ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain's ability to process stochastic sound sequences.
Towards Model Checking Stochastic Process Algebra
Hermanns, H.; Grieskamp, W.; Santen, T.; Katoen, Joost P.; Stoddart, B.; Meyer-Kayser, J.; Siegle, M.
2000-01-01
Stochastic process algebras have been proven useful because they allow behaviour-oriented performance and reliability modelling. As opposed to traditional performance modelling techniques, the behaviour- oriented style supports composition and abstraction in a natural way. However, analysis of
Hadjilouka, Agni; Mantzourani, Kyriaki-Sofia; Katsarou, Anastasia; Cavaiuolo, Marina; Ferrante, Antonio; Paramithiotis, Spiros; Mataragas, Marios; Drosinos, Eleftherios H
2015-02-01
The aims of the present study were to determine the prevalence and levels of Listeria monocytogenes and Escherichia coli O157:H7 in rocket and cucumber samples by deterministic (estimation of a single value) and stochastic (estimation of a range of values) approaches. In parallel, the chromogenic media commonly used for the recovery of these microorganisms were evaluated and compared, and the efficiency of an enzyme-linked immunosorbent assay (ELISA)-based protocol was validated. L. monocytogenes and E. coli O157:H7 were detected and enumerated using agar Listeria according to Ottaviani and Agosti plus RAPID' L. mono medium and Fluorocult plus sorbitol MacConkey medium with cefixime and tellurite in parallel, respectively. Identity was confirmed with biochemical and molecular tests and the ELISA. Performance indices of the media and the prevalence of both pathogens were estimated using Bayesian inference. In rocket, prevalence of both L. monocytogenes and E. coli O157:H7 was estimated at 7% (7 of 100 samples). In cucumber, prevalence was 6% (6 of 100 samples) and 3% (3 of 100 samples) for L. monocytogenes and E. coli O157:H7, respectively. The levels derived from the presence-absence data using Bayesian modeling were estimated at 0.12 CFU/25 g (0.06 to 0.20) and 0.09 CFU/25 g (0.04 to 0.170) for L. monocytogenes in rocket and cucumber samples, respectively. The corresponding values for E. coli O157:H7 were 0.59 CFU/25 g (0.43 to 0.78) and 1.78 CFU/25 g (1.38 to 2.24), respectively. The sensitivity and specificity of the culture media differed for rocket and cucumber samples. The ELISA technique had a high level of cross-reactivity. Parallel testing with at least two culture media was required to achieve a reliable result for L. monocytogenes or E. coli O157:H7 prevalence in rocket and cucumber samples.
International Nuclear Information System (INIS)
Tzounis, Lazaros; Debnath, Subhas; Rooj, Sandip; Fischer, Dieter; Mäder, Edith; Das, Amit; Stamm, Manfred; Heinrich, Gert
2014-01-01
A simple and facile method for depositing multiwall carbon nanotubes (MWCNTs) onto the surface of naturally occurring short jute fibers (JFs) is reported. Hierarchical multi-scale structures were formed with CNT-networks uniformly distributed and fully covering the JFs (JF–CNT), as depicted by the scanning electron microscopy (SEM) micrographs. The impact of these hybrid fillers on the mechanical properties of a natural rubber (NR) matrix was systematically investigated. Pristine JFs were cut initially to an average length of 2.0 mm and exposed to an alkali treatment (a-JFs) to remove impurities existing in the raw jute. MWCNTs were treated under mild acidic conditions to generate carboxylic acid moieties. Afterward, MWCNTs were dispersed in an aqueous media and short a-JFs were allowed to react with them. Raman spectroscopy confirmed the chemical interaction between CNTs and JFs. The JF–CNT exposed quite hydrophobic behavior as revealed by the water contact angle measurements, improving the wettability of the non-polar NR. Consequently, the composite interfacial adhesion strength was significantly enhanced while a micro-scale “mechanical interlocking” mechanism was observed from the interphase-section transmission electron microscopy (TEM) images. SEM analysis of the composite fracture surfaces demonstrated the interfacial strength of NR/a-JF and NR/JF–CNT composites, at different fiber loadings. It can be presumed that the CNT-coating effectively compatibillized the composite structure acting as a macromolecular coupling agent. A detailed analysis of stress-strain and dynamic mechanical spectra confirmed the high mechanical performance of the hierarchical composites, consisting mainly of materials arising from natural resources. - Highlights: • Natural rubber (NR) composites reinforced with CNT-modified short jute fibers. • MWCNTs deposited to the surface of jute fibers via non-covalent interactions. • Hierarchical reinforcement structure with
Chromosome Aberration on High Level Background Natural Radiation Areas
International Nuclear Information System (INIS)
Yanti-Lusiyanti; Zubaidah-Alatas
2001-01-01
When the body is irradiated, all cells can suffer cytogenetic damage that can be seen as structural damage of chromosome in the lymphocytes. People no matter where they live in world are exposed to background radiation from natural sources both internal and external such as cosmic radiation, terrestrial radiation, cosmogenic radiation radon and thoron. Level of area natural ionizing radiation is varies depending on the altitude, the soil or rock conditions, particular food chains and the building materials and construction features. Level of normal areas of background exposure is annual effective dose 2.4 mSv and the high level areas of background exposure 20 mSv. This paper discuses the frequency of aberration chromosome especially dysenteries in several countries having high level radiation background. It seems that frequency of chromosome aberrations increase, generally with the increase of age of the people and the accumulated dose received. (author)
High-dose dosimetry using natural silicate minerals
International Nuclear Information System (INIS)
Carmo, Lucas S. do; Mendes, Leticia; Watanabe, Shigueo; Rao, Gundu; Lucas, Natasha; Sato, Karina; Barbosa, Renata F.
2015-01-01
In the present study, certain natural silicate minerals such as aquamarine (AB), morganite (PB), goshenite (WB), white jadeite (JW), green jadeite (JG), pink tourmaline (PT) and two varieties of jadeite-like quartz, denoted here by JQ1 and JQ2, were investigated using the thermoluminescence technique to evaluate their potential for use as very-high- and high-dose dosimeters. These minerals respond to high doses of γ-rays of up to 1000 kGy and often to very high doses of up to 3000 kGy. The TL response of these minerals may be considered to be satisfactory for applications in high-dose dosimetry. Investigations of electron paramagnetic resonance and optically stimulated luminescence dosimetry are in progress. (author)
High-dose dosimetry using natural silicate minerals
Energy Technology Data Exchange (ETDEWEB)
Carmo, Lucas S. do; Mendes, Leticia, E-mail: isatiro@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Watanabe, Shigueo; Rao, Gundu; Lucas, Natasha; Sato, Karina, E-mail: lacifid@if.usp.br [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Instituto de Fisica. Departamento de Fisica Nuclear; Barbosa, Renata F., E-mail: profcelta@hotmail.com [Universidade Federal de Sao Paulo (UNIFESP), Santos, SP (Brazil). Departamento de Ciencias do Mar
2015-07-01
In the present study, certain natural silicate minerals such as aquamarine (AB), morganite (PB), goshenite (WB), white jadeite (JW), green jadeite (JG), pink tourmaline (PT) and two varieties of jadeite-like quartz, denoted here by JQ1 and JQ2, were investigated using the thermoluminescence technique to evaluate their potential for use as very-high- and high-dose dosimeters. These minerals respond to high doses of γ-rays of up to 1000 kGy and often to very high doses of up to 3000 kGy. The TL response of these minerals may be considered to be satisfactory for applications in high-dose dosimetry. Investigations of electron paramagnetic resonance and optically stimulated luminescence dosimetry are in progress. (author)
Adaptive stochastic Galerkin FEM with hierarchical tensor representations
Eigel, Martin
2016-01-01
PDE with stochastic data usually lead to very high-dimensional algebraic problems which easily become unfeasible for numerical computations because of the dense coupling structure of the discretised stochastic operator. Recently, an adaptive
Clay membrane made of natural high plasticity clay
DEFF Research Database (Denmark)
Foged, Niels; Baumann, Jens
1998-01-01
Leachate containment in Denmark has through years been regulated by the DIF Recommendation for Sanitary Landfill Liners (DS/R 466). It states natural clay deposits may be used for membrane material provided the membrane and drainage system may contain at least 95% of all leachate created throughout...... ion transport as well as diffusion.Clay prospection for clays rich in smectite has revealed large deposits of Tertiary clay of very high plasticity in the area around Rødbyhavn on the Danish island Lolland. The natural clay contains 60 to 75% smectite, dominantly as a sodium-type. The clay material...... has been evaluated using standardised methods related to mineralogy, classification, compaction and permeability, and initial studies of diffusion properties have been carried out. Furthermore, at a test site the construction methods for establishing a 0.15 to 0.3m thick clay membrane have been tested...
Clay membrane made of natural high plasticity clay:
DEFF Research Database (Denmark)
Foged, Niels; Baumann, Jens
1999-01-01
Leachate containment in Denmark has throughout the years been regulated by the DIF Recommendation for Sanitary Landfill Liners (DS/R4669. It states that natural clay deposits may be used as membrane material provided the membrane and drainage system contains at least 95% of all leachate created...... into account advective ion transport as well as diffusion. Clay prospecting for clays rich in smectite has revealed large deposits of Tertiary clay of very high plasticity in the area around Rødbyhavn on the Danish island of Lolland. The natural clay contains 60-75% smectite, dominantly as a sodium......-type. The clay material has been evaluated using the standardized methods related to mineralogy, classification, compaction and permeability, and initial studies of diffusion properties have been carried out. Furthermore, at a test site the construction methods for establishing a 0.15-0.3 m thick clay membrane...
Hardware implementation of stochastic spiking neural networks.
Rosselló, Josep L; Canals, Vincent; Morro, Antoni; Oliver, Antoni
2012-08-01
Spiking Neural Networks, the last generation of Artificial Neural Networks, are characterized by its bio-inspired nature and by a higher computational capacity with respect to other neural models. In real biological neurons, stochastic processes represent an important mechanism of neural behavior and are responsible of its special arithmetic capabilities. In this work we present a simple hardware implementation of spiking neurons that considers this probabilistic nature. The advantage of the proposed implementation is that it is fully digital and therefore can be massively implemented in Field Programmable Gate Arrays. The high computational capabilities of the proposed model are demonstrated by the study of both feed-forward and recurrent networks that are able to implement high-speed signal filtering and to solve complex systems of linear equations.
Kirishites, a new type of natural high-carbon compounds
Marin, Yu. B.; Skublov, G. T.; Yushkin, N. P.
2010-01-01
On the right-hand bank of the Volkhov River, in the natural area of tektite-like glasses (Volkhovites), fragments of shungites and slags with bunches of hairlike dark brownish enclosures were found. The filament thickness ranged from 20 to 100 μm, and separate “hairlines” were 3 cm in length. The composition of shungites and “hairlines” was found to be identical, which allowed us to consider the latter as aposhungite carbon formations. The high-carbon hairline structures associated with volkhovites are called kirishites. Kirishites are a new type of high-carbon structures that formed simultaneously with volkhovites in the case of explosion-type delivery of carbon slag and shungite fragments to the daylight surface during Holocene explosive activity. Under sharply reductive conditions, the slags partially melted, the melts were segregated, and carbonaceous-silicate and carbonaceous-ferriferous glasses formed with subsequent decompression-explosive liberation of carbon-supersaturated structures, which were extruded from shungite and slag fragments in the form of a resinoid mass. The “hairlines” were found to be zonal in structure: the central axial zones are composed of high-nitrogen hydrocarbon compounds, and peripheral regions are essentially carbonaceous with a high content of organic-mineral compounds and numerous microanomalies of petrogenic, volatile, rare, and ore elements. Infrared spectroscopy identified in kirishites proteinlike compounds, diagnosed in absorption bands (in cm-1) 600-720 (Amid V), 1200-1300 (Amid III), 1480-1590 (Amid II), 1600-1700 (Amid I), 3000-3800 (vibrations in NH2 and II groups). Gas chromatography, with the possibility of differentiation of left- and right-handed forms, revealed a broad spectrum of amino acids in kirishites, with their total content found to be the absolutely highest record for natural bitumens, an order of magnitude higher than the largest amino acid concentrations ever revealed in fibrous high
Moschos, Evangelos; Manou, Georgia; Georganta, Xristina; Dimitriadis, Panayiotis; Iliopoulou, Theano; Tyralis, Hristos; Koutsoyiannis, Demetris; Tsoukala, Vicky
2017-04-01
The large energy potential of ocean dynamics is not yet being efficiently harvested mostly due to several technological and financial drawbacks. Nevertheless, modern renewable energy systems include wave and tidal energy in cases of nearshore locations. Although the variability of tidal waves can be adequately predictable, wind-generated waves entail a much larger uncertainty due to their dependence to the wind process. Recent research has shown, through estimation of the wave energy potential in coastal areas of the Aegean Sea, that installation of wave energy converters in nearshore locations could be an applicable scenario, assisting the electrical network of Greek islands. In this context, we analyze numerous of observations and we investigate the long-term behaviour of wave height and wave period processes. Additionally, we examine the case of a remote island in the Aegean sea, by estimating the local wave climate through past analysis data and numerical methods, and subsequently applying a parsimonious stochastic model to a theoretical scenario of wave energy production. 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.
Stochastic tools in turbulence
Lumey, John L
2012-01-01
Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the
Preparation of highly stabilised natural rubber latex for radiation vulcanisation
International Nuclear Information System (INIS)
Kulatunge, S.S.; Nadarajah, M.; Kalyani, N.M.V.; Chandralal, H.N.K.K.; Devendra, R.
1996-01-01
There is a bright future for radiation vulcanised natural rubber latex (RVNRL) but there are problems in manufacturing it as the centrifuged latex to be used for radiation has to be kept for at least a month or sometimes even three to six months before adding the sensitisers and even then the latex sometimes coagulates on adding the sensitisers. This paper describes a process by which the latex can be stabilised by addition of an anionic soap before centrifuging so that it has a high mechanical stability and hence can be used even within one week of the manufacture of the centrifuged latex
Optical spectroscopy and high pressure on emeralds: synthetic and natural
Sánchez-Alejo, M. A.; Hernández-Alcántara, J. M.; Flores Jiménez, C.; Calderón, T.; Murrieta S., H.; Camarillo García, E.
2011-09-01
Emerald, natural and synthetic, are the subject of study by means of optical spectroscopy techniques. Particularly, natural emeralds have been considered as a gemstone in jewelry not being so the synthetic ones. But, in general, the properties of these are very good for applications, for instance as a laser system, due to the impurities control. In this work a comparison between natural and synthetic emeralds is done. Chromium ions are the main responsible of the characteristic fascinating green color of these gemstones, entering in the crystals in octahedral sites. Absorption at room temperature show up two broad bands in the visible region and two narrow bands called the R-lines. That spectrum corresponds to trivalent chromium ions in an octahedral site, as it happens in ruby and alexandrite. On other hand, photoemission arises in the range 640-850 nm. at room temperature . It is shown that the luminescence spectra changes as the temperature is lowered. The effect on the main peak of luminescence when high pressure is applied on small samples of emerald shows as a linear function.
Geometric integrators for stochastic rigid body dynamics
Tretyakov, Mikhail
2016-01-05
Geometric integrators play an important role in simulating dynamical systems on long time intervals with high accuracy. We will illustrate geometric integration ideas within the stochastic context, mostly on examples of stochastic thermostats for rigid body dynamics. The talk will be mainly based on joint recent work with Rusland Davidchak and Tom Ouldridge.
Geometric integrators for stochastic rigid body dynamics
Tretyakov, Mikhail
2016-01-01
Geometric integrators play an important role in simulating dynamical systems on long time intervals with high accuracy. We will illustrate geometric integration ideas within the stochastic context, mostly on examples of stochastic thermostats for rigid body dynamics. The talk will be mainly based on joint recent work with Rusland Davidchak and Tom Ouldridge.
High level natural radiation areas with special regard to Ramsar
International Nuclear Information System (INIS)
Sohrabi, M.
1993-01-01
The studies of high level natural radiation areas (HLNRAs) around the world are of great importance for determination of risks due to long-term low-level whole body exposures of public. Many areas of the world possess HLNRAs the number of which depends on the criteria defined. Detailed radiological studies have been carried out in some HLNRAs the results of which have been reported at least in three international conferences. Among the HLNRAs, Ramsar has so far the highest level of natural radiation in some areas where radiological studies have been of concern. A program was established for Ramsar and its HLNRAs to study indoor and outdoor gamma exposures and external and internal doses of the inhabitants, 226 Ra content of public water supplies and hot springs, of food stuffs, etc., 222 Rn levels measured in 473 rooms of near 350 houses, 16 schools and 89 rooms and many locations of old and new Ramsar Hotels in different seasons, cytogenetic effects on inhabitants of Talesh Mahalleh, the highest radiation area, compared to that of a control area and radiological parameters of a house with a high potential for internal and external exposures of the inhabitants. It was concluded that the epidemiological studies in a number of countries did not show any evidence of increased health detriment in HLNRAs compared to control groups. In this paper, the conclusions drawn from studies in some HLNRAs around the world in particular Ramsar are discussed. (author). 20 refs, 2 figs, 1 tab
STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION
Directory of Open Access Journals (Sweden)
Nataša Krejić
2014-12-01
Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.
Adaptation in stochastic environments
Clark, Colib
1993-01-01
The classical theory of natural selection, as developed by Fisher, Haldane, and 'Wright, and their followers, is in a sense a statistical theory. By and large the classical theory assumes that the underlying environment in which evolution transpires is both constant and stable - the theory is in this sense deterministic. In reality, on the other hand, nature is almost always changing and unstable. We do not yet possess a complete theory of natural selection in stochastic environ ments. Perhaps it has been thought that such a theory is unimportant, or that it would be too difficult. Our own view is that the time is now ripe for the development of a probabilistic theory of natural selection. The present volume is an attempt to provide an elementary introduction to this probabilistic theory. Each author was asked to con tribute a simple, basic introduction to his or her specialty, including lively discussions and speculation. We hope that the book contributes further to the understanding of the roles of "Cha...
Is human failure a stochastic process?
International Nuclear Information System (INIS)
Dougherty, Ed M.
1997-01-01
Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance
High Resolution Nature Runs and the Big Data Challenge
Webster, W. Phillip; Duffy, Daniel Q.
2015-01-01
NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center is undertaking a series of very computationally intensive Nature Runs and a downscaled reanalysis. The nature runs use the GEOS-5 as an Atmospheric General Circulation Model (AGCM) while the reanalysis uses the GEOS-5 in Data Assimilation mode. This paper will present computational challenges from three runs, two of which are AGCM and one is downscaled reanalysis using the full DAS. The nature runs will be completed at two surface grid resolutions, 7 and 3 kilometers and 72 vertical levels. The 7 km run spanned 2 years (2005-2006) and produced 4 PB of data while the 3 km run will span one year and generate 4 BP of data. The downscaled reanalysis (MERRA-II Modern-Era Reanalysis for Research and Applications) will cover 15 years and generate 1 PB of data. Our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS), a specialization of the concept of business process-as-a-service that is an evolving extension of IaaS, PaaS, and SaaS enabled by cloud computing. In this presentation, we will describe two projects that demonstrate this shift. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS. MERRA/AS enables MapReduce analytics over MERRA reanalysis data collection by bringing together the high-performance computing, scalable data management, and a domain-specific climate data services API. NASA's High-Performance Science Cloud (HPSC) is an example of the type of compute-storage fabric required to support CAaaS. The HPSC comprises a high speed Infinib and network, high performance file systems and object storage, and a virtual system environments specific for data intensive, science applications. These technologies are providing a new tier in the data and analytic services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility
High Altitude Aerial Natural Gas Leak Detection System
Energy Technology Data Exchange (ETDEWEB)
Richard T. Wainner; Mickey B. Frish; B. David Green; Matthew C. Laderer; Mark G. Allen; Joseph R. Morency
2006-12-31
The objective of this program was to develop and demonstrate a cost-effective and power-efficient advanced standoff sensing technology able to detect and quantify, from a high-altitude (> 10,000 ft) aircraft, natural gas leaking from a high-pressure pipeline. The advanced technology is based on an enhanced version of the Remote Methane Leak Detector (RMLD) platform developed previously by Physical Sciences Inc. (PSI). The RMLD combines a telecommunications-style diode laser, fiber-optic components, and low-cost DSP electronics with the well-understood principles of Wavelength Modulation Spectroscopy (WMS), to indicate the presence of natural gas located between the operator and a topographic target. The transceiver transmits a laser beam onto a topographic target and receives some of the laser light reflected by the target. The controller processes the received light signal to deduce the amount of methane in the laser's path. For use in the airborne platform, we modified three aspects of the RMLD, by: (1) inserting an Erbium-doped optical fiber laser amplifier to increase the transmitted laser power from 10 mW to 5W; (2) increasing the optical receiver diameter from 10 cm to 25 cm; and (3) altering the laser wavelength from 1653 nm to 1618 nm. The modified RMLD system provides a path-integrated methane concentration sensitivity {approx}5000 ppm-m, sufficient to detect the presence of a leak from a high capacity transmission line while discriminating against attenuation by ambient methane. In ground-based simulations of the aerial leak detection scenario, we demonstrated the ability to measure methane leaks within the laser beam path when it illuminates a topographic target 2000 m away. We also demonstrated simulated leak detection from ranges of 200 m using the 25 cm optical receiver without the fiber amplifier.
Applied probability and stochastic processes
Sumita, Ushio
1999-01-01
Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...
STOCHASTIC METHODS IN RISK ANALYSIS
Directory of Open Access Journals (Sweden)
Vladimíra OSADSKÁ
2017-06-01
Full Text Available In this paper, we review basic stochastic methods which can be used to extend state-of-the-art deterministic analytical methods for risk analysis. We can conclude that the standard deterministic analytical methods highly depend on the practical experience and knowledge of the evaluator and therefore, the stochastic methods should be introduced. The new risk analysis methods should consider the uncertainties in input values. We present how large is the impact on the results of the analysis solving practical example of FMECA with uncertainties modelled using Monte Carlo sampling.
Lichen Symbiosis: Nature's High Yielding Machines for Induced Hydrogen Production
Papazi, Aikaterini; Kastanaki, Elizabeth; Pirintsos, Stergios; Kotzabasis, Kiriakos
2015-01-01
Hydrogen is a promising future energy source. Although the ability of green algae to produce hydrogen has long been recognized (since 1939) and several biotechnological applications have been attempted, the greatest obstacle, being the O2-sensitivity of the hydrogenase enzyme, has not yet been overcome. In the present contribution, 75 years after the first report on algal hydrogen production, taking advantage of a natural mechanism of oxygen balance, we demonstrate high hydrogen yields by lichens. Lichens have been selected as the ideal organisms in nature for hydrogen production, since they consist of a mycobiont and a photobiont in symbiosis. It has been hypothesized that the mycobiont’s and photobiont’s consumption of oxygen (increase of COX and AOX proteins of mitochondrial respiratory pathways and PTOX protein of chrolorespiration) establishes the required anoxic conditions for the activation of the phycobiont’s hydrogenase in a closed system. Our results clearly supported the above hypothesis, showing that lichens have the ability to activate appropriate bioenergetic pathways depending on the specific incubation conditions. Under light conditions, they successfully use the PSII-dependent and the PSII-independent pathways (decrease of D1 protein and parallel increase of PSaA protein) to transfer electrons to hydrogenase, while under dark conditions, lichens use the PFOR enzyme and the dark fermentative pathway to supply electrons to hydrogenase. These advantages of lichen symbiosis in combination with their ability to survive in extreme environments (while in a dry state) constitute them as unique and valuable hydrogen producing natural factories and pave the way for future biotechnological applications. PMID:25826211
Lichen symbiosis: nature's high yielding machines for induced hydrogen production.
Directory of Open Access Journals (Sweden)
Aikaterini Papazi
Full Text Available Hydrogen is a promising future energy source. Although the ability of green algae to produce hydrogen has long been recognized (since 1939 and several biotechnological applications have been attempted, the greatest obstacle, being the O2-sensitivity of the hydrogenase enzyme, has not yet been overcome. In the present contribution, 75 years after the first report on algal hydrogen production, taking advantage of a natural mechanism of oxygen balance, we demonstrate high hydrogen yields by lichens. Lichens have been selected as the ideal organisms in nature for hydrogen production, since they consist of a mycobiont and a photobiont in symbiosis. It has been hypothesized that the mycobiont's and photobiont's consumption of oxygen (increase of COX and AOX proteins of mitochondrial respiratory pathways and PTOX protein of chrolorespiration establishes the required anoxic conditions for the activation of the phycobiont's hydrogenase in a closed system. Our results clearly supported the above hypothesis, showing that lichens have the ability to activate appropriate bioenergetic pathways depending on the specific incubation conditions. Under light conditions, they successfully use the PSII-dependent and the PSII-independent pathways (decrease of D1 protein and parallel increase of PSaA protein to transfer electrons to hydrogenase, while under dark conditions, lichens use the PFOR enzyme and the dark fermentative pathway to supply electrons to hydrogenase. These advantages of lichen symbiosis in combination with their ability to survive in extreme environments (while in a dry state constitute them as unique and valuable hydrogen producing natural factories and pave the way for future biotechnological applications.
Schilstra, Maria J; Martin, Stephen R
2009-01-01
Stochastic simulations may be used to describe changes with time of a reaction system in a way that explicitly accounts for the fact that molecules show a significant degree of randomness in their dynamic behavior. The stochastic approach is almost invariably used when small numbers of molecules or molecular assemblies are involved because this randomness leads to significant deviations from the predictions of the conventional deterministic (or continuous) approach to the simulation of biochemical kinetics. Advances in computational methods over the three decades that have elapsed since the publication of Daniel Gillespie's seminal paper in 1977 (J. Phys. Chem. 81, 2340-2361) have allowed researchers to produce highly sophisticated models of complex biological systems. However, these models are frequently highly specific for the particular application and their description often involves mathematical treatments inaccessible to the nonspecialist. For anyone completely new to the field to apply such techniques in their own work might seem at first sight to be a rather intimidating prospect. However, the fundamental principles underlying the approach are in essence rather simple, and the aim of this article is to provide an entry point to the field for a newcomer. It focuses mainly on these general principles, both kinetic and computational, which tend to be not particularly well covered in specialist literature, and shows that interesting information may even be obtained using very simple operations in a conventional spreadsheet.
Uncertainty Reduction for Stochastic Processes on Complex Networks
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 control of traffic patterns
DEFF Research Database (Denmark)
Gaididei, Yuri B.; Gorria, Carlos; Berkemer, Rainer
2013-01-01
A stochastic modulation of the safety distance can reduce traffic jams. It is found that the effect of random modulation on congestive flow formation depends on the spatial correlation of the noise. Jam creation is suppressed for highly correlated noise. The results demonstrate the advantage of h...
Condensation heat transfer on natural convection at the high pressure
International Nuclear Information System (INIS)
Jong-Won, Kim; Hyoung-Kyoun, Ahn; Goon-Cherl, Park
2007-01-01
The Regional Energy Research Institute for the Next Generation is to develop a small scale electric power system driven by an environment-friendly and stable small nuclear reactor. REX-10 has been developed to assure high system safety in order to be placed in densely populated region and island. REX-10 adopts the steam-gas pressurizer to assure the inherent safety. The thermal-hydraulic phenomena in the steam-gas pressurizer are very complex. Especially, the condensation heat transfer with noncondensable gas on the natural convection is important to evaluate the pressurizer behavior. However, there have been few investigations on the condensation in the presence of noncondensable gas at the high pressure. In this study, the theoretical model is developed to estimate the condensation heat transfer at the high pressure using heat and mass transfer analogy. The analysis results show good agreement with correlations and experimental data. It is found that the condensation heat transfer coefficient increases as the total pressure increases or the mass fraction of the non-condensable gas decreases. In addition, the heat transfer coefficient no more increases over the specific pressure
Nutritional strategies of high level natural bodybuilders during competition preparation.
Chappell, A J; Simper, T; Barker, M E
2018-01-01
Competitive bodybuilders employ a combination of resistance training, cardiovascular exercise, calorie reduction, supplementation regimes and peaking strategies in order to lose fat mass and maintain fat free mass. Although recommendations exist for contest preparation, applied research is limited and data on the contest preparation regimes of bodybuilders are restricted to case studies or small cohorts. Moreover, the influence of different nutritional strategies on competitive outcome is unknown. Fifty-one competitors (35 male and 16 female) volunteered to take part in this project. The British Natural Bodybuilding Federation (BNBF) runs an annual national competition for high level bodybuilders; competitors must qualify by winning at a qualifying events or may be invited at the judge's discretion. Competitors are subject to stringent drug testing and have to undergo a polygraph test. Study of this cohort provides an opportunity to examine the dietary practices of high level natural bodybuilders. We report the results of a cross-sectional study of bodybuilders competing at the BNBF finals. Volunteers completed a 34-item questionnaire assessing diet at three time points. At each time point participants recorded food intake over a 24-h period in grams and/or portions. Competitors were categorised according to contest placing. A "placed" competitor finished in the top 5, and a "Non-placed" (DNP) competitor finished outside the top 5. Nutrient analysis was performed using Nutritics software. Repeated measures ANOVA and effect sizes (Cohen's d ) were used to test if nutrient intake changed over time and if placing was associated with intake. Mean preparation time for a competitor was 22 ± 9 weeks. Nutrient intake of bodybuilders reflected a high-protein, high-carbohydrate, low-fat diet. Total carbohydrate, protein and fat intakes decreased over time in both male and female cohorts ( P preparation (5.1 vs 3.7 g/kg BW) than DNP competitors ( d = 1.02, 95% CI
Stochastic Blind Motion Deblurring
Xiao, Lei
2015-05-13
Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can therefore only be obtained with the help of prior information in the form of (often non-convex) regularization terms for both the intrinsic image and the kernel. While the best choice of image priors is still a topic of ongoing investigation, this research is made more complicated by the fact that historically each new prior requires the development of a custom optimization method. In this paper, we develop a stochastic optimization method for blind deconvolution. Since this stochastic solver does not require the explicit computation of the gradient of the objective function and uses only efficient local evaluation of the objective, new priors can be implemented and tested very quickly. We demonstrate that this framework, in combination with different image priors produces results with PSNR values that match or exceed the results obtained by much more complex state-of-the-art blind motion deblurring algorithms.
International Nuclear Information System (INIS)
Evans, T.E.; Moyer, R.A.; Watkins, J.G.
2005-01-01
Large sub-millisecond heat pulses due to Type-I ELMs have been eliminated reproducibly in DIII.D for periods approaching 7 energy confinement times with small dc currents driven in a simple magnetic perturbation coil. The current required to eliminate all but a few isolated Type-I ELM impulses during a coil pulse is less than 0.4% of plasma current. Based on vacuum magnetic field line modeling, the perturbation fields resonate strongly with plasma flux surfaces across most of the pedestal region (0.9 ≤ Ψ N ≤ 1.0) when q 95 = 3.7±0.2 creating small remnant magnetic islands surrounded by weakly stochastic field lines. The stored energy, β N , H-mode quality factor and global energy confinement time are unaltered. Although some isolated ELM-like events typically occur, long periods free of large Type-I ELMs (Δt > 4-6 τ E ) have been reproduced numerous times, on multiple experimental run days including cases matching the ITER scenario 2 flux surface shape. Since large Type-I ELM impulses represent a severe constraint on the survivability of the divertor target plates in future fusion devices such as ITER, a proven method of eliminating these impulses is critical for the development of tokamak reactors. Results presented in this paper indicate that non-axisymmetric edge magnetic perturbations could be a promising option for controlling ELMs in future tokamaks such as ITER. (author)
Hua, Changchun; Zhang, Liuliu; Guan, Xinping
2017-01-01
This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.
PC analysis of stochastic differential equations driven by Wiener noise
Le Maitre, Olivier
2015-03-01
A polynomial chaos (PC) analysis with stochastic expansion coefficients is proposed for stochastic differential equations driven by additive or multiplicative Wiener noise. It is shown that for this setting, a Galerkin formalism naturally leads to the definition of a hierarchy of stochastic differential equations governing the evolution of the PC modes. Under the mild assumption that the Wiener and uncertain parameters can be treated as independent random variables, it is also shown that the Galerkin formalism naturally separates parametric uncertainty and stochastic forcing dependences. This enables us to perform an orthogonal decomposition of the process variance, and consequently identify contributions arising from the uncertainty in parameters, the stochastic forcing, and a coupled term. Insight gained from this decomposition is illustrated in light of implementation to simplified linear and non-linear problems; the case of a stochastic bifurcation is also considered.
Elitism and Stochastic Dominance
Bazen, Stephen; Moyes, Patrick
2011-01-01
Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...
Stochastic Effects; Application in Nuclear Physics
International Nuclear Information System (INIS)
Mazonka, O.
2000-04-01
Stochastic effects in nuclear physics refer to the study of the dynamics of nuclear systems evolving under stochastic equations of motion. In this dissertation we restrict our attention to classical scattering models. We begin with introduction of the model of nuclear dynamics and deterministic equations of evolution. We apply a Langevin approach - an additional property of the model, which reflect the statistical nature of low energy nuclear behaviour. We than concentrate our attention on the problem of calculating tails of distribution functions, which actually is the problem of calculating probabilities of rare outcomes. Two general strategies are proposed. Result and discussion follow. Finally in the appendix we consider stochastic effects in nonequilibrium systems. A few exactly solvable models are presented. For one model we show explicitly that stochastic behaviour in a microscopic description can lead to ordered collective effects on the macroscopic scale. Two others are solved to confirm the predictions of the fluctuation theorem. (author)
Transport stochastic multi-dimensional media
International Nuclear Information System (INIS)
Haran, O.; Shvarts, D.
1996-01-01
Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors)
Transport stochastic multi-dimensional media
Energy Technology Data Exchange (ETDEWEB)
Haran, O; Shvarts, D [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev; Thiberger, R [Ben-Gurion Univ. of the Negev, Beersheba (Israel)
1996-12-01
Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors).
Singular stochastic differential equations
Cherny, Alexander S
2005-01-01
The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.
Characterizing economic trends by Bayesian stochastic model specifi cation search
Grassi, Stefano; Proietti, Tommaso
2010-01-01
We apply a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. We illustrate that the methodology can be quite successfully applied to discriminate between stochastic and deterministic trends. In particular, we formulate autoregressive models with stochastic trends components and decide on whether a specific feature of the series, i.e. the underlying level and/or the rate...
Trends in High Nature Value farmland studies: A systematic review
Directory of Open Access Journals (Sweden)
Benedetti Yanina
2017-12-01
Full Text Available Background. Since the High Nature Value (HNV concept was defined in the early 1990s, several studies on HNV farmland has been increasing over the past 30 years in Europe, highlighting the interest by scientific community of HNV farming systems supporting biodiversity conservation. The aim of this study was to evaluate the trends and main gaps on HNV farmland peer-reviewed publications in order to contribute to the effectiveness of future research in this field. Methods. Searches were conducted using the databases Web of SciencesTM and Scopus in order to identify only peer-reviewed articles on HNV farmland, published prior to July 2017. The inclusion and exclusion criteria were developed a priori. Data as year, country, type of document, subject area, taxa studied and biodiversity metrics assessed were extracted and explored in order to analyse the spatial and temporal distribution of the concept, including the main topics addressed in HNV farmland literature. Results. After screening 308 original articles, 90 were selected for this review. HNV farmland studies involved several disciplines, mainly biodiversity and conservation and environmental sciences and ecology. Most peer-reviewed articles focused on HNV farming were conducted in Spain, Italy, Ireland and Portugal. The main studied taxa were plants and birds. Taxonomic diversity was the biodiversity metric more often used to assess the biodiversity status on HNV farmland areas. A positive correlation was found between HNV farmland area and HNV farmland studies conducted in respective countries. Discussion. The HNV farmland research subject is a relative novel approach, and this systematic review provides a comprehensive overview about the main topics in the HNV farmland peer-reviewed literature contributing to highlight the main gaps and provide some considerations in order to assist the performance of HNV farming systems and conservation policies, addressed to sustain high levels of
STOCHASTIC CHARACTERISTICS AND MODELING OF RELATIVE ...
African Journals Online (AJOL)
Test
Results are highly accurate and promising for all models based on Lewis' criteria. ... hydrological cycle. Future increases in ... STOCHASTIC CHARACTERISTICS AND MODELING OF RELATIVE HUMIDITY OF OGUN BASIN, NIGERIA. 71 ...
The dynamics of stochastic processes
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas
In the present thesis the dynamics of stochastic processes is studied with a special attention to the semimartingale property. This is mainly motivated by the fact that semimartingales provide the class of the processes for which it is possible to define a reasonable stochastic calculus due...... to the Bichteler-Dellacherie Theorem. The semimartingale property of Gaussian processes is characterized in terms of their covariance function, spectral measure and spectral representation. In addition, representation and expansion of filtration results are provided as well. Special attention is given to moving...... average processes, and when the driving process is a Lévy or a chaos process the semimartingale property is characterized in the filtration spanned by the driving process and in the natural filtration when the latter is a Brownian motion. To obtain some of the above results an integrability of seminorm...
Thornburg, Christopher C; Britt, John R; Evans, Jason R; Akee, Rhone K; Whitt, James A; Trinh, Spencer K; Harris, Matthew J; Thompson, Jerell R; Ewing, Teresa L; Shipley, Suzanne M; Grothaus, Paul G; Newman, David J; Schneider, Joel P; Grkovic, Tanja; O'Keefe, Barry R
2018-06-13
The US National Cancer Institute's (NCI) Natural Product Repository is one of the world's largest, most diverse collections of natural products containing over 230,000 unique extracts derived from plant, marine, and microbial organisms that have been collected from biodiverse regions throughout the world. Importantly, this national resource is available to the research community for the screening of extracts and the isolation of bioactive natural products. However, despite the success of natural products in drug discovery, compatibility issues that make extracts challenging for liquid handling systems, extended timelines that complicate natural product-based drug discovery efforts and the presence of pan-assay interfering compounds have reduced enthusiasm for the high-throughput screening (HTS) of crude natural product extract libraries in targeted assay systems. To address these limitations, the NCI Program for Natural Product Discovery (NPNPD), a newly launched, national program to advance natural product discovery technologies and facilitate the discovery of structurally defined, validated lead molecules ready for translation will create a prefractionated library from over 125,000 natural product extracts with the aim of producing a publicly-accessible, HTS-amenable library of >1,000,000 fractions. This library, representing perhaps the largest accumulation of natural-product based fractions in the world, will be made available free of charge in 384-well plates for screening against all disease states in an effort to reinvigorate natural product-based drug discovery.
High-Fidelity Aerodynamic Shape Optimization for Natural Laminar Flow
Rashad, Ramy
To ensure the long-term sustainability of aviation, serious effort is underway to mitigate the escalating economic, environmental, and social concerns of the industry. Significant improvement to the energy efficiency of air transportation is required through the research and development of advanced and unconventional airframe and engine technologies. In the quest to reduce airframe drag, this thesis is concerned with the development and demonstration of an effective design tool for improving the aerodynamic efficiency of subsonic and transonic airfoils. The objective is to advance the state-of-the-art in high-fidelity aerodynamic shape optimization by incorporating and exploiting the phenomenon of laminar-turbulent transition in an efficient manner. A framework for the design and optimization of Natural Laminar Flow (NLF) airfoils is developed and demonstrated with transition prediction capable of accounting for the effects of Reynolds number, freestream turbulence intensity, Mach number, and pressure gradients. First, a two-dimensional Reynolds-averaged Navier-Stokes (RANS) flow solver has been extended to incorporate an iterative laminar-turbulent transition prediction methodology. The natural transition locations due to Tollmien-Schlichting instabilities are predicted using the simplified eN envelope method of Drela and Giles or, alternatively, the compressible form of the Arnal-Habiballah-Delcourt criterion. The boundary-layer properties are obtained directly from the Navier-Stokes flow solution, and the transition to turbulent flow is modeled using an intermittency function in conjunction with the Spalart-Allmaras turbulence model. The RANS solver is subsequently employed in a gradient-based sequential quadratic programming shape optimization framework. The laminar-turbulent transition criteria are tightly coupled into the objective and gradient evaluations. The gradients are obtained using a new augmented discrete-adjoint formulation for non-local transition
The stochastic chemomechanics of the F(1)-ATPase molecular motor.
Gaspard, P; Gerritsma, E
2007-08-21
We report a theoretical study of the F(1)-ATPase molecular rotary motor experimentally studied by R. Yasuda, H. Noji, M. Yoshida, K. Kinosita Jr., H. Itoh [Nature 410 (2001) 898]. The motor is modeled as a stochastic process for the angle of its shaft and the chemical state of its catalytic sites. The stochastic process is ruled by six coupled Fokker-Planck equations for the biased diffusion of the angle and the random jumps between the chemical states. The model reproduces the experimental observations that the motor proceeds by substeps and the rotation rate saturates at high concentrations of adenosine triphosphate or at low values of the friction coefficient. Moreover, predictions are made about the dependence of the rotation rate on temperature, and about the behavior of the F(1) motor under the effect of an external torque, especially, in the regime of synthesis of adenosine triphosphate.
The intrinsic stochasticity of near-integrable Hamiltonian systems
Energy Technology Data Exchange (ETDEWEB)
Krlin, L [Ceskoslovenska Akademie Ved, Prague (Czechoslovakia). Ustav Fyziky Plazmatu
1989-09-01
Under certain conditions, the dynamics of near-integrable Hamiltonian systems appears to be stochastic. This stochasticity (intrinsic stochasticity, or deterministic chaos) is closely related to the Kolmogorov-Arnold-Moser (KAM) theorem of the stability of near-integrable multiperiodic Hamiltonian systems. The effect of the intrinsic stochasticity attracts still growing attention both in theory and in various applications in contemporary physics. The paper discusses the relation of the intrinsic stochasticity to the modern ergodic theory and to the KAM theorem, and describes some numerical experiments on related astrophysical and high-temperature plasma problems. Some open questions are mentioned in conclusion. (author).
Stochastic particle acceleration and statistical closures
International Nuclear Information System (INIS)
Dimits, A.M.; Krommes, J.A.
1985-10-01
In a recent paper, Maasjost and Elsasser (ME) concluded, from the results of numerical experiments and heuristic arguments, that the Bourret and the direct-interaction approximation (DIA) are ''of no use in connection with the stochastic acceleration problem'' because (1) their predictions were equivalent to that of the simpler Fokker-Planck (FP) theory, and (2) either all or none of the closures were in good agreement with the data. Here some analytically tractable cases are studied and used to test the accuracy of these closures. The cause of the discrepancy (2) is found to be the highly non-Gaussian nature of the force used by ME, a point not stressed by them. For the case where the force is a position-independent Ornstein-Uhlenbeck (i.e., Gaussian) process, an effective Kubo number K can be defined. For K << 1 an FP description is adequate, and conclusion (1) of ME follows; however, for K greater than or equal to 1 the DIA behaves much better qualitatively than the other two closures. For the non-Gaussian stochastic force used by ME, all common approximations fail, in agreement with (2)
An Approach to Stochastic Peridynamic Theory.
Energy Technology Data Exchange (ETDEWEB)
Demmie, Paul N.
2018-04-01
In many material systems, man-made or natural, we have an incomplete knowledge of geometric or material properties, which leads to uncertainty in predicting their performance under dynamic loading. Given the uncertainty and a high degree of spatial variability in properties of materials subjected to impact, a stochastic theory of continuum mechanics would be useful for modeling dynamic response of such systems. Peridynamic theory is such a theory. It is formulated as an integro- differential equation that does not employ spatial derivatives, and provides for a consistent formulation of both deformation and failure of materials. We discuss an approach to stochastic peridynamic theory and illustrate the formulation with examples of impact loading of geological materials with uncorrelated or correlated material properties. We examine wave propagation and damage to the material. The most salient feature is the absence of spallation, referred to as disorder toughness, which generalizes similar results from earlier quasi-static damage mechanics. Acknowledgements This research was made possible by the support from DTRA grant HDTRA1-08-10-BRCWM. I thank Dr. Martin Ostoja-Starzewski for introducing me to the mechanics of random materials and collaborating with me throughout and after this DTRA project.
Perception of stochastically undersampled sound waveforms: A model of auditory deafferentation
Directory of Open Access Journals (Sweden)
Enrique A Lopez-Poveda
2013-07-01
Full Text Available 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.
Perception of stochastically undersampled sound waveforms: a model of auditory deafferentation
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 analytic regularization
International Nuclear Information System (INIS)
Alfaro, J.
1984-07-01
Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)
Instantaneous stochastic perturbation theory
International Nuclear Information System (INIS)
Lüscher, Martin
2015-01-01
A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.
Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.
2017-01-01
In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of
Meyer, Joerg M.
2018-01-01
The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.
High recombination rate in natural populations of Plasmodium falciparum
Conway, D. J.; Roper, C.; Oduola, A. M.; Arnot, D. E.; Kremsner, P. G.; Grobusch, M. P.; Curtis, C. F.; Greenwood, B. M.
1999-01-01
Malaria parasites are sexually reproducing protozoa, although the extent of effective meiotic recombination in natural populations has been debated. If meiotic recombination occurs frequently, compared with point mutation and mitotic rearrangement, linkage disequilibrium between polymorphic sites is
Multiscale Hy3S: Hybrid stochastic simulation for supercomputers
Directory of Open Access Journals (Sweden)
Kaznessis Yiannis N
2006-02-01
Full Text Available Abstract Background Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. Results Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users
Stochastic quantization and gravity
International Nuclear Information System (INIS)
Rumpf, H.
1984-01-01
We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)
Greenwood, Priscilla E
2016-01-01
This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...
Introduction to stochastic analysis integrals and differential equations
Mackevicius, Vigirdas
2013-01-01
This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide audience, from students of mathematics to practitioners in biology, chemistry, physics, and finances. The presentation is based on the naïve stochastic integration, rather than on abstract theories of measure and stochastic processes. The proofs are rather simple for practitioners and, at the same time, rather rigorous for mathematicians. Detailed application examples in natural sciences and finance are presented. Much attention is paid to simulation diffusion pro
Stochastic resonance during a polymer translocation process
International Nuclear Information System (INIS)
Mondal, Debasish; Muthukumar, M.
2016-01-01
We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.
Stochastic inflation and nonlinear gravity
International Nuclear Information System (INIS)
Salopek, D.S.; Bond, J.R.
1991-01-01
We show how nonlinear effects of the metric and scalar fields may be included in stochastic inflation. Our formalism can be applied to non-Gaussian fluctuation models for galaxy formation. Fluctuations with wavelengths larger than the horizon length are governed by a network of Langevin equations for the physical fields. Stochastic noise terms arise from quantum fluctuations that are assumed to become classical at horizon crossing and that then contribute to the background. Using Hamilton-Jacobi methods, we solve the Arnowitt-Deser-Misner constraint equations which allows us to separate the growing modes from the decaying ones in the drift phase following each stochastic impulse. We argue that the most reasonable choice of time hypersurfaces for the Langevin system during inflation is T=ln(Ha), where H and a are the local values of the Hubble parameter and the scale factor, since T is the natural time for evolving the short-wavelength scalar field fluctuations in an inhomogeneous background
Directory of Open Access Journals (Sweden)
Sharon Baruch-Mordo
Full Text Available The rapid expansion of global urban development is increasing opportunities for wildlife to forage and become dependent on anthropogenic resources. Wildlife using urban areas are often perceived dichotomously as urban or not, with some individuals removed in the belief that dependency on anthropogenic resources is irreversible and can lead to increased human-wildlife conflict. For American black bears (Ursus americanus, little is known about the degree of bear urbanization and its ecological mechanisms to guide the management of human-bear conflicts. Using 6 years of GPS location and activity data from bears in Aspen, Colorado, USA, we evaluated the degree of bear urbanization and the factors that best explained its variations. We estimated space use, activity patterns, survival, and reproduction and modeled their relationship with ecological covariates related to bear characteristics and natural food availability. Space use and activity patterns were dependent on natural food availability (good or poor food years, where bears used higher human density areas and became more nocturnal in poor food years. Patterns were reversible, i.e., individuals using urban areas in poor food years used wildland areas in subsequent good food years. While reproductive output was similar across years, survival was lower in poor food years when bears used urban areas to a greater extent. Our findings suggest that bear use of urban areas is reversible and fluctuates with the availability of natural food resources, and that removal of urban individuals in times of food failures has the potential to negatively affect bear populations. Given that under current predictions urbanization is expected to increase by 11% across American black bear range, and that natural food failure years are expected to increase in frequency with global climate change, alternative methods of reducing urban human-bear conflict are required if the goal is to prevent urban areas from
Baruch-Mordo, Sharon; Wilson, Kenneth R; Lewis, David L; Broderick, John; Mao, Julie S; Breck, Stewart W
2014-01-01
The rapid expansion of global urban development is increasing opportunities for wildlife to forage and become dependent on anthropogenic resources. Wildlife using urban areas are often perceived dichotomously as urban or not, with some individuals removed in the belief that dependency on anthropogenic resources is irreversible and can lead to increased human-wildlife conflict. For American black bears (Ursus americanus), little is known about the degree of bear urbanization and its ecological mechanisms to guide the management of human-bear conflicts. Using 6 years of GPS location and activity data from bears in Aspen, Colorado, USA, we evaluated the degree of bear urbanization and the factors that best explained its variations. We estimated space use, activity patterns, survival, and reproduction and modeled their relationship with ecological covariates related to bear characteristics and natural food availability. Space use and activity patterns were dependent on natural food availability (good or poor food years), where bears used higher human density areas and became more nocturnal in poor food years. Patterns were reversible, i.e., individuals using urban areas in poor food years used wildland areas in subsequent good food years. While reproductive output was similar across years, survival was lower in poor food years when bears used urban areas to a greater extent. Our findings suggest that bear use of urban areas is reversible and fluctuates with the availability of natural food resources, and that removal of urban individuals in times of food failures has the potential to negatively affect bear populations. Given that under current predictions urbanization is expected to increase by 11% across American black bear range, and that natural food failure years are expected to increase in frequency with global climate change, alternative methods of reducing urban human-bear conflict are required if the goal is to prevent urban areas from becoming population sinks.
Baruch-Mordo, Sharon; Wilson, Kenneth R.; Lewis, David L.; Broderick, John; Mao, Julie S.; Breck, Stewart W.
2014-01-01
The rapid expansion of global urban development is increasing opportunities for wildlife to forage and become dependent on anthropogenic resources. Wildlife using urban areas are often perceived dichotomously as urban or not, with some individuals removed in the belief that dependency on anthropogenic resources is irreversible and can lead to increased human-wildlife conflict. For American black bears (Ursus americanus), little is known about the degree of bear urbanization and its ecological mechanisms to guide the management of human-bear conflicts. Using 6 years of GPS location and activity data from bears in Aspen, Colorado, USA, we evaluated the degree of bear urbanization and the factors that best explained its variations. We estimated space use, activity patterns, survival, and reproduction and modeled their relationship with ecological covariates related to bear characteristics and natural food availability. Space use and activity patterns were dependent on natural food availability (good or poor food years), where bears used higher human density areas and became more nocturnal in poor food years. Patterns were reversible, i.e., individuals using urban areas in poor food years used wildland areas in subsequent good food years. While reproductive output was similar across years, survival was lower in poor food years when bears used urban areas to a greater extent. Our findings suggest that bear use of urban areas is reversible and fluctuates with the availability of natural food resources, and that removal of urban individuals in times of food failures has the potential to negatively affect bear populations. Given that under current predictions urbanization is expected to increase by 11% across American black bear range, and that natural food failure years are expected to increase in frequency with global climate change, alternative methods of reducing urban human-bear conflict are required if the goal is to prevent urban areas from becoming population sinks
High concentrations of natural rubber latex allergens in gloves used ...
African Journals Online (AJOL)
Introduction. Gloves made of natural rubber latex (NRL) are commonly used by healthcare workers because of their good qualities. However, allergic reactions to latex allergens are still commonly reported. Objective. To measure the concentrations of Hev b 1, Hev b 3, Hev b 5 and Hev b 6.02 allergens in gloves used by a ...
Human genetic studies in areas of high natural radiation
International Nuclear Information System (INIS)
Freire-Maia, A.; Krieger, H.
1978-01-01
Data have been obtained by a genetic-epidemiological survey of a population living in the State of Espirito Santo (Brazil), and subjected to mean levels of natural radiation, per locality, ranging from 7 to 133 μrad/hr. Multiple regression models have been applied to the data, and the results showed no detectable effect of natural radiation on the sex ratio at birth, on the occurrence of congenital anomalies, and on the numbers of pregnancy terminations, stillbirths, livebirths, and post-infant mortality in the children, as well as fecundity and fertility of the couples (these observations contradict some data from the literature, based on official records and without analyses of the concomitant effects of other variables). However, nonsignificant results cannot be considered as disproving harmful effects of natural radiation on mortality and morbidity. These results may simply mean that other causes of mortality and morbidity are so important, under the conditions of the study, that the contribution of low-level, chronic natural radiation is made negligible. (author)
Stochastic background of atmospheric cascades
International Nuclear Information System (INIS)
Wilk, G.; Wlodarczyk, Z.
1993-01-01
Fluctuations in the atmospheric cascades developing during the propagation of very high energy cosmic rays through the atmosphere are investigated using stochastic branching model of pure birth process with immigration. In particular, we show that the multiplicity distributions of secondaries emerging from gamma families are much narrower than those resulting from hadronic families. We argue that the strong intermittent like behaviour found recently in atmospheric families results from the fluctuations in the cascades themselves and are insensitive to the details of elementary interactions
Micronuclei frequency in albino rats exposed to high natural radiation
International Nuclear Information System (INIS)
Aneesh, D.; Godwin Wesley, S.
2013-01-01
Genotoxicity and DNA damage endpoints are used to evaluate results in the context of cell survival. Genotoxicity in mammalian cells is monitored mostly by using cytokinesis-block micronucleus (CBMN) assay. The score of micronuclei (MN) in peripheral blood lymphocytes can be used as a biomarker and also as a bio-dosimeter of radiation exposure. In the present study the effect of natural radiation on albino rats has been investigated, to find out if there is any increase in MN frequency in peripheral blood lymphocytes. Animals at the age of 2-3 weeks were exposed to natural radiation, at the dose of 10.38 μGyh -1 for a period of 6 months. A parallel control set was also maintained (0.12 μGy h -1 '). Blood samples were collected from both test (exposed to natural radiation) and control rats. Lymphocyte culture was done following 'microculture techniques' for 72 h. Cytochalasin B, at a concentration of 6.0 μg/ml, was added to the lymphocyte cultures at 44 h to block cytokinesis. The frequency of MN was evaluated by scoring a total of 1000 binucleated (BN) cells from one slide. The frequency of MN among the rats exposed to natural radiation was found to be 1.83±0.05 per 1000 BN cells and in the control it was 1.82±0.07 per 1000 BN cells. No statistically significant difference in the MN frequencies of exposed and control groups (p>0.05) was seen. The lower MN frequency in natural radiation exposed rats could be an indication of adaptive response. (author)
Sequential stochastic optimization
Cairoli, Renzo
1996-01-01
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet
Remarks on stochastic acceleration
International Nuclear Information System (INIS)
Graeff, P.
1982-12-01
Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)
Bacterial natural transformation by highly fragmented and damaged DNA
DEFF Research Database (Denmark)
Overballe-Petersen, Søren; Harms, Klaus; Orlando, Ludovic Antoine Alexandre
2013-01-01
for microbes, but not as potential substrate for bacterial evolution. Here, we show that fragmented DNA molecules (≥20 bp) that additionally may contain abasic sites, cross-links, or miscoding lesions are acquired by the environmental bacterium Acinetobacter baylyi through natural transformation. With uptake......DNA molecules are continuously released through decomposition of organic matter and are ubiquitous in most environments. Such DNA becomes fragmented and damaged (often DNA is recognized as nutrient source...... of DNA from a 43,000-y-old woolly mammoth bone, we further demonstrate that such natural transformation events include ancient DNA molecules. We find that the DNA recombination is RecA recombinase independent and is directly linked to DNA replication. We show that the adjacent nucleotide variations...
FERN - a Java framework for stochastic simulation and evaluation of reaction networks.
Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf
2008-08-29
Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand-alone program and within new
Human genetics studies in areas of high natural radiation, 7
International Nuclear Information System (INIS)
Freire-Maia, A.
1975-01-01
Two methods to estimate the inbreeding load, employed in our analysis, are reviewed. Besides the total population, a sample constituted of individuals with no alien ancestral is also analysed. The measurements by genetic load models show any clear effect of natural radioactivity (especially for abortions, pre-natal mortality, anomalies, and abnormalities in general). The results on stillbirths and post-natal and total mortalities are discussed and it is concluded that uncontrolled concomitant variables (if not chance alone) cause the differences [pt
Stochastic gene expression in Arabidopsis thaliana.
Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin
2017-12-14
Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.
Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales
Energy Technology Data Exchange (ETDEWEB)
Xiu, Dongbin [Univ. of Utah, Salt Lake City, UT (United States)
2017-03-03
The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.
Stochastic time scale for the Universe
International Nuclear Information System (INIS)
Szydlowski, M.; Golda, Z.
1986-01-01
An intrinsic time scale is naturally defined within stochastic gradient dynamical systems. It should be interpreted as a ''relaxation time'' to a local potential minimum after the system has been randomly perturbed. It is shown that for a flat Friedman-like cosmological model this time scale is of order of the age of the Universe. 7 refs. (author)
Stochastic cooling in muon colliders
International Nuclear Information System (INIS)
Barletta, W.A.; Sessler, A.M.
1993-09-01
Analysis of muon production techniques for high energy colliders indicates the need for rapid and effective beam cooling in order that one achieve luminosities > 10 30 cm -2 s -1 as required for high energy physics experiments. This paper considers stochastic cooling to increase the phase space density of the muons in the collider. Even at muon energies greater than 100 GeV, the number of muons per bunch must be limited to ∼10 3 for the cooling rate to be less than the muon lifetime. With such a small number of muons per bunch, the final beam emittance implied by the luminosity requirement is well below the thermodynamic limit for beam electronics at practical temperatures. Rapid bunch stacking after the cooling process can raise the number of muons per bunch to a level consistent with both the luminosity goals and with practical temperatures for the stochastic cooling electronics. A major advantage of our stochastic cooling/stacking scheme over scenarios that employ only ionization cooling is that the power on the production target can be reduced below 1 MW
Stochastic processes inference theory
Rao, Malempati M
2014-01-01
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Introduction to stochastic calculus
Karandikar, Rajeeva L
2018-01-01
This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...
Doberkat, Ernst-Erich
2009-01-01
Combining coalgebraic reasoning, stochastic systems and logic, this volume presents the principles of coalgebraic logic from a categorical perspective. Modal logics are also discussed, including probabilistic interpretations and an analysis of Kripke models.
Energy losses (gains) of massive coloured particles in stochastic colour medium
International Nuclear Information System (INIS)
Leonidov, A.; Rossijskaya Akademiya Nauk, Moscow
1995-01-01
The propagation of massive coloured particles in stochastic background chromoelectric field is studied using the semiclassical equations of motion. Depending on the nature of the stochastic background we obtain the formulae for the energy losses of heavy coloured projectile in nonperturbative hadronic medium and for the energy gains in the stochastic field present, e.g., in the turbulent plasma. The result appears to be significantly dependent on the form of the correlation function of stochastic external field. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Evans, T.E. [General Atomics, P.O. Box 85608, San Diego, CA 92186-5608 (United States)]. E-mail: evans@fusion.gat.com; Moyer, R.A. [University of California at San Diego, La Jolla, CA 92093-0417 (United States); Watkins, J.G. [Sandia National Laboratories, Albuquerque, NM 87185-1129 (United States); Thomas, P.R. [Association Euratom-CEA, CEA Cadarache, F-13108, St. Paul-lez-Durance (France); Osborne, T.H. [General Atomics, P.O. Box 85608, San Diego, CA 92186-5608 (United States); Boedo, J.A. [University of California at San Diego, La Jolla, CA 92093-0417 (United States); Fenstermacher, M.E. [Lawrence Livermore National Laborabory, Livermore, CA 94550 (United States); Finken, K.H. [Forschungszentrum Juelich, Institute for Plasma Physics, D52425 Juelich (Germany); Groebner, R.J. [General Atomics, P.O. Box 85608, San Diego, CA 92186-5608 (United States); Groth, M. [Lawrence Livermore National Laborabory, Livermore, CA 94550 (United States); Harris, J. [Australian National University, Canberra (Australia); Jackson, G.L. [General Atomics, P.O. Box 85608, San Diego, CA 92186-5608 (United States); Haye, R.J. La [General Atomics, P.O. Box 85608, San Diego, CA 92186-5608 (United States); Lasnier, C.J. [Lawrence Livermore National Laborabory, Livermore, CA 94550 (United States); Schaffer, M.J. [General Atomics, P.O. Box 85608, San Diego, CA 92186-5608 (United States); Wang, G. [University of California, Los Angeles, California (United States); Zeng, L. [University of California, Los Angeles, California (United States)
2005-03-01
Large 70 Hz Type-I edge localized modes (ELMs) are converted into small 130 Hz oscillations using edge resonant magnetic perturbations (RMPs) from a coil with currents 0.4% I {sub p} in double null DIII-D plasmas. When the RMP is properly phased with respect to the background field errors, all but a few isolated ELM-like events are suppressed. The impulsive pedestal energy loss {delta}E {sub ELM}/{delta}t {sup 1/2} to the scrape-of layer is reduced a factor of 20 relative to the Type-I ELMs and the core confinement is unaffected by the perturbation field. Significant changes in the properties of the ELMs are also observed when edge RMPs are applied to lower single null plasmas but the nature of these changes are much more complex. Both lower single null and double null plasmas are being studied to determine how ELM control techniques based on the application of edge RMPs can be expected to scale to future devices such as ITER.
Approximating Preemptive Stochastic Scheduling
Megow Nicole; Vredeveld Tjark
2009-01-01
We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...
The stochastic goodwill problem
Marinelli, Carlo
2003-01-01
Stochastic control problems related to optimal advertising under uncertainty are considered. In particular, we determine the optimal strategies for the problem of maximizing the utility of goodwill at launch time and minimizing the disutility of a stream of advertising costs that extends until the launch time for some classes of stochastic perturbations of the classical Nerlove-Arrow dynamics. We also consider some generalizations such as problems with constrained budget and with discretionar...
International Nuclear Information System (INIS)
Hueffel, H.
1990-01-01
After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)
AESS: Accelerated Exact Stochastic Simulation
Jenkins, David D.; Peterson, Gregory D.
2011-12-01
The Stochastic Simulation Algorithm (SSA) developed by Gillespie provides a powerful mechanism for exploring the behavior of chemical systems with small species populations or with important noise contributions. Gene circuit simulations for systems biology commonly employ the SSA method, as do ecological applications. This algorithm tends to be computationally expensive, so researchers seek an efficient implementation of SSA. In this program package, the Accelerated Exact Stochastic Simulation Algorithm (AESS) contains optimized implementations of Gillespie's SSA that improve the performance of individual simulation runs or ensembles of simulations used for sweeping parameters or to provide statistically significant results. Program summaryProgram title: AESS Catalogue identifier: AEJW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: University of Tennessee copyright agreement No. of lines in distributed program, including test data, etc.: 10 861 No. of bytes in distributed program, including test data, etc.: 394 631 Distribution format: tar.gz Programming language: C for processors, CUDA for NVIDIA GPUs Computer: Developed and tested on various x86 computers and NVIDIA C1060 Tesla and GTX 480 Fermi GPUs. The system targets x86 workstations, optionally with multicore processors or NVIDIA GPUs as accelerators. Operating system: Tested under Ubuntu Linux OS and CentOS 5.5 Linux OS Classification: 3, 16.12 Nature of problem: Simulation of chemical systems, particularly with low species populations, can be accurately performed using Gillespie's method of stochastic simulation. Numerous variations on the original stochastic simulation algorithm have been developed, including approaches that produce results with statistics that exactly match the chemical master equation (CME) as well as other approaches that approximate the CME. Solution
Stochastic lag time in nucleated linear self-assembly
Energy Technology Data Exchange (ETDEWEB)
Tiwari, Nitin S. [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Schoot, Paul van der [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Institute for Theoretical Physics, Utrecht University, Leuvenlaan 4, 3584 CE Utrecht (Netherlands)
2016-06-21
Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerization reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerization commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.
Extinction in neutrally stable stochastic Lotka-Volterra models
Dobrinevski, Alexander; Frey, Erwin
2012-05-01
Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.
Electricity price modeling with stochastic time change
International Nuclear Information System (INIS)
Borovkova, Svetlana; Schmeck, Maren Diane
2017-01-01
In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.
High folate production by naturally occurring Lactobacillus sp. with ...
African Journals Online (AJOL)
African Journal of Biotechnology. Journal Home ... Milk products are good sources of such vitamins which are produced by probiotics. In order to ... Therefore, two new strains with an ability of high folate production were isolated and identified.
High folate production by naturally occurring Lactobacillus sp. with ...
African Journals Online (AJOL)
USER
2010-08-16
Aug 16, 2010 ... high folate production, isolation and identification of Lactobacilli in traditional fermented milk ... mended for pregnant women (Van Der Put et al., 2001; ...... utilization of folic acid and vitamin B12 by lactic cultures in skim milk.
International Nuclear Information System (INIS)
Nagl, Stephan; Fuersch, Michaela; Lindenberger, Dietmar
2012-01-01
Renewable energies are meant to produce a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions and therefore weather characteristics must be considered when optimizing the future electricity mix. In this article we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include the overestimation of fluctuating renewables and underestimation of total system costs compared to deterministic investment and dispatch models. Furthermore, solar technologies are - relative to wind turbines - underestimated when neglecting negative correlations between wind speeds and solar radiation.
Symmetries of th-Order Approximate Stochastic Ordinary Differential Equations
Fredericks, E.; Mahomed, F. M.
2012-01-01
Symmetries of $n$ th-order approximate stochastic ordinary differential equations (SODEs) are studied. The determining equations of these SODEs are derived in an Itô calculus context. These determining equations are not stochastic in nature. SODEs are normally used to model nature (e.g., earthquakes) or for testing the safety and reliability of models in construction engineering when looking at the impact of random perturbations.
Directory of Open Access Journals (Sweden)
Ron Karl Hoeke
2015-09-01
Full Text Available Wind-wave contributions to tropical cyclone (TC-induced extreme sea levels are known to be significant in areas with narrow littoral zones, particularly at oceanic islands. Despite this, little information exists in many of these locations to assess the likelihood of inundation, the relative contribution of wind and wave setup to this inundation, and how it may change with sea level rise (SLR, particularly at scales relevant to coastal infrastructure. In this study, we explore TC-induced extreme sea levels at spatial scales on the order of tens of meters at Apia, the capitol of Samoa, a nation in the tropical South Pacific with typical high-island fringing reef morphology. Ensembles of stochastically generated TCs (based on historical information are combined with numerical simulations of wind waves, storm-surge, and wave setup to develop high-resolution statistical information on extreme sea levels and local contributions of wind setup and wave setup. The results indicate that storm track and local morphological details lead to local differences in extreme sea levels on the order of 1 m at spatial scales of less than 1 km. Wave setup is the overall largest contributor at most locations; however, wind setup may exceed wave setup in some sheltered bays. When an arbitrary SLR scenario (+1 m is introduced, overall extreme sea levels are found to modestly decrease relative to SLR, but wave energy near the shoreline greatly increases, consistent with a number of other recent studies. These differences have implications for coastal adaptation strategies.
Laboratory Evidence for Stochastic Plasma-Wave Growth
International Nuclear Information System (INIS)
Austin, D. R.; Hole, M. J.; Robinson, P. A.; Cairns, Iver H.; Dallaqua, R.
2007-01-01
The first laboratory confirmation of stochastic growth theory is reported. Floating potential fluctuations are measured in a vacuum arc centrifuge using a Langmuir probe. Statistical analysis of the energy density reveals a lognormal distribution over roughly 2 orders of magnitude, with a high-field nonlinear cutoff whose spatial dependence is consistent with the predicted eigenmode profile. These results are consistent with stochastic growth and nonlinear saturation of a spatially extended eigenmode, the first evidence for stochastic growth of an extended structure
Stochastic partial differential equations an introduction
Liu, Wei
2015-01-01
This book provides an introduction to the theory of stochastic partial differential equations (SPDEs) of evolutionary type. SPDEs are one of the main research directions in probability theory with several wide ranging applications. Many types of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. The theory of SPDEs is based both on the theory of deterministic partial differential equations, as well as on modern stochastic analysis. Whilst this volume mainly follows the ‘variational approach’, it also contains a short account on the ‘semigroup (or mild solution) approach’. In particular, the volume contains a complete presentation of the main existence and uniqueness results in the case of locally monotone coefficients. Various types of generalized coercivity conditions are shown to guarantee non-explosion, but also a systematic approach to treat SPDEs with explosion in finite time is developed. It is, so far, the only book where the latter and t...
The nature of temper brittleness of high-chromium ferrite
Energy Technology Data Exchange (ETDEWEB)
Sarrak, V.I.; Suvorova, S.O.; Golovin, I.S.; Mishin, V.M.; Kislyuk, I.V. [Central Scientific-Research Institute for Ferrous Metallurgy, Moscow (Russian Federation)
1995-03-01
The reasons for development of {open_quotes}475{degrees}C brittleness{close_quotes} of high-chromium ferritic steels are considered from the standpoint of fracture mechanics. It is shown that the general rise in the curve of temperature-dependent local flow stress has the decisive influence on the position of the ductile-to-brittle transformation temperature and the increase in it as the result of a hold at temperatures of development of brittleness. The established effect is related to the change in the parameters determining dislocation mobility, that is, the activation energy of dislocation movement in high-chromium ferrite and the resistance to microplastic deformation, both caused by processes of separation into layers of high-chromium ferrite and decomposition of the interstitial solid solution.
Stochastic catastrophe theory and instabilities in plasma turbulence
International Nuclear Information System (INIS)
Rajkovic, Milan; Skoric, Milos
2009-01-01
Full text: A Langevin equation (LE) describing evolution of turbulence amplitude in plasma is analyzed from the aspect of stochastic catastrophe theory (SCT) so that turbulent plasma is considered as a stochastic gradient system. According to SCT the dynamics of the system is completely determined by the stochastic potential function and the maximum likelihood estimates of stable and unstable equilibria are associated with the modes and anti-modes, respectively, of the system's stationary probability density function. First order phase transitions occur at degenerate equilibrium points and the potential function at these points may be represented in a generic way. Since the diffusion function of plasma LE is not constant the probability density function (pdf) is not a reliable estimator of the number of stable states. We show that the generalized pdf represented as the product of the stationary pdf and the diffusion function is a reliable estimator of the stable states and that it can be evaluated from the zero mean crossing analysis of plasma turbulence signal. Stochastic bifurcations, and particularly the sudden (catastrophic) ones, are recognized from the pdf's obtained by the zero crossing analysis and we illustrate the applications of SCT in plasma turbulence on data obtained from the MAST (Mega Ampere Spherical Tokamak) for low (L), high (H) and unstable dithering (L/H) confinement regimes. The relationship of the transformation invariant zero-crossing function and SCT is shown to provide important information about the nature of edge localized modes (ELMs) and L-H transition. Finally we show that ELMs occur as a result of catastrophic (hard) bifurcations ruling out the self-organized criticality scenario for their origin. (author)
Stochastic incompleteness of quantum mechanics
International Nuclear Information System (INIS)
Suppes, P.; Zanotti, M.
1976-01-01
This article brings out in as conceptually clear terms as possible what seems to be a major incompleteness in the probability theory of particles offered by classical quantum mechanics. The exact nature of this incompleteness is illustrated by consideration of some simple quantum-mechanical examples. In addition, these examples are contrasted with the fundamental assumptions of Brownian motion in classical physics on the one hand, and with a controversey of a deecade ago in mathematical physchology. The central claim is that clasical quantum mechanics is radically incomplete in its probabilistic account of the motion of particles. In the last part of the article the time-dependent joint distribution of position and momentum of the linear harmonic oscillator is derived, and it is shown how the apparently physically paradoxical statistical independence of position and momentum has a natural explanation. The explanation is given within the framework of the non-quantum-mechanical stochastic theory constructed for such oscillators. (Auth.)
Pedretti, Daniele; Masetti, Marco; Beretta, Giovanni Pietro
2017-10-01
The expected long-term efficiency of vertical cutoff walls coupled to pump-and-treat technologies to contain solute plumes in highly heterogeneous aquifers was analyzed. A well-characterized case study in Italy, with a hydrogeological database of 471 results from hydraulic tests performed on the aquifer and the surrounding 2-km-long cement-bentonite (CB) walls, was used to build a conceptual model and assess a representative remediation site adopting coupled technologies. In the studied area, the aquifer hydraulic conductivity Ka [m/d] is log-normally distributed with mean E (Ya) = 0.32 , variance σYa2 = 6.36 (Ya = lnKa) and spatial correlation well described by an exponential isotropic variogram with integral scale less than 1/12 the domain size. The hardened CB wall's hydraulic conductivity, Kw [m/d], displayed strong scaling effects and a lognormal distribution with mean E (Yw) = - 3.43 and σYw2 = 0.53 (Yw =log10Kw). No spatial correlation of Kw was detected. Using this information, conservative transport was simulated across a CB wall in spatially correlated 1-D random Ya fields within a numerical Monte Carlo framework. Multiple scenarios representing different Kw values were tested. A continuous solute source with known concentration and deterministic drains' discharge rates were assumed. The efficiency of the confining system was measured by the probability of exceedance of concentration over a threshold (C∗) at a control section 10 years after the initial solute release. It was found that the stronger the aquifer heterogeneity, the higher the expected efficiency of the confinement system and the lower the likelihood of aquifer pollution. This behavior can be explained because, for the analyzed aquifer conditions, a lower Ka generates more pronounced drawdown in the water table in the proximity of the drain and consequently a higher advective flux towards the confined area, which counteracts diffusive fluxes across the walls. Thus, a higher σYa2 results
Directory of Open Access Journals (Sweden)
Elías Gómez Macías
2006-01-01
Full Text Available Partiendo de óxido de magnesio comercial se preparó una suspensión acuosa, la cual se secó y calcinó para conferirle estabilidad térmica. El material, tanto fresco como usado, se caracterizó mediante DRX, área superficial BET y SEM-EPMA. El catalizador mostró una matriz de MgO tipo periclasa con CaO en la superficie. Las pruebas de actividad catalítica se efectuaron en lecho fijo empacado con partículas obtenidas mediante prensado, trituración y clasificación del material. El flujo de reactivos consistió en mezclas gas natural-aire por debajo del límite inferior de inflamabilidad. Para diferentes flujos y temperaturas de entrada de la mezcla reactiva, se midieron las concentraciones de CH4, CO2 y CO en los gases de combustión con un analizador de gases tipo infrarrojo no dispersivo (NDIR. Para alcanzar conversión total de metano se requirió aumentar la temperatura de entrada al lecho a medida que se incrementó el flujo de gases reaccionantes. Los resultados obtenidos permiten desarrollar un sistema de combustión catalítica de bajo costo con un material térmicamente estable, que promueva la alta eficiencia en la combustión de gas natural y elimine los problemas de estabilidad, seguridad y de impacto ambiental negativo inherentes a los procesos de combustión térmica convencional.
International Nuclear Information System (INIS)
Haran, O.; Shvarts, D.; Thieberger, R.
1998-01-01
Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption
Energy Technology Data Exchange (ETDEWEB)
Dulikravich, George S.; Sikka, Vinod K.; Muralidharan, G.
2006-06-01
The goal of this project was to adapt and use an advanced semi-stochastic algorithm for constrained multiobjective optimization and combine it with experimental testing and verification to determine optimum concentrations of alloying elements in heat-resistant and corrosion-resistant H-series stainless steel alloys that will simultaneously maximize a number of alloy's mechanical and corrosion properties.
Smits, N.; Finkelman, M.D.; Kelderman, H.
2016-01-01
In clinical assessment, efficient screeners are needed to ensure low respondent burden. In this article, Stochastic Curtailment (SC), a method for efficient computerized testing for classification into two classes for observable outcomes, was extended to three classes. In a post hoc simulation study
The appreciation of stochastic motion in particle accelerators
International Nuclear Information System (INIS)
Symon, Keith; Sessler, Andrew
2003-01-01
A description is given of the analytic and numerical work, performed from July 1955 through August 1956, so as to develop, and then study, the process of making intense proton beams, suitable for colliding beams. It is shown how this investigation led, in a most natural way, to the realization that stochasticity can arise in a simple Hamiltonian system. Furthermore, the criterion for the onset of stochasticity was understood, and carefully studied, in two different situations. The first situation was the proposed (and subsequently used) ''stacking process'' for developing an intense beam, where stochasticity occurs as additional particles are added to the intense circulating beam. The second situation occurs when one seeks to develop ''stochastic accelerators'' in which particles are accelerated (continuously) by a collection of radio frequency systems. It was in the last connection that the well-known criterion for stochasticity, resonance overlap, was obtained
Stochastic samples versus vacuum expectation values in cosmology
International Nuclear Information System (INIS)
Tsamis, N.C.; Tzetzias, Aggelos; Woodard, R.P.
2010-01-01
Particle theorists typically use expectation values to study the quantum back-reaction on inflation, whereas many cosmologists stress the stochastic nature of the process. While expectation values certainly give misleading results for some things, such as the stress tensor, we argue that operators exist for which there is no essential problem. We quantify this by examining the stochastic properties of a noninteracting, massless, minimally coupled scalar on a locally de Sitter background. The square of the stochastic realization of this field seems to provide an example of great relevance for which expectation values are not misleading. We also examine the frequently expressed concern that significant back-reaction from expectation values necessarily implies large stochastic fluctuations between nearby spatial points. Rather than viewing the stochastic formalism in opposition to expectation values, we argue that it provides a marvelously simple way of capturing the leading infrared logarithm corrections to the latter, as advocated by Starobinsky
Stochastic equations for complex systems theoretical and computational topics
Bessaih, Hakima
2015-01-01
Mathematical analyses and computational predictions of the behavior of complex systems are needed to effectively deal with weather and climate predictions, for example, and the optimal design of technical processes. Given the random nature of such systems and the recognized relevance of randomness, the equations used to describe such systems usually need to involve stochastics. The basic goal of this book is to introduce the mathematics and application of stochastic equations used for the modeling of complex systems. A first focus is on the introduction to different topics in mathematical analysis. A second focus is on the application of mathematical tools to the analysis of stochastic equations. A third focus is on the development and application of stochastic methods to simulate turbulent flows as seen in reality. This book is primarily oriented towards mathematics and engineering PhD students, young and experienced researchers, and professionals working in the area of stochastic differential equations ...
12th Workshop on Stochastic Models, Statistics and Their Applications
Rafajłowicz, Ewaryst; Szajowski, Krzysztof
2015-01-01
This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Stochastic approach to microphysics
Energy Technology Data Exchange (ETDEWEB)
Aron, J.C.
1987-01-01
The presently widespread idea of ''vacuum population'', together with the quantum concept of vacuum fluctuations leads to assume a random level below that of matter. This stochastic approach starts by a reminder of the author's previous work, first on the relation of diffusion laws with the foundations of microphysics, and then on hadron spectrum. Following the latter, a random quark model is advanced; it gives to quark pairs properties similar to those of a harmonic oscillator or an elastic string, imagined as an explanation to their asymptotic freedom and their confinement. The stochastic study of such interactions as electron-nucleon, jets in e/sup +/e/sup -/ collisions, or pp -> ..pi../sup 0/ + X, gives form factors closely consistent with experiment. The conclusion is an epistemological comment (complementarity between stochastic and quantum domains, E.P.R. paradox, etc...).
Stochastic dynamics and irreversibility
Tomé, Tânia
2015-01-01
This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...
Stochastic optimization methods
Marti, Kurt
2005-01-01
Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
Separable quadratic stochastic operators
International Nuclear Information System (INIS)
Rozikov, U.A.; Nazir, S.
2009-04-01
We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)
Stochastic Feedforward Control Technique
Halyo, Nesim
1990-01-01
Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.
Markov stochasticity coordinates
International Nuclear Information System (INIS)
Eliazar, Iddo
2017-01-01
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
DEFF Research Database (Denmark)
Simonsen, Maria
This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...
Stochastic dynamics and control
Sun, Jian-Qiao; Zaslavsky, George
2006-01-01
This book is a result of many years of author's research and teaching on random vibration and control. It was used as lecture notes for a graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control is also reviewed in the book. Random vibration analyses of SDOF, MDOF and continuous structural systems are presented in a pedagogical order. The application of the random vibration theory to reliability and fatigue analysis is also discussed. Recent research results on fatigue analysis of non-Gaussian stress proc
CSIR Research Space (South Africa)
Roux, FS
2013-09-01
Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...
Foundations of stochastic analysis
Rao, M M; Lukacs, E
1981-01-01
Foundations of Stochastic Analysis deals with the foundations of the theory of Kolmogorov and Bochner and its impact on the growth of stochastic analysis. Topics covered range from conditional expectations and probabilities to projective and direct limits, as well as martingales and likelihood ratios. Abstract martingales and their applications are also discussed. Comprised of five chapters, this volume begins with an overview of the basic Kolmogorov-Bochner theorem, followed by a discussion on conditional expectations and probabilities containing several characterizations of operators and mea
Markov stochasticity coordinates
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: iddo.eliazar@intel.com
2017-01-15
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Stochastic energy balancing in substation energy management
Directory of Open Access Journals (Sweden)
Hassan Shirzeh
2015-12-01
Full Text Available In the current research, a smart grid is considered as a network of distributed interacting nodes represented by renewable energy sources, storage and loads. The source nodes become active or inactive in a stochastic manner due to the intermittent nature of natural resources such as wind and solar irradiance. Prediction and stochastic modelling of electrical energy flow is a critical task in such a network in order to achieve load levelling and/or peak shaving in order to minimise the fluctuation between off-peak and peak energy demand. An effective approach is proposed to model and administer the behaviour of source nodes in this grid through a scheduling strategy control algorithm using the historical data collected from the system. The stochastic model predicts future power consumption/injection to determine the power required for storage components. The stochastic models developed based on the Box-Jenkins method predict the most efficient state of the electrical energy flow between a distribution network and nodes and minimises the peak demand and off-peak consumption of acquiring electrical energy from the main grid. The performance of the models is validated against the autoregressive moving average (ARIMA and the Markov chain models used in previous work. The results demonstrate that the proposed method outperforms both the ARIMA and the Markov chain model in terms of forecast accuracy. Results are presented, the strengths and limitations of the approach are discussed, and possible future work is described.
Stochastic models, estimation, and control
Maybeck, Peter S
1982-01-01
This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.
A heterogeneous stochastic FEM framework for elliptic PDEs
International Nuclear Information System (INIS)
Hou, Thomas Y.; Liu, Pengfei
2015-01-01
We introduce a new concept of sparsity for the stochastic elliptic operator −div(a(x,ω)∇(⋅)), which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially heterogeneous stochastic structure. This new concept of sparsity motivates a heterogeneous stochastic finite element method (HSFEM) framework for linear elliptic equations, which discretizes the equations using the heterogeneous coupling of spatial basis with local stochastic basis to exploit the local stochastic structure of the solution space. We also provide a sampling method to construct the local stochastic basis for this framework using the randomized range finding techniques. The resulting HSFEM involves two stages and suits the multi-query setting: in the offline stage, the local stochastic structure of the solution space is identified; in the online stage, the equation can be efficiently solved for multiple forcing functions. An online error estimation and correction procedure through Monte Carlo sampling is given. Numerical results for several problems with high dimensional stochastic input are presented to demonstrate the efficiency of the HSFEM in the online stage
Stochastic quantization of Proca field
International Nuclear Information System (INIS)
Lim, S.C.
1981-03-01
We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)
Stochastic Estimation via Polynomial Chaos
2015-10-01
AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic
Stochastic growth of localized plasma waves
International Nuclear Information System (INIS)
Robinson, P.A.; Cairns, I.H.
2000-01-01
Full text: Localized bursty plasma waves occur in many natural systems, where they are detected by spacecraft. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the wave-driver interaction, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; observed bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it for much longer times and distances than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. Growth mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing, power-law distributed in strong turbulence, and uniformly distributed in log under secular growth. After delineating stochastic growth and strong-turbulence regimes, recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type II and III solar radio sources, foreshock regions upstream of the bow shocks of Earth and planets, and Earth's magnetosheath, auroras, and polar-caps. It is shown that when combined with wave-wave processes, SGT accounts for type II and III solar radio emissions. SGT thus removes longstanding problems in understanding persistent unstable distributions, bursty fields, and radio emissions observed in space
Direct observation of stochastic domain-wall depinning in magnetic nanowires
Energy Technology Data Exchange (ETDEWEB)
Im, Mi-Young; Bocklage, Lars; Fischer, Peter; Meier, Guido
2008-11-01
The stochastic field-driven depinning of a domain wall pinned at a notch in a magnetic nanowire is directly observed using magnetic X-ray microscopy with high lateral resolution down to 15 nm. The depinning-field distribution in Ni{sub 80}Fe{sub 20} nanowires considerably depends on the wire width and the notch depth. The difference in the multiplicity of domain-wall types generated in the vicinity of a notch is responsible for the observed dependence of the stochastic nature of the domain wall depinning field on the wire width and the notch depth. Thus the random nature of the domain wall depinning process is controllable by an appropriate design of the nanowire.
Mellin Transform Method for European Option Pricing with Hull-White Stochastic Interest Rate
Directory of Open Access Journals (Sweden)
Ji-Hun Yoon
2014-01-01
Full Text Available Even though interest rates fluctuate randomly in the marketplace, many option-pricing models do not fully consider their stochastic nature owing to their generally limited impact on option prices. However, stochastic dynamics in stochastic interest rates may have a significant impact on option prices as we take account of issues of maturity, hedging, or stochastic volatility. In this paper, we derive a closed form solution for European options in Black-Scholes model with stochastic interest rate using Mellin transform techniques.
Energy Technology Data Exchange (ETDEWEB)
Tollestrup, A.V.; Dugan, G
1983-12-01
Major headings in this review include: proton sources; antiproton production; antiproton sources and Liouville, the role of the Debuncher; transverse stochastic cooling, time domain; the accumulator; frequency domain; pickups and kickers; Fokker-Planck equation; calculation of constants in the Fokker-Planck equation; and beam feedback. (GHT)
Schrager, D.F.
2006-01-01
We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing
Composite stochastic processes
Kampen, N.G. van
Certain problems in physics and chemistry lead to the definition of a class of stochastic processes. Although they are not Markovian they can be treated explicitly to some extent. In particular, the probability distribution for large times can be found. It is shown to obey a master equation. This
Entropy Production in Stochastics
Directory of Open Access Journals (Sweden)
Demetris Koutsoyiannis
2017-10-01
Full Text Available While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT or conditionally on the past and present having been observed (CEPLT. We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.
Stochastic modelling of turbulence
DEFF Research Database (Denmark)
Sørensen, Emil Hedevang Lohse
previously been shown to be closely connected to the energy dissipation. The incorporation of the small scale dynamics into the spatial model opens the door to a fully fledged stochastic model of turbulence. Concerning the interaction of wind and wind turbine, a new method is proposed to extract wind turbine...
Research in Stochastic Processes.
1982-10-31
Office of Scientific Research Grant AFOSR F49620 82 C 0009 Period: 1 Noveber 1981 through 31 October 1982 Title: Research in Stochastic Processes Co...STA4ATIS CAMBANIS The work briefly described here was developed in connection with problems arising from and related to the statistical comunication
Stochastic Control - External Models
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
2005-01-01
This note is devoted to control of stochastic systems described in discrete time. We are concerned with external descriptions or transfer function model, where we have a dynamic model for the input output relation only (i.e.. no direct internal information). The methods are based on LTI systems...
Stochastic nonlinear beam equations
Czech Academy of Sciences Publication Activity Database
Brzezniak, Z.; Maslowski, Bohdan; Seidler, Jan
2005-01-01
Roč. 132, č. 1 (2005), s. 119-149 ISSN 0178-8051 R&D Projects: GA ČR(CZ) GA201/01/1197 Institutional research plan: CEZ:AV0Z10190503 Keywords : stochastic beam equation * stability Subject RIV: BA - General Mathematics Impact factor: 0.896, year: 2005
Stacking with stochastic cooling
Energy Technology Data Exchange (ETDEWEB)
Caspers, Fritz E-mail: Fritz.Caspers@cern.ch; Moehl, Dieter
2004-10-11
Accumulation of large stacks of antiprotons or ions with the aid of stochastic cooling is more delicate than cooling a constant intensity beam. Basically the difficulty stems from the fact that the optimized gain and the cooling rate are inversely proportional to the number of particles 'seen' by the cooling system. Therefore, to maintain fast stacking, the newly injected batch has to be strongly 'protected' from the Schottky noise of the stack. Vice versa the stack has to be efficiently 'shielded' against the high gain cooling system for the injected beam. In the antiproton accumulators with stacking ratios up to 10{sup 5} the problem is solved by radial separation of the injection and the stack orbits in a region of large dispersion. An array of several tapered cooling systems with a matched gain profile provides a continuous particle flux towards the high-density stack core. Shielding of the different systems from each other is obtained both through the spatial separation and via the revolution frequencies (filters). In the 'old AA', where the antiproton collection and stacking was done in one single ring, the injected beam was further shielded during cooling by means of a movable shutter. The complexity of these systems is very high. For more modest stacking ratios, one might use azimuthal rather than radial separation of stack and injected beam. Schematically half of the circumference would be used to accept and cool new beam and the remainder to house the stack. Fast gating is then required between the high gain cooling of the injected beam and the low gain stack cooling. RF-gymnastics are used to merge the pre-cooled batch with the stack, to re-create free space for the next injection, and to capture the new batch. This scheme is less demanding for the storage ring lattice, but at the expense of some reduction in stacking rate. The talk reviews the 'radial' separation schemes and also gives some
Pan-European stochastic flood event set
Kadlec, Martin; Pinto, Joaquim G.; He, Yi; Punčochář, Petr; Kelemen, Fanni D.; Manful, Desmond; Palán, Ladislav
2017-04-01
Impact Forecasting (IF), the model development center of Aon Benfield, has been developing a large suite of catastrophe flood models on probabilistic bases for individual countries in Europe. Such natural catastrophes do not follow national boundaries: for example, the major flood in 2016 was responsible for the Europe's largest insured loss of USD3.4bn and affected Germany, France, Belgium, Austria and parts of several other countries. Reflecting such needs, IF initiated a pan-European flood event set development which combines cross-country exposures with country based loss distributions to provide more insightful data to re/insurers. Because the observed discharge data are not available across the whole Europe in sufficient quantity and quality to permit a detailed loss evaluation purposes, a top-down approach was chosen. This approach is based on simulating precipitation from a GCM/RCM model chain followed by a calculation of discharges using rainfall-runoff modelling. IF set up this project in a close collaboration with Karlsruhe Institute of Technology (KIT) regarding the precipitation estimates and with University of East Anglia (UEA) in terms of the rainfall-runoff modelling. KIT's main objective is to provide high resolution daily historical and stochastic time series of key meteorological variables. A purely dynamical downscaling approach with the regional climate model COSMO-CLM (CCLM) is used to generate the historical time series, using re-analysis data as boundary conditions. The resulting time series are validated against the gridded observational dataset E-OBS, and different bias-correction methods are employed. The generation of the stochastic time series requires transfer functions between large-scale atmospheric variables and regional temperature and precipitation fields. These transfer functions are developed for the historical time series using reanalysis data as predictors and bias-corrected CCLM simulated precipitation and temperature as
Kandel, Prem P; Lopez, Samantha M; Almeida, Rodrigo P P; De La Fuente, Leonardo
2016-09-01
Xylella fastidiosa is a xylem-limited bacterium that is the causal agent of emerging diseases in a number of economically important crops. Genetic diversity studies have demonstrated homologous recombination occurring among X. fastidiosa strains, which has been proposed to contribute to host plant shifts. Moreover, experimental evidence confirmed that X. fastidiosa is naturally competent for recombination in vitro Here, as an approximation of natural habitats (plant xylem vessels and insect mouthparts), recombination was studied in microfluidic chambers (MCs) filled with media amended with grapevine xylem sap. First, different media were screened for recombination in solid agar plates using a pair of X. fastidiosa strains that were previously reported to recombine in coculture. The highest frequency of recombination was obtained with PD3 medium, compared to those with the other two media (X. fastidiosa medium [XFM] and periwinkle wilt [PW] medium) used in previous studies. Dissection of the media components led to the identification of bovine serum albumin as an inhibitor of recombination that was correlated to its previously known effect on inhibition of twitching motility. When recombination was performed in liquid culture, the frequencies were significantly higher under flow conditions (MCs) than under batch conditions (test tubes). The recombination frequencies in MCs and agar plates were not significantly different from each other. Grapevine xylem sap from both susceptible and tolerant varieties allowed high recombination frequency in MCs when mixed with PD3. These results suggest that X. fastidiosa has the ability to be naturally competent in the natural growth environment of liquid flow, and this phenomenon could have implications in X. fastidiosa environmental adaptation. Xylella fastidiosa is a plant pathogen that lives inside xylem vessels (where water and nutrients are transported inside the plant) and the mouthparts of insect vectors. This bacterium
Liss, Alexander
Extreme weather events, such as heat waves and cold spells, cause substantial excess mortality and morbidity in the vulnerable elderly population, and cost billions of dollars. The accurate and reliable assessment of adverse effects of extreme weather events on human health is crucial for environmental scientists, economists, and public health officials to ensure proper protection of vulnerable populations and efficient allocation of scarce resources. However, the methodology for the analysis of large national databases is yet to be developed. The overarching objective of this dissertation is to examine the effect of extreme weather on the elderly population of the Conterminous US (ConUS) with respect to seasonality in temperature in different climatic regions by utilizing heterogeneous high frequency and spatio-temporal resolution data. To achieve these goals the author: 1) incorporated dissimilar stochastic high frequency big data streams and distinct data types into the integrated data base for use in analytical and decision support frameworks; 2) created an automated climate regionalization system based on remote sensing and machine learning to define climate regions for the Conterminous US; 3) systematically surveyed the current state of the art and identified existing gaps in the scientific knowledge; 4) assessed the dose-response relationship of exposure to temperature extremes on human health in relatively homogeneous climate regions using different statistical models, such as parametric and non-parametric, contemporaneous and asynchronous, applied to the same data; 5) assessed seasonal peak timing and synchronization delay of the exposure and the disease within the framework of contemporaneous high frequency harmonic time series analysis and modification of the effect by the regional climate; 6) modeled using hyperbolic functional form non-linear properties of the effect of exposure to extreme temperature on human health. The proposed climate
Introduction to probability and stochastic processes with applications
Castañ, Blanco; Arunachalam, Viswanathan; Dharmaraja, Selvamuthu
2012-01-01
An easily accessible, real-world approach to probability and stochastic processes Introduction to Probability and Stochastic Processes with Applications presents a clear, easy-to-understand treatment of probability and stochastic processes, providing readers with a solid foundation they can build upon throughout their careers. With an emphasis on applications in engineering, applied sciences, business and finance, statistics, mathematics, and operations research, the book features numerous real-world examples that illustrate how random phenomena occur in nature and how to use probabilistic t
Dynamic Stochastic Superresolution of sparsely observed turbulent systems
International Nuclear Information System (INIS)
Branicki, M.; Majda, A.J.
2013-01-01
Real-time capture of the relevant features of the unresolved turbulent dynamics of complex natural systems from sparse noisy observations and imperfect models is a notoriously difficult problem. The resulting lack of observational resolution and statistical accuracy in estimating the important turbulent processes, which intermittently send significant energy to the large-scale fluctuations, hinders efficient parameterization and real-time prediction using discretized PDE models. This issue is particularly subtle and important when dealing with turbulent geophysical systems with an vast range of interacting spatio-temporal scales and rough energy spectra near the mesh scale of numerical models. Here, we introduce and study a suite of general Dynamic Stochastic Superresolution (DSS) algorithms and show that, by appropriately filtering sparse regular observations with the help of cheap stochastic exactly solvable models, one can derive stochastically ‘superresolved’ velocity fields and gain insight into the important characteristics of the unresolved dynamics, including the detection of the so-called black swans. The DSS algorithms operate in Fourier domain and exploit the fact that the coarse observation network aliases high-wavenumber information into the resolved waveband. It is shown that these cheap algorithms are robust and have significant skill on a test bed of turbulent solutions from realistic nonlinear turbulent spatially extended systems in the presence of a significant model error. In particular, the DSS algorithms are capable of successfully capturing time-localized extreme events in the unresolved modes, and they provide good and robust skill for recovery of the unresolved processes in terms of pattern correlation. Moreover, we show that DSS improves the skill for recovering the primary modes associated with the sparse observation mesh which is equally important in applications. The skill of the various DSS algorithms depends on the energy spectrum
Reserves and cash flows under stochastic retirement
DEFF Research Database (Denmark)
Gad, Kamille Sofie Tågholt; Nielsen, Jeppe Woetmann
2016-01-01
Uncertain time of retirement and uncertain structure of retirement benefits are risk factors for life insurance companies. Nevertheless, classical life insurance models assume these are deterministic. In this paper, we include the risk from stochastic time of retirement and stochastic benefit...... structure in a classical finite-state Markov model for a life insurance contract. We include discontinuities in the distribution of the retirement time. First, we derive formulas for appropriate scaling of the benefits according to the time of retirement and discuss the link between the scaling...... and the guarantees provided. Stochastic retirement creates a need to rethink the construction of disability products for high ages and ways to handle this are discussed. We show how to calculate market reserves and how to use modified transition probabilities to calculate expected cash flows without significantly...
Stochastic Modeling Of Wind Turbine Drivetrain Components
DEFF Research Database (Denmark)
Rafsanjani, Hesam Mirzaei; Sørensen, John Dalsgaard
2014-01-01
reliable components are needed for wind turbine. In this paper focus is on reliability of critical components in drivetrain such as bearings and shafts. High failure rates of these components imply a need for more reliable components. To estimate the reliability of these components, stochastic models...... are needed for initial defects and damage accumulation. In this paper, stochastic models are formulated considering some of the failure modes observed in these components. The models are based on theoretical considerations, manufacturing uncertainties, size effects of different scales. It is illustrated how...
Neuro-Inspired Computing with Stochastic Electronics
Naous, Rawan
2016-01-06
The extensive scaling and integration within electronic systems have set the standards for what is addressed to as stochastic electronics. The individual components are increasingly diverting away from their reliable behavior and producing un-deterministic outputs. This stochastic operation highly mimics the biological medium within the brain. Hence, building on the inherent variability, particularly within novel non-volatile memory technologies, paves the way for unconventional neuromorphic designs. Neuro-inspired networks with brain-like structures of neurons and synapses allow for computations and levels of learning for diverse recognition tasks and applications.
Stochastic processes in cell biology
Bressloff, Paul C
2014-01-01
This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods. This text is primarily...
Project Evaluation and Cash Flow Forecasting by Stochastic Simulation
Directory of Open Access Journals (Sweden)
Odd A. Asbjørnsen
1983-10-01
Full Text Available The net present value of a discounted cash flow is used to evaluate projects. It is shown that the LaPlace transform of the cash flow time function is particularly useful when the cash flow profiles may be approximately described by ordinary linear differential equations in time. However, real cash flows are stochastic variables due to the stochastic nature of the disturbances during production.
Network interdiction and stochastic integer programming
2003-01-01
On March 15, 2002 we held a workshop on network interdiction and the more general problem of stochastic mixed integer programming at the University of California, Davis. Jesús De Loera and I co-chaired the event, which included presentations of on-going research and discussion. At the workshop, we decided to produce a volume of timely work on the topics. This volume is the result. Each chapter represents state-of-the-art research and all of them were refereed by leading investigators in the respective fields. Problems - sociated with protecting and attacking computer, transportation, and social networks gain importance as the world becomes more dep- dent on interconnected systems. Optimization models that address the stochastic nature of these problems are an important part of the research agenda. This work relies on recent efforts to provide methods for - dressing stochastic mixed integer programs. The book is organized with interdiction papers first and the stochastic programming papers in the second part....
A Newton-Based Extremum Seeking MPPT Method for Photovoltaic Systems with Stochastic Perturbations
Directory of Open Access Journals (Sweden)
Heng Li
2014-01-01
Full Text Available Microcontroller based maximum power point tracking (MPPT has been the most popular MPPT approach in photovoltaic systems due to its high flexibility and efficiency in different photovoltaic systems. It is well known that PV systems typically operate under a range of uncertain environmental parameters and disturbances, which implies that MPPT controllers generally suffer from some unknown stochastic perturbations. To address this issue, a novel Newton-based stochastic extremum seeking MPPT method is proposed. Treating stochastic perturbations as excitation signals, the proposed MPPT controller has a good tolerance of stochastic perturbations in nature. Different from conventional gradient-based extremum seeking MPPT algorithm, the convergence rate of the proposed controller can be totally user-assignable rather than determined by unknown power map. The stability and convergence of the proposed controller are rigorously proved. We further discuss the effects of partial shading and PV module ageing on the proposed controller. Numerical simulations and experiments are conducted to show the effectiveness of the proposed MPPT algorithm.
International Nuclear Information System (INIS)
Tabatabaee, Sajad; Mortazavi, Seyed Saeedallah; Niknam, Taher
2016-01-01
This paper addresses the optimal stochastic scheduling of the distributed generation units in a micro-grid. In this way, it introduces a new sufficient stochastic framework to model the correlated uncertainties in the micro-grid that includes different types of RESs such as photovoltaics, wind turbines, micro-turbine, fuel cell as well as battery as the storage device. The proposed stochastic method makes use of unscented transforms to model correlated uncertain parameters. The ability of the unscented transform method to model correlated uncertain variables is particularly appealing in the context of power systems, wherein noticeable inherent correlation exists. Due to the highly complex nature of the problem, a new optimization method based on the harmony search algorithm along with an intelligent modification method is devised to solve the proposed optimization problem, efficiently. The proposed optimization algorithm is equipped with powerful search mechanisms that make it suitable for solving both discrete and continuous problems. In comparison with the original harmony search algorithm, the proposed modified optimization algorithm has few setting parameters. The new modified harmony search algorithm provides proper balance between the local and global searches. The feasibility and satisfactory performance of performance of the proposed method are examined on two typical grid-connected MGs. - Highlights: • Introducing a new artificial optimization algorithm based on HS evolutionary technique. • Introducing a new stochastic framework based on unscented transform to model the uncertainties of the problem. • Proposing a new modification method for HS to improve its total search ability.
Energy-Efficient FPGA-Based Parallel Quasi-Stochastic Computing
Directory of Open Access Journals (Sweden)
Ramu Seva
2017-11-01
Full Text Available The high performance of FPGA (Field Programmable Gate Array in image processing applications is justified by its flexible reconfigurability, its inherent parallel nature and the availability of a large amount of internal memories. Lately, the Stochastic Computing (SC paradigm has been found to be significantly advantageous in certain application domains including image processing because of its lower hardware complexity and power consumption. However, its viability is deemed to be limited due to its serial bitstream processing and excessive run-time requirement for convergence. To address these issues, a novel approach is proposed in this work where an energy-efficient implementation of SC is accomplished by introducing fast-converging Quasi-Stochastic Number Generators (QSNGs and parallel stochastic bitstream processing, which are well suited to leverage FPGA’s reconfigurability and abundant internal memory resources. The proposed approach has been tested on the Virtex-4 FPGA, and results have been compared with the serial and parallel implementations of conventional stochastic computation using the well-known SC edge detection and multiplication circuits. Results prove that by using this approach, execution time, as well as the power consumption are decreased by a factor of 3.5 and 4.5 for the edge detection circuit and multiplication circuit, respectively.
Greenhouse gas emissions from high demand, natural gas-intensive energy scenarios
International Nuclear Information System (INIS)
Victor, D.G.
1990-01-01
Since coal and oil emit 70% and 30% more CO 2 per unit of energy than natural gas (methane), fuel switching to natural gas is an obvious pathway to lower CO 2 emissions and reduced theorized greenhouse warming. However, methane is, itself, a strong greenhouse gas so the CO 2 advantages of natural gas may be offset by leaks in the natural gas recovery and supply system. Simple models of atmospheric CO 2 and methane are used to test this hypothesis for several natural gas-intensive energy scenarios, including the work of Ausubel et al (1988). It is found that the methane leaks are significant and may increase the total 'greenhouse effect' from natural gas-intensive energy scenarios by 10%. Furthermore, because methane is short-lived in the atmosphere, leaking methane from natural gas-intensive, high energy growth scenarios effectively recharges the concentration of atmospheric methane continuously. For such scenarios, the problem of methane leaks is even more serious. A second objective is to explore some high demand scenarios that describe the role of methane leaks in the greenhouse tradeoff between gas and coal as energy sources. It is found that the uncertainty in the methane leaks from the natural gas system are large enough to consume the CO 2 advantages from using natural gas instead of coal for 20% of the market share. (author)
Applications of stochastic geometry in image analysis
Lieshout, van M.N.M.; Kendall, W.S.; Molchanov, I.S.
2009-01-01
A discussion is given of various stochastic geometry models (random fields, sequential object processes, polygonal field models) which can be used in intermediate and high-level image analysis. Two examples are presented of actual image analysis problems (motion tracking in video,
Efficient Estimating Functions for Stochastic Differential Equations
DEFF Research Database (Denmark)
Jakobsen, Nina Munkholt
The overall topic of this thesis is approximate martingale estimating function-based estimationfor solutions of stochastic differential equations, sampled at high frequency. Focuslies on the asymptotic properties of the estimators. The first part of the thesis deals with diffusions observed over...
Location iron-Mantua an area with high securities gives natural radioactivity
International Nuclear Information System (INIS)
Alcaide Orpi, J.; Oliveira Acosta, J.; Valdes Hernadez, G.M.; Leal Ramirez, M.R.; Blanco Jorrin, N.
1998-01-01
The work shows the high natural radioactivity and the concentration to the natural radioelements (U,Th, Ra, K) it is exists in the sulfurous Hierro Mantua location. The objective is to know the possible radiological risk to that would be subjected the workers during the mining exploitation, because the high gamma radiation doses that could receive and to the risks product the internal contamination due to the inhalation the radon 222 and uranium aerosols and particles
High levels of natural radionuclides in a deep-sea infaunal xenophyophore
Energy Technology Data Exchange (ETDEWEB)
Swinbanks, D D; Shirayama, Y
1986-03-27
The paper concerns the high levels of natural radionuclides in a deep-sea infaunal xenophyophore from the Izu-Ogasawara Trench. Measured /sup 210/Po activities and barium contents of various parts of Occultammina profunda and the surrounding sediment are given, together with their estimated /sup 210/Pb and /sup 226/Ra activities. The data suggest that xenophyphores are probably subject to unusually high levels of natural radiation.
Stochastic calculus and applications
Cohen, Samuel N
2015-01-01
Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance. Building upon the original release of this title, this text will be of great interest to research mathematicians and graduate students working in those fields, as well as quants in the finance industry. New features of this edition include: End of chapter exercises; New chapters on basic measure theory and Backward SDEs; Reworked proofs, examples and explanatory material; Increased focus on motivating the mathematics; Extensive topical index. "Such a self-contained and complete exposition of stochastic calculus and applications fills an existing gap in the literature. The book can be recommended for first-year graduate studies. It will be useful for all who intend to wo...
Some illustrations of stochasticity
International Nuclear Information System (INIS)
Laslett, L.J.
1977-01-01
A complex, and apparently stochastic, character frequently can be seen to occur in the solutions to simple Hamiltonian problems. Such behavior is of interest, and potentially of importance, to designers of particle accelerators--as well as to workers in other fields of physics and related disciplines. Even a slow development of disorder in the motion of particles in a circular accelerator or storage ring could be troublesome, because a practical design requires the beam particles to remain confined in an orderly manner within a narrow beam tube for literally tens of billions of revolutions. The material presented is primarily the result of computer calculations made to investigate the occurrence of ''stochasticity,'' and is organized in a manner similar to that adopted for presentation at a 1974 accelerator conference
Stochastic ice stream dynamics.
Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca
2016-08-09
Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.
Fractional Stochastic Field Theory
Honkonen, Juha
2018-02-01
Models describing evolution of physical, chemical, biological, social and financial processes are often formulated as differential equations with the understanding that they are large-scale equations for averages of quantities describing intrinsically random processes. Explicit account of randomness may lead to significant changes in the asymptotic behaviour (anomalous scaling) in such models especially in low spatial dimensions, which in many cases may be captured with the use of the renormalization group. Anomalous scaling and memory effects may also be introduced with the use of fractional derivatives and fractional noise. Construction of renormalized stochastic field theory with fractional derivatives and fractional noise in the underlying stochastic differential equations and master equations and the interplay between fluctuation-induced and built-in anomalous scaling behaviour is reviewed and discussed.
Essentials of stochastic processes
Durrett, Richard
2016-01-01
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...
Stochastic porous media equations
Barbu, Viorel; Röckner, Michael
2016-01-01
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.
Multistage stochastic optimization
Pflug, Georg Ch
2014-01-01
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book
Identifiability in stochastic models
1992-01-01
The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of ""characterization problems"" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.
Stochastic split determinant algorithms
International Nuclear Information System (INIS)
Horvatha, Ivan
2000-01-01
I propose a large class of stochastic Markov processes associated with probability distributions analogous to that of lattice gauge theory with dynamical fermions. The construction incorporates the idea of approximate spectral split of the determinant through local loop action, and the idea of treating the infrared part of the split through explicit diagonalizations. I suggest that exact algorithms of practical relevance might be based on Markov processes so constructed
naturally high temperature and high total alkalinity environment of the Red Sea
Roik, Anna Krystyna; Roethig, Till; Pogoreutz, Claudia; Saderne, Vincent; Voolstra, Christian R.
2018-01-01
The coral structural framework is crucial for maintaining reef ecosystem function and services. Rising seawater temperatures impair the calcification capacity of reef-building organisms on a global scale, but in the Red Sea total alkalinity is naturally high and beneficial to reef growth. It is currently unknown how beneficial and detrimental factors affect the balance between calcification and erosion, and thereby overall reef growth, in the Red Sea. To provide estimates of present-day carbonate budgets and reef growth dynamics in the central Red Sea, we measured in situ net-accretion and net-erosion rates (Gnet) by deployment of limestone blocks to estimate census-based carbonate budgets (Gbudget) in four reef sites along a cross-shelf gradient (25 km). In addition, we assessed abiotic (i.e., temperature, inorganic nutrients, and carbonate system variables) and biotic (i.e., calcifier and bioeroder abundances) variables. Our data show that aragonite saturation states (Ω = 3.65–4.20) were in the upper range compared to the chemistry of other tropical reef sites. Further, Gnet and Gbudget encompassed positive (offshore) and negative (midshore-lagoon and exposed nearshore site) carbonate budgets. Notably, Gbudget maxima were lower compared to reef growth from undisturbed Indian Ocean reefs, but erosive forces for Red Sea reefs were not as strong as observed elsewhere. In line with this, a comparison with recent historical data from the northern Red Sea suggests that overall reef growth in the Red Sea has remained similar since 1995. When assessing reef sites across the shelf gradient, AT correlated well and positive with reef growth (ρ = 0.9), while temperature (ρ = −0.7), pH variation (ρ = −0.8), and pCO2 (ρ = −0.8) were weaker negative correlates. Noteworthy for this oligotrophic sea was the positive effect of PO43− (ρ = 0.7) on reef growth. In the best-fitting distance-based linear model, AT explained about 64 % of Gbudget. Interestingly
naturally high temperature and high total alkalinity environment of the Red Sea
Roik, Anna Krystyna
2018-02-28
The coral structural framework is crucial for maintaining reef ecosystem function and services. Rising seawater temperatures impair the calcification capacity of reef-building organisms on a global scale, but in the Red Sea total alkalinity is naturally high and beneficial to reef growth. It is currently unknown how beneficial and detrimental factors affect the balance between calcification and erosion, and thereby overall reef growth, in the Red Sea. To provide estimates of present-day carbonate budgets and reef growth dynamics in the central Red Sea, we measured in situ net-accretion and net-erosion rates (Gnet) by deployment of limestone blocks to estimate census-based carbonate budgets (Gbudget) in four reef sites along a cross-shelf gradient (25 km). In addition, we assessed abiotic (i.e., temperature, inorganic nutrients, and carbonate system variables) and biotic (i.e., calcifier and bioeroder abundances) variables. Our data show that aragonite saturation states (Ω = 3.65–4.20) were in the upper range compared to the chemistry of other tropical reef sites. Further, Gnet and Gbudget encompassed positive (offshore) and negative (midshore-lagoon and exposed nearshore site) carbonate budgets. Notably, Gbudget maxima were lower compared to reef growth from undisturbed Indian Ocean reefs, but erosive forces for Red Sea reefs were not as strong as observed elsewhere. In line with this, a comparison with recent historical data from the northern Red Sea suggests that overall reef growth in the Red Sea has remained similar since 1995. When assessing reef sites across the shelf gradient, AT correlated well and positive with reef growth (ρ = 0.9), while temperature (ρ = −0.7), pH variation (ρ = −0.8), and pCO2 (ρ = −0.8) were weaker negative correlates. Noteworthy for this oligotrophic sea was the positive effect of PO43− (ρ = 0.7) on reef growth. In the best-fitting distance-based linear model, AT explained about 64 % of Gbudget. Interestingly
Sensory optimization by stochastic tuning.
Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees
2013-10-01
Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system's preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: The higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Stochasticity Modeling in Memristors
Naous, Rawan; Al-Shedivat, Maruan; Salama, Khaled N.
2015-01-01
Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.
Stochasticity Modeling in Memristors
Naous, Rawan
2015-10-26
Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.
Stochastic quantization of instantons
International Nuclear Information System (INIS)
Grandati, Y.; Berard, A.; Grange, P.
1996-01-01
The method of Parisi and Wu to quantize classical fields is applied to instanton solutions var-phi I of euclidian non-linear theory in one dimension. The solution var-phi var-epsilon of the corresponding Langevin equation is built through a singular perturbative expansion in var-epsilon=h 1/2 in the frame of the center of the mass of the instanton, where the difference var-phi var-epsilon -var-phi I carries only fluctuations of the instanton form. The relevance of the method is shown for the stochastic K dV equation with uniform noise in space: the exact solution usually obtained by the inverse scattering method is retrieved easily by the singular expansion. A general diagrammatic representation of the solution is then established which makes a thorough use of regrouping properties of stochastic diagrams derived in scalar field theory. Averaging over the noise and in the limit of infinite stochastic time, the authors obtain explicit expressions for the first two orders in var-epsilon of the pertrubed instanton of its Green function. Specializing to the Sine-Gordon and var-phi 4 models, the first anaharmonic correction is obtained analytically. The calculation is carried to second order for the var-phi 4 model, showing good convergence. 21 refs., 5 fig
Stochastic goal-oriented error estimation with memory
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.
Stochastic and non-stochastic effects - a conceptual analysis
International Nuclear Information System (INIS)
Karhausen, L.R.
1980-01-01
The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)
Stochastic modeling of virus capsid assembly pathways
Schwartz, Russell
2009-03-01
Virus capsids have become a key model system for understanding self-assembly due to their high complexity, robust and efficient assembly processes, and experimental tractability. Our ability to directly examine and manipulate capsid assembly kinetics in detail nonetheless remains limited, creating a need for computer models that can infer experimentally inaccessible features of the assembly process and explore the effects of hypothetical manipulations on assembly trajectories. We have developed novel algorithms for stochastic simulation of capsid assembly [1,2] that allow us to model capsid assembly over broad parameter spaces [3]. We apply these methods to study the nature of assembly pathway control in virus capsids as well as their sensitivity to assembly conditions and possible experimental interventions. [4pt] [1] F. Jamalyaria, R. Rohlfs, and R. Schwartz. J Comp Phys 204, 100 (2005). [0pt] [2] N. Misra and R. Schwartz. J Chem Phys 129, in press (2008). [0pt] [3] B. Sweeney, T. Zhang, and R. Schwartz. Biophys J 94, 772 (2008).
Energy Technology Data Exchange (ETDEWEB)
Chong, E.L.; Ahmad, Ishak [Polymer Research Center (PORCE), School of Chemical Science and Food Technology, Universiti Kebangsaan Malaysia 4, 43600 UKM Bangi, Selangor Darul Ehsan (Malaysia); Dahlan, H.M. [Radiation Processing Technology Division, Malaysian Nuclear Agency (Nuclear Malaysia), Bangi, 43000 Kajang, Selangor Darul Ehsan (Malaysia); Abdullah, Ibrahim, E-mail: dia@ukm.m [Polymer Research Center (PORCE), School of Chemical Science and Food Technology, Universiti Kebangsaan Malaysia 4, 43600 UKM Bangi, Selangor Darul Ehsan (Malaysia)
2010-08-15
Coating of rice husk (RH) surface with liquid natural rubber (LNR) and exposure to electron beam irradiation in air were studied. FTIR analysis on the LNR-coated RH (RHR) exposed to electron beam (EB) showed a decrease in the double bonds and an increase in hydroxyl and hydrogen bonded carbonyl groups arising from the chemical interaction between the active groups on RH surface with LNR. The scanning electron micrograph showed that the LNR formed a coating on the RH particles which transformed to a fine and clear fibrous layer at 20 kGy irradiation. The LNR film appeared as patches at 50 kGy irradiation due to degradation of rubber. Composites of natural rubber (NR)/high density polyethylene (HDPE)/RHR showed an optimum at 20-30 kGy dosage with the maximum stress, tensile modulus and impact strength of 6.5, 79 and 13.2 kJ/m{sup 2}, respectively. The interfacial interaction between the modified RH and TPNR matrix had improved on exposure of RHR to e-beam at 20-30 kGy dosage.
Energy Technology Data Exchange (ETDEWEB)
Liu, Ruo-Yu; Rieger, F. M.; Aharonian, F. A., E-mail: ruoyu@mpi-hd.mpg.de, E-mail: frank.rieger@mpi-hd.mpg.de, E-mail: aharon@mpi-hd.mpg.de [Max-Planck-Institut für Kernphysik, Saupfercheckweg 1, D-69117 Heidelberg (Germany)
2017-06-10
The origin of the extended X-ray emission in the large-scale jets of active galactic nuclei (AGNs) poses challenges to conventional models of acceleration and emission. Although electron synchrotron radiation is considered the most feasible radiation mechanism, the formation of the continuous large-scale X-ray structure remains an open issue. As astrophysical jets are expected to exhibit some turbulence and shearing motion, we here investigate the potential of shearing flows to facilitate an extended acceleration of particles and evaluate its impact on the resultant particle distribution. Our treatment incorporates systematic shear and stochastic second-order Fermi effects. We show that for typical parameters applicable to large-scale AGN jets, stochastic second-order Fermi acceleration, which always accompanies shear particle acceleration, can play an important role in facilitating the whole process of particle energization. We study the time-dependent evolution of the resultant particle distribution in the presence of second-order Fermi acceleration, shear acceleration, and synchrotron losses using a simple Fokker–Planck approach and provide illustrations for the possible emergence of a complex (multicomponent) particle energy distribution with different spectral branches. We present examples for typical parameters applicable to large-scale AGN jets, indicating the relevance of the underlying processes for understanding the extended X-ray emission and the origin of ultrahigh-energy cosmic rays.
Sparse Learning with Stochastic Composite Optimization.
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).
A retrodictive stochastic simulation algorithm
International Nuclear Information System (INIS)
Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.
2010-01-01
In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.
Stochastic processes and quantum theory
International Nuclear Information System (INIS)
Klauder, J.R.
1975-01-01
The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)
Forecasting financial asset processes: stochastic dynamics via learning neural networks.
Giebel, S; Rainer, M
2010-01-01
Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.
A concise course on stochastic partial differential equations
Prévôt, Claudia
2007-01-01
These lectures concentrate on (nonlinear) stochastic partial differential equations (SPDE) of evolutionary type. All kinds of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. To keep the technicalities minimal we confine ourselves to the case where the noise term is given by a stochastic integral w.r.t. a cylindrical Wiener process.But all results can be easily generalized to SPDE with more general noises such as, for instance, stochastic integral w.r.t. a continuous local martingale. There are basically three approaches to analyze SPDE: the "martingale measure approach", the "mild solution approach" and the "variational approach". The purpose of these notes is to give a concise and as self-contained as possible an introduction to the "variational approach". A large part of necessary background material, such as definitions and results from the theory of Hilbert spaces, are included in appendices.
Stochastic theory for classical and quantum mechanical systems
International Nuclear Information System (INIS)
Pena, L. de la; Cetto, A.M.
1975-01-01
From first principles a theory of stochastic processes in configuration space is formulated. The fundamental equations of the theory are an equation of motion which generalizes Newton's second law and an equation which expresses the condition of conservation of matter. Two types of stochastic motion are possible, both described by the same general equations, but leading in one case to classical Brownian motion behavior and in the other to quantum mechanical behavior. The Schroedinger equation, which is derived with no further assumption, is thus shown to describe a specific stochastic process. It is explicitly shown that only in the quantum mechanical process does the superposition of probability amplitudes give rise to interference phenomena; moreover, the presence of dissipative forces in the Brownian motion equations invalidates the superposition principle. At no point are any special assumptions made concerning the physical nature of the underlying stochastic medium, although some suggestions are discussed in the last section
Hybrid Semantics of Stochastic Programs with Dynamic Reconfiguration
Directory of Open Access Journals (Sweden)
Alberto Policriti
2009-10-01
Full Text Available We begin by reviewing a technique to approximate the dynamics of stochastic programs --written in a stochastic process algebra-- by a hybrid system, suitable to capture a mixed discrete/continuous evolution. In a nutshell, the discrete dynamics is kept stochastic while the continuous evolution is given in terms of ODEs, and the overall technique, therefore, naturally associates a Piecewise Deterministic Markov Process with a stochastic program. The speciﬁc contribution in this work consists in an increase of the ﬂexibility of the translation scheme, obtained by allowing a dynamic reconﬁguration of the degree of discreteness/continuity of the semantics. We also discuss the relationships of this approach with other hybrid simulation strategies for biochemical systems.
Stochastic Analysis with Financial Applications
Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi
2011-01-01
Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li
Synthesis of Zeolite NaA from Low Grade (High Impurities) Indonesian Natural Zeolite
Mustain, Asalil; Wibawa, Gede; Nais, Mukhammad Furoiddun; Falah, Miftakhul
2014-01-01
The zeolite NaA has been successfully synthesized from the low grade natural zeolite with high impurities. The synthesis method was started by mixing natural zeolite powder with NH4Cl aqueous solution in the reactor as pretreatment. The use of pretreatment was to reduce the impurities contents in the zeolite. The process was followed by alkaline fusion hydrothermal treatment to modify the framework structure of natural zeolite and reduce the SiO2/Al2O3 ratio. Finally, the synthesized zeolite ...
Workshop on the role of natural analogs in geologic disposal of high-level nuclear waste
International Nuclear Information System (INIS)
Murphy, W.M.; Kovach, L.A.
1995-01-01
A workshop on the Role of Natural Analogs in Geologic Disposal of High-Level Nuclear Waste (HLW) was held in San Antonio, Texas, on July 22-25, 1991. It was sponsored by the US Nuclear Regulatory Commission (NRC) and the Center for Nuclear Waste Regulatory Analyses (CNWRA). Invitations to the workshop were extended to a large number of individuals with a variety of technical and professional interests related to geologic disposal of nuclear waste and natural analog studies. The objective of the workshop was to examine the role of natural analog studies in performance assessment, site characterization, and prioritization of research related to geologic disposal of HLW
Natural radionuclides in food in an area with high concentrations of radionuclides
International Nuclear Information System (INIS)
Pereira, W.S.; Moraes, S.R.; Cavalcante, J.J.V.; Kelecom, A.; Silva, A.X. da; Lopez, J.M.; Filgueiras, R.; Carmo, A.S.
2017-01-01
Areas of high natural radiation expose the local population to doses greater than the world average. One of the routes of exposure is food intake. The activity concentration (AC) of 5 natural radionuclides in 7 types of foods was analyzed. The highest CA measured was 2.40 Bq.kg -1 for the U nat in the potato. The multivariate statistic identified two groups: (U nat e 232 Th) and [( 210 Pb and 228 Ra) and 226 Ra
Dai, Ke; He, Lvqin; Chang, Yung-Fu; Cao, Sanjie; Zhao, Qin; Huang, Xiaobo; Wu, Rui; Huang, Yong; Yan, Qigui; Han, Xinfeng; Ma, Xiaoping; Wen, Xintian; Wen, Yiping
2018-01-01
Haemophilus parasuis causes Glässer's disease and pneumonia, incurring serious economic losses in the porcine industry. In this study, natural competence was investigated in H. parasuis. We found competence genes in H. parasuis homologous to ones in Haemophilus influenzae and a high consensus battery of Sxy-dependent cyclic AMP (cAMP) receptor protein (CRP-S) regulons using bioinformatics. High rates of natural competence were found from the onset of stationary-phase growth condition to mid-stationary phase (OD600 from 0.29 to 1.735); this rapidly dropped off as cells reached mid-stationary phase (OD600 from 1.735 to 1.625). As a whole, bacteria cultured in liquid media were observed to have lower competence levels than those grown on solid media plates. We also revealed that natural transformation in this species is stable after 200 passages and is largely dependent on DNA concentration. Transformation competition experiments showed that heterogeneous DNA cannot outcompete intraspecific natural transformation, suggesting an endogenous uptake sequence or other molecular markers may be important in differentiating heterogeneous DNA. We performed qRT-PCR targeting multiple putative competence genes in an effort to compare bacteria pre-cultured in TSB++ vs. TSA++ and SC1401 vs. SH0165 to determine expression profiles of the homologs of competence-genes in H. influenzae. Taken together, this study is the first to investigate natural transformation in H. parasuis based on a highly naturally transformable strain SC1401. PMID:29473023
Stochastic Modeling of Past Volcanic Crises
Woo, Gordon
2018-01-01
The statistical foundation of disaster risk analysis is past experience. From a scientific perspective, history is just one realization of what might have happened, given the randomness and chaotic dynamics of Nature. Stochastic analysis of the past is an exploratory exercise in counterfactual history, considering alternative possible scenarios. In particular, the dynamic perturbations that might have transitioned a volcano from an unrest to an eruptive state need to be considered. The stochastic modeling of past volcanic crises leads to estimates of eruption probability that can illuminate historical volcanic crisis decisions. It can also inform future economic risk management decisions in regions where there has been some volcanic unrest, but no actual eruption for at least hundreds of years. Furthermore, the availability of a library of past eruption probabilities would provide benchmark support for estimates of eruption probability in future volcanic crises.
Energy Technology Data Exchange (ETDEWEB)
Hardwick, Robert J.; Vennin, Vincent; Wands, David [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO1 3FX (United Kingdom); Byrnes, Christian T.; Torrado, Jesús, E-mail: robert.hardwick@port.ac.uk, E-mail: vincent.vennin@port.ac.uk, E-mail: c.byrnes@sussex.ac.uk, E-mail: jesus.torrado@sussex.ac.uk, E-mail: david.wands@port.ac.uk [Department of Physics and Astronomy, University of Sussex, Brighton BN1 9QH (United Kingdom)
2017-10-01
We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.
International Nuclear Information System (INIS)
Hardwick, Robert J.; Vennin, Vincent; Wands, David; Byrnes, Christian T.; Torrado, Jesús
2017-01-01
We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.
Portfolio Optimization with Stochastic Dividends and Stochastic Volatility
Varga, Katherine Yvonne
2015-01-01
We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…
Stochastic hyperfine interactions modeling library
Zacate, Matthew O.; Evenson, William E.
2011-04-01
The stochastic hyperfine interactions modeling library (SHIML) provides a set of routines to assist in the development and application of stochastic models of hyperfine interactions. The library provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental techniques that measure hyperfine interactions can be calculated. The optimized vector and matrix operations of the BLAS and LAPACK libraries are utilized; however, there was a need to develop supplementary code to find an orthonormal set of (left and right) eigenvectors of complex, non-Hermitian matrices. In addition, example code is provided to illustrate the use of SHIML to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A can be neglected. Program summaryProgram title: SHIML Catalogue identifier: AEIF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 3 No. of lines in distributed program, including test data, etc.: 8224 No. of bytes in distributed program, including test data, etc.: 312 348 Distribution format: tar.gz Programming language: C Computer: Any Operating system: LINUX, OS X RAM: Varies Classification: 7.4 External routines: TAPP [1], BLAS [2], a C-interface to BLAS [3], and LAPACK [4] Nature of problem: In condensed matter systems, hyperfine methods such as nuclear magnetic resonance (NMR), Mössbauer effect (ME), muon spin rotation (μSR), and perturbed angular correlation spectroscopy (PAC) measure electronic and magnetic structure within Angstroms of nuclear probes through the hyperfine interaction. When
Stochastic ontogenetic growth model
West, B. J.; West, D.
2012-02-01
An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.
Stochastic calculus in physics
International Nuclear Information System (INIS)
Fox, R.F.
1987-01-01
The relationship of Ito-Stratonovich stochastic calculus to studies of weakly colored noise is explained. A functional calculus approach is used to obtain an effective Fokker-Planck equation for the weakly colored noise regime. In a smooth limit, this representation produces the Stratonovich version of the Ito-Stratonovich calculus for white noise. It also provides an approach to steady state behavior for strongly colored noise. Numerical simulation algorithms are explored, and a novel suggestion is made for efficient and accurate simulation of white noise equations
The stochastic quality calculus
DEFF Research Database (Denmark)
Zeng, Kebin; Nielson, Flemming; Nielson, Hanne Riis
2014-01-01
We introduce the Stochastic Quality Calculus in order to model and reason about distributed processes that rely on each other in order to achieve their overall behaviour. The calculus supports broadcast communication in a truly concurrent setting. Generally distributed delays are associated...... with the outputs and at the same time the inputs impose constraints on the waiting times. Consequently, the expected inputs may not be available when needed and therefore the calculus allows to express the absence of data.The communication delays are expressed by general distributions and the resulting semantics...
Stochastic conditional intensity processes
DEFF Research Database (Denmark)
Bauwens, Luc; Hautsch, Nikolaus
2006-01-01
model allows for a wide range of (cross-)autocorrelation structures in multivariate point processes. The model is estimated by simulated maximum likelihood (SML) using the efficient importance sampling (EIS) technique. By modeling price intensities based on NYSE trading, we provide significant evidence......In this article, we introduce the so-called stochastic conditional intensity (SCI) model by extending Russell’s (1999) autoregressive conditional intensity (ACI) model by a latent common dynamic factor that jointly drives the individual intensity components. We show by simulations that the proposed...... for a joint latent factor and show that its inclusion allows for an improved and more parsimonious specification of the multivariate intensity process...
Stochastic cooling for beginners
International Nuclear Information System (INIS)
Moehl, D.
1984-01-01
These two lectures have been prepared to give a simple introduction to the principles. In Part I we try to explain stochastic cooling using the time-domain picture which starts from the pulse response of the system. In Part II the discussion is repeated, looking more closely at the frequency-domain response. An attempt is made to familiarize the beginners with some of the elementary cooling equations, from the 'single particle case' up to equations which describe the evolution of the particle distribution. (orig.)
Trajectory averaging for stochastic approximation MCMC algorithms
Liang, Faming
2010-01-01
to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic
Stochastic models in reliability and maintenance
2002-01-01
Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to analyze the future behavior quantitatively. Reliability and maintainability technologies are of great interest and importance to the maintenance of such systems. Many mathematical models have been and will be proposed to describe reliability and maintainability systems by using the stochastic processes. The theme of this book is "Stochastic Models in Reliability and Main tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling. Chapter 1 is devoted to "Renewal Processes," under which cla...
Compressible cavitation with stochastic field method
Class, Andreas; Dumond, Julien
2012-11-01
Non-linear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally the simulation of pdf transport requires Monte-Carlo codes based on Lagrange particles or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic field method solving pdf transport based on Euler fields has been proposed which eliminates the necessity to mix Euler and Lagrange techniques or prescribed pdf assumptions. In the present work, part of the PhD Design and analysis of a Passive Outflow Reducer relying on cavitation, a first application of the stochastic field method to multi-phase flow and in particular to cavitating flow is presented. The application considered is a nozzle subjected to high velocity flow so that sheet cavitation is observed near the nozzle surface in the divergent section. It is demonstrated that the stochastic field formulation captures the wide range of pdf shapes present at different locations. The method is compatible with finite-volume codes where all existing physical models available for Lagrange techniques, presumed pdf or binning methods can be easily extended to the stochastic field formulation.
MCdevelop - a universal framework for Stochastic Simulations
Slawinska, M.; Jadach, S.
2011-03-01
://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 48 136 No. of bytes in distributed program, including test data, etc.: 355 698 Distribution format: tar.gz Programming language: ANSI C++ Computer: Any computer system or cluster with C++ compiler and UNIX-like operating system. Operating system: Most UNIX systems, Linux. The application programs were thoroughly tested under Ubuntu 7.04, 8.04 and CERN Scientific Linux 5. Has the code been vectorised or parallelised?: Tools (scripts) for optional parallelisation on a PC farm are included. RAM: 500 bytes Classification: 11.3 External routines: ROOT package version 5.0 or higher ( http://root.cern.ch/drupal/). Nature of problem: Developing any type of stochastic simulation program for high energy physics and other areas. Solution method: Object Oriented programming in C++ with added persistency mechanism, batch scripts for running on PC farms and Autotools.
International Nuclear Information System (INIS)
1993-01-01
The brochure contains abstracts of the papers presented at the symposium. The potential, performance and marketing problems of natural gas high-efficiency boiler systems are outlined, and new ideas are presented for gas utilities, producers of appliances, fitters, and chimneysweeps. 13 papers are available as separate regards in this database. (HW) [de
Chekroun, Mickaël D; Wang, Shouhong
2015-01-01
In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.
International Nuclear Information System (INIS)
Punjabi, Alkesh; Ali, Halima; Farhat, Hamidullah
2009-01-01
Extra terms are added to the generating function of the simple map (Punjabi et al 1992 Phys. Rev. Lett. 69 3322) to adjust shear of magnetic field lines in divertor tokamaks. From this new generating function, a higher shear map is derived from a canonical transformation. A continuous analog of the higher shear map is also derived. The method of maps (Punjabi et al 1994 J. Plasma Phys. 52 91) is used to calculate the average shear, stochastic broadening of the ideal separatrix near the X-point in the principal plane of the tokamak, loss of poloidal magnetic flux from inside the ideal separatrix, magnetic footprint on the collector plate, and its area, and the radial diffusion coefficient of magnetic field lines near the X-point. It is found that the width of the stochastic layer near the X-point and the loss of poloidal flux from inside the ideal separatrix scale linearly with average shear. The area of magnetic footprints scales roughly linearly with average shear. Linear scaling of the area is quite good when the average shear is greater than or equal to 1.25. When the average shear is in the range 1.1-1.25, the area of the footprint fluctuates (as a function of average shear) and scales faster than linear scaling. Radial diffusion of field lines near the X-point increases very rapidly by about four orders of magnitude as average shear increases from about 1.15 to 1.5. For higher values of average shear, diffusion increases linearly, and comparatively very slowly. The very slow scaling of the radial diffusion of the field can flatten the plasma pressure gradient near the separatrix, and lead to the elimination of type-I edge localized modes.
Effect of high-frequency excitation on natural frequencies of spinning discs
DEFF Research Database (Denmark)
Hansen, Morten Hartvig
2000-01-01
The effect of high-frequency, non-resonant parametric excitation on the low-frequency response of spinning discs is considered. The parametric excitation is obtained through a non-constant rotation speed, where the frequency of the pulsating overlay is much higher than the lowest natural frequenc......The effect of high-frequency, non-resonant parametric excitation on the low-frequency response of spinning discs is considered. The parametric excitation is obtained through a non-constant rotation speed, where the frequency of the pulsating overlay is much higher than the lowest natural...
Albert, Carlo; Ulzega, Simone; Stoop, Ruedi
2016-04-01
Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.
AA, stochastic precooling pickup
CERN PhotoLab
1980-01-01
The freshly injected antiprotons were subjected to fast stochastic "precooling". In this picture of a precooling pickup, the injection orbit is to the left, the stack orbit to the far right. After several seconds of precooling with the system's kickers (in momentum and in the vertical plane), the precooled antiprotons were transferred, by means of RF, to the stack tail, where they were subjected to further stochastic cooling in momentum and in both transverse planes, until they ended up, deeply cooled, in the stack core. During precooling, a shutter near the central orbit shielded the pickups from the signals emanating from the stack-core, whilst the stack-core was shielded from the violent action of the precooling kickers by a shutter on these. All shutters were opened briefly during transfer of the precooled antiprotons to the stack tail. Here, the shutter is not yet mounted. Precooling pickups and kickers had the same design, except that the kickers had cooling circuits and the pickups had none. Peering th...
Behavioral Stochastic Resonance
Freund, Jan A.; Schimansky-Geier, Lutz; Beisner, Beatrix; Neiman, Alexander; Russell, David F.; Yakusheva, Tatyana; Moss, Frank
2001-03-01
Zooplankton emit weak electric fields into the surrounding water that originate from their own muscular activities associated with swimming and feeding. Juvenile paddlefish prey upon single zooplankton by detecting and tracking these weak electric signatures. The passive electric sense in the fish is provided by an elaborate array of electroreceptors, Ampullae Lorenzini, spread over the surface of an elongated rostrum. We have previously shown that the fish use stochastic resonance to enhance prey capture near the detection threshold of their sensory system. But stochastic resonance requires an external source of electrical noise in order to function. The required noise can be provided by a swarm of plankton, for example Daphnia. Thus juvenile paddlefish can detect and attack single Daphnia as outliers in the vicinity of the swarm by making use of noise from the swarm itself. From the power spectral density of the noise plus the weak signal from a single Daphnia we calculate the signal-to-noise ratio and the Fisher information at the surface of the paddlefish's rostrum. The results predict a specific attack pattern for the paddlefish that appears to be experimentally testable.
Collisionally induced stochastic dynamics of fast ions in solids
International Nuclear Information System (INIS)
Burgdoerfer, J.
1989-01-01
Recent developments in the theory of excited state formation in collisions of fast highly charged ions with solids are reviewed. We discuss a classical transport theory employing Monte-Carlo sampling of solutions of a microscopic Langevin equation. Dynamical screening by the dielectric medium as well as multiple collisions are incorporated through the drift and stochastic forces in the Langevin equation. The close relationship between the extrinsically stochastic dynamics described by the Langevin and the intrinsic stochasticity in chaotic nonlinear dynamical systems is stressed. Comparison with experimental data and possible modification by quantum corrections are discussed. 49 refs., 11 figs
Stochastic programming with integer recourse
van der Vlerk, Maarten Hendrikus
1995-01-01
In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic
Thermal mixtures in stochastic mechanics
Energy Technology Data Exchange (ETDEWEB)
Guerra, F [Rome Univ. (Italy). Ist. di Matematica; Loffredo, M I [Salerno Univ. (Italy). Ist. di Fisica
1981-01-17
Stochastic mechanics is extended to systems in thermal equilibrium. The resulting stochastic processes are mixtures of Nelson processes. Their Markov property is investigated in some simple cases. It is found that in order to inforce Markov property the algebra of observable associated to the present must be suitably enlarged.
Stochastic Pi-calculus Revisited
DEFF Research Database (Denmark)
Cardelli, Luca; Mardare, Radu Iulian
2013-01-01
We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...
Alternative Asymmetric Stochastic Volatility Models
M. Asai (Manabu); M.J. McAleer (Michael)
2010-01-01
textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is
Stochastic ferromagnetism analysis and numerics
Brzezniak, Zdzislaw; Neklyudov, Mikhail; Prohl, Andreas
2013-01-01
This monograph examines magnetization dynamics at elevated temperatures which can be described by the stochastic Landau-Lifshitz-Gilbert equation (SLLG). Comparative computational studies with the stochastic model are included. Constructive tools such as e.g. finite element methods are used to derive the theoretical results, which are then used for computational studies.
International Nuclear Information System (INIS)
Minagawa, Keisuke; Fujita, Satoshi; Endo, Rokuro; Amemiya, Mitsuhiko
2009-01-01
In this study, vibration characteristics of mechanical structure having high natural frequency are investigated from the viewpoint of energy balance. Mechanical structures having high natural frequency in a nuclear power plant are generally designed statically and elastically. However it has been reported that fracture of ordinary piping is produced not by momentary large load but by cumulative fatigue damage. Therefore it is very important to grasp seismic performance dynamically by considering cyclic load. This paper deals with an investigation regarding seismic performance evaluation of high natural frequency mechanical structure. The energy balance equation that is one of valid methods for structural calculation is applied through the investigation. The main feature of the energy balance equation is that it explains accumulated information of motion. Therefore the energy balance equation is adequate for the investigation of the influence of cumulative load such as seismic response. In this paper, vibration experiment and simulation using sinusoidal waves and artificial seismic waves were examined in order to investigate relationship between natural frequency of structure and energy. As a result, we found that input energy decreases with an increase in the natural frequency. (author)
How do the high school biology textbooks introduce the nature of science?
Lee, Young H.
2007-05-01
Although helping students to achieve an adequate understanding of the nature of science has been a consistent goal for science education for over half a century, current research reveals that the majority of students and teachers have naive views of the nature of science (Abd-El-khalick & Akerson, 2004; Bianchini & Colburn, 2000). This problem could be attributed not only to the complex nature of science, but also to the way the nature of science is presented to students during instruction. Thus, research must be conducted to examine how the science is taught, especially in science textbooks, which are a major instructional resource for teaching science. The aim of this study was to conduct a content analysis of the first chapter of four high school biology textbooks, which typically discusses "What is science?" and "What is biology?" This research used a content analysis technique to analyze the four high school biology textbooks, using a conceptual framework that has been used often for science textbook analysis. This conceptual framework consists of four themes of the nature of science: (a) science as a body of knowledge, (b) science as a way of thinking, (c) science as a way of investigating, and (d) the interaction of science, technology, and society. For this study, the four-theme-framework was modified to incorporate descriptors from national-level documents, such as Science for All Americans (AAAS, 1990) Benchmarks for Science Literacy (AAAS, 1993) and the National Science Education Standards (NRC, 1996), as well as science education research reports. A scoring procedure was used that resulted in good to excellent intercoder agreement with Cohen's kappa (k) ranging from .63 to .96. The findings show that the patterns of presentation of the four themes of the nature of science in the four high school biology textbooks are similar across the different locations of data, text, figures, and assessments. On the other hand, the pattern of presentation of the four
Variance decomposition in stochastic simulators.
Le Maître, O P; Knio, O M; Moraes, A
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maître, O. P.; Knio, O. M.; Moraes, A.
2015-06-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Brownian motion and stochastic calculus
Karatzas, Ioannis
1998-01-01
This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...
Variance decomposition in stochastic simulators
Energy Technology Data Exchange (ETDEWEB)
Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro
2015-01-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Human genetics studies in areas of high natural radiation. IV. Research in radioactive areas
Energy Technology Data Exchange (ETDEWEB)
Freire-Maia, A [Faculdade de Ciencias Medicas e Biologicas de Botucatu (Brazil). Departamento de Genetica
1974-01-01
A review is made on researches performed in areas with high levels of natural radioactivity. Some considerations are made on the importance and difficulties involved in projects of this kind. Although there is no doubt that natural radioactivity is one of the causes of the so-called spontaneous mutations, the practical demonstration of this assertion is extremely complex. Projects trying to correlate high levels of natural radioactivity with the occurrence of cancer (in general, or specific), leukemia, congenital malformations (in general or specific), neuro-vegetative disturbs, sex ratio, mortality, and physical development, as well as other characteristics. Some researches with animals are also mentioned, and references are given for plant studies. A critical analysis is made of some works relating to human populations.
International Nuclear Information System (INIS)
Atilhan, Mert; Aparicio, Santiago; Ejaz, Saquib; Zhou, Jingjun; Al-Marri, Mohammed; Holste, James J.; Hall, Kenneth R.
2015-01-01
This paper includes high-accuracy density measurements and phase envelopes for deepwater natural gas mixtures. Mixtures primarily consist of (0.88 and 0.94) mole fraction methane and both mixtures includes heavy components (C 6+ ) more than 0.002 mole fraction. Experimental density and phase envelope data for deep and ultra-deep reservoir mixtures are scarce in literature and high accuracy measurements for such parameters for such natural gas-like mixtures are essential to validate the benchmark equations for custody transfer such as AGA8-DC92 and GERG-2008 equation of states (EOS). Thus, in this paper we report density and phase envelope experimental data via compact single-sinker magnetic suspension densimeter and isochoric apparatuses. Such data help gas industry to avoid retrograde condensation in natural gas pipelines
Human genetics studies in areas of high natural radiation.IV. Research in radioactive areas
International Nuclear Information System (INIS)
Freire-Maia, A.
1974-01-01
A review is made on researches performed in areas with high levels of natural radioactivity. Some considerations are made on the importance and difficulties involved in projects of this kind. Although there is no doubt that natural radioactivity is one of the causes of the so-called spontaneous mutations, the practical demonstration of this assertion is extremely complex. Projects trying to correlate high levels of natural radioactivity with the occurrence of cancer (in general, or specific), leukemia, congenital malformations (in general or specific), neuro-vegetative disturbs, sex ratio, mortality, and physical development, as well as other characteristics. Some researches with animals are also mentioned, and references are given for plant studies. A critical analysis is made of some works relating to human populations [pt
Multivariate moment closure techniques for stochastic kinetic models
International Nuclear Information System (INIS)
Lakatos, Eszter; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H.
2015-01-01
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 temporally 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
Multivariate moment closure techniques for stochastic kinetic models
Energy Technology Data Exchange (ETDEWEB)
Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H., E-mail: m.stumpf@imperial.ac.uk [Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ (United Kingdom)
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 temporally 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.
Processing bulk natural wood into a high-performance structural material
Song, Jianwei; Chen, Chaoji; Zhu, Shuze; Zhu, Mingwei; Dai, Jiaqi; Ray, Upamanyu; Li, Yiju; Kuang, Yudi; Li, Yongfeng; Quispe, Nelson; Yao, Yonggang; Gong, Amy; Leiste, Ulrich H.; Bruck, Hugh A.; Zhu, J. Y.; Vellore, Azhar; Li, Heng; Minus, Marilyn L.; Jia, Zheng; Martini, Ashlie; Li, Teng; Hu, Liangbing
2018-02-01
Synthetic structural materials with exceptional mechanical performance suffer from either large weight and adverse environmental impact (for example, steels and alloys) or complex manufacturing processes and thus high cost (for example, polymer-based and biomimetic composites). Natural wood is a low-cost and abundant material and has been used for millennia as a structural material for building and furniture construction. However, the mechanical performance of natural wood (its strength and toughness) is unsatisfactory for many advanced engineering structures and applications. Pre-treatment with steam, heat, ammonia or cold rolling followed by densification has led to the enhanced mechanical performance of natural wood. However, the existing methods result in incomplete densification and lack dimensional stability, particularly in response to humid environments, and wood treated in these ways can expand and weaken. Here we report a simple and effective strategy to transform bulk natural wood directly into a high-performance structural material with a more than tenfold increase in strength, toughness and ballistic resistance and with greater dimensional stability. Our two-step process involves the partial removal of lignin and hemicellulose from the natural wood via a boiling process in an aqueous mixture of NaOH and Na2SO3 followed by hot-pressing, leading to the total collapse of cell walls and the complete densification of the natural wood with highly aligned cellulose nanofibres. This strategy is shown to be universally effective for various species of wood. Our processed wood has a specific strength higher than that of most structural metals and alloys, making it a low-cost, high-performance, lightweight alternative.
Directory of Open Access Journals (Sweden)
Xiaona Leng
2017-06-01
Full Text Available Abstract This paper proposes a new nonlinear stochastic SIVS epidemic model with double epidemic hypothesis and Lévy jumps. The main purpose of this paper is to investigate the threshold dynamics of the stochastic SIVS epidemic model. By using the technique of a series of stochastic inequalities, we obtain sufficient conditions for the persistence in mean and extinction of the stochastic system and the threshold which governs the extinction and the spread of the epidemic diseases. Finally, this paper describes the results of numerical simulations investigating the dynamical effects of stochastic disturbance. Our results significantly improve and generalize the corresponding results in recent literatures. The developed theoretical methods and stochastic inequalities technique can be used to investigate the high-dimensional nonlinear stochastic differential systems.
Two decades of research in the Brazilian areas of high natural radioactivity
International Nuclear Information System (INIS)
Cullen, T.L.; Paschoa, A.S.; Franca, E.P.; Costa-Ribeiro, C.; Barcinski, M.; Eisenbud, M.
1980-01-01
A review is made of the most important findings obtained in the decades 1960-1980 in the Brazilian regions of high natural radioactivity. The research was carried out by three university groups: Pontificia Universidade Catolica do Rio de Janeiro, Universidade Federal do Rio de Janeiro and New York Universisity. (Author) [pt
The gyrotron - a natural source of high-power orbital angular momentum millimeter-wave beams
Thumm, M.; Sawant, A.; Choe, M. S.; Choi, E. M.
2017-08-01
Orbital angular momentum (OAM) of electromagnetic-wave beams provides further diversity to multiplexing in wireless communication. The present report shows that higher-order mode gyrotrons are natural sources of high-power OAM millimeter (mm) wave beams. The well-defined OAM of their rotating cavity modes operating at near cutoff frequency has been derived by photonic and electromagnetic wave approaches.
Effects of CO 2 on a High Performance Hollow-Fiber Membrane for Natural Gas Purification
Omole, Imona C.; Adams, Ryan T.; Miller, Stephen J.; Koros, William J.
2010-01-01
A 6FDA-based, cross-linkable polyimide was characterized in the form of a defect-free asymmetric hollow-fiber membrane. The novel membrane was cross-linked at various temperatures and tested for natural gas purification in the presence of high CO2
The Nature, Causes and Effects of School Violence in South African High Schools
Ncontsa, Vusumzi Nelson; Shumba, Almon
2013-01-01
We sought to investigate the nature, causes and effects of school violence in four South African high schools. A purposive sample of five principals, 80 learners and 20 educators was selected from the four schools used in the study. A sequential mixed method approach was used in this study; both questionnaires and interviews were used. The design…
Processing bulk natural wood into a high-performance structural material
Jianwei Song; Chaoji Chen; Shuze Zhu; Mingwei Zhu; Jiaqi Dai; Upamanyu Ray; Yiju Li; Yudi Kuang; Yongfeng Li; Nelson Quispe; Yonggang Yao; Amy Gong; Ulrich H. Leiste; Hugh A. Bruck; J. Y. Zhu; Azhar Vellore; Heng Li; Marilyn L. Minus; Zheng Jia; Ashlie Martini; Teng Li; Liangbing Hu
2018-01-01
Synthetic structural materials with exceptional mechanical performance suffer from either large weight and adverse environmental impact (for example, steels and alloys) or complex manufacturing processes and thus high cost (for example, polymer-based and biomimetic composites)1â8. Natural wood is a low-cost and abundant material and has been used...
Simulating biological processes: stochastic physics from whole cells to colonies
Earnest, Tyler M.; Cole, John A.; Luthey-Schulten, Zaida
2018-05-01
The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a ‘minimal cell’. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.
Modeling stochasticity and robustness in gene regulatory networks.
Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis
2009-06-15
Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.
Brain-inspired Stochastic Models and Implementations
Al-Shedivat, Maruan
2015-05-12
One of the approaches to building artificial intelligence (AI) is to decipher the princi- ples of the brain function and to employ similar mechanisms for solving cognitive tasks, such as visual perception or natural language understanding, using machines. The recent breakthrough, named deep learning, demonstrated that large multi-layer networks of arti- ficial neural-like computing units attain remarkable performance on some of these tasks. Nevertheless, such artificial networks remain to be very loosely inspired by the brain, which rich structures and mechanisms may further suggest new algorithms or even new paradigms of computation. In this thesis, we explore brain-inspired probabilistic mechanisms, such as neural and synaptic stochasticity, in the context of generative models. The two questions we ask here are: (i) what kind of models can describe a neural learning system built of stochastic components? and (ii) how can we implement such systems e ̆ciently? To give specific answers, we consider two well known models and the corresponding neural architectures: the Naive Bayes model implemented with a winner-take-all spiking neural network and the Boltzmann machine implemented in a spiking or non-spiking fashion. We propose and analyze an e ̆cient neuromorphic implementation of the stochastic neu- ral firing mechanism and study the e ̄ects of synaptic unreliability on learning generative energy-based models implemented with neural networks.
High-temperature apparatus for chaotic mixing of natural silicate melts
Energy Technology Data Exchange (ETDEWEB)
Morgavi, D.; Petrelli, M.; Vetere, F. P.; González-García, D.; Perugini, D., E-mail: diego.perugini@unipg.it [Department of Physics and Geology, Petro-Volcanology Research Group (PVRG), University of Perugia, Piazza Università, Perugia 06100 (Italy)
2015-10-15
A unique high-temperature apparatus was developed to trigger chaotic mixing at high-temperature (up to 1800 °C). This new apparatus, which we term Chaotic Magma Mixing Apparatus (COMMA), is designed to carry out experiments with high-temperature and high-viscosity (up to 10{sup 6} Pa s) natural silicate melts. This instrument allows us to follow in time and space the evolution of the mixing process and the associated modulation of chemical composition. This is essential to understand the dynamics of magma mixing and related chemical exchanges. The COMMA device is tested by mixing natural melts from Aeolian Islands (Italy). The experiment was performed at 1180 °C using shoshonite and rhyolite melts, resulting in a viscosity ratio of more than three orders of magnitude. This viscosity ratio is close to the maximum possible ratio of viscosity between high-temperature natural silicate melts. Results indicate that the generated mixing structures are topologically identical to those observed in natural volcanic rocks highlighting the enormous potential of the COMMA to replicate, as a first approximation, the same mixing patterns observed in the natural environment. COMMA can be used to investigate in detail the space and time development of magma mixing providing information about this fundamental petrological and volcanological process that would be impossible to investigate by direct observations. Among the potentials of this new experimental device is the construction of empirical relationships relating the mixing time, obtained through experimental time series, and chemical exchanges between the melts to constrain the mixing-to-eruption time of volcanic systems, a fundamental topic in volcanic hazard assessment.
High-temperature apparatus for chaotic mixing of natural silicate melts
International Nuclear Information System (INIS)
Morgavi, D.; Petrelli, M.; Vetere, F. P.; González-García, D.; Perugini, D.
2015-01-01
A unique high-temperature apparatus was developed to trigger chaotic mixing at high-temperature (up to 1800 °C). This new apparatus, which we term Chaotic Magma Mixing Apparatus (COMMA), is designed to carry out experiments with high-temperature and high-viscosity (up to 10 6 Pa s) natural silicate melts. This instrument allows us to follow in time and space the evolution of the mixing process and the associated modulation of chemical composition. This is essential to understand the dynamics of magma mixing and related chemical exchanges. The COMMA device is tested by mixing natural melts from Aeolian Islands (Italy). The experiment was performed at 1180 °C using shoshonite and rhyolite melts, resulting in a viscosity ratio of more than three orders of magnitude. This viscosity ratio is close to the maximum possible ratio of viscosity between high-temperature natural silicate melts. Results indicate that the generated mixing structures are topologically identical to those observed in natural volcanic rocks highlighting the enormous potential of the COMMA to replicate, as a first approximation, the same mixing patterns observed in the natural environment. COMMA can be used to investigate in detail the space and time development of magma mixing providing information about this fundamental petrological and volcanological process that would be impossible to investigate by direct observations. Among the potentials of this new experimental device is the construction of empirical relationships relating the mixing time, obtained through experimental time series, and chemical exchanges between the melts to constrain the mixing-to-eruption time of volcanic systems, a fundamental topic in volcanic hazard assessment
How daylight influences high-order chromatic descriptors in natural images.
Ojeda, Juan; Nieves, Juan Luis; Romero, Javier
2017-07-01
Despite the global and local daylight changes naturally occurring in natural scenes, the human visual system usually adapts quite well to those changes, developing a stable color perception. Nevertheless, the influence of daylight in modeling natural image statistics is not fully understood and has received little attention. The aim of this work was to analyze the influence of daylight changes in different high-order chromatic descriptors (i.e., color volume, color gamut, and number of discernible colors) derived from 350 color images, which were rendered under 108 natural illuminants with Correlated Color Temperatures (CCT) from 2735 to 25,889 K. Results suggest that chromatic and luminance information is almost constant and does not depend on the CCT of the illuminant for values above 14,000 K. Nevertheless, differences between the red-green and blue-yellow image components were found below that CCT, with most of the statistical descriptors analyzed showing local extremes in the range 2950 K-6300 K. Uniform regions and areas of the images attracting observers' attention were also considered in this analysis and were characterized by their patchiness index and their saliency maps. Meanwhile, the results of the patchiness index do not show a clear dependence on CCT, and it is remarkable that a significant reduction in the number of discernible colors (58% on average) was found when the images were masked with their corresponding saliency maps. Our results suggest that chromatic diversity, as defined in terms of the discernible colors, can be strongly reduced when an observer scans a natural scene. These findings support the idea that a reduction in the number of discernible colors will guide visual saliency and attention. Whatever the modeling is mediating the neural representation of natural images, natural image statistics, it is clear that natural image statistics should take into account those local maxima and minima depending on the daylight illumination and
Morgan, Byron JT; Tanner, Martin Abba; Carlin, Bradley P
2008-01-01
Introduction and Examples Introduction Examples of data sets Basic Model Fitting Introduction Maximum-likelihood estimation for a geometric model Maximum-likelihood for the beta-geometric model Modelling polyspermy Which model? What is a model for? Mechanistic models Function Optimisation Introduction MATLAB: graphs and finite differences Deterministic search methods Stochastic search methods Accuracy and a hybrid approach Basic Likelihood ToolsIntroduction Estimating standard errors and correlations Looking at surfaces: profile log-likelihoods Confidence regions from profiles Hypothesis testing in model selectionScore and Wald tests Classical goodness of fit Model selection biasGeneral Principles Introduction Parameterisation Parameter redundancy Boundary estimates Regression and influence The EM algorithm Alternative methods of model fitting Non-regular problemsSimulation Techniques Introduction Simulating random variables Integral estimation Verification Monte Carlo inference Estimating sampling distributi...
Stochastic population theories
Ludwig, Donald
1974-01-01
These notes serve as an introduction to stochastic theories which are useful in population biology; they are based on a course given at the Courant Institute, New York, in the Spring of 1974. In order to make the material. accessible to a wide audience, it is assumed that the reader has only a slight acquaintance with probability theory and differential equations. The more sophisticated topics, such as the qualitative behavior of nonlinear models, are approached through a succession of simpler problems. Emphasis is placed upon intuitive interpretations, rather than upon formal proofs. In most cases, the reader is referred elsewhere for a rigorous development. On the other hand, an attempt has been made to treat simple, useful models in some detail. Thus these notes complement the existing mathematical literature, and there appears to be little duplication of existing works. The authors are indebted to Miss Jeanette Figueroa for her beautiful and speedy typing of this work. The research was supported by the Na...
Propagator of stochastic electrodynamics
International Nuclear Information System (INIS)
Cavalleri, G.
1981-01-01
The ''elementary propagator'' for the position of a free charged particle subject to the zero-point electromagnetic field with Lorentz-invariant spectral density proportionalω 3 is obtained. The nonstationary process for the position is solved by the stationary process for the acceleration. The dispersion of the position elementary propagator is compared with that of quantum electrodynamics. Finally, the evolution of the probability density is obtained starting from an initial distribution confined in a small volume and with a Gaussian distribution in the velocities. The resulting probability density for the position turns out to be equal, to within radiative corrections, to psipsi* where psi is the Kennard wave packet. If the radiative corrections are retained, the present result is new since the corresponding expression in quantum electrodynamics has not yet been found. Besides preceding quantum electrodynamics for this problem, no renormalization is required in stochastic electrodynamics
Past and present views in the approach to the problem of high natural background areas
International Nuclear Information System (INIS)
Mastino, G.G.
1982-01-01
High natural background areas are of great interest because they present anomalous conditions in their geological and geochemical features and consequently in the background radiation levels. High natural background areas have been recognised as representing a valid field of investigation for assessing the effects induced by low-level exposures. Such an approach represents the first attempt to draw an environmental impact evaluation, even if focussed on a single potentially harmful parameter only. Past and current studies on High Background Radiation Areas are reviewed with special emphasis on the ongoing programs and prospectives; their significance is discussed on the basis of the sectorial approach mostly used in the environmental studies. A more complete approach is suggested based on the impact evaluation and extention to all the potentially harmful environmental factors
Pauk, Volodymyr; Barták, Petr; Lemr, Karel
2014-12-01
High-performance liquid chromatography plays an important role in analysis of historical organic colorants. A number of papers have been published in this field over the last 30 years. Classification of the most commonly used natural dyes and an overview of high-performance liquid chromatography methods with main focus on recent works (2008 to the beginning of 2014) are provided. The review deals with an entire analytical protocol covering sample preparation, chromatographic separation, and suitable detection (UV/visible and fluorescent spectroscopy and mass spectrometric techniques). High-performance liquid chromatography has been successfully used in the complete characterization of some organic dyestuffs present in historical and art objects. The possibilities and difficulties for identification of natural sources of historical colorants are also discussed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
International Nuclear Information System (INIS)
Ouellette, P.
2001-01-01
In an effort to reduce Greenhouse Gases, Westport Innovations is developing a high pressure direct injection (HPDI) technology for gaseous fuels. This technology adapts the diesel cycle for gaseous fuels, since the diesel cycle provides high efficiency, high low-speed torque, fast transient capabilities and reliability. Because of their high efficiency, diesels are very favorable from a Greenhouse Gas (GHG) point of view, however they remain challenged by high nitrogen oxides (NOx) and particulate matter (PM) emissions. When directly injecting natural gas, NOx and PM emissions can be reduced by approximately 50% while maintaining the performance of the diesel engine. This allows the use of abundant and historically cheaper natural gas. Because of its lower carbon content per unit energy, natural gas also offers further GHG reduction over the diesel if the efficiency is preserved and if methane emissions are low. This paper discusses development efforts at Westport for several applications including on-highway trucks, light-duty delivery trucks and power generation
Lectures on Dynamics of Stochastic Systems
Klyatskin, Valery I
2010-01-01
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. Models naturally render to statistical description, where random processes and fields express the input parameters and solutions. The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of the system and initial data. This book is a revised a
Neutron stochastic transport theory with delayed neutrons
International Nuclear Information System (INIS)
Munoz-Cobo, J.L.; Verdu, G.
1987-01-01
From the stochastic transport theory with delayed neutrons, the Boltzmann transport equation with delayed neutrons for the average flux emerges in a natural way without recourse to any approximation. From this theory a general expression is obtained for the Feynman Y-function when delayed neutrons are included. The single mode approximation for the particular case of a subcritical assembly is developed, and it is shown that Y-function reduces to the familiar expression quoted in many books, when delayed neutrons are not considered, and spatial and source effects are not included. (author)
Predicting extinction rates in stochastic epidemic models
International Nuclear Information System (INIS)
Schwartz, Ira B; Billings, Lora; Dykman, Mark; Landsman, Alexandra
2009-01-01
We investigate the stochastic extinction processes in a class of epidemic models. Motivated by the process of natural disease extinction in epidemics, we examine the rate of extinction as a function of disease spread. We show that the effective entropic barrier for extinction in a susceptible–infected–susceptible epidemic model displays scaling with the distance to the bifurcation point, with an unusual critical exponent. We make a direct comparison between predictions and numerical simulations. We also consider the effect of non-Gaussian vaccine schedules, and show numerically how the extinction process may be enhanced when the vaccine schedules are Poisson distributed
Stochastic estimation of electricity consumption
International Nuclear Information System (INIS)
Kapetanovic, I.; Konjic, T.; Zahirovic, Z.
1999-01-01
Electricity consumption forecasting represents a part of the stable functioning of the power system. It is very important because of rationality and increase of control process efficiency and development planning of all aspects of society. On a scientific basis, forecasting is a possible way to solve problems. Among different models that have been used in the area of forecasting, the stochastic aspect of forecasting as a part of quantitative models takes a very important place in applications. ARIMA models and Kalman filter as stochastic estimators have been treated together for electricity consumption forecasting. Therefore, the main aim of this paper is to present the stochastic forecasting aspect using short time series. (author)
Linear stochastic neutron transport theory
International Nuclear Information System (INIS)
Lewins, J.
1978-01-01
A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)
Stochasticity in the Josephson map
International Nuclear Information System (INIS)
Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.
1996-04-01
The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)
Introduction to stochastic dynamic programming
Ross, Sheldon M; Lukacs, E
1983-01-01
Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the
Directory of Open Access Journals (Sweden)
Elston Timothy C
2004-03-01
Full Text Available Abstract Background Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks. Results We have developed the software package Biochemical Network Stochastic Simulator (BioNetS for efficientlyand accurately simulating stochastic models of biochemical networks. BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous for each chemical species in the network. The discrete variables are simulated using an efficient implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solvesthe appropriate chemical Langevin equations. The software package has been developed to scale efficiently with network size, thereby allowing large systems to be studied. BioNetS runs as a BioSpice agent and can be downloaded from http://www.biospice.org. BioNetS also can be run as a stand alone package. All the required files are accessible from http://x.amath.unc.edu/BioNetS. Conclusions We have developed BioNetS to be a reliable tool for studying the stochastic dynamics of large biochemical networks. Important features of BioNetS are its ability to handle hybrid models that consist of both continuous and discrete random variables and its ability to model cell growth and division. We have verified the accuracy and efficiency of the numerical methods by considering several test systems.
Polymer Electrolyte Prepared from Highly Deproteinized Natural Rubber Having Epoxy Group
Klinklai, W.; Kawahara, S.; Isono, Y.; Mizumo, T.; Yoshizawa, M.; Ohno, H.
Deproteinized natural rubber having epoxy group (EDPNR) was applied to transport Li+ as a solid polymer electrolyte. The deproteinized natural rubber, incubated with proteolytic enzyme and surfactant, was subjected to epoxidation followed by oxidative depolymerization in latex stage. The resulting rubber was proved to be a liquid deproteinized natural rubber (LEDPNR) having polar epoxy groups, low Tg, low Mn and well-defined terminal units. Ionic conductivity of LEDPNR mixed with alkali metal salts was investigated through impedance analysis to clarify an effect of proteins present in the rubber. The ionic conductivity of the resulting LEDPNR depended on the kind of salts, their concentrations and temperature. The ionic conductivity of LEDPNR/lithium bis(trifluoromethan sulfonyl)imide (LiTFSI) was higher than that of LEDPNR/ lithium perchlorate (LiClO4). The difference in the ionic conductivity was attributed to the solubility of the salts as results of both high-resolution solid-state 13C-NMR spectroscopy and measurements of spin-lattice relaxation time. The conductivity of LEDPNR/LiTFSI was also dependent upon concentrations of LiTFSI and it reached the highest value at 20 wt%, which was different from the monotonic increase in the Li+ conductivity of liquid epoxidized natural rubber prepared from untreated natural rubber.
Functional Abstraction of Stochastic Hybrid Systems
Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.
2006-01-01
The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways
An introduction to probability and stochastic processes
Melsa, James L
2013-01-01
Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.
MONTE CARLO SIMULATION OF MULTIFOCAL STOCHASTIC SCANNING SYSTEM
Directory of Open Access Journals (Sweden)
LIXIN LIU
2014-01-01
Full Text Available Multifocal multiphoton microscopy (MMM has greatly improved the utilization of excitation light and imaging speed due to parallel multiphoton excitation of the samples and simultaneous detection of the signals, which allows it to perform three-dimensional fast fluorescence imaging. Stochastic scanning can provide continuous, uniform and high-speed excitation of the sample, which makes it a suitable scanning scheme for MMM. In this paper, the graphical programming language — LabVIEW is used to achieve stochastic scanning of the two-dimensional galvo scanners by using white noise signals to control the x and y mirrors independently. Moreover, the stochastic scanning process is simulated by using Monte Carlo method. Our results show that MMM can avoid oversampling or subsampling in the scanning area and meet the requirements of uniform sampling by stochastically scanning the individual units of the N × N foci array. Therefore, continuous and uniform scanning in the whole field of view is implemented.
Stochastic models for predicting pitting corrosion damage of HLRW containers
International Nuclear Information System (INIS)
Henshall, G.A.
1991-10-01
Stochastic models for predicting aqueous pitting corrosion damage of high-level radioactive-waste containers are described. These models could be used to predict the time required for the first pit to penetrate a container and the increase in the number of breaches at later times, both of which would be useful in the repository system performance analysis. Monte Carlo implementations of the stochastic models are described, and predictions of induction time, survival probability and pit depth distributions are presented. These results suggest that the pit nucleation probability decreases with exposure time and that pit growth may be a stochastic process. The advantages and disadvantages of the stochastic approach, methods for modeling the effects of environment, and plans for future work are discussed
Strategies for dereplication of natural compounds using high-resolution tandem mass spectrometry.
Kind, Tobias; Fiehn, Oliver
2017-09-01
Complete structural elucidation of natural products is commonly performed by nuclear magnetic resonance spectroscopy (NMR), but annotating compounds to most likely structures using high-resolution tandem mass spectrometry is a faster and feasible first step. The CASMI contest 2016 (Critical Assessment of Small Molecule Identification) provided spectra of eighteen compounds for the best manual structure identification in the natural products category. High resolution precursor and tandem mass spectra (MS/MS) were available to characterize the compounds. We used the Seven Golden Rules, Sirius2 and MS-FINDER software for determination of molecular formulas, and then we queried the formulas in different natural product databases including DNP, UNPD, ChemSpider and REAXYS to obtain molecular structures. We used different in-silico fragmentation tools including CFM-ID, CSI:FingerID and MS-FINDER to rank these compounds. Additional neutral losses and product ion peaks were manually investigated. This manual and time consuming approach allowed for the correct dereplication of thirteen of the eighteen natural products.
Natural analogues to the conditions around a final repository for high-level radioactive waste
International Nuclear Information System (INIS)
Smellie, J.A.T.
1984-12-01
This report documents the proceedings resulting from a Workshop held at Lake Geneva, Wisconsin, USA, from 1-3 October, 1984. The theme of the Workshop was entitled 'Natural analogues to the conditions around a final repository for high-level radioactive waste', and was restricted to ultimate disposal in a crystalline bedrock environment. The Workshop provided an important first step in co-ordinating and focussing different national and individual interests and approaches towards natural analogue studies. One of the points highlighted at the concluding forum of the meeting was the necessity to first define the geochemical processes which are assumed to occur after disposal of the radioactive waste, and then locate suitable analogue systems which can be used to test the mechanisms of one, or a simple combination of these geochemical processes. Even accepting that the choice of which geochemical process(es) to be selected for validation will be sensitive to individual national disposal strategies, farfield radionuclide retardation mechanisms in the geosphere were considered to be a central topic of importance, and should therefore be given high priority. At this early stage in the development of natural analogue studies it was not possible to cover all the important aspects. In retrospect, the role of the models should have received more attention; bridging the gap between geoscientists and the modellers was seen as being of prime importance in future meetings of this nature. (author)
Aguda, Adeleke H; Lavallee, Vincent; Cheng, Ping; Bott, Tina M; Meimetis, Labros G; Law, Simon; Nguyen, Nham T; Williams, David E; Kaleta, Jadwiga; Villanueva, Ivan; Davies, Julian; Andersen, Raymond J; Brayer, Gary D; Brömme, Dieter
2016-08-26
Natural products are an important source of novel drug scaffolds. The highly variable and unpredictable timelines associated with isolating novel compounds and elucidating their structures have led to the demise of exploring natural product extract libraries in drug discovery programs. Here we introduce affinity crystallography as a new methodology that significantly shortens the time of the hit to active structure cycle in bioactive natural product discovery research. This affinity crystallography approach is illustrated by using semipure fractions of an actinomycetes culture extract to isolate and identify a cathepsin K inhibitor and to compare the outcome with the traditional assay-guided purification/structural analysis approach. The traditional approach resulted in the identification of the known inhibitor antipain (1) and its new but lower potency dehydration product 2, while the affinity crystallography approach led to the identification of a new high-affinity inhibitor named lichostatinal (3). The structure and potency of lichostatinal (3) was verified by total synthesis and kinetic characterization. To the best of our knowledge, this is the first example of isolating and characterizing a potent enzyme inhibitor from a partially purified crude natural product extract using a protein crystallographic approach.
Stochastic processes and applications diffusion processes, the Fokker-Planck and Langevin equations
Pavliotis, Grigorios A
2014-01-01
This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to eq...
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Computational Methods in Stochastic Dynamics Volume 2
Stefanou, George; Papadopoulos, Vissarion
2013-01-01
The considerable influence of inherent uncertainties on structural behavior has led the engineering community to recognize the importance of a stochastic approach to structural problems. Issues related to uncertainty quantification and its influence on the reliability of the computational models are continuously gaining in significance. In particular, the problems of dynamic response analysis and reliability assessment of structures with uncertain system and excitation parameters have been the subject of continuous research over the last two decades as a result of the increasing availability of powerful computing resources and technology. This book is a follow up of a previous book with the same subject (ISBN 978-90-481-9986-0) and focuses on advanced computational methods and software tools which can highly assist in tackling complex problems in stochastic dynamic/seismic analysis and design of structures. The selected chapters are authored by some of the most active scholars in their respective areas and...
Parameter estimation in stochastic differential equations
Bishwal, Jaya P N
2008-01-01
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume.
Polonium-210 and Lead-210 in marine biota from a coastal region with high natural radioactivity
International Nuclear Information System (INIS)
Zafrul Kabir, M.; Deeba, Farah; Hossain, Sushmita; Fharim, Massoud; Md Moniruzzaman; Carvalho, Fernando P.; Oliveira, João M.; Malta, M.; Silva, L.
2013-01-01
Coastal sediments and marine fish from a region with high natural radioactivity in Cox Bazar Bangladesh, were analyzed in order to investigate the levels of naturally occurring radionuclides. Sediment from the sea shore in high ambient radiation dose rate areas contained naturally occurring radionuclides at high concentrations. These sediments displayed 226 Ra, 232 Th and 235 U activity concentrations of 2184 ± 88 Bq kg -1 dry weight (d.w.), 3808 ± 200 Bq kg -1 (d.w.) and 123 ± 15 Bq kg -1 (d.w.), respectively. In contrast with these high values, radionuclide concentrations in sand from other areas of the Cox's Bazar coast were as low as 42 ± 3, 70 ± 4 and < 8 Bq kg -1 (d.w.) for the same radionuclides, respectively, which are comparable to concentrations determined in many coastal areas elsewhere. The presence of sand deposits with high concentration of uranium series radionuclides could potentially originate high accumulation of alpha emitting radionuclides such as 210 Po in marine biota, and food chain transfer to man. 210 Po is a major contributor to the radiation dose both in marine organisms and sea food consumers. Determination of 210 Po in marine fish and shrimp from the area lead to concentration values ranging from 4.5±0.3 to 124±3 Bq kg -1 (d.w.) in fish and 82.9±1.6 Bq kg -1 (d.w.) in shrimp. Similar concentrations are commonly reported in marine biota from several regions. Therefore, in spite of the deposits of heavy mineral sands containing high concentrations of radionuclides such as 210 Pb and 210 Po no significant raise in the accumulation of these radionuclides in biota seems to occur, which suggests that radionuclides are tightly bound in sediment grains and are not significantly bioavailable. (author)
Robust authentication through stochastic femtosecond laser filament induced scattering surfaces
International Nuclear Information System (INIS)
Zhang, Haisu; Tzortzakis, Stelios
2016-01-01
We demonstrate a reliable authentication method by femtosecond laser filament induced scattering surfaces. The stochastic nonlinear laser fabrication nature results in unique authentication robust properties. This work provides a simple and viable solution for practical applications in product authentication, while also opens the way for incorporating such elements in transparent media and coupling those in integrated optical circuits.
BUNCHED BEAM STOCHASTIC COOLING SIMULAITONS AND COMPARISON WITH DATA
Energy Technology Data Exchange (ETDEWEB)
BLASKIEWICZ,M.; BRENNAN, J.M.
2007-09-10
With the experimental success of longitudinal, bunched beam stochastic cooling in RHIC it is natural to ask whether the system works as well as it might and whether upgrades or new systems are warranted. A computer code, very similar to those used for multi-particle coherent instability simulations, has been written and is being used to address these questions.
Robust authentication through stochastic femtosecond laser filament induced scattering surfaces
Energy Technology Data Exchange (ETDEWEB)
Zhang, Haisu [Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas, Heraklion 71110 (Greece); Tzortzakis, Stelios, E-mail: stzortz@iesl.forth.gr [Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas, Heraklion 71110 (Greece); Materials Science and Technology Department, University of Crete, 71003 Heraklion (Greece); Science Program, Texas A& M University at Qatar, P.O. Box 23874, Doha (Qatar)
2016-05-23
We demonstrate a reliable authentication method by femtosecond laser filament induced scattering surfaces. The stochastic nonlinear laser fabrication nature results in unique authentication robust properties. This work provides a simple and viable solution for practical applications in product authentication, while also opens the way for incorporating such elements in transparent media and coupling those in integrated optical circuits.
Characterizing economic trends by Bayesian stochastic model specification search
DEFF Research Database (Denmark)
Grassi, Stefano; Proietti, Tommaso
We extend a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. In particular, we focus on autoregressive models with possibly time-varying intercept and slope and decide on ...
Natural geochemical analogues of the near field of high-level nuclear waste repositories
International Nuclear Information System (INIS)
Apps, J.A.
1995-01-01
United States practice has been to design high-level nuclear waste (HLW) geological repositories with waste densities sufficiently high that repository temperatures surrounding the waste will exceed 100 degrees C and could reach 250 degrees C. Basalt and devitrified vitroclastic tuff are among the host rocks considered for waste emplacement. Near-field repository thermal behavior and chemical alteration in such rocks is expected to be similar to that observed in many geothermal systems. Therefore, the predictive modeling required for performance assessment studies of the near field could be validated and calibrated using geothermal systems as natural analogues. Examples are given which demonstrate the need for refinement of the thermodynamic databases used in geochemical modeling of near-field natural analogues and the extent to which present models can predict conditions in geothermal fields
Implementing High-Performance Geometric Multigrid Solver with Naturally Grained Messages
Energy Technology Data Exchange (ETDEWEB)
Shan, H; Williams, S; Zheng, Y; Kamil, A; Yelick, K
2015-10-26
Structured-grid linear solvers often require manually packing and unpacking of communication data to achieve high performance.Orchestrating this process efficiently is challenging, labor-intensive, and potentially error-prone.In this paper, we explore an alternative approach that communicates the data with naturally grained messagesizes without manual packing and unpacking. This approach is the distributed analogue of shared-memory programming, taking advantage of the global addressspace in PGAS languages to provide substantial programming ease. However, its performance may suffer from the large number of small messages. We investigate theruntime support required in the UPC ++ library for this naturally grained version to close the performance gap between the two approaches and attain comparable performance at scale using the High-Performance Geometric Multgrid (HPGMG-FV) benchmark as a driver.
On the probability distribution of the stochastic saturation scale in QCD
International Nuclear Information System (INIS)
Marquet, C.; Soyez, G.; Xiao Bowen
2006-01-01
It was recently noticed that high-energy scattering processes in QCD have a stochastic nature. An event-by-event scattering amplitude is characterised by a saturation scale which is a random variable. The statistical ensemble of saturation scales formed with all the events is distributed according to a probability law whose cumulants have been recently computed. In this work, we obtain the probability distribution from the cumulants. We prove that it can be considered as Gaussian over a large domain that we specify and our results are confirmed by numerical simulations
Stochastic backgrounds of gravitational waves
International Nuclear Information System (INIS)
Maggiore, M.
2001-01-01
We review the motivations for the search for stochastic backgrounds of gravitational waves and we compare the experimental sensitivities that can be reached in the near future with the existing bounds and with the theoretical predictions. (author)
Stochastic theories of quantum mechanics
International Nuclear Information System (INIS)
De la Pena, L.; Cetto, A.M.
1991-01-01
The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)
International Nuclear Information System (INIS)
Faris, W.G.
1981-01-01
Dankel has shown how to incorporate spin into stochastic mechanics. The resulting non-local hidden variable theory gives an appealing picture of spin correlation experiments in which Bell's inequality is violated. (orig.)
Statistical inference for stochastic processes
National Research Council Canada - National Science Library
Basawa, Ishwar V; Prakasa Rao, B. L. S
1980-01-01
The aim of this monograph is to attempt to reduce the gap between theory and applications in the area of stochastic modelling, by directing the interest of future researchers to the inference aspects...
Stochastic singular optics (Conference paper)
CSIR Research Space (South Africa)
Roux, FS
2014-09-01
Full Text Available The study of optical vortices in stochastic optical fields involves various quantities, including the vortex density and topological charge density, that are defined in terms of local expectation values of distributions of optical vortices...
International Nuclear Information System (INIS)
Mollah, A.S.; Rahman, M.M.; Koddus, M.A.; Husain, S.R.; Malek, M.A.
1987-01-01
High natural background radiation levels at the Cox's Bazar coastal areas in Bangladesh were measured by LiF (TLD-100) dosemeters. The dose rates varied from 2621 to 35391 μGy.y -1 with a mean of 11968 μGy.y -1 . The average dose rate is found to significantly higher than the world average value. In order to formulate appropriate guidelines for radiation protection of the population in this area, the necessary recommendations are described. (author)
Stochastic massless fields I: Integer spin
International Nuclear Information System (INIS)
Lim, S.C.
1981-04-01
Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)
Control of high natural activity building materials and land areas in the Nordic countries
International Nuclear Information System (INIS)
Mjoenes, L.
1997-01-01
Enhanced levels of natural radioactivity in the ground can cause problems with high concentrations of indoor 222 Rn, elevated levels of gamma radiation and natural radioactive elements in drinking water. Of the Nordic countries it is essentially Finland, Norway and Sweden that have problems with enhanced natural radioactivity in the ground and in building materials. Finland and Sweden have among the highest mean 222 Rn concentrations in dwellings in the world, 123 Bq m -3 and 108 Bq m -3 with a corresponding mean annual effective dose of about 2 mSv. In Sweden about 500,000 and in Finland and Norway about 200,000 persons get their drinking water from wells drilled in bedrock. The water from a large number of these wells contain elevated levels of naturally occurring radioactive elements, primarily 222 Rn. The action levels for 222 Rn in dwellings and above-ground workplaces are essentially the same in Finland, Norway and Sweden: 200 Bq m -3 for new buildings and 400 Bq m -3 for existing buildings. For mines and underground excavations, however, there are some differences. The treatment of gamma emitting natural radionuclides in building materials etc. is similar, although there are differences in the degree of control. The action levels for 222 Rn in drinking water differ from 100 Bq l -1 to 500 Bq l -1 . The action level in Finland has the form of an activity index that restricts also other radioactive nuclides. Denmark has not adopted a formal radon policy and has no recommended or legally binding action levels for 222 Rn or any other naturally occurring radionuclides. (author)
Stochastic theory of fatigue corrosion
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.
Stochastic quantization and gauge theories
International Nuclear Information System (INIS)
Kolck, U. van.
1987-01-01
Stochastic quantization is presented taking the Flutuation-Dissipation Theorem as a guide. It is shown that the original approach of Parisi and Wu to gauge theories fails to give the right results to gauge invariant quantities when dimensional regularization is used. Although there is a simple solution in an abelian theory, in the non-abelian case it is probably necessary to start from a BRST invariant action instead of a gauge invariant one. Stochastic regularizations are also discussed. (author) [pt
Stochasticity induced by coherent wavepackets
International Nuclear Information System (INIS)
Fuchs, V.; Krapchev, V.; Ram, A.; Bers, A.
1983-02-01
We consider the momentum transfer and diffusion of electrons periodically interacting with a coherent longitudinal wavepacket. Such a problem arises, for example, in lower-hybrid current drive. We establish the stochastic threshold, the stochastic region δv/sub stoch/ in velocity space, the associated momentum transfer j, and the diffusion coefficient D. We concentrate principally on the weak-field regime, tau/sub autocorrelation/ < tau/sub bounce/
Stochastic runaway of dynamical systems
International Nuclear Information System (INIS)
Pfirsch, D.; Graeff, P.
1984-10-01
One-dimensional, stochastic, dynamical systems are well studied with respect to their stability properties. Less is known for the higher dimensional case. This paper derives sufficient and necessary criteria for the asymptotic divergence of the entropy (runaway) and sufficient ones for the moments of n-dimensional, stochastic, dynamical systems. The crucial implication is the incompressibility of their flow defined by the equations of motion in configuration space. Two possible extensions to compressible flow systems are outlined. (orig.)
Stochastic Models of Polymer Systems
2016-01-01
Distribution Unlimited Final Report: Stochastic Models of Polymer Systems The views, opinions and/or findings contained in this report are those of the...ADDRESS. Princeton University PO Box 0036 87 Prospect Avenue - 2nd floor Princeton, NJ 08544 -2020 14-Mar-2014 ABSTRACT Number of Papers published in...peer-reviewed journals: Number of Papers published in non peer-reviewed journals: Final Report: Stochastic Models of Polymer Systems Report Title
Stochastic efficiency: five case studies
International Nuclear Information System (INIS)
Proesmans, Karel; Broeck, Christian Van den
2015-01-01
Stochastic efficiency is evaluated in five case studies: driven Brownian motion, effusion with a thermo-chemical and thermo-velocity gradient, a quantum dot and a model for information to work conversion. The salient features of stochastic efficiency, including the maximum of the large deviation function at the reversible efficiency, are reproduced. The approach to and extrapolation into the asymptotic time regime are documented. (paper)
Optimal Liquidation under Stochastic Liquidity
Becherer, Dirk; Bilarev, Todor; Frentrup, Peter
2016-01-01
We solve explicitly a two-dimensional singular control problem of finite fuel type for infinite time horizon. The problem stems from the optimal liquidation of an asset position in a financial market with multiplicative and transient price impact. Liquidity is stochastic in that the volume effect process, which determines the inter-temporal resilience of the market in spirit of Predoiu, Shaikhet and Shreve (2011), is taken to be stochastic, being driven by own random noise. The optimal contro...
Memory effects on stochastic resonance
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.
Stochastic optimization: beyond mathematical programming
CERN. Geneva
2015-01-01
Stochastic optimization, among which bio-inspired algorithms, is gaining momentum in areas where more classical optimization algorithms fail to deliver satisfactory results, or simply cannot be directly applied. This presentation will introduce baseline stochastic optimization algorithms, and illustrate their efficiency in different domains, from continuous non-convex problems to combinatorial optimization problem, to problems for which a non-parametric formulation can help exploring unforeseen possible solution spaces.
Stochastic quantization and gauge invariance
International Nuclear Information System (INIS)
Viana, R.L.
1987-01-01
A survey of the fundamental ideas about Parisi-Wu's Stochastic Quantization Method, with applications to Scalar, Gauge and Fermionic theories, is done. In particular, the Analytic Stochastic Regularization Scheme is used to calculate the polarization tensor for Quantum Electrodynamics with Dirac bosons or Fermions. The regularization influence is studied for both theories and an extension of this method for some supersymmetrical models is suggested. (author)
Stochastic Analysis and Related Topics
Ustunel, Ali
1988-01-01
The Silvri Workshop was divided into a short summer school and a working conference, producing lectures and research papers on recent developments in stochastic analysis on Wiener space. The topics treated in the lectures relate to the Malliavin calculus, the Skorohod integral and nonlinear functionals of white noise. Most of the research papers are applications of these subjects. This volume addresses researchers and graduate students in stochastic processes and theoretical physics.
Stochastic Optical Reconstruction Microscopy (STORM).
Xu, Jianquan; Ma, Hongqiang; Liu, Yang
2017-07-05
Super-resolution (SR) fluorescence microscopy, a class of optical microscopy techniques at a spatial resolution below the diffraction limit, has revolutionized the way we study biology, as recognized by the Nobel Prize in Chemistry in 2014. Stochastic optical reconstruction microscopy (STORM), a widely used SR technique, is based on the principle of single molecule localization. STORM routinely achieves a spatial resolution of 20 to 30 nm, a ten-fold improvement compared to conventional optical microscopy. Among all SR techniques, STORM offers a high spatial resolution with simple optical instrumentation and standard organic fluorescent dyes, but it is also prone to image artifacts and degraded image resolution due to improper sample preparation or imaging conditions. It requires careful optimization of all three aspects-sample preparation, image acquisition, and image reconstruction-to ensure a high-quality STORM image, which will be extensively discussed in this unit. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.
Feasibility of high-helium natural gas exploration in the Presinian strata, Sichuan Basin
Directory of Open Access Journals (Sweden)
Jian Zhang
2015-01-01
Full Text Available Helium in China highly depends on import at present, so the most practical way to change the situation is searching for medium-to-large natural gas fields with high helium content. Therefore, the hydrocarbon accumulation mechanism and the helium origin of the Weiyuan high-helium natural gas reservoir have been analyzed to find out the feasibility of finding natural gas field with high helium content in the Presinian strata of the Sichuan Basin. Based on twelve outcrop sections and drilling data of four wells encountering the Presinian strata, the petrological features, sedimentary facies and source rocks of Presinian strata were systematically analyzed, which shows that the sedimentary formation developed in the Presinian is the Nanhua system, and the stratigraphic sequence revealed by outcrop section in the eastern margin includes the Nantuo, Datangpo, Gucheng and Liantuo Fms, and it is inferred that the same stratigraphic sequence may occur inside the basin. The Nantuo, Gucheng and Liantuo Fms are mainly glacial deposits of glutenite interbedded with mudstone; the Datangpo Fm is interglacial deposits of sandstone and shale, the lower part shale, rich in organic matter, is fairly good source rock. Further study showed that the Nantuo coarse-grained clastic reservoir, Datangpo source rock and the intruded granite “helium source rock” make up a good high-helium gas system. Controlled by the early rift, the thick Presinian sedimentary rocks occur primarily inside the rift. The distribution of sedimentary rocks and granite in the basin was predicted by use of the seismic data, which shows that the feasibility of finding high-helium gas reservoirs in Ziyang area of the Sichuan Basin is great.
Phenomenology of stochastic exponential growth
Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya
2017-06-01
Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.
Epidemiologic studies in the areas with a high level of natural radioactivity
International Nuclear Information System (INIS)
Laurier, D.; Martin, J.M.; Hubert, Ph.
2000-10-01
Since 1970, numerous studies have been interested in high level of natural radiations areas (H.L.N.R.A.) or high background radiation areas (H.B.R.A.). An international conference stands every four years, and the last one was at Munich (Germany). The aim of this note is to make a review of epidemiologic studies made with the populations living in H.L.N.R.A. and to present a synthesis of achieved results. The cytogenetic studies are equally mentioned but not detailed. (N.C.)
Natural gaits of the non-pathological flat foot and high-arched foot
Fan, Yifang; Fan, Yubo; Li, Zhiyu; Lv, Changsheng; Luo, Donglin
2010-01-01
There has been a controversy as to whether or not the non-pathological flat foot and high-arched foot have an effect on human walking activities. The 3D foot scanning system was employed to obtain static footprints from subjects adopting a half-weight-bearing stance. Based upon their footprints, the subjects were divided into two groups: the flat-footed and the high-arched. The plantar pressure measurement system was used to measure and record the subjects' successive natural gaits. Two indic...
Breuer, Rebecca J; Bandyopadhyay, Arpan; O'Brien, Sofie A; Barnes, Aaron M T; Hunter, Ryan C; Hu, Wei-Shou; Dunny, Gary M
2017-07-01
In Enterococcus faecalis, sex pheromone-mediated transfer of antibiotic resistance plasmids can occur under unfavorable conditions, for example, when inducing pheromone concentrations are low and inhibiting pheromone concentrations are high. To better understand this paradox, we adapted fluorescence in situ hybridization chain reaction (HCR) methodology for simultaneous quantification of multiple E. faecalis transcripts at the single cell level. We present direct evidence for variability in the minimum period, maximum response level, and duration of response of individual cells to a specific inducing condition. Tracking of induction patterns of single cells temporally using a fluorescent reporter supported HCR findings. It also revealed subpopulations of rapid responders, even under low inducing pheromone concentrations where the overall response of the entire population was slow. The strong, rapid induction of small numbers of cells in cultures exposed to low pheromone concentrations is in agreement with predictions of a stochastic model of the enterococcal pheromone response. The previously documented complex regulatory circuitry controlling the pheromone response likely contributes to stochastic variation in this system. In addition to increasing our basic understanding of the biology of a horizontal gene transfer system regulated by cell-cell signaling, demonstration of the stochastic nature of the pheromone response also impacts any future efforts to develop therapeutic agents targeting the system. Quantitative single cell analysis using HCR also has great potential to elucidate important bacterial regulatory mechanisms not previously amenable to study at the single cell level, and to accelerate the pace of functional genomic studies.
Rules of thumb for conservation of metapopulations based on a stochastic winking-patch model
Etienne, R.S.; Heesterbeek, J.A.P.
2001-01-01
From a theoretical viewpoint, nature management basically has two options to prolong metapopulation persistence: decreasing local extinction probabilities and increasing colonization probabilities. This article focuses on those options with a stochastic, single-species metapopulation model. We found
Stochastic Effects in Microstructure
Directory of Open Access Journals (Sweden)
Glicksman M.E.
2002-01-01
Full Text Available We are currently studying microstructural responses to diffusion-limited coarsening in two-phase materials. A mathematical solution to late-stage multiparticle diffusion in finite systems is formulated with account taken of particle-particle interactions and their microstructural correlations, or "locales". The transition from finite system behavior to that for an infinite microstructure is established analytically. Large-scale simulations of late-stage phase coarsening dynamics show increased fluctuations with increasing volume fraction, Vv, of the mean flux entering or leaving particles of a given size class. Fluctuations about the mean flux were found to depend on the scaled particle size, R/, where R is the radius of a particle and is the radius of the dispersoid averaged over the population within the microstructure. Specifically, small (shrinking particles tend to display weak fluctuations about their mean flux, whereas particles of average, or above average size, exhibit strong fluctuations. Remarkably, even in cases of microstructures with a relatively small volume fraction (Vv ~ 10-4, the particle size distribution is broader than that for the well-known Lifshitz-Slyozov limit predicted at zero volume fraction. The simulation results reported here provide some additional surprising insights into the effect of diffusion interactions and stochastic effects during evolution of a microstructure, as it approaches its thermodynamic end-state.
Kallianpur, Gopinath; Hida, Takeyuki
1987-01-01
The use of probabilistic methods in the biological sciences has been so well established by now that mathematical biology is regarded by many as a distinct dis cipline with its own repertoire of techniques. The purpose of the Workshop on sto chastic methods in biology held at Nagoya University during the week of July 8-12, 1985, was to enable biologists and probabilists from Japan and the U. S. to discuss the latest developments in their respective fields and to exchange ideas on the ap plicability of the more recent developments in stochastic process theory to problems in biology. Eighteen papers were presented at the Workshop and have been grouped under the following headings: I. Population genetics (five papers) II. Measure valued diffusion processes related to population genetics (three papers) III. Neurophysiology (two papers) IV. Fluctuation in living cells (two papers) V. Mathematical methods related to other problems in biology, epidemiology, population dynamics, etc. (six papers) An important f...
Stochastic partial differential equations
Lototsky, Sergey V
2017-01-01
Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very active research discipline, this textbook provides all the necessary background from functional analysis and the theory of PDEs. It covers the main types of equations (elliptic, hyperbolic and parabolic) and discusses different types of random forcing. The objective is to give the reader the necessary tools to understand the proofs of existing theorems about SPDEs (from other sources) and perhaps even to formulate and prove a few new ones. Most of the material could be covered in about 40 hours of lectures, as long as not too much time is spent on the general discussion of stochastic analysis in infinite dimensions. As the subject of SPDEs is currently making the transition from the research level to that of a graduate or even undergraduate course, the book attempts to present enough exercise material to fill potential exams and homework assignments. Exercises appear throughout and are usually directly connected ...
AA, stochastic precooling kicker
CERN PhotoLab
1980-01-01
The freshly injected antiprotons were subjected to fast stochastic "precooling", while a shutter shielded the deeply cooled antiproton stack from the violent action of the precooling kicker. In this picture, the injection orbit is to the left, the stack orbit to the far right, the separating shutter is in open position. After several seconds of precooling (in momentum and in the vertical plane), the shutter was opened briefly, so that by means of RF the precooled antiprotons could be transferred to the stack tail, where they were subjected to further cooling in momentum and both transverse planes, until they ended up, deeply cooled, in the stack core. The fast shutter, which had to open and close in a fraction of a second was an essential item of the cooling scheme and a mechanical masterpiece. Here the shutter is in the open position. The precooling pickups were of the same design, with the difference that the kickers had cooling circuits and the pickups not. 8401150 shows a precooling pickup with the shutte...
International Nuclear Information System (INIS)
Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira
2009-01-01
The identification of areas with high concentrations of natural radionuclides is an important task in classifying these areas in relation to the health risk for residents in the region. The aim of this work is to identify areas of high exposure to nuclear radiation using a geographic representation based on the theory of fuzzy sets. Radiometric data obtained from previous works developed in a region of high concentrations in natural uranium were used to create a fuzzy map of the local radiation levels. During the image processing, a nonlinear filter was applied to eliminate noise i.e. to reduce isolated pixels that would eventually cause major uncertainties in the results. A resulting image was geographically positioned (WGS40) and obtained in gray scale. This image was fuzzified for membership functions that represent linguistic variables as low exposure, medium exposure and high exposure. After representing the membership grade in a RGB (red, green and blue) image it was possible to visualize the radiation level in the area of exposure. When compared to data from the region, results demonstrated the good efficiency of the technique here employed for the representation of areas with high radioactivity levels. The image obtained also provided important information about those areas where exposure to radiation is more pronounced. Hence, the fuzzy map can be applied in decision-making of experts when a risk situation is identified. (author)
Evaluation of High-Pressure RCS Natural Circulations Under Severe Accident Conditions
International Nuclear Information System (INIS)
Lee, Byung Chul; Bang, Young Suk; Suh, Nam Duk
2006-01-01
Since TMI-2 accident, the occurrence of severe accident natural circulations inside RCS during entire in-vessel core melt progressions before the reactor vessel breach had been emphasized and tried to clarify its thermal-hydraulic characteristics. As one of consolidated outcomes of these efforts, sophisticated models have been presented to explain the effects of a variety of engineering and phenomenological factors involved during severe accident mitigation on the integrity of RCS pressure boundaries, i.e. reactor pressure vessel(RPV), RCS coolant pipe and steam generator tubes. In general, natural circulation occurs due to density differences, which for single phase flow, is typically generated by temperature differences. Three natural circulation flows can be formed during severe accidents: in-vessel, hot leg countercurrent flow and flow through the coolant loops. Each of these flows may be present during high-pressure transients such as station blackout (SBO) and total loss of feedwater (TLOFW). As a part of research works in order to contribute on the completeness of severe accident management guidance (SAMG) in domestic plants by quantitatively assessing the RCS natural circulations on its integrity, this study presents basic approach for this work and some preliminary results of these efforts with development of appropriately detailed RCS model using MELCOR computer code
High throughput Screening to Identify Natural Human Monoamine Oxidase B Inhibitors
Mazzio, E; Deiab, S; Park, K; Soliman, KFA
2012-01-01
Age-related increase in monoamine oxidase B (MAO-B) may contribute to CNS neurodegenerative diseases. Moreover, MAO-B inhibitors are used in the treatment of idiopathic Parkinson disease as preliminary monotherapy or adjunct therapy with L-dopa. To date, meager natural sources of MAO-B inhibitors have been identified, and the relative strength, potency and rank of many plants relative to standard drugs such as Selegiline (L-deprenyl, Eldepryl) are not known. In this work, we developed and utilized a high throughput enzyme microarray format to screen and evaluate 905 natural product extracts (0.025–.7 mg/ml) to inhibit human MAO-B derived from BTI-TN-5B1-4 cells infected with recombinant baculovirus. The protein sequence of purified enzyme was confirmed using 1D gel electrophoresis-matrix assisted laser desorption ionization-time-of-flight-tandem mass spectroscopy, and enzyme activity was confirmed by [1] substrate conversion (3-mM benzylamine) to H202 and [2] benzaldehyde. Of the 905 natural extracts tested, the lowest IC50s [Comfrey, Bringraj, Skullcap, Kava-kava, Wild Indigo, Gentian and Green Tea. In conclusion, the data reflect relative potency information by rank of commonly used herbs and plants that contain human MAO-B inhibitory properties in their natural form. PMID:22887993
Mean Field Games for Stochastic Growth with Relative Utility
Energy Technology Data Exchange (ETDEWEB)
Huang, Minyi, E-mail: mhuang@math.carleton.ca [Carleton University, School of Mathematics and Statistics (Canada); Nguyen, Son Luu, E-mail: sonluu.nguyen@upr.edu [University of Puerto Rico, Department of Mathematics (United States)
2016-12-15
This paper considers continuous time stochastic growth-consumption optimization in a mean field game setting. The individual capital stock evolution is determined by a Cobb–Douglas production function, consumption and stochastic depreciation. The individual utility functional combines an own utility and a relative utility with respect to the population. The use of the relative utility reflects human psychology, leading to a natural pattern of mean field interaction. The fixed point equation of the mean field game is derived with the aid of some ordinary differential equations. Due to the relative utility interaction, our performance analysis depends on some ratio based approximation error estimate.
Response spectrum analysis of a stochastic seismic model
International Nuclear Information System (INIS)
Kimura, Koji; Sakata, Masaru; Takemoto, Shinichiro.
1990-01-01
The stochastic response spectrum approach is presented for predicting the dynamic behavior of structures to earthquake excitation expressed by a random process, one of whose sample functions can be regarded as a recorded strong-motion earthquake accelerogram. The approach consists of modeling recorded ground motion by a random process and the root-mean-square response (rms) analysis of a single-degree-of-freedom system by using the moment equations method. The stochastic response spectrum is obtained as a plot of the maximum rms response versus the natural period of the system and is compared with the conventional response spectrum. (author)
Mean Field Games for Stochastic Growth with Relative Utility
International Nuclear Information System (INIS)
Huang, Minyi; Nguyen, Son Luu
2016-01-01
This paper considers continuous time stochastic growth-consumption optimization in a mean field game setting. The individual capital stock evolution is determined by a Cobb–Douglas production function, consumption and stochastic depreciation. The individual utility functional combines an own utility and a relative utility with respect to the population. The use of the relative utility reflects human psychology, leading to a natural pattern of mean field interaction. The fixed point equation of the mean field game is derived with the aid of some ordinary differential equations. Due to the relative utility interaction, our performance analysis depends on some ratio based approximation error estimate.
CISM course on stochastic methods in fluid mechanics
Chibbaro, Sergio
2013-01-01
Since their first introduction in natural sciences through the work of Einstein on Brownian motion in 1905 and further works, in particular by Langevin, Smoluchowski and others, stochastic processes have been used in several areas of science and technology. For example, they have been applied in chemical studies, or in fluid turbulence and for combustion and reactive flows. The articles in this book provide a general and unified framework in which stochastic processes are presented as modeling tools for various issues in engineering, physics and chemistry, with particular focus on fluid mechan
Stochastic control and the second law of thermodynamics
Brockett, R. W.; Willems, J. C.
1979-01-01
The second law of thermodynamics is studied from the point of view of stochastic control theory. We find that the feedback control laws which are of interest are those which depend only on average values, and not on sample path behavior. We are lead to a criterion which, when satisfied, permits one to assign a temperature to a stochastic system in such a way as to have Carnot cycles be the optimal trajectories of optimal control problems. Entropy is also defined and we are able to prove an equipartition of energy theorem using this definition of temperature. Our formulation allows one to treat irreversibility in a quite natural and completely precise way.
Soil remediation: humic acids as natural surfactants in the washings of highly contaminated soils
International Nuclear Information System (INIS)
Conte, Pellegrino; Agretto, Anna; Spaccini, Riccardo; Piccolo, Alessandro
2005-01-01
The remediation of the highly contaminated site around the former chemical plant of ACNA (near Savona) in Northern Italy is a top priority in Italy. The aim of the present work was to contribute in finding innovative and environmental-friendly technology to remediate soils from the ACNA contaminated site. Two soils sampled from the ACNA site (A and B), differing in texture and amount and type of organic contaminants, were subjected to soil washings by comparing the removal efficiency of water, two synthetic surfactants, sodium dodecylsulphate (SDS) and Triton X-100 (TX100), and a solution of a natural surfactant, a humic acid (HA) at its critical micelle concentration (CMC). The extraction of pollutants by sonication and soxhlet was conducted before and after the soil washings. Soil A was richer in polycyclic aromatic hydrocarbons, whereas soil B had a larger content of thiophenes. Sonication resulted more analytically efficient in the fine-textured soil B. The coarse-textured soil A was extracted with a general equal efficiency also by soxhlet. Clean-up by water was unable to exhaustively remove contaminants from the two soils, whereas all the organic surfactants revealed very similar efficiencies (up to 90%) in the removal of the contaminants from the soils. Hence, the use of solutions of natural HAs appears as a better choice for soil washings of highly polluted soils due to their additional capacity to promote microbial activity, in contrast to synthetic surfactants, for a further natural attenuation in washed soils. - Solutions of natural humic acids appear to be a better choice for washing highly polluted soils
Energy Technology Data Exchange (ETDEWEB)
Silva, Milena Wollmann da; Vilhena, Marco Tullio M.B.; Bodmann, Bardo Ernst J.; Vasques, Richard, E-mail: milena.wollmann@ufrgs.br, E-mail: vilhena@mat.ufrgs.br, E-mail: bardobodmann@ufrgs.br, E-mail: richard.vasques@fulbrightmail.org [Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica
2015-07-01
The neutron point kinetics equation, which models the time-dependent behavior of nuclear reactors, is often used to understand the dynamics of nuclear reactor operations. It consists of a system of coupled differential equations that models the interaction between (i) the neutron population; and (II) the concentration of the delayed neutron precursors, which are radioactive isotopes formed in the fission process that decay through neutron emission. These equations are deterministic in nature, and therefore can provide only average values of the modeled populations. However, the actual dynamical process is stochastic: the neutron density and the delayed neutron precursor concentrations vary randomly with time. To address this stochastic behavior, Hayes and Allen have generalized the standard deterministic point kinetics equation. They derived a system of stochastic differential equations that can accurately model the random behavior of the neutron density and the precursor concentrations in a point reactor. Due to the stiffness of these equations, this system was numerically implemented using a stochastic piecewise constant approximation method (Stochastic PCA). Here, we present a study of the influence of stochastic fluctuations on the results of the neutron point kinetics equation. We reproduce the stochastic formulation introduced by Hayes and Allen and compute Monte Carlo numerical results for examples with constant and time-dependent reactivity, comparing these results with stochastic and deterministic methods found in the literature. Moreover, we introduce a modified version of the stochastic method to obtain a non-stiff solution, analogue to a previously derived deterministic approach. (author)
International Nuclear Information System (INIS)
Silva, Milena Wollmann da; Vilhena, Marco Tullio M.B.; Bodmann, Bardo Ernst J.; Vasques, Richard
2015-01-01
The neutron point kinetics equation, which models the time-dependent behavior of nuclear reactors, is often used to understand the dynamics of nuclear reactor operations. It consists of a system of coupled differential equations that models the interaction between (i) the neutron population; and (II) the concentration of the delayed neutron precursors, which are radioactive isotopes formed in the fission process that decay through neutron emission. These equations are deterministic in nature, and therefore can provide only average values of the modeled populations. However, the actual dynamical process is stochastic: the neutron density and the delayed neutron precursor concentrations vary randomly with time. To address this stochastic behavior, Hayes and Allen have generalized the standard deterministic point kinetics equation. They derived a system of stochastic differential equations that can accurately model the random behavior of the neutron density and the precursor concentrations in a point reactor. Due to the stiffness of these equations, this system was numerically implemented using a stochastic piecewise constant approximation method (Stochastic PCA). Here, we present a study of the influence of stochastic fluctuations on the results of the neutron point kinetics equation. We reproduce the stochastic formulation introduced by Hayes and Allen and compute Monte Carlo numerical results for examples with constant and time-dependent reactivity, comparing these results with stochastic and deterministic methods found in the literature. Moreover, we introduce a modified version of the stochastic method to obtain a non-stiff solution, analogue to a previously derived deterministic approach. (author)
Araujo Rodrigues Lomba, de Angela; Alves, Paulo; Jongman, R.H.G.; McCracken, D.
2015-01-01
Agriculture constitutes a dominant land cover worldwide, and rural landscapes
under extensive farming practices acknowledged due to high biodiversity
levels. The High Nature Value farmland (HNVf) concept has been
highlighted in the EU environmental and rural policies due to their
Darwinism in Context: An interdisciplinary, highly contextualized course on nature of science
Directory of Open Access Journals (Sweden)
Kostas Kampourakis
2015-10-01
Full Text Available In this article, we describe a course, titled Darwinism in Context, which focuses on the social, cultural and scientific influences on the development of Darwin's theory. This was an interdisciplinary, highly contextualized nature of science course that aimed to help students learn about a core nature of science aspect: that there are historical, cultural and social influences on the practice and directions of science. For this purpose, the course was based on a well-documented historical case study: the development of Darwin's theory. The course consisted of five classes that focused on: (a Victorian society, (b the views and beliefs of scholars that had an impact on Darwin's thinking (historical influences, (c aspects of Darwin's personal and social life that influenced the publication of his theory (social influences, (d the reception of Darwin's theory and the relationship between religion and science (cultural influences and (e the relationship between science and literature. In all cases, teaching included presentations of the historical events but was mostly based on the analysis and discussion of excerpts from the respective original writings. During the classes only a few examples were presented; students were motivated to study further the original writings and identify some key concepts and ideas after the classes. It is concluded that this kind of highly contextualized nature of science instruction can provide students with a more authentic view of science.
High-pressure measuring cell for Raman spectroscopic studies of natural gas
DEFF Research Database (Denmark)
Hansen, Susanne Brunsgaard; Berg, Rolf W.; Stenby, Erling Halfdan
2001-01-01
A system for obtaining Raman spectra of gases at high pressure has been constructed. In order to ensure that a natural gas sample is totally representative, a high-pressure gas-measuring cell has been developed, built up by stainless steel fittings and a sapphire tube. The design and construction...... of this cell are described. A perfect pressure seal has been demonstrated up to 15.0 MPaA (MPa absolute). The cell has been successfully used to obtain Raman spectra of natural gas samples. Some of these spectra are presented and assigned. The most remarkable observation in the spectra is that it is possible...... to detect hydrogen sulfide at concentrations of 1-3 mg H2S/Nm(3). An attempt to make a quantitative analysis of natural gas by the so-called "ratio method" is presented. In addition to this, the relative normalized differential Raman scattering cross sections for ethane and i-butane molecules at 8.0 MPa...
Stochastic phenomena in a fiber Raman amplifier
Energy Technology Data Exchange (ETDEWEB)
Kalashnikov, Vladimir [Aston Institute of Photonic Technologies, Aston University, Birmingham (United Kingdom); Institute of Photonics, Vienna University of Technology (Austria); Sergeyev, Sergey V. [Aston Institute of Photonic Technologies, Aston University, Birmingham (United Kingdom); Ania-Castanon, Juan Diego [Instituto de Optica CSIC, Madrid (Spain); Jacobsen, Gunnar [Acreo, Kista (Sweden); Popov, Sergei [Royal Institute of Technology (KTH), Stockholm (Sweden)
2017-01-15
The interplay of such cornerstones of modern nonlinear fiber optics as a nonlinearity, stochasticity and polarization leads to variety of the noise induced instabilities including polarization attraction and escape phenomena harnessing of which is a key to unlocking the fiber optic systems specifications required in high resolution spectroscopy, metrology, biomedicine and telecommunications. Here, by using direct stochastic modeling, the mapping of interplay of the Raman scattering-based nonlinearity, the random birefringence of a fiber, and the pump-to-signal intensity noise transfer has been done in terms of the fiber Raman amplifier parameters, namely polarization mode dispersion, the relative intensity noise of the pump laser, fiber length, and the signal power. The obtained results reveal conditions for emergence of the random birefringence-induced resonance-like enhancement of the gain fluctuations (stochastic anti-resonance) accompanied by pulse broadening and rare events in the form of low power output signals having probability heavily deviated from the Gaussian distribution. (copyright 2016 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Stochastic Simulation of Process Calculi for Biology
Directory of Open Access Journals (Sweden)
Andrew Phillips
2010-10-01
Full Text Available Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programming languages based on process calculi have been developed, many of which are expressive enough to generate unbounded numbers of molecular species and reactions. As a result of this expressiveness, such calculi cannot rely on standard reaction-based simulation methods, which require fixed numbers of species and reactions. Rather than implementing custom stochastic simulation algorithms for each process calculus, we propose to use a generic abstract machine that can be instantiated to a range of process calculi and a range of reaction-based simulation algorithms. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. In this short paper we give a brief summary of the generic abstract machine, and show how it can be instantiated with the stochastic simulation algorithm known as Gillespie's Direct Method. We also discuss the wider implications of such an abstract machine, and outline how it can be used to simulate multiple calculi simultaneously within a common framework.
Ground source heat pumps versus high efficiency natural gas furnaces in Alberta
Energy Technology Data Exchange (ETDEWEB)
Shaw, J.
2003-02-02
For the past twenty years or so, the heating and cooling of numerous buildings in northern Europe has been accomplished using ground source heat pumps (GSHPs), while in North America they have been in use for approximately ten years. In the Prairies, natural gas furnaces dominate, while GSHP are more popular in eastern Canada. The author noted that natural gas furnaces have an efficiency of 80 per cent or less, while high efficiency natural gas (HENG) furnaces, more expensive, have an efficiency in the 90 per cent range. A brief outline of the principles behind GSHPs was provided. The Coefficient of Performance (COP) of GSHP reaches up to 500 per cent depending whether the unit is cooling or heating. The amount of heat produced by a heating system expressed as a percentage of the energy input required to operate the system is the definition used for the efficiency. In those cases where it is possible to amortize the initial costs, pay now or obtain a subsidy, the installation of GSHP is advantageous. Several factors affect the total cost of heating a building, such as the airtightness of the building and its insulation, the coldness of the climate, and the inside controlled temperature setting. The author then examined the cost of operating a GSHP versus a natural gas furnace. In most examples studied, the cost of operating a GSHP was less than the cost of operating a natural gas furnace. The Total Equivalent Warming Impact (TEWI) of GSHPs and HENG furnaces was examined. The author concluded that the cost of heating by GSHP in Alberta will be lower than the cost of heating by HENG which requires a separate air conditioning unit for the summer months, with additional improvements in efficiency and insulation. 7 refs., 4 tabs.
Sexual cannibalism: high incidence in a natural population with benefits to females.
Directory of Open Access Journals (Sweden)
Rubén Rabaneda-Bueno
Full Text Available Sexual cannibalism may be a form of extreme sexual conflict in which females benefit more from feeding on males than mating with them, and males avoid aggressive, cannibalistic females in order to increase net fitness. A thorough understanding of the adaptive significance of sexual cannibalism is hindered by our ignorance of its prevalence in nature. Furthermore, there are serious doubts about the food value of males, probably because most studies that attempt to document benefits of sexual cannibalism to the female have been conducted in the laboratory with non-natural alternative prey. Thus, to understand more fully the ecology and evolution of sexual cannibalism, field experiments are needed to document the prevalence of sexual cannibalism and its benefits to females.We conducted field experiments with the Mediterranean tarantula (Lycosa tarantula, a burrowing wolf spider, to address these issues. At natural rates of encounter with males, approximately a third of L. tarantula females cannibalized the male. The rate of sexual cannibalism increased with male availability, and females were more likely to kill and consume an approaching male if they had previously mated with another male. We show that females benefit from feeding on a male by breeding earlier, producing 30% more offspring per egg sac, and producing progeny of higher body condition. Offspring of sexually cannibalistic females dispersed earlier and were larger later in the season than spiderlings of non-cannibalistic females.In nature a substantial fraction of female L. tarantula kill and consume approaching males instead of mating with them. This behaviour is more likely to occur if the female has mated previously. Cannibalistic females have higher rates of reproduction, and produce higher-quality offspring, than non-cannibalistic females. Our findings further suggest that female L. tarantula are nutrient-limited in nature and that males are high-quality prey. The results of these
Nuclear power for coexistence with nature, high temperature gas-cooled reactors
International Nuclear Information System (INIS)
Kaneko, Yoshihiko
1996-01-01
Until this century, it is sufficient to aim at the winner of competition in human society to obtain resources, and to entrust waste to natural cleaning action. However, the expansion of social activities has been too fast, and the scale has become too large, consequently, in the next century, the expansion of social activities will be caught by the structure of trilemma that is subjected to the strong restraint and selection from the problems of finite energy and resources and environment preservation. In 21st century, the problems change to those between mankind and nature. Energy supply and population increase, envrionment preservation and human activities, and the matters that human wisdom should bear regarding energy technology are discussed. In Japan, the construction of the high temperature engineering test reactor (HTTR) is in progress. The design of high temperature gas-cooled reactors and their features on the safety are explained. The capability of reducing CO 2 release of high temperature gas-cooled reactors is reported. In future, it is expected that the time of introducing high temperature gas-cooled reactors will come. (K.I.)
Dynamic behaviour of high-pressure natural-gas flow in pipelines
International Nuclear Information System (INIS)
Gato, L.M.C.; Henriques, J.C.C.
2005-01-01
The aim of the present study is the numerical modelling of the dynamic behaviour of high-pressure natural-gas flow in pipelines. The numerical simulation was performed by solving the conservation equations, for one-dimensional compressible flow, using the Runge-Kutta discontinuous Galerkin method, with third-order approximation in space and time. The boundary conditions were imposed using a new weak formulation based on the characteristic variables. The occurrence of pressure oscillations in natural-gas pipelines was studied as a result of the compression wave originated by the rapid closure of downstream shut-off valves. The effect of the partial reflection of pressure waves was also analyzed in the transition between pipes of different cross-sectional areas
Resilience-Based Perspectives to Guiding High-Nature-Value Farmland through Socioeconomic Change
Directory of Open Access Journals (Sweden)
Tobias Plieninger
2013-12-01
Full Text Available Global environmental challenges require approaches that integrate biodiversity conservation, food production, and livelihoods at landscape scales. We reviewed the approach of conserving biodiversity on "high-nature-value" (HNV farmland, covering 75 million ha in Europe, from a resilience perspective. Despite growing recognition in natural resource policies, many HNV farmlands have vanished, and the remaining ones are vulnerable to socioeconomic changes. Using landscape-level cases across Europe, we considered the following social-ecological system properties and components and their integration into HNV farmland management: (1 coupling of social and ecological systems, (2 key variables, (3 adaptive cycles, (4 regime shifts, (5 cascading effects, (6 ecosystem stewardship and collaboration, (7 social capital, and (8 traditional ecological knowledge. We argue that previous conservation efforts for HNV farmland have focused too much on static, isolated, and monosectoral conservation strategies, and that stimulation of resilience and adaptation is essential for guiding HNV farmland through rapid change.
Survival of rapidly fluctuating natural low winter temperatures by High Arctic soil invertebrates
DEFF Research Database (Denmark)
Convey, Peter; Abbandonato, Holly; Bergan, Frode
2015-01-01
The extreme polar environment creates challenges for its resident invertebrate communities and the stress tolerance of some of these animals has been examined over many years. However, although it is well appreciated that standard air temperature records often fail to describe accurately conditions...... microhabitats. To assess survival of natural High Arctic soil invertebrate communities contained in soil and vegetation cores to natural winter temperature variations, the overwintering temperatures they experienced were manipulated by deploying cores in locations with varying snow accumulation: No Snow...... and did not decrease below -12. °C. Those under deep snow were even more stable and did not decline below -2. °C. Despite these striking differences in winter thermal regimes, there were no clear differences in survival of the invertebrate fauna between treatments, including oribatid, prostigmatid...
Natural radionuclides in rocks and soils of the high-mountain regions of the Great Caucasus
Asvarova, T. A.; Abdulaeva, A. S.; Magomedov, M. A.
2012-06-01
The results of the radioecological survey in the high-mountain regions of the Great Caucasus at the heights from 2200 to 3800 m a.s.l. are considered. This survey encompassed the territories of Dagestan, Azerbaijan, Georgia, Chechnya, Northern Ossetia-Alania, Kabardino-Balkaria, Karachay-Cherkessia, and the Stavropol and Krasnodar regions. The natural γ background radiation in the studied regions is subjected to considerable fluctuations and varies from 6 to 40 μR/h. The major regularities of the migration of natural radionuclides 238U, 232Th, 226Ra, and 40K in soils in dependence on the particular environmental conditions (the initial concentration of the radionuclides in the parent material; the intensity of pedogenesis; the intensity of the vertical and horizontal migration; and the geographic, climatic, and landscape-geochemical factors) are discussed.
Dynamic behaviour of high-pressure natural-gas flow in pipelines
Energy Technology Data Exchange (ETDEWEB)
Gato, L.M.C. [Department of Mechanical Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)]. E-mail: lgato@mail.ist.utl.pt; Henriques, J.C.C. [Department of Mechanical Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)]. E-mail: jcch@mail.ist.utl.pt
2005-10-01
The aim of the present study is the numerical modelling of the dynamic behaviour of high-pressure natural-gas flow in pipelines. The numerical simulation was performed by solving the conservation equations, for one-dimensional compressible flow, using the Runge-Kutta discontinuous Galerkin method, with third-order approximation in space and time. The boundary conditions were imposed using a new weak formulation based on the characteristic variables. The occurrence of pressure oscillations in natural-gas pipelines was studied as a result of the compression wave originated by the rapid closure of downstream shut-off valves. The effect of the partial reflection of pressure waves was also analyzed in the transition between pipes of different cross-sectional areas.
Françoise Benz
2002-01-01
17, 18, 19 June LECTURE SERIES from 11.00 to 12.00 hrs - Auditorium, bldg. 500 Probing nature with high precision; particle traps, laser spectroscopy and optical combs by G. GABRIELSE / Harvard University, USA Experiments with atomic energy scales probe nature and its symmetries with exquisite precision. Particle traps allow the manipulation of single charged particles for months at a time, allow the most accurate comparison of theory and experiment, and promise to allow better measurement of fundamental quantities like the fine structure constant. Ions and atoms can be probed with lasers that are phase locked to microwave frequency standards via optical combs, thus calibrating optical sources in terms of the official cesium second. A series of three lectures will illustrate what can be measured and discuss key techniques. ACADEMIC TRAINING Françoise Benz Tel. 73127 francoise.benz@cern.ch
Trends in high performance compressors for petrochemical and natural gas industry in China
Zhao, Yuanyang; Li, Liansheng
2015-08-01
Compressors are the key equipment in the petrochemical and natural gas industry system. The performance and reliability of them are very important for the process system. The application status of petrochemical & natural gas compressors in China is presented in this paper. The present status of design and operating technologies of compressors in China are mentioned in this paper. The turbo, reciprocating and twin screw compressors are discussed. The market demands for different structure compressors in process gas industries are analysed. This paper also introduces the research and developments for high performance compressors in China. The recent research results on efficiency improvement methods, stability improvement, online monitor and fault diagnosis will also be presented in details.
On the physical realizability of quantum stochastic walks
Taketani, Bruno; Govia, Luke; Schuhmacher, Peter; Wilhelm, Frank
Quantum walks are a promising framework that can be used to both understand and implement quantum information processing tasks. The recently developed quantum stochastic walk combines the concepts of a quantum walk and a classical random walk through open system evolution of a quantum system, and have been shown to have applications in as far reaching fields as artificial intelligence. However, nature puts significant constraints on the kind of open system evolutions that can be realized in a physical experiment. In this work, we discuss the restrictions on the allowed open system evolution, and the physical assumptions underpinning them. We then introduce a way to circumvent some of these restrictions, and simulate a more general quantum stochastic walk on a quantum computer, using a technique we call quantum trajectories on a quantum computer. We finally describe a circuit QED approach to implement discrete time quantum stochastic walks.
Sensitivity of Footbridge Vibrations to Stochastic Walking Parameters
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
2010-01-01
of the pedestrian. A stochastic modelling approach is adopted for this paper and it facilitates quantifying the probability of exceeding various vibration levels, which is useful in a discussion of serviceability of a footbridge design. However, estimates of statistical distributions of footbridge vibration levels...... to walking loads might be influenced by the models assumed for the parameters of the load model (the walking parameters). The paper explores how sensitive estimates of the statistical distribution of vertical footbridge response are to various stochastic assumptions for the walking parameters. The basis...... for the study is a literature review identifying different suggestions as to how the stochastic nature of these parameters may be modelled, and a parameter study examines how the different models influence estimates of the statistical distribution of footbridge vibrations. By neglecting scatter in some...
Stochastic fractional differential equations: Modeling, method and analysis
International Nuclear Information System (INIS)
Pedjeu, Jean-C.; Ladde, Gangaram S.
2012-01-01
By introducing a concept of dynamic process operating under multi-time scales in sciences and engineering, a mathematical model described by a system of multi-time scale stochastic differential equations is formulated. The classical Picard–Lindelöf successive approximations scheme is applied to the model validation problem, namely, existence and uniqueness of solution process. Naturally, this leads to the problem of finding closed form solutions of both linear and nonlinear multi-time scale stochastic differential equations of Itô–Doob type. Finally, to illustrate the scope of ideas and presented results, multi-time scale stochastic models for ecological and epidemiological processes in population dynamic are outlined.
Stochastic reaction-diffusion algorithms for macromolecular crowding
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.
Stochastic approach for radionuclides quantification
Clement, A.; Saurel, N.; Perrin, G.
2018-01-01
Gamma spectrometry is a passive non-destructive assay used to quantify radionuclides present in more or less complex objects. Basic methods using empirical calibration with a standard in order to quantify the activity of nuclear materials by determining the calibration coefficient are useless on non-reproducible, complex and single nuclear objects such as waste packages. Package specifications as composition or geometry change from one package to another and involve a high variability of objects. Current quantification process uses numerical modelling of the measured scene with few available data such as geometry or composition. These data are density, material, screen, geometric shape, matrix composition, matrix and source distribution. Some of them are strongly dependent on package data knowledge and operator backgrounds. The French Commissariat à l'Energie Atomique (CEA) is developing a new methodology to quantify nuclear materials in waste packages and waste drums without operator adjustment and internal package configuration knowledge. This method suggests combining a global stochastic approach which uses, among others, surrogate models available to simulate the gamma attenuation behaviour, a Bayesian approach which considers conditional probability densities of problem inputs, and Markov Chains Monte Carlo algorithms (MCMC) which solve inverse problems, with gamma ray emission radionuclide spectrum, and outside dimensions of interest objects. The methodology is testing to quantify actinide activity in different kind of matrix, composition, and configuration of sources standard in terms of actinide masses, locations and distributions. Activity uncertainties are taken into account by this adjustment methodology.
Natural plasmid transformation in a high-frequency-of transformation marine Vibrio strain
International Nuclear Information System (INIS)
Frischer, M.E.; Thurmond, J.M.; Paul, J.H.
1990-01-01
The estuarine bacterium Vibrio strain DI-9 has been shown to be naturally transformable with both broad host range plasmid multimers and homologous chromosomal DNA at average frequencies of 3.5 x 10 -9 and 3.4 x 10 -7 transformants per recipient, respectively. Growth of plasmid transformants in nonselective medium resulted in cured strains that transformed 6 to 42,857 times more frequently than the parental strain, depending on the type of transforming DNA. These high-frequency-of-transformation (HfT) strains were transformed at frequencies ranging from 1.1 x 10 -8 to 1.3 x 10 -4 transformants per recipient with plasmid DNA and at an average frequency of 8.3 x 10 -5 transformants per recipient with homologous chromosomal DNA. The highest transformation frequencies were observed by using multimers of an R1162 derivative carrying the transposon Tn5 (pQSR50). Probing of total DNA preparations from one of the cured strains demonstrated that no plasmid DNA remained in the cured strains which may have provided homology to the transforming DNA. All transformants and cured strains could be differentiated from the parental strains by colony morphology. DNA binding studies indicated that late-log-phase HfT strains bound [ 3 H]bacteriophage lambda DNA 2.1 times more rapidly than the parental strain. These results suggest that the original plasmid transformation event of strain DI-9 was the result of uptake and expression of plasmid DNA by a competent mutant (HfT strain). Additionally, it was found that a strain of Vibrio parahaemolyticus, USFS 3420, could be naturally transformed with plasmid DNA. Natural plasmid transformation by high-transforming mutants may be a means of plasmid acquisition by natural aquatic bacterial populations
Electricity Market Stochastic Dynamic Model and Its Mean Stability Analysis
Directory of Open Access Journals (Sweden)
Zhanhui Lu
2014-01-01
Full Text Available Based on the deterministic dynamic model of electricity market proposed by Alvarado, a stochastic electricity market model, considering the random nature of demand sides, is presented in this paper on the assumption that generator cost function and consumer utility function are quadratic functions. The stochastic electricity market model is a generalization of the deterministic dynamic model. Using the theory of stochastic differential equations, stochastic process theory, and eigenvalue techniques, the determining conditions of the mean stability for this electricity market model under small Gauss type random excitation are provided and testified theoretically. That is, if the demand elasticity of suppliers is nonnegative and the demand elasticity of consumers is negative, then the stochastic electricity market model is mean stable. It implies that the stability can be judged directly by initial data without any computation. Taking deterministic electricity market data combined with small Gauss type random excitation as numerical samples to interpret random phenomena from a statistical perspective, the results indicate the conclusions above are correct, valid, and practical.
Stochastic Cell Fate Progression in Embryonic Stem Cells
Zou, Ling-Nan; Doyle, Adele; Jang, Sumin; Ramanathan, Sharad
2013-03-01
Studies on the directed differentiation of embryonic stem (ES) cells suggest that some early developmental decisions may be stochastic in nature. To identify the sources of this stochasticity, we analyzed the heterogeneous expression of key transcription factors in single ES cells as they adopt distinct germ layer fates. We find that under sufficiently stringent signaling conditions, the choice of lineage is unambiguous. ES cells flow into differentiated fates via diverging paths, defined by sequences of transitional states that exhibit characteristic co-expression of multiple transcription factors. These transitional states have distinct responses to morphogenic stimuli; by sequential exposure to multiple signaling conditions, ES cells are steered towards specific fates. However, the rate at which cells travel down a developmental path is stochastic: cells exposed to the same signaling condition for the same amount of time can populate different states along the same path. The heterogeneity of cell states seen in our experiments therefore does not reflect the stochastic selection of germ layer fates, but the stochastic rate of progression along a chosen developmental path. Supported in part by the Jane Coffin Childs Fund
Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara
2016-01-01
Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington's genetic assimilation
Directory of Open Access Journals (Sweden)
Lin Chao
2016-01-01
Full Text Available Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington
Effects of CO 2 on a High Performance Hollow-Fiber Membrane for Natural Gas Purification
Omole, Imona C.
2010-05-19
A 6FDA-based, cross-linkable polyimide was characterized in the form of a defect-free asymmetric hollow-fiber membrane. The novel membrane was cross-linked at various temperatures and tested for natural gas purification in the presence of high CO2 partial pressures. The cross-linked membrane material shows high intrinsic separation performance for CO2 and CH4 (selectivity ∼49, CO2 permeability ∼161 barrer, with a feed at 65 psia, 35 °C, and 10% CO2). Cross-linked asymmetric hollow-fiber membranes made from the material show good resistance to CO2-induced plasticization. Carbon dioxide partial pressures as high as ∼400 psia were employed, and the membrane was shown to be promisingly stable under these aggressive conditions. The performance of the membrane was also analyzed using the dual-mode sorption/transport model. © 2010 American Chemical Society.
Fuzzy stochastic multiobjective programming
Sakawa, Masatoshi; Katagiri, Hideki
2011-01-01
With a stress on interactive decision-making, this work breaks new ground by covering both the random nature of events related to environments, and the fuzziness of human judgements. The text runs from mathematical preliminaries to future research directions.
Water-rock interaction in a high-FeO olivine rock in nature
International Nuclear Information System (INIS)
Hellmuth, K.H.; Lindberg, A.; Tullborg, E.L.
1992-12-01
The long-term behaviour in nature of high-FeO olivine rock in contact with surface water has been studied at the Lovasjaervi instrusion, SE-Finland. The rock has been proposed as a high-capasity, higly reactive redox-buffer backfill in a repository for spent fuel. Favourable groundwater chemistry is a major parameter relevant to safety of such a repository. Reducing conditions favour the retardation of long-lived, redox-sensitive radionuclides. Weathering influences have been studied at the natural outcrop of the rock mass. The interaction of oxidizing surface waters with rock at greater depths has been studied by using fissure filling minerals. Investigation of weathered rock from the outcrop indicates that the olivine rock is highly reactive on a geological time scale and its redox capasity is available although the instrusion as a whole is surprisingly well preserved. The fissure fillings studied allow the conclusion that oxygen seems to be efficiently removed from intruding surface water. Oxidation seem to have caused visible effects only along very conducting fractures and near the contact zones of the surrounding granitic rock. Stable isotope data of fissure filling calcites indicate that the influence of surface waters can be traced clearly down to a depth of about 50 m, but also at greater depths re-equilibration has occurred. Groundwater data from the site were not available. (orig.)
2nd Workshop on the Nature of the High-Energy Unidentified Sources
Cheng, K S; Multiwavelength Approach to Unidentified Gamma-Ray Sources
2005-01-01
Nearly one half of the point-like gamma-ray sources detected by EGRET instrument of the late Compton satellite are still defeating our attempts at identifying them. To establish the origin and nature of these enigmatic sources has become a major problem of current high-energy astrophysics. The second workshop on Multiwavelength Approach to Unidentified Gamma-ray Sources intends to shed new and fresh light on the problem of the nature of these mysterious sources and the objects behind them. The proceedings contain 46 contributed papers in this subject, which cover theoretical models on gamma-ray sources as well as the best multiwavelength strategies for the identification of the promising candidates. The topics of this conference also include energetic phenomena ocurring both in galactic and extragalactic scenarios, phenomena that might lead to the appearance of what we have called high-energy unidentified sources. The book will be of interest for all active researchers in the high-energy astrophysics and rela...
Sun, Xiaoming; Hua, Stephane; Chen, Hsiao-Rong; Ouyang, Zhengyu; Einkauf, Kevin; Tse, Samantha; Ard, Kevin; Ciaranello, Andrea; Yawetz, Sigal; Sax, Paul; Rosenberg, Eric S; Lichterfeld, Mathias; Yu, Xu G
2017-12-19
Although dendritic cells are among the human cell population best equipped for cell-intrinsic antiviral immune defense, they seem highly susceptible to infection with the Zika virus (ZIKV). Using highly purified myeloid dendritic cells isolated from individuals with naturally acquired acute infection, we here show that ZIKV induces profound perturbations of transcriptional signatures relative to healthy donors. Interestingly, we noted a remarkable downregulation of antiviral interferon-stimulated genes and innate immune sensors, suggesting that ZIKV can actively suppress interferon-dependent immune responses. In contrast, several host factors known to support ZIKV infection were strongly upregulated during natural ZIKV infection; these transcripts included AXL, the main entry receptor for ZIKV; SOCS3, a negative regulator of ISG expression; and IDO-1, a recognized inducer of regulatory T cell responses. Thus, during in vivo infection, ZIKV can transform the transcriptome of dendritic cells in favor of the virus to render these cells highly conducive to ZIKV infection. Published by Elsevier Inc.
Natural gaits of the non-pathological flat foot and high-arched foot.
Directory of Open Access Journals (Sweden)
Yifang Fan
Full Text Available There has been a controversy as to whether or not the non-pathological flat foot and high-arched foot have an effect on human walking activities. The 3D foot scanning system was employed to obtain static footprints from subjects adopting a half-weight-bearing stance. Based upon their footprints, the subjects were divided into two groups: the flat-footed and the high-arched. The plantar pressure measurement system was used to measure and record the subjects' successive natural gaits. Two indices were proposed: distribution of vertical ground reaction force (VGRF of plantar and the rate of change of footprint areas. Using these two indices to compare the natural gaits of the two subject groups, we found that (1 in stance phase, there is a significant difference (p<0.01 in the distributions of VGRF of plantar; (2 in a stride cycle, there is also a significant difference (p<0.01 in the rate of change of footprint area. Our analysis suggests that when walking, the VGRF of the plantar brings greater muscle tension to the flat-footed while a smaller rate of change of footprint area brings greater stability to the high-arched.
Natural gaits of the non-pathological flat foot and high-arched foot.
Fan, Yifang; Fan, Yubo; Li, Zhiyu; Lv, Changsheng; Luo, Donglin
2011-03-18
There has been a controversy as to whether or not the non-pathological flat foot and high-arched foot have an effect on human walking activities. The 3D foot scanning system was employed to obtain static footprints from subjects adopting a half-weight-bearing stance. Based upon their footprints, the subjects were divided into two groups: the flat-footed and the high-arched. The plantar pressure measurement system was used to measure and record the subjects' successive natural gaits. Two indices were proposed: distribution of vertical ground reaction force (VGRF) of plantar and the rate of change of footprint areas. Using these two indices to compare the natural gaits of the two subject groups, we found that (1) in stance phase, there is a significant difference (pplantar; (2) in a stride cycle, there is also a significant difference (pfootprint area. Our analysis suggests that when walking, the VGRF of the plantar brings greater muscle tension to the flat-footed while a smaller rate of change of footprint area brings greater stability to the high-arched.
High-resolution phenotypic profiling of natural products-induced effects on the single-cell level
Kremb, Stephan Georg; Voolstra, Christian R.
2017-01-01
Natural products (NPs) are highly evolved molecules making them a valuable resource for new therapeutics. Here we demonstrate the usefulness of broad-spectrum phenotypic profiling of NP-induced perturbations on single cells with imaging-based High
International Nuclear Information System (INIS)
Sohrabi, M.; Borhan Azad, S.; Katouzi, M.
1990-01-01
Papers presented in international conference on high levels of natural radiation was in the following subjects: A review of world natural radiation, environmental transfer pathway,technologically enhanced natural radiation environment,radon in the environment,radium determination in water,cytogenetic studies in high natural radiation areas,epidemiological studies in high natural radiation areas and radiation measurements methods
Natural asphalt modified binders used for high stiffness modulus asphalt concrete
Bilski, Marcin; Słowik, Mieczysław
2018-05-01
This paper presents a set of test results supporting the possibility of replacing, in Polish climate conditions, hard road 20/30 penetration grade bitumen used in the binder course and/or base course made of high stiffness modulus asphalt concrete with binders comprising of 35/50 or 50/70 penetration grade bitumens and additives in the form of natural Gilsonite or Trinidad Epuré asphalts. For the purpose of comparing the properties of the discussed asphalt binders, values of the Performance Grade have been determined according to the American Superpave system criteria.
Estimative of the soil amount ingested by cattle in high natural radioactive region
International Nuclear Information System (INIS)
Rosa, Roosevelt; Silva, Lucia H.C.; Taddei, Maria H.T.
1997-01-01
Considering that Pocos de Caldas is a region of high natural radioactivity, where many environmental impacts have been studied, 27 samples of cattle faeces and 24 samples of local soil were collected and analyzed for Ti concentrations, during dry and rain periods. Using this element as an indicator, the percentage of soil ingestion by cattle were estimated for three management practices: confined, semi-confined and free. The results showed the management practices influence on the cattle soil ingestion percentage, and the importance of this pathway in the environmental impact assessment. (author). 7 refs., 1 tab
DEFF Research Database (Denmark)
Adewole, Jimoh K.; Jensen, Lars; Al-Mubaiyedh, Usamah A.
2012-01-01
High density polyethylene (HDPE)/clay nanocomposites containing nanoclay concentrations of 1, 2.5, and 5 wt% were prepared by a melt blending process. The effects of various types of nanoclays and their concentrations on permeability, solubility, and diffusivity of natural gas in the nanocomposites...... at constant temperature had little influence on the permeability, whereas increasing the temperature from 30 to 70 degrees C significantly increased the permeability of the gas. Additionally, the effect of crystallinity on permeability, solubility, and diffusivity was investigated. Thus, the permeability...
Determination of kinetics parameters using stochastic methods in a 252Cf system
International Nuclear Information System (INIS)
Difilippo, F.C.
1988-01-01
Safety analysis and control system design of nuclear systems require the knowledge of neutron kinetics related parameters like effective delayed neutron fraction, neutron lifetime, time between neutron generations and subcriticality margins. Many methods, deterministic and stochastic, are being used, some since the beginning of nuclear power, to measure these important parameters. The method based on the use of the 252 Cf neutron source has been under intense study at the Oak Ridge National Laboratory, both experimentally and theoretically, during the last years. The increasing demand for this isotope in industrial and medical applications and new designs of advanced high flux reactors to produce it make the isotope available as neutron source (only few micrograms are necessary). A thin layer of 252 Cf is deposited in one of the electrodes of a fission chamber which produces pulses each time the 252 Cf disintegrates via α or spontaneous fission decay; the smaller pulses associated with the α decay can be easily discriminated with the important result that we known the time when v/sub c/ neutrons are injected into the system (number of neutrons per fission of 252 Cf). Thus, a small (few cm 3 ) and nonintrusive device can be used as a random pulsed neutron source with known natural properties that do no depend on biases associated with more complex interrogating devices like accelerators. This paper presents a general formalism that relates the kinetics parameters with stochastic descriptors that naturally appear because of the random nature of the production and transport of neutrons
Stochastic models: theory and simulation.
Energy Technology Data Exchange (ETDEWEB)
Field, Richard V., Jr.
2008-03-01
Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.
Stochastic Still Water Response Model
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2002-01-01
In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...
Stochastic quantization and topological theories
International Nuclear Information System (INIS)
Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.
1992-01-01
In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones
Stochastic quantization of Einstein gravity
International Nuclear Information System (INIS)
Rumpf, H.
1986-01-01
We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''
Synthesis of high capacity cation exchangers from a low-grade Chinese natural zeolite
International Nuclear Information System (INIS)
Wang Yifei; Lin Feng
2009-01-01
The Chinese natural zeolite, in which clinoptilolite coexists with quartz was treated hydrothermally with NaOH solutions, either with or without fusion with NaOH powder as pretreatment. Zeolite Na-P, Na-Y and analcime were identified as the reacted products, depending on the reaction conditions such as NaOH concentration, reaction time and hydrothermal temperature. The products were identified by X-ray diffraction, and characterized by Fourier transform IR and ICP. With hydrothermal treatment after fusion of natural zeolite with NaOH, high purity of zeolite Na-Y and Na-P can be selectively formed, their cation exchange capacity (CEC) are 275 and 355 meq/100 g respectively, which are greatly higher than that of the natural zeolite (97 meq/100 g). Furthermore, the ammonium removal by the synthetic zeolite Na-P in aqueous solution was also studied. The equilibrium isotherms have been got and the influence of other cations present in water upon the ammonia uptake suggested an order of preference Ca 2+ > K + > Mg 2+ .
Caridi, F.; Marguccio, S.; Durante, G.; Trozzo, R.; Fullone, F.; Belvedere, A.; D'Agostino, M.; Belmusto, G.
2017-01-01
In this article natural radioactivity measurements and dosimetric evaluations in soil samples contaminated by Naturally Occurring Radioactive Materials (NORM) are made, in order to assess any possible radiological hazard for the population and for workers professionally exposed to ionizing radiations. Investigated samples came from the district of Crotone, Calabria region, South of Italy. The natural radioactivity investigation was performed by high-resolution gamma-ray spectrometry. From the measured gamma spectra, activity concentrations were determined for 226Ra , 234-mPa , 224Ra , 228Ac and 40K and compared with their clearance levels for NORM. The total effective dose was calculated for each sample as due to the committed effective dose for inhalation and to the effective dose from external irradiation. The sum of the total effective doses estimated for all investigated samples was compared to the action levels provided by the Italian legislation (D.Lgs.230/95 and subsequent modifications) for the population members (0.3mSv/y) and for professionally exposed workers (1mSv/y). It was found to be less than the limit of no radiological significance (10μSv/y).