Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC
More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)
MCNP variance reduction overview
The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code
Mira Antonietta; Tenconi Paolo; Bressanini Dario
2003-01-01
We propose a general purpose variance reduction technique for MCMC estimators. The idea is obtained by combining standard variance reduction principles known for regular Monte Carlo simulations (Ripley, 1987) and the Zero-Variance principle introduced in the physics literature (Assaraf and Caffarel, 1999). The potential of the new idea is illustrated with some toy examples and an application to Bayesian estimation
Advanced Variance Reduction for Global k-Eigenvalue Simulations in MCNP
The 'criticality' or k-eigenvalue of a nuclear system determines whether the system is critical (k=1), or the extent to which it is subcritical (k1). Calculations of k are frequently performed at nuclear facilities to determine the criticality of nuclear reactor cores, spent nuclear fuel storage casks, and other fissile systems. These calculations can be expensive, and current Monte Carlo methods have certain well-known deficiencies. In this project, we have developed and tested a new 'functional Monte Carlo' (FMC) method that overcomes several of these deficiencies. The current state-of-the-art Monte Carlo k-eigenvalue method estimates the fission source for a sequence of fission generations (cycles), during each of which M particles per cycle are processed. After a series of 'inactive' cycles during which the fission source 'converges', a series of 'active' cycles are performed. For each active cycle, the eigenvalue and eigenfunction are estimated; after N >> 1 active cycles are performed, the results are averaged to obtain estimates of the eigenvalue and eigenfunction and their standard deviations. This method has several disadvantages: (i) the estimate of k depends on the number M of particles per cycle, (iii) for optically thick systems, the eigenfunction estimate may not converge due to undersampling of the fission source, and (iii) since the fission source in any cycle depends on the estimated fission source from the previous cycle (the fission sources in different cycles are correlated), the estimated variance in k is smaller than the real variance. For an acceptably large number M of particles per cycle, the estimate of k is nearly independent of M; this essentially takes care of item (i). Item (ii) can be addressed by taking M sufficiently large, but for optically thick systems a sufficiently large M can easily be unrealistic. Item (iii) cannot be accounted for by taking M or N sufficiently large; it is an inherent deficiency due to the correlations
A Hilbert Space Approach to Variance Reduction
Szechtman, Roberto
2006-01-01
Elsevier Handbooks in Operations Research and Management Science: Simulation, pp 259-289. In this chapter we explain variance reduction techniques from the Hilbert space standpoint, in the terminating simulation context. We use projection ideas to explain how variance is reduced, and to link different variance reduction techniques. Our focus is on the methods of control variates, conditional Monte Carlo, weighted Monte Carlo, stratification, and Latin hypercube sampling.
Markov bridges, bisection and variance reduction
Asmussen, Søren; Hobolth, Asger
this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are...
Discussion on variance reduction technique for shielding
Maekawa, Fujio [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1998-03-01
As the task of the engineering design activity of the international thermonuclear fusion experimental reactor (ITER), on 316 type stainless steel (SS316) and the compound system of SS316 and water, the shielding experiment using the D-T neutron source of FNS in Japan Atomic Energy Research Institute has been carried out. However, in these analyses, enormous working time and computing time were required for determining the Weight Window parameter. Limitation or complication was felt when the variance reduction by Weight Window method of MCNP code was carried out. For the purpose of avoiding this difficulty, investigation was performed on the effectiveness of the variance reduction by cell importance method. The conditions of calculation in all cases are shown. As the results, the distribution of fractional standard deviation (FSD) related to neutrons and gamma-ray flux in the direction of shield depth is reported. There is the optimal importance change, and when importance was increased at the same rate as that of the attenuation of neutron or gamma-ray flux, the optimal variance reduction can be done. (K.I.)
Dimension reduction based on weighted variance estimate
无
2009-01-01
In this paper, we propose a new estimate for dimension reduction, called the weighted variance estimate (WVE), which includes Sliced Average Variance Estimate (SAVE) as a special case. Bootstrap method is used to select the best estimate from the WVE and to estimate the structure dimension. And this selected best estimate usually performs better than the existing methods such as Sliced Inverse Regression (SIR), SAVE, etc. Many methods such as SIR, SAVE, etc. usually put the same weight on each observation to estimate central subspace (CS). By introducing a weight function, WVE puts different weights on different observations according to distance of observations from CS. The weight function makes WVE have very good performance in general and complicated situations, for example, the distribution of regressor deviating severely from elliptical distribution which is the base of many methods, such as SIR, etc. And compared with many existing methods, WVE is insensitive to the distribution of the regressor. The consistency of the WVE is established. Simulations to compare the performances of WVE with other existing methods confirm the advantage of WVE.
Variance Reduction Using Nonreversible Langevin Samplers
Duncan, A. B.; Lelièvre, T.; Pavliotis, G. A.
2016-05-01
A standard approach to computing expectations with respect to a given target measure is to introduce an overdamped Langevin equation which is reversible with respect to the target distribution, and to approximate the expectation by a time-averaging estimator. As has been noted in recent papers [30, 37, 61, 72], introducing an appropriately chosen nonreversible component to the dynamics is beneficial, both in terms of reducing the asymptotic variance and of speeding up convergence to the target distribution. In this paper we present a detailed study of the dependence of the asymptotic variance on the deviation from reversibility. Our theoretical findings are supported by numerical simulations.
Monte Carlo variance reduction approaches for non-Boltzmann tallies
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed
Variance reduction methods for simulation of densities on Wiener space
Kohatsu, Arturo; Pettersson, Roger
2002-01-01
We develop a general error analysis framework for the Monte Carlo simulation of densities for functionals in Wiener space. We also study variance reduction methods with the help of Malliavin derivatives. For this, we give some general heuristic principles which are applied to diffusion processes. A comparison with kernel density estimates is made.
Methods for variance reduction in Monte Carlo simulations
Bixler, Joel N.; Hokr, Brett H.; Winblad, Aidan; Elpers, Gabriel; Zollars, Byron; Thomas, Robert J.
2016-03-01
Monte Carlo simulations are widely considered to be the gold standard for studying the propagation of light in turbid media. However, due to the probabilistic nature of these simulations, large numbers of photons are often required in order to generate relevant results. Here, we present methods for reduction in the variance of dose distribution in a computational volume. Dose distribution is computed via tracing of a large number of rays, and tracking the absorption and scattering of the rays within discrete voxels that comprise the volume. Variance reduction is shown here using quasi-random sampling, interaction forcing for weakly scattering media, and dose smoothing via bi-lateral filtering. These methods, along with the corresponding performance enhancements are detailed here.
Variance reduction methods applied to deep-penetration problems
All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course
Stochastic Variance Reduction Methods for Saddle-Point Problems
Balamurugan, P.; Bach, Francis
2016-01-01
We consider convex-concave saddle-point problems where the objective functions may be split in many components, and extend recent stochastic variance reduction methods (such as SVRG or SAGA) to provide the first large-scale linearly convergent algorithms for this class of problems which is common in machine learning. While the algorithmic extension is straightforward, it comes with challenges and opportunities: (a) the convex minimization analysis does not apply and we use the notion of monot...
Fringe biasing: A variance reduction technique for optically thick meshes
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
MC Estimator Variance Reduction with Antithetic and Common Random Fields
Guthke, P.; Bardossy, A.
2011-12-01
Monte Carlo methods are widely used to estimate the outcome of complex physical models. For physical models with spatial parameter uncertainty, it is common to apply spatial random functions to the uncertain variables, which can then be used to interpolate between known values or to simulate a number of equally likely realizations .The price, that has to be paid for such a stochastic approach, are many simulations of the physical model instead of just running one model with one 'best' input parameter set. The number of simulations is often limited because of computational constraints, so that a modeller has to make a compromise between the benefit in terms of an increased accuracy of the results and the effort in terms of a massively increased computational time. Our objective is, to reduce the estimator variance of dependent variables in Monte Carlo frameworks. Therefore, we adapt two variance reduction techniques (antithetic variates and common random numbers) to a sequential random field simulation scheme that uses copulas as spatial dependence functions. The proposed methodology leads to pairs of spatial random fields with special structural properties, that are advantageous in MC frameworks. Antithetic Random fields (ARF) exhibit a reversed structure on the large scale, while the dependence on the local scale is preserved. Common random fields (CRF) show the same large scale structures, but different spatial dependence on the local scale. The performances of the proposed methods are examined with two typical applications of stochastic hydrogeology. It is shown, that ARF have the property to massively reduce the number of simulation runs required for convergence in Monte Carlo frameworks while keeping the same accuracy in terms of estimator variance. Furthermore, in multi-model frameworks like in sensitivity analysis of the spatial structure, where more than one spatial dependence model is used, the influence of different dependence structures becomes obvious
A comparison of variance reduction techniques for radar simulation
Divito, A.; Galati, G.; Iovino, D.
Importance sampling and extreme value technique (EVT) and its generalization (G-EVT) were compared as to reduction of the variance of radar simulation estimates. Importance sampling has a greater potential for including a priori information in the simulation experiment, and subsequently to reduce the estimation errors. This feature is paid for by a lack of generality of the simulation procedure. The EVT technique is only valid when a probability tail should be estimated (false alarm problems) and requires, as the only a priori information, that the considered variate belongs to the exponential class. The G-EVT introducing a shape parameter to be estimated (when unknown), allows smaller estimation error to be attained than EVT. The G-EVT and, to a greater extent, the EVT, lead to a straightforward and general simulation procedure for probability tails estimations.
Improving computational efficiency of Monte Carlo simulations with variance reduction
CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)
Problems of variance reduction in the simulation of random variables
The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced
Experience with Monte Carlo variance reduction using adjoint solutions in HYPER neutronics analysis
The variance reduction techniques using adjoint solutions are applied to the Monte Carlo calculation of the HYPER(HYbrid Power Extraction Reactor) core neutronics. The applied variance reduction techniques are the geometry splitting and the weight windows. The weight bounds and the cell importance needed for these techniques are generated from an adjoint discrete ordinate calculation by the two-dimensional TWODANT code. The flux distribution variances of the Monte Carlo calculations by these variance reduction techniques are compared with the results of the standard Monte Carlo calculations. It is shown that the variance reduction techniques using adjoint solutions to the HYPER core neutronics result in a decrease in the efficiency of the Monte Carlo calculation
Variance reduction in Monte Carlo analysis of rarefied gas diffusion.
Perlmutter, M.
1972-01-01
The problem of rarefied diffusion between parallel walls is solved using the Monte Carlo method. The diffusing molecules are evaporated or emitted from one of the two parallel walls and diffuse through another molecular species. The Monte Carlo analysis treats the diffusing molecule as undergoing a Markov random walk, and the local macroscopic properties are found as the expected value of the random variable, the random walk payoff. By biasing the transition probabilities and changing the collision payoffs, the expected Markov walk payoff is retained but its variance is reduced so that the Monte Carlo result has a much smaller error.
Variance reduction techniques in the simulation of Markov processes
We study a functional r of the stationary distribution of a homogeneous Markov chain. It is often difficult or impossible to perform the analytical calculation of r and so it is reasonable to estimate r by a simulation process. A consistent estimator r(n) of r is obtained with respect to a chain with a countable state space. Suitably modifying the estimator r(n) of r one obtains a new consistent estimator which has a smaller variance than r(n). The same is obtained in the case of finite state space
Deflation as a Method of Variance Reduction for Estimating the Trace of a Matrix Inverse
Gambhir, Arjun Singh; Orginos, Kostas
2016-01-01
Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors are random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can b...
Computation time constitutes an important and a problematic parameter in Monte Carlo simulations, which is inversely proportional to the statistical errors so there comes the idea to use the variance reduction techniques. These techniques play an important role in reducing uncertainties and improving the statistical results. Several variance reduction techniques have been developed. The most known are Transport cutoffs, Interaction forcing, Bremsstrahlung splitting and Russian roulette. Also, the use of a phase space seems to be appropriate to reduce enormously the computing time. In this work, we applied these techniques on a linear accelerator (LINAC) using the MCNPX computer Monte Carlo code. This code gives a rich palette of variance reduction techniques. In this study we investigated various cards related to the variance reduction techniques provided by MCNPX. The parameters found in this study are warranted to be used efficiently in MCNPX code. Final calculations are performed in two steps that are related by a phase space. Results show that, comparatively to direct simulations (without neither variance-reduction nor phase space), the adopted method allows an improvement in the simulation efficiency by a factor greater than 700.
Verification of the history-score moment equations for weight-window variance reduction
Solomon, Clell J [Los Alamos National Laboratory; Sood, Avneet [Los Alamos National Laboratory; Booth, Thomas E [Los Alamos National Laboratory; Shultis, J. Kenneth [KANSAS STATE UNIV.
2010-12-06
The history-score moment equations that describe the moments of a Monte Carlo score distribution have been extended to weight-window variance reduction, The resulting equations have been solved deterministically to calculate the population variance of the Monte Carlo score distribution for a single tally, Results for one- and two-dimensional one-group problems are presented that predict the population variances to less than 1% deviation from the Monte Carlo for one-dimensional problems and between 1- 2% for two-dimensional problems,
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ''real'' particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ''black box''. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases
Simulating individual-based models of bacterial chemotaxis with asymptotic variance reduction
Rousset, Mathias
2011-01-01
We discuss variance reduced simulations for an individual-based model of chemotaxis of bacteria with internal dynamics. The variance reduction is achieved via a coupling of this model with a simpler process in which the internal dynamics has been replaced by a direct gradient sensing of the chemoattractants concentrations. In the companion paper \\cite{limits}, we have rigorously shown, using a pathwise probabilistic technique, that both processes converge towards the same advection-diffusion process in the diffusive asymptotics. In this work, a direct coupling is achieved between paths of individual bacteria simulated by both models, by using the same sets of random numbers in both simulations. This coupling is used to construct a hybrid scheme with reduced variance. We first compute a deterministic solution of the kinetic density description of the direct gradient sensing model; the deviations due to the presence of internal dynamics are then evaluated via the coupled individual-based simulations. We show th...
Numerous variance reduction techniques, such as splitting/Russian roulette, weight windows, and the exponential transform exist for improving the efficiency of Monte Carlo transport calculations. Typically, however, these methods, while reducing the variance in the problem area of interest tend to increase the variance in other, presumably less important, regions. As such, these methods tend to be not as effective in Monte Carlo calculations which require the minimization of the variance everywhere. Recently, ''Local'' Exponential Transform (LET) methods have been developed as a means of approximating the zero-variance solution. A numerical solution to the adjoint diffusion equation is used, along with an exponential representation of the adjoint flux in each cell, to determine ''local'' biasing parameters. These parameters are then used to bias the forward Monte Carlo transport calculation in a manner similar to the conventional exponential transform, but such that the transform parameters are now local in space and energy, not global. Results have shown that the Local Exponential Transform often offers a significant improvement over conventional geometry splitting/Russian roulette with weight windows. Since the biasing parameters for the Local Exponential Transform were determined from a low-order solution to the adjoint transport problem, the LET has been applied in problems where it was desirable to minimize the variance in a detector region. The purpose of this paper is to show that by basing the LET method upon a low-order solution to the forward transport problem, one can instead obtain biasing parameters which will minimize the maximum variance in a Monte Carlo transport calculation
Use experiences of MCNP in nuclear energy study. 2. Review of variance reduction techniques
Sakurai, Kiyoshi; Yamamoto, Toshihiro [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment] [eds.
1998-03-01
`MCNP Use Experience` Working Group was established in 1996 under the Special Committee on Nuclear Code Evaluation. This year`s main activity of the working group has been focused on the review of variance reduction techniques of Monte Carlo calculations. This working group dealt with the variance reduction techniques of (1) neutron and gamma ray transport calculation of fusion reactor system, (2) concept design of nuclear transmutation system using accelerator, (3) JMTR core calculation, (4) calculation of prompt neutron decay constant, (5) neutron and gamma ray transport calculation for exposure evaluation, (6) neutron and gamma ray transport calculation of shielding system, etc. Furthermore, this working group started an activity to compile `Guideline of Monte Carlo Calculation` which will be a standard in the future. The appendices of this report include this `Guideline`, the use experience of MCNP 4B and examples of Monte Carlo calculations of high energy charged particles. The 11 papers are indexed individually. (J.P.N.)
PWR Facility Dose Modeling Using MCNP5 and the CADIS/ADVANTG Variance-Reduction Methodology
Blakeman, Edward D [ORNL; Peplow, Douglas E. [ORNL; Wagner, John C [ORNL; Murphy, Brian D [ORNL; Mueller, Don [ORNL
2007-09-01
The feasibility of modeling a pressurized-water-reactor (PWR) facility and calculating dose rates at all locations within the containment and adjoining structures using MCNP5 with mesh tallies is presented. Calculations of dose rates resulting from neutron and photon sources from the reactor (operating and shut down for various periods) and the spent fuel pool, as well as for the photon source from the primary coolant loop, were all of interest. Identification of the PWR facility, development of the MCNP-based model and automation of the run process, calculation of the various sources, and development of methods for visually examining mesh tally files and extracting dose rates were all a significant part of the project. Advanced variance reduction, which was required because of the size of the model and the large amount of shielding, was performed via the CADIS/ADVANTG approach. This methodology uses an automatically generated three-dimensional discrete ordinates model to calculate adjoint fluxes from which MCNP weight windows and source bias parameters are generated. Investigative calculations were performed using a simple block model and a simplified full-scale model of the PWR containment, in which the adjoint source was placed in various regions. In general, it was shown that placement of the adjoint source on the periphery of the model provided adequate results for regions reasonably close to the source (e.g., within the containment structure for the reactor source). A modification to the CADIS/ADVANTG methodology was also studied in which a global adjoint source is weighted by the reciprocal of the dose response calculated by an earlier forward discrete ordinates calculation. This method showed improved results over those using the standard CADIS/ADVANTG approach, and its further investigation is recommended for future efforts.
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method
Vidal-Codina, F., E-mail: fvidal@mit.edu [Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Nguyen, N.C., E-mail: cuongng@mit.edu [Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Giles, M.B., E-mail: mike.giles@maths.ox.ac.uk [Mathematical Institute, University of Oxford, Oxford (United Kingdom); Peraire, J., E-mail: peraire@mit.edu [Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)
2015-09-15
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.
Recently, it has been shown that the figure of merit (FOM) of Monte Carlo source-detector problems can be enhanced by using a variational rather than a direct functional to estimate the detector response. The direct functional, which is traditionally employed in Monte Carlo simulations, requires an estimate of the solution of the forward problem within the detector region. The variational functional is theoretically more accurate than the direct functional, but it requires estimates of the solutions of the forward and adjoint source-detector problems over the entire phase-space of the problem. In recent work, we have performed Monte Carlo simulations using the variational functional by (a) approximating the adjoint solution deterministically and representing this solution as a function in phase-space and (b) estimating the forward solution using Monte Carlo. We have called this general procedure variational variance reduction (VVR). The VVR method is more computationally expensive per history than traditional Monte Carlo because extra information must be tallied and processed. However, the variational functional yields a more accurate estimate of the detector response. Our simulations have shown that the VVR reduction in variance usually outweighs the increase in cost, resulting in an increased FOM. In recent work on source-detector problems, we have calculated the adjoint solution deterministically and represented this solution as a linear-in-angle, histogram-in-space function. This procedure has several advantages over previous implementations: (a) it requires much less adjoint information to be stored and (b) it is highly efficient for diffusive problems, due to the accurate linear-in-angle representation of the adjoint solution. (Traditional variance-reduction methods perform poorly for diffusive problems.) Here, we extend this VVR method to Monte Carlo criticality calculations, which are often diffusive and difficult for traditional variance-reduction methods
Vincenza Di Stefano
2009-11-01
Full Text Available The Multicomb variance reduction technique has been introduced in the Direct Monte Carlo Simulation for submicrometric semiconductor devices. The method has been implemented in bulk silicon. The simulations show that the statistical variance of hot electrons is reduced with some computational cost. The method is efficient and easy to implement in existing device simulators.
The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool
Nuclear criticality safety and other neutronics analyses usually require a converged fission source for accurate eigenvalues and spatial distributions. While convergence may be rapid for compact systems, it can be either slow or erratic (or both) if a system contains loosely coupled multiplying components. This work is aimed at understanding the influence of Monte Carlo fission source algorithms on estimated fission rate distributions in two simple cases. The results show that sampling of fission sites should be avoided to the extent possible and that eliminating unnecessary sampling can reduce reaction rate estimate variances substantially and accordingly reduce the computational effort for reaction rate estimation. The fundamental purpose of Monte Carlo neutronics is to simulate faithfully the effects of fission on the neutron population. The methods employed vary among codes, but they must not generate biases or underestimates of uncertainties, and they ought to be computationally efficient. For example, a code may produce a potential fission either when a neutron collides or at absorption. The site weight can be the probability either of producing a fission neutron or of causing fission and may be adjusted by keff or some similar constant to keep the site population roughly constant. Potential sites are somehow selected for the site bank, and the starting neutrons for the next generation are then picked from the bank, perhaps re-sampled in some way to control the neutron population. The daughter neutron may be emitted with weight nu-bar or one. Using the VIM code, we have analyzed the fission site behavior of a simple system consisting of two thick homogeneous slabs of aqueous fissile solution separated by a thick slab of water in a symmetrical arrangement using 2000 histories/generation. Yamamoto et al. reported fluctuations of 75% in the instantaneous fission site populations in each slab, which is much larger than one expects in a Monte Carlo calculation
Variance reduction techniques for 14 MeV neutron streaming problem in rectangular annular bent duct
Ueki, Kotaro [Ship Research Inst., Mitaka, Tokyo (Japan)
1998-03-01
Monte Carlo method is the powerful technique for solving wide range of radiation transport problems. Its features are that it can solve the Boltzmann`s transport equation almost without approximation, and that the complexity of the systems to be treated rarely becomes a problem. However, the Monte Carlo calculation is always accompanied by statistical errors called variance. In shielding calculation, standard deviation or fractional standard deviation (FSD) is used frequently. The expression of the FSD is shown. Radiation shielding problems are roughly divided into transmission through deep layer and streaming problem. In the streaming problem, the large difference in the weight depending on the history of particles makes the FSD of Monte Carlo calculation worse. The streaming experiment in the 14 MeV neutron rectangular annular bent duct, which is the typical streaming bench mark experiment carried out of the OKTAVIAN of Osaka University, was analyzed by MCNP 4B, and the reduction of variance or FSD was attempted. The experimental system is shown. The analysis model by MCNP 4B, the input data and the results of analysis are reported, and the comparison with the experimental results was examined. (K.I.)
Importance Sampling Variance Reduction for the Fokker-Planck Rarefied Gas Particle Method
Collyer, Benjamin; Lockerby, Duncan
2015-01-01
Models and methods that are able to accurately and efficiently predict the flows of low-speed rarefied gases are in high demand, due to the increasing ability to manufacture devices at micro and nano scales. One such model and method is a Fokker-Planck approximation to the Boltzmann equation, which can be solved numerically by a stochastic particle method. The stochastic nature of this method leads to noisy estimates of the thermodynamic quantities one wishes to sample when the signal is small in comparison to the thermal velocity of the gas. Recently, Gorji et al have proposed a method which is able to greatly reduce the variance of the estimators, by creating a correlated stochastic process which acts as a control variate for the noisy estimates. However, there are potential difficulties involved when the geometry of the problem is complex, as the method requires the density to be solved for independently. Importance sampling is a variance reduction technique that has already been shown to successfully redu...
Application of fuzzy sets to estimate cost savings due to variance reduction
Munoz, Jairo; Ostwald, Phillip F.
1993-12-01
One common assumption of models to evaluate the cost of variation is that the quality characteristic can be approximated by a standard normal distribution. Such an assumption is invalid for three important cases: (a) when the random variable is always positive, (b) when manual intervention distorts random variation, and (c) when the variable of interest is evaluated by linguistic terms. This paper applies the Weibull distribution to address nonnormal situations and fuzzy logic theory to study the case of quality evaluated via lexical terms. The approach concentrates on the cost incurred by inspection to formulate a probabilistic-possibilistic model that determines cost savings due to variance reduction. The model is tested with actual data from a manual TIG welding process.
A method based on a combination of the variance-reduction techniques of particle splitting and Russian roulette is presented. This method improves the efficiency of radiation transport through linear accelerator geometries simulated with the Monte Carlo method. The method named as ‘splitting-roulette’ was implemented on the Monte Carlo code PENELOPE and tested on an Elekta linac, although it is general enough to be implemented on any other general-purpose Monte Carlo radiation transport code and linac geometry. Splitting-roulette uses any of the following two modes of splitting: simple splitting and ‘selective splitting’. Selective splitting is a new splitting mode based on the angular distribution of bremsstrahlung photons implemented in the Monte Carlo code PENELOPE. Splitting-roulette improves the simulation efficiency of an Elekta SL25 linac by a factor of 45. (paper)
Adewunmi, Adrian; Aickelin, Uwe
2013-01-01
Variance reduction techniques have been shown by others in the past to be a useful tool to reduce variance in Simulation studies. However, their application and success in the past has been mainly domain specific, with relatively little guidelines as to their general applicability, in particular for novices in this area. To facilitate their use, this study aims to investigate the robustness of individual techniques across a set of scenarios from different domains. Experimental results show th...
A zero-variance (ZV) Monte Carlo transport method is a theoretical construct that, if it could be implemented on a practical computer, would produce the exact result after any number of histories. Unfortunately, ZV methods are impractical; to implement them, one must have complete knowledge of a certain adjoint flux, and acquiring this knowledge is an infinitely greater task than solving the original criticality or source-detector problem. (In fact, the adjoint flux itself yields the desired result, with no need of a Monte Carlo simulation) Nevertheless, ZV methods are of practical interest because it is possible to approximate them in ways that yield efficient variance-reduction schemes. Such implementations must be done carefully. For example, one must not change the mean of the final answer) The goal of variance reduction is to estimate the true mean with greater efficiency. In this paper, we describe new ZV methods for Monte Carlo criticality and source-detector problems. These methods have the same requirements (and disadvantages) as described earlier. However, their implementation is very different. Thus, the concept of approximating them to obtain practical variance-reduction schemes opens new possibilities. In previous ZV methods, (a) a single characteristic parameter (the k-eigenvalue or a detector response) of a forward transport problem is sought; (b) the exact solution of an adjoint problem must be known for all points in phase-space; and (c) a non-analog process, defined in terms of the adjoint solution, transports forward Monte Carlo particles from the source to the detector (in criticality problems, from the fission region, where a generation n fission neutron is born, back to the fission region, where generation n+1 fission neutrons are born). In the non-analog transport process, Monte Carlo particles (a) are born in the source region with weight equal to the desired characteristic parameter, (b) move through the system by an altered transport
Implementation of background scattering variance reduction on the RapidNano particle scanner
van der Walle, P.; Hannemann, S.; Eijk, D.(Nikhef National Institute for Subatomic Physics, Amsterdam, The Netherlands); Mulckhuyse, W.F.W.; Donck, J.C.J. van der
2014-01-01
The background in simple dark field particle inspection shows a high scatter variance which cannot be distinguished from signals by small particles. According to our models, illumination from different azimuths can reduce the background variance. A multi-azimuth illumination has been successfully integrated on the Rapid Nano particle scanner. This illumination method reduces the variance of the background scattering on substrate roughness. It allows for a lower setting of the detection thresh...
Application of variance reduction technique to nuclear transmutation system driven by accelerator
Sasa, Toshinobu [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1998-03-01
In Japan, it is the basic policy to dispose the high level radioactive waste arising from spent nuclear fuel in stable deep strata after glass solidification. If the useful elements in the waste can be separated and utilized, resources are effectively used, and it can be expected to guarantee high economical efficiency and safety in the disposal in strata. Japan Atomic Energy Research Institute proposed the hybrid type transmutation system, in which high intensity proton accelerator and subcritical fast core are combined, or the nuclear reactor which is optimized for the exclusive use for transmutation. The tungsten target, minor actinide nitride fuel transmutation system and the melted minor actinide chloride salt target fuel transmutation system are outlined. The conceptual figures of both systems are shown. As the method of analysis, Version 2.70 of Lahet Code System which was developed by Los Alamos National Laboratory in USA was adopted. In case of carrying out the analysis of accelerator-driven subcritical core in the energy range below 20 MeV, variance reduction technique must be applied. (K.I.)
Validation of variance reduction techniques in Mediso (SPIRIT DH-V) SPECT system by Monte Carlo
Monte Carlo simulation of nuclear medical imaging systems is a widely used method for reproducing their operation in a real clinical environment, There are several Single Photon Emission Tomography (SPECT) systems in Cuba. For this reason it is clearly necessary to introduce a reliable and fast simulation platform in order to obtain consistent image data. This data will reproduce the original measurements conditions. In order to fulfill these requirements Monte Carlo platform GAMOS (Geant4 Medicine Oriented Architecture for Applications) have been used. Due to the very size and complex configuration of parallel hole collimators in real clinical SPECT systems, Monte Carlo simulation usually consumes excessively high time and computing resources. main goal of the present work is to optimize the efficiency of calculation by means of new GAMOS functionality. There were developed and validated two GAMOS variance reduction techniques to speed up calculations. These procedures focus and limit transport of gamma quanta inside the collimator. The obtained results were asses experimentally in Mediso (SPIRIT DH-V) SPECT system. Main quality control parameters, such as sensitivity and spatial resolution were determined. Differences of 4.6% sensitivity and 8.7% spatial resolution were reported against manufacturer values. Simulation time was decreased up to 650 times. Using these techniques it was possible to perform several studies in almost 8 hours each. (Author)
Makgae, R. [Pebble Bed Modular Reactor (PBMR), P.O. Box 9396, Centurion (South Africa)
2008-07-01
A private company, Citrus Research International (CIR) is intending to construct an insect irradiation facility for the irradiation of insect for pest management in south western region of South Africa. The facility will employ a Co-60 cylindrical source in the chamber. An adequate thickness for the concrete shielding walls and the ability of the labyrinth leading to the irradiation chamber, to attenuate radiation to dose rates that are acceptably low, were determined. Two methods of MCNP variance reduction techniques were applied to accommodate the two pathways of deep penetration to evaluate the radiological impact outside the 150 cm concrete walls and steaming of gamma photons through the labyrinth. The point-kernel based MicroShield software was used in the deep penetration calculations for the walls around the source room to test its accuracy and the results obtained are in good agreement with about 15-20% difference. The dose rate mapping due to radiation Streaming along the labyrinth to the facility entrance is also to be validated with the Attila code, which is a deterministic code that solves the Discrete Ordinates approximation. This file provides a template for writing papers for the conference. (authors)
A private company, Citrus Research International (CIR) is intending to construct an insect irradiation facility for the irradiation of insect for pest management in south western region of South Africa. The facility will employ a Co-60 cylindrical source in the chamber. An adequate thickness for the concrete shielding walls and the ability of the labyrinth leading to the irradiation chamber, to attenuate radiation to dose rates that are acceptably low, were determined. Two methods of MCNP variance reduction techniques were applied to accommodate the two pathways of deep penetration to evaluate the radiological impact outside the 150 cm concrete walls and steaming of gamma photons through the labyrinth. The point-kernel based MicroShield software was used in the deep penetration calculations for the walls around the source room to test its accuracy and the results obtained are in good agreement with about 15-20% difference. The dose rate mapping due to radiation Streaming along the labyrinth to the facility entrance is also to be validated with the Attila code, which is a deterministic code that solves the Discrete Ordinates approximation. This file provides a template for writing papers for the conference. (authors)
Somasundaram, E.; Palmer, T. S. [Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, 116 Radiation Center, Corvallis, OR 97332-5902 (United States)
2013-07-01
In this paper, the work that has been done to implement variance reduction techniques in a three dimensional, multi group Monte Carlo code - Tortilla, that works within the frame work of the commercial deterministic code - Attila, is presented. This project is aimed to develop an integrated Hybrid code that seamlessly takes advantage of the deterministic and Monte Carlo methods for deep shielding radiation detection problems. Tortilla takes advantage of Attila's features for generating the geometric mesh, cross section library and source definitions. Tortilla can also read importance functions (like adjoint scalar flux) generated from deterministic calculations performed in Attila and use them to employ variance reduction schemes in the Monte Carlo simulation. The variance reduction techniques that are implemented in Tortilla are based on the CADIS (Consistent Adjoint Driven Importance Sampling) method and the LIFT (Local Importance Function Transform) method. These methods make use of the results from an adjoint deterministic calculation to bias the particle transport using techniques like source biasing, survival biasing, transport biasing and weight windows. The results obtained so far and the challenges faced in implementing the variance reduction techniques are reported here. (authors)
In this paper, the work that has been done to implement variance reduction techniques in a three dimensional, multi group Monte Carlo code - Tortilla, that works within the frame work of the commercial deterministic code - Attila, is presented. This project is aimed to develop an integrated Hybrid code that seamlessly takes advantage of the deterministic and Monte Carlo methods for deep shielding radiation detection problems. Tortilla takes advantage of Attila's features for generating the geometric mesh, cross section library and source definitions. Tortilla can also read importance functions (like adjoint scalar flux) generated from deterministic calculations performed in Attila and use them to employ variance reduction schemes in the Monte Carlo simulation. The variance reduction techniques that are implemented in Tortilla are based on the CADIS (Consistent Adjoint Driven Importance Sampling) method and the LIFT (Local Importance Function Transform) method. These methods make use of the results from an adjoint deterministic calculation to bias the particle transport using techniques like source biasing, survival biasing, transport biasing and weight windows. The results obtained so far and the challenges faced in implementing the variance reduction techniques are reported here. (authors)
Advanced digital signal processing and noise reduction
Vaseghi, Saeed V
2008-01-01
Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates an
Advanced sludge reduction and phosphorous removal process
无
2006-01-01
An advanced sludge reduction process, i.e. sludge reduction and phosphorous removal process, was developed. The results show that excellent sludge reduction and biological phosphorous removal can be achieved perfectly in this system. When chemical oxygen demand ρ(COD) is 332 - 420 mg/L, concentration of ammonia ρ(NH3-N) is 30 - 40 mg/L and concentration of total phosphorous ρ(TP) is 6.0 - 9.0 mg/L in influent, the system still ensures ρ(COD)＜23 mg/L, ρ(NH3-N)＜3.2 mg/L and ρ(TP)＜0.72 mg/L in effluent. Besides, when the concentration of dissolved oxygen ρ(DO) is around 1.0 mg/L, sludge production is less than 0. 140 g with the consumption of 1 g COD, and the phosphorous removal exceeds 91%. Also, 48.4% of total nitrogen is removed by simultaneous nitrification and denitrification.
We develop a 'Local' Exponential Transform method which distributes the particles nearly uniformly across the system in Monte Carlo transport calculations. An exponential approximation to the continuous transport equation is used in each mesh cell to formulate biasing parameters. The biasing parameters, which resemble those of the conventional exponential transform, tend to produce a uniform sampling of the problem geometry when applied to a forward Monte Carlo calculation, and thus they help to minimize the maximum variance of the flux. Unlike the conventional exponential transform, the biasing parameters are spatially dependent, and are automatically determined from a forward diffusion calculation. We develop two versions of the forward Local Exponential Transform method, one with spatial biasing only, and one with spatial and angular biasing. The method is compared to conventional geometry splitting/Russian roulette for several sample one-group problems in X-Y geometry. The forward Local Exponential Transform method with angular biasing is found to produce better results than geometry splitting/Russian roulette in terms of minimizing the maximum variance of the flux. (orig.)
The variance reduction method can be classified to three technical categories that are source, collision, and transport biasing. All of the variance reduction techniques require specific parameters to control the transport probability. One of well-known methods to determine the optimized transport probability is called as the Consistent Adjoint Driven Importance Sampling (CADIS) method. The CADIS method uses adjoint function to reduce the error of the response. This method can give high variance reduction efficiency on the single response in any problem. However, the CADIS method cannot properly reduce individual relative error for the cases, which have more than two responses. In this study, a multi-response CADIS method was derived by considering each position of the responses. Using the multi-response CADIS method, a radiation transport problem was estimated by applying it into the source angular biasing. The results were compared with those of the CADIS approach and the analog MC method. In this study, a multi-response CADIS method was proposed for minimizing relative errors in various tally regions. To reduce all relative errors for various responses, a weight decision equation was derived. For the verification of the proposed method, a shielding problem was set and the MC simulations were pursued. The results with the proposed method were compared with those estimated by CADIS and analog MC methods. The analysis shows that the relative error of each tally region can be successfully and efficiently reduced for overall regions than the other methods. It can be utilized for accurate calculation of various radiation transport problems, as well as to save the calculation time. Therefore, it is expected that the proposed method can contribute the improvement of expandability in Monte Carlo simulation
We address the problem of estimating steady-state quantities associated to systems of stochastic chemical kinetics. In most cases of interest, these systems are analytically intractable, and one has to resort to computational methods to estimate stationary values of cost functions. In this work, we introduce a novel variance reduction algorithm for stochastic chemical kinetics, inspired by related methods in queueing theory, in particular the use of shadow functions. Using two numerical examples, we demonstrate the efficiency of the method for the calculation of steady-state parametric sensitivities and evaluate its performance in comparison to other estimation methods
Milias-Argeitis, Andreas; Lygeros, John; Khammash, Mustafa
2014-07-01
We address the problem of estimating steady-state quantities associated to systems of stochastic chemical kinetics. In most cases of interest, these systems are analytically intractable, and one has to resort to computational methods to estimate stationary values of cost functions. In this work, we introduce a novel variance reduction algorithm for stochastic chemical kinetics, inspired by related methods in queueing theory, in particular the use of shadow functions. Using two numerical examples, we demonstrate the efficiency of the method for the calculation of steady-state parametric sensitivities and evaluate its performance in comparison to other estimation methods.
Golzari, Fahimeh; Jalili, Saeed
2015-07-21
In protein function prediction (PFP) problem, the goal is to predict function of numerous well-sequenced known proteins whose function is not still known precisely. PFP is one of the special and complex problems in machine learning domain in which a protein (regarded as instance) may have more than one function simultaneously. Furthermore, the functions (regarded as classes) are dependent and also are organized in a hierarchical structure in the form of a tree or directed acyclic graph. One of the common learning methods proposed for solving this problem is decision trees in which, by partitioning data into sharp boundaries sets, small changes in the attribute values of a new instance may cause incorrect change in predicted label of the instance and finally misclassification. In this paper, a Variance Reduction based Binary Fuzzy Decision Tree (VR-BFDT) algorithm is proposed to predict functions of the proteins. This algorithm just fuzzifies the decision boundaries instead of converting the numeric attributes into fuzzy linguistic terms. It has the ability of assigning multiple functions to each protein simultaneously and preserves the hierarchy consistency between functional classes. It uses the label variance reduction as splitting criterion to select the best "attribute-value" at each node of the decision tree. The experimental results show that the overall performance of the proposed algorithm is promising. PMID:25865524
In this study, azimuthal particle redistribution (APR), and azimuthal particle rotational splitting (APRS) methods are implemented in MCNPX2.4 source code. First of all, the efficiency of these methods was compared to two tallying methods. The APRS is more efficient than the APR method in track length estimator tallies. However in the energy deposition tally, both methods have nearly the same efficiency. Latent variance reduction factors were obtained for 6, 10 and 18 MV photons as well. The APRS relative efficiency contours were obtained. These obtained contours reveal that by increasing the photon energies, the contours depth and the surrounding areas were further increased. The relative efficiency contours indicated that the variance reduction factor is position and energy dependent. The out of field voxels relative efficiency contours showed that latent variance reduction methods increased the Monte Carlo (MC) simulation efficiency in the out of field voxels. The APR and APRS average variance reduction factors had differences less than 0.6% for splitting number of 1000. -- Highlights: ► The efficiency of APR and APRS methods was compared to two tallying methods. ► The APRS is more efficient than the APR method in track length estimator tallies. ► In the energy deposition tally, both methods have nearly the same efficiency. ► Variance reduction factors of these methods are position and energy dependent.
Golosio, Bruno; Schoonjans, Tom; Brunetti, Antonio; Oliva, Piernicola; Masala, Giovanni Luca
2014-03-01
The simulation of X-ray imaging experiments is often performed using deterministic codes, which can be relatively fast and easy to use. However, such codes are generally not suitable for the simulation of even slightly more complex experimental conditions, involving, for instance, first-order or higher-order scattering, X-ray fluorescence emissions, or more complex geometries, particularly for experiments that combine spatial resolution with spectral information. In such cases, simulations are often performed using codes based on the Monte Carlo method. In a simple Monte Carlo approach, the interaction position of an X-ray photon and the state of the photon after an interaction are obtained simply according to the theoretical probability distributions. This approach may be quite inefficient because the final channels of interest may include only a limited region of space or photons produced by a rare interaction, e.g., fluorescent emission from elements with very low concentrations. In the field of X-ray fluorescence spectroscopy, this problem has been solved by combining the Monte Carlo method with variance reduction techniques, which can reduce the computation time by several orders of magnitude. In this work, we present a C++ code for the general simulation of X-ray imaging and spectroscopy experiments, based on the application of the Monte Carlo method in combination with variance reduction techniques, with a description of sample geometry based on quadric surfaces. We describe the benefits of the object-oriented approach in terms of code maintenance, the flexibility of the program for the simulation of different experimental conditions and the possibility of easily adding new modules. Sample applications in the fields of X-ray imaging and X-ray spectroscopy are discussed. Catalogue identifier: AERO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERO_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland
Modern portfolio theory is applied to the problem of selecting which vehicle technologies and fuels to use in the next generation of vehicles. Selecting vehicles with the lowest lifetime cost is complicated by the fact that future prices are uncertain, just as selecting securities for an investment portfolio is complicated by the fact that future returns are uncertain. A quadratic program is developed based on modern portfolio theory, with the objective of minimizing the expected lifetime cost of the 'vehicle portfolio'. Constraints limit greenhouse gas emissions, as well as the variance of the cost. A case study is performed for light-duty passenger vehicles in the United States, drawing emissions and usage data from the US Environmental Protection Agency's MOVES and Department of Energy's GREET models, among other sources. Four vehicle technologies are considered: conventional gasoline, conventional diesel, grid-independent (non-plug-in) gasoline-electric hybrid, and flex fuel using E85. Results indicate that much of the uncertainty surrounding cost stems from fuel price fluctuations, and that fuel efficient vehicles can lower cost variance. Hybrids exhibit the lowest cost variances of the technologies considered, making them an arguably financially conservative choice.
Targeted reduction of advanced glycation improves renal function in obesity
Harcourt, Brooke E; Sourris, Karly C; Coughlan, Melinda T;
2011-01-01
Obesity is highly prevalent in Western populations and is considered a risk factor for the development of renal impairment. Interventions that reduce the tissue burden of advanced glycation end-products (AGEs) have shown promise in stemming the progression of chronic disease. Here we tested if...... function and an inflammatory profile (monocyte chemoattractant protein-1 (MCP-1) and macrophage migration inhibitory factor (MIF)) were improved following the low-AGE diet. Mechanisms of advanced glycation-related renal damage were investigated in a mouse model of obesity using the AGE......, and renal oxidative stress. Alagebrium treatment, however, resulted in decreased weight gain and improved glycemic control compared with wild-type mice on a high-fat Western diet. Thus, targeted reduction of the advanced glycation pathway improved renal function in obesity....
In the fixed source problem such as a neutron deep penetration calculation with the Monte Carlo method, the application of the variance reduction method is most important for a high figure of merit (FOM) and the most reliable calculation. But, MCNP calculation inputs written in published literature are not to be best solution. The most concerned items are setting method for the lower weight bound on the weight window method and the exclusion radius for a point estimator. In those literatures, the lower weight bound is estimated by engineering judge or weight window generator in the MCNP. In the latter case, the lower weight bound is used with no turning process. Because of abnormal large lower weight bounds, many neutron are killed in no meaning by the Russian Roulette. The adjoint flux method for setting of lower weight bound should be adapted as a standard variance reduction method. The Monte Carlo calculation should be turned from the experience such as engineering judge to science such as adjoint method. (author)
Fluid Mechanics, Drag Reduction and Advanced Configuration Aeronautics
Bushnell, Dennis M.
2000-01-01
This paper discusses Advanced Aircraft configurational approaches across the speed range, which are either enabled, or greatly enhanced, by clever Flow Control. Configurations considered include Channel Wings with circulation control for VTOL (but non-hovering) operation with high cruise speed, strut-braced CTOL transports with wingtip engines and extensive ('natural') laminar flow control, a midwing double fuselage CTOL approach utilizing several synergistic methods for drag-due-to-lift reduction, a supersonic strut-braced configuration with order of twice the L/D of current approaches and a very advanced, highly engine flow-path-integrated hypersonic cruise machine. This paper indicates both the promise of synergistic flow control approaches as enablers for 'Revolutions' in aircraft performance and fluid mechanic 'areas of ignorance' which impede their realization and provide 'target-rich' opportunities for Fluids Research.
Cycle update : advanced fuels and technologies for emissions reduction
Smallwood, G. [National Research Council of Canada, Ottawa, ON (Canada)
2009-07-01
This paper provided a summary of key achievements of the Program of Energy Research and Development advanced fuels and technologies for emissions reduction (AFTER) program over the funding cycle from fiscal year 2005/2006 to 2008/2009. The purpose of the paper was to inform interested parties of recent advances in knowledge and in science and technology capacities in a concise manner. The paper discussed the high level research and development themes of the AFTER program through the following 4 overarching questions: how could advanced fuels and internal combustion engine designs influence emissions; how could emissions be reduced through the use of engine hardware including aftertreatment devices; how do real-world duty cycles and advanced technology vehicles operating on Canadian fuels compare with existing technologies, models and estimates; and what are the health risks associated with transportation-related emissions. It was concluded that the main issues regarding the use of biodiesel blends in current technology diesel engines are the lack of consistency in product quality; shorter shelf life of biodiesel due to poorer oxidative stability; and a need to develop characterization methods for the final oxygenated product because most standard methods are developed for hydrocarbons and are therefore inadequate. 2 tabs., 13 figs.
Advanced MMIS Toward Substantial Reduction in Human Errors in NPPs
This paper aims to give an overview of the methods to inherently prevent human errors and to effectively mitigate the consequences of such errors by securing defense-in-depth during plant management through the advanced man-machine interface system (MMIS). It is needless to stress the significance of human error reduction during an accident in nuclear power plants (NPPs). Unexpected shutdowns caused by human errors not only threaten nuclear safety but also make public acceptance of nuclear power extremely lower. We have to recognize there must be the possibility of human errors occurring since humans are not essentially perfect particularly under stressful conditions. However, we have the opportunity to improve such a situation through advanced information and communication technologies on the basis of lessons learned from our experiences. As important lessons, authors explained key issues associated with automation, man-machine interface, operator support systems, and procedures. Upon this investigation, we outlined the concept and technical factors to develop advanced automation, operation and maintenance support systems, and computer-based procedures using wired/wireless technology. It should be noted that the ultimate responsibility of nuclear safety obviously belongs to humans not to machines. Therefore, safety culture including education and training, which is a kind of organizational factor, should be emphasized as well. In regard to safety culture for human error reduction, several issues that we are facing these days were described. We expect the ideas of the advanced MMIS proposed in this paper to lead in the future direction of related researches and finally supplement the safety of NPPs
Potential for Landing Gear Noise Reduction on Advanced Aircraft Configurations
Thomas, Russell H.; Nickol, Craig L.; Burley, Casey L.; Guo, Yueping
2016-01-01
The potential of significantly reducing aircraft landing gear noise is explored for aircraft configurations with engines installed above the wings or the fuselage. An innovative concept is studied that does not alter the main gear assembly itself but does shorten the main strut and integrates the gear in pods whose interior surfaces are treated with acoustic liner. The concept is meant to achieve maximum noise reduction so that main landing gears can be eliminated as a major source of airframe noise. By applying this concept to an aircraft configuration with 2025 entry-into-service technology levels, it is shown that compared to noise levels of current technology, the main gear noise can be reduced by 10 EPNL dB, bringing the main gear noise close to a floor established by other components such as the nose gear. The assessment of the noise reduction potential accounts for design features for the advanced aircraft configuration and includes the effects of local flow velocity in and around the pods, gear noise reflection from the airframe, and reflection and attenuation from acoustic liner treatment on pod surfaces and doors. A technical roadmap for maturing this concept is discussed, and the possible drag increase at cruise due to the addition of the pods is identified as a challenge, which needs to be quantified and minimized possibly with the combination of detailed design and application of drag reduction technologies.
Reduction of repository heat load using advanced fuel cycles
With the geologic repository at Yucca Mountain already nearing capacity full before opening, advanced fuel cycles that introduce reprocessing, fast reactors, and temporary storage sites have the potential to allow the repository to support the current reactor fleet and future expansion. An uncertainty analysis methodology that combines Monte Carlo distribution sampling, reactor physics data simulation, and neural network interpolation methods enable investigation into the factor reduction of heat capacity by using the hybrid fuel cycle. Using a Super PRISM fast reactor with a conversion ratio of 0.75, burn ups reach up to 200 MWd/t that decrease the plutonium inventory by about 5 metric tons every 12 years. Using the long burn up allows the footprint of 1 single core loading of FR fuel to have an integral decay heat of about 2.5x105 MW*yr over a 1500 year period that replaces the footprint of about 6 full core loadings of LWR fuel for the number of years required to fuel the FR, which have an integral decay heat of about.3 MW*yr for the same time integral. This results in an increase of a factor of 4 in repository support capacity from implementing a single fast reactor in an equilibrium cycle. (authors)
Advanced Acoustic Blankets for Improved Aircraft Interior Noise Reduction Project
National Aeronautics and Space Administration — In this project advanced acoustic blankets for improved low frequency interior noise control in aircraft will be developed and demonstrated. The improved...
[Advances in molecular mechanism of bacterial reduction of hexavalent chromium].
Li, Dou; Zhao, You-Cai; Song, Li-Yan; Yin, Ya-Jie; Wang, Yang-Qing; Xu, Zhong-Hui
2014-04-01
Cr(VI) has been causing serious environmental pollution due to its carcinogenicity, teratogenicity and strong migration. Reduction of Cr( VI) to Cr(III), a precipitation that is much less toxic, is an efficient strategy to control Cr pollution. Within the strategy, bacterial reduction of Cr(VI) to Cr(III) has been considered as one of the best bioremediation methods because of its efficiency, environment friendly, and low cost; however, the molecular mechanism remains large unknown. This review summarizes Cr(VI) reduction bacterial species and its application in pollution control, elaborates the pathways of Cr( VI) reduction and functional proteins involved, concludes the molecular mechanism of baterial reduction Cr(VI), and discusses the orientation of the future research. PMID:24946623
Advanced Acoustic Blankets for Improved Aircraft Interior Noise Reduction Project
National Aeronautics and Space Administration — The objective of the proposed Phase II research effort is to develop heterogeneous (HG) blankets for improved sound reduction in aircraft structures. Phase I...
Peter Carr; Liuren Wu
2004-01-01
We propose a direct and robust method for quantifying the variance risk premium on financial assets. We theoretically and numerically show that the risk-neutral expected value of the return variance, also known as the variance swap rate, is well approximated by the value of a particular portfolio of options. Ignoring the small approximation error, the difference between the realized variance and this synthetic variance swap rate quantifies the variance risk premium. Using a large options data...
Recent Advances in Electrical Resistance Preheating of Aluminum Reduction Cells
Ali, Mohamed Mahmoud; Kvande, Halvor
2016-06-01
ABSTRACT There are two mainpreheating methods that are used nowadays for aluminum reduction cells. One is based on electrical resistance preheating with a thin bed of small coke and/or graphite particles between the anodes and the cathode carbon blocks. The other is flame preheating, where two or more gas or oil burners are used. Electrical resistance preheating is the oldest method, but is still frequently used by different aluminum producers. Many improvements have been made to this method by different companies over the last decade. In this paper, important points pertaining to the preparation and preheating of these cells, as well as measurements made during the preheating process and evaluation of the performance of the preheating, are illustrated. The preheating times of these cells were found to be between 36 h and 96 h for cell currents between 176 kA and 406 kA, while the resistance bed thickness was between 13 mm and 60 mm. The average cathode surface temperature at the end of the preheating was usually between 800°C and 950°C. The effect of the preheating methods on cell life is unclear and no quantifiable conclusions can be drawn. Some works carried out in the mathematical modeling area are also discussed. It is concluded that there is a need for more studies with real situations for preheated cells on the basis of actual measurements. The expected development in electrical resistance preheating of aluminum reduction cells is also summarized.
Ian Martin
2011-01-01
The large asset price jumps that took place during 2008 and 2009 disrupted volatility derivatives markets and caused the single-name variance swap market to dry up completely. This paper defines and analyzes a simple variance swap, a relative of the variance swap that in several respects has more desirable properties. First, simple variance swaps are robust: they can be easily priced and hedged even if prices can jump. Second, simple variance swaps supply a more accurate measure of market-imp...
Byrne, Vicky; Orndoff, Evelyne; Poritz, Darwin; Schlesinger, Thilini
2013-01-01
All human space missions require significant logistical mass and volume that will become an excessive burden for long duration missions beyond low Earth orbit. The goal of the Advanced Exploration Systems (AES) Logistics Reduction & Repurposing (LRR) project is to bring new ideas and technologies that will enable human presence in farther regions of space. The LRR project has five tasks: 1) Advanced Clothing System (ACS) to reduce clothing mass and volume, 2) Logistics to Living (L2L) to repurpose existing cargo, 3) Heat Melt Compactor (HMC) to reprocess materials in space, 4) Trash to Gas (TTG) to extract useful gases from trash, and 5) Systems Engineering and Integration (SE&I) to integrate these logistical components. The current International Space Station (ISS) crew wardrobe has already evolved not only to reduce some of the logistical burden but also to address crew preference. The ACS task is to find ways to further reduce this logistical burden while examining human response to different types of clothes. The ACS task has been broken into a series of studies on length of wear of various garments: 1) three small studies conducted through other NASA projects (MMSEV, DSH, HI-SEAS) focusing on length of wear of garments treated with an antimicrobial finish; 2) a ground study, which is the subject of this report, addressing both length of wear and subject perception of various types of garments worn during aerobic exercise; and 3) an ISS study replicating the ground study, and including every day clothing to collect information on perception in reduced gravity in which humans experience physiological changes. The goal of the ground study is first to measure how long people can wear the same exercise garment, depending on the type of fabric and the presence of antimicrobial treatment, and second to learn why. Human factors considerations included in the study consist of the Institutional Review Board approval, test protocol and participants' training, and a web
Variance Effects in Cyclic Production Systems
Debashish Sarkar; Willard I. Zangwill
1991-01-01
Utilizing a cyclic queue system, this paper investigates the effect of variance on a multi-item production facility. The variance of setup time, service rate and arrival rate is shown to have a powerful and sometimes paradoxical influence. Reduction in setup time, for example, is usually presumed to reduce inventory. We demonstrate that inventory can blow up if setup time is cut. Another paradoxical effect of variance is on processing rate. Speeding up the processing rate should reduce the ma...
Variance bounding Markov chains
Roberts, Gareth O.; Jeffrey S. Rosenthal
2008-01-01
We introduce a new property of Markov chains, called variance bounding. We prove that, for reversible chains at least, variance bounding is weaker than, but closely related to, geometric ergodicity. Furthermore, variance bounding is equivalent to the existence of usual central limit theorems for all L2 functionals. Also, variance bounding (unlike geometric ergodicity) is preserved under the Peskun order. We close with some applications to Metropolis–Hastings algorithms.
Pollmann, Olaf Axel.
2012-01-01
Sustainable development and resource efficiency are the common global strategies of the 21st century. The actual global natural resource consumption of humankind went far over the limit and to cover this worldwide resource consumption the productivity of 1.5 earths is now necessary. The work “Reduction of anthropogenic environmental influences by advanced and optimized technologies” discussed the problem of advanced resource efficiencies with mining activities in South Afric...
WANG Zhi-hua; ZHOU Jun-hu; ZHANG Yan-wei; LU Zhi-min; FAN Jian-ren; CEN Ke-fa
2005-01-01
Pulverized coal reburning, ammonia injection and advanced reburning in a pilot scale drop tube furnace were investigated. Premix of petroleum gas, air and NH3 were burned in a porous gas burner to generate the needed flue gas. Four kinds of pulverized coal were fed as reburning fuel at constant rate of 1g/min. The coal reburning process parameters including 15%～25% reburn heat input, temperature range from 1100 ℃ to 1400 ℃ and also the carbon in fly ash, coal fineness, reburn zone stoichiometric ratio, etc. were investigated. On the condition of 25% reburn heat input, maximum of 47% NO reduction with Yanzhou coal was obtained by pure coal reburning. Optimal temperature for reburning is about 1300 ℃ and fuel-rich stoichiometric ratio is essential; coal fineness can slightly enhance the reburning ability. The temperature window for ammonia injection is about 700 ℃～1100 ℃. CO can improve the NH3 ability at lower temperature. During advanced reburning, 72.9% NO reduction was measured. To achieve more than 70% NO reduction, Selective Non-catalytic NOx Reduction (SNCR) should need NH3/NO stoichiometric ratio larger than 5, while advanced reburning only uses common dose of ammonia as in conventional SNCR technology. Mechanism study shows the oxidization of CO can improve the decomposition of H2O, which will rich the radical pools igniting the whole reactions at lower temperatures.
Wang, Zhi-hua; Zhou, Jun-hu; Zhang, Yan-wei; Lu, Zhi-min; Fan, Jian-ren; Cen, Ke-fa
2005-01-01
Pulverized coal reburning, ammonia injection and advanced reburning in a pilot scale drop tube furnace were investigated. Premix of petroleum gas, air and NH3 were burned in a porous gas burner to generate the needed flue gas. Four kinds of pulverized coal were fed as reburning fuel at constant rate of 1g/min. The coal reburning process parameters including 15%~25% reburn heat input, temperature range from 1100 °C to 1400 °C and also the carbon in fly ash, coal fineness, reburn zone stoichiometric ratio, etc. were investigated. On the condition of 25% reburn heat input, maximum of 47% NO reduction with Yanzhou coal was obtained by pure coal reburning. Optimal temperature for reburning is about 1300 °C and fuel-rich stoichiometric ratio is essential; coal fineness can slightly enhance the reburning ability. The temperature window for ammonia injection is about 700 °C~1100 °C. CO can improve the NH3 ability at lower temperature. During advanced reburning, 72.9% NO reduction was measured. To achieve more than 70% NO reduction, Selective Non-catalytic NOx Reduction (SNCR) should need NH3/NO stoichiometric ratio larger than 5, while advanced reburning only uses common dose of ammonia as in conventional SNCR technology. Mechanism study shows the oxidization of CO can improve the decomposition of H2O, which will rich the radical pools igniting the whole reactions at lower temperatures. PMID:15682503
Estimation of measurement variances
The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented
Chabuda, Krzysztof; Leroux, Ian; Demkowicz-Dobrzanski, Rafal
2016-01-01
In atomic clocks, the frequency of a local oscillator is stabilized based on the feedback signal obtained by periodically interrogating an atomic reference system. The instability of the clock is characterized by the Allan variance, a measure widely used to describe the noise of frequency standards. We provide an explicit method to find the ultimate bound on the Allan variance of an atomic clock in the most general scenario where N atoms are prepared in an arbitrarily entangled state and arbi...
ZAYAS Pérez Teresa; GEISSLER Gunther; HERNANDEZ Fernando
2007-01-01
The removal of the natural organic matter present in coffee processing wastewater through chemical coagulation-flocculatio and advanced oxidation processes(AOP)had been studied.The effectiveness of the removal of natural organic matter using commercial flocculants and UV/H202,UVO3 and UV/H-H202/O3 processes was determined under acidic conditions.For each of these processes,different operational conditions were explored to optimize the treatment efficiency of the coffee wastewater.Coffee wastewater is characterized by a high chemical oxygen demand(COD)and low total suspended solids.The outcomes of coffee wastewater reeatment using coagulation-flocculation and photodegradation processes were assessed in terms of reduction of COD,color,and turbidity.It was found that a reductiOn in COD of 67%could be realized when the coffee wastewater was treated by chemical coagulation-flocculatlon witll lime and coagulant T-1.When coffee wastewater was treated by coagulation-flocculation in combination with UV/H202,a COD reduction of 86%was achieved,although only after prolonged UV irradiation.Of the three advanced oxidation processes considered,UV/H202,uv/03 and UV/H202/03,we found that the treatment with UV/H2O2/O3 was the most effective,with an efficiency of color,turbidity and further COD removal of 87%,when applied to the flocculated coffee wastewater.
Zayas Pérez, Teresa; Geissler, Gunther; Hernandez, Fernando
2007-01-01
The removal of the natural organic matter present in coffee processing wastewater through chemical coagulation-flocculation and advanced oxidation processes (AOP) had been studied. The effectiveness of the removal of natural organic matter using commercial flocculants and UV/H2O2, UV/O3 and UV/H2O2/O3 processes was determined under acidic conditions. For each of these processes, different operational conditions were explored to optimize the treatment efficiency of the coffee wastewater. Coffee wastewater is characterized by a high chemical oxygen demand (COD) and low total suspended solids. The outcomes of coffee wastewater treatment using coagulation-flocculation and photodegradation processes were assessed in terms of reduction of COD, color, and turbidity. It was found that a reduction in COD of 67% could be realized when the coffee wastewater was treated by chemical coagulation-flocculation with lime and coagulant T-1. When coffee wastewater was treated by coagulation-flocculation in combination with UV/H2O2, a COD reduction of 86% was achieved, although only after prolonged UV irradiation. Of the three advanced oxidation processes considered, UV/H2O2, UV/O3 and UV/H2O2/O3, we found that the treatment with UV/H2O2/O3 was the most effective, with an efficiency of color, turbidity and further COD removal of 87%, when applied to the flocculated coffee wastewater. PMID:17918591
Recent Advances in Inorganic Heterogeneous Electrocatalysts for Reduction of Carbon Dioxide.
Zhu, Dong Dong; Liu, Jin Long; Qiao, Shi Zhang
2016-05-01
In view of the climate changes caused by the continuously rising levels of atmospheric CO2 , advanced technologies associated with CO2 conversion are highly desirable. In recent decades, electrochemical reduction of CO2 has been extensively studied since it can reduce CO2 to value-added chemicals and fuels. Considering the sluggish reaction kinetics of the CO2 molecule, efficient and robust electrocatalysts are required to promote this conversion reaction. Here, recent progress and opportunities in inorganic heterogeneous electrocatalysts for CO2 reduction are discussed, from the viewpoint of both experimental and computational aspects. Based on elemental composition, the inorganic catalysts presented here are classified into four groups: metals, transition-metal oxides, transition-metal chalcogenides, and carbon-based materials. However, despite encouraging accomplishments made in this area, substantial advances in CO2 electrolysis are still needed to meet the criteria for practical applications. Therefore, in the last part, several promising strategies, including surface engineering, chemical modification, nanostructured catalysts, and composite materials, are proposed to facilitate the future development of CO2 electroreduction. PMID:26996295
Purpose: To investigate the prognostic significance of tumor volume reduction rate (TVRR) after preoperative chemoradiotherapy (CRT) in locally advanced rectal cancer (LARC). Methods and Materials: In total, 430 primary LARC (cT3–4) patients who were treated with preoperative CRT and curative radical surgery between May 2002 and March 2008 were analyzed retrospectively. Pre- and post-CRT tumor volumes were measured using three-dimensional region-of-interest MR volumetry. Tumor volume reduction rate was determined using the equation TVRR (%) = (pre-CRT tumor volume − post-CRT tumor volume) × 100/pre-CRT tumor volume. The median follow-up period was 64 months (range, 27–99 months) for survivors. Endpoints were disease-free survival (DFS) and overall survival (OS). Results: The median TVRR was 70.2% (mean, 64.7% ± 22.6%; range, 0–100%). Downstaging (ypT0–2N0M0) occurred in 183 patients (42.6%). The 5-year DFS and OS rates were 77.7% and 86.3%, respectively. In the analysis that included pre-CRT and post-CRT tumor volumes and TVRR as continuous variables, only TVRR was an independent prognostic factor. Tumor volume reduction rate was categorized according to a cutoff value of 45% and included with clinicopathologic factors in the multivariate analysis; ypN status, circumferential resection margin, and TVRR were significant prognostic factors for both DFS and OS. Conclusions: Tumor volume reduction rate was a significant prognostic factor in LARC patients receiving preoperative CRT. Tumor volume reduction rate data may be useful for tailoring surgery and postoperative adjuvant therapy after preoperative CRT.
Janáček, Jiří
Jena : Friedrich-Schiller-Universität, 2007. s. 23-23. [Workshop on Stochastic Geometry, Stereology and Image Analysis /14./. 23.09.2007-28.09.2007, Neudietendorf] R&D Projects: GA AV ČR(CZ) IAA100110502 Institutional research plan: CEZ:AV0Z50110509 Keywords : spr2 * stereology * volume * variance Subject RIV: EA - Cell Biology
Minimum variance geographic sampling
Terrell, G. R. (Principal Investigator)
1980-01-01
Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.
Conversations across Meaning Variance
Cordero, Alberto
2013-01-01
Progressive interpretations of scientific theories have long been denounced as naive, because of the inescapability of meaning variance. The charge reportedly applies to recent realist moves that focus on theory-parts rather than whole theories. This paper considers the question of what "theory-parts" of epistemic significance (if any) relevantly…
Braun, W. John
2012-01-01
The Analysis of Variance is often taught in introductory statistics courses, but it is not clear that students really understand the method. This is because the derivation of the test statistic and p-value requires a relatively sophisticated mathematical background which may not be well-remembered or understood. Thus, the essential concept behind…
Spectral Ambiguity of Allan Variance
Greenhall, C. A.
1996-01-01
We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.
Local variances in biomonitoring
The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)
Ambiguity Aversion and Variance Premium
Jianjun Miao; Bin Wei; Hao Zhou
2012-01-01
This paper offers an ambiguity-based interpretation of variance premium - the differ- ence between risk-neutral and objective expectations of market return variance - as a com- pounding effect of both belief distortion and variance differential regarding the uncertain economic regimes. Our approach endogenously generates variance premium without impos- ing exogenous stochastic volatility or jumps in consumption process. Such a framework can reasonably match the mean variance premium as well a...
Multivariate variance ratio statistics
Hong, Seok Young; Linton, Oliver; Zhang, Hui Jun
2014-01-01
We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the Efficient Market Hypothesis). We do not impose the no leverage assumption of Lo and MacKinlay (1988) but our asymptotic standard errors are relatively simple and in particular do not require the selection of a band- width parameter. We extend the...
Advancing Development and Greenhouse Gas Reductions in Vietnam's Wind Sector
Bilello, D.; Katz, J.; Esterly, S.; Ogonowski, M.
2014-09-01
Clean energy development is a key component of Vietnam's Green Growth Strategy, which establishes a target to reduce greenhouse gas (GHG) emissions from domestic energy activities by 20-30 percent by 2030 relative to a business-as-usual scenario. Vietnam has significant wind energy resources, which, if developed, could help the country reach this target while providing ancillary economic, social, and environmental benefits. Given Vietnam's ambitious clean energy goals and the relatively nascent state of wind energy development in the country, this paper seeks to fulfill two primary objectives: to distill timely and useful information to provincial-level planners, analysts, and project developers as they evaluate opportunities to develop local wind resources; and, to provide insights to policymakers on how coordinated efforts may help advance large-scale wind development, deliver near-term GHG emission reductions, and promote national objectives in the context of a low emission development framework.
Materials selection of surface coatings in an advanced size reduction facility
A materials selection test program was conducted to characterize optimum interior surface coatings for an advanced size reduction facility. The equipment to be processed by this facility consists of stainless steel apparatus (e.g., glove boxes, piping, and tanks) used for the chemical recovery of plutonium. Test results showed that a primary requirement for a satisfactory coating is ease of decontamination. A closely related concern is the resistance of paint films to nitric acid - plutonium environments. A vinyl copolymer base paint was the only coating, of eight paints tested, with properties that permitted satisfactory decontamination of plutonium and also performed equal to or better than the other paints in the chemical resistance, radiation stability, and impact tests
DEMONSTRATION OF AN ADVANCED INTEGRATED CONTROL SYSTEM FOR SIMULTANEOUS EMISSIONS REDUCTION
Suzanne Shea; Randhir Sehgal; Ilga Celmins; Andrew Maxson
2002-02-01
The primary objective of the project titled ''Demonstration of an Advanced Integrated Control System for Simultaneous Emissions Reduction'' was to demonstrate at proof-of-concept scale the use of an online software package, the ''Plant Environmental and Cost Optimization System'' (PECOS), to optimize the operation of coal-fired power plants by economically controlling all emissions simultaneously. It combines physical models, neural networks, and fuzzy logic control to provide both optimal least-cost boiler setpoints to the boiler operators in the control room, as well as optimal coal blending recommendations designed to reduce fuel costs and fuel-related derates. The goal of the project was to demonstrate that use of PECOS would enable coal-fired power plants to make more economic use of U.S. coals while reducing emissions.
DEMONSTRATION OF AN ADVANCED INTEGRATED CONTROL SYSTEM FOR SIMULTANEOUS EMISSIONS REDUCTION; FINAL
The primary objective of the project titled ''Demonstration of an Advanced Integrated Control System for Simultaneous Emissions Reduction'' was to demonstrate at proof-of-concept scale the use of an online software package, the ''Plant Environmental and Cost Optimization System'' (PECOS), to optimize the operation of coal-fired power plants by economically controlling all emissions simultaneously. It combines physical models, neural networks, and fuzzy logic control to provide both optimal least-cost boiler setpoints to the boiler operators in the control room, as well as optimal coal blending recommendations designed to reduce fuel costs and fuel-related derates. The goal of the project was to demonstrate that use of PECOS would enable coal-fired power plants to make more economic use of U.S. coals while reducing emissions
Biclustering with heterogeneous variance.
Chen, Guanhua; Sullivan, Patrick F; Kosorok, Michael R
2013-07-23
In cancer research, as in all of medicine, it is important to classify patients into etiologically and therapeutically relevant subtypes to improve diagnosis and treatment. One way to do this is to use clustering methods to find subgroups of homogeneous individuals based on genetic profiles together with heuristic clinical analysis. A notable drawback of existing clustering methods is that they ignore the possibility that the variance of gene expression profile measurements can be heterogeneous across subgroups, and methods that do not consider heterogeneity of variance can lead to inaccurate subgroup prediction. Research has shown that hypervariability is a common feature among cancer subtypes. In this paper, we present a statistical approach that can capture both mean and variance structure in genetic data. We demonstrate the strength of our method in both synthetic data and in two cancer data sets. In particular, our method confirms the hypervariability of methylation level in cancer patients, and it detects clearer subgroup patterns in lung cancer data. PMID:23836637
Local variances in biomonitoring
The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)
EPA RREL's mobile volume reduction unit advances soil washing at four Superfund sites
Research testing of the US. Environmental Protection Agency (EPA) Risk Reduction Engineering Laboratory's (RREL) Volume Reduction Unit (VRU), produced data helping advance soil washing as a remedial technology for contaminated soils. Based on research at four Superfund sites, each with a different matrix of organic contaminants, EPA evaluated the soil technology and provided information to forecast realistic, full-scale remediation costs. Primarily a research tool, the VRU is RREL's mobile test unit for investigating the breadth of this technology. During a Superfund Innovative Technology Evaluation (SITE) Demonstration at Escambia Wood Treating Company Site, Pensacola, FL, the VRU treated soil contaminated with pentachlorophenol (PCP) and polynuclear aromatic hydrocarbon-laden creosote (PAH). At Montana Pole and Treatment Plant Site, Butte, MT, the VRU treated soil containing PCP mixed with diesel oil (measured as total petroleum hydrocarbons) and a trace of dioxin. At Dover Air Force Base Site, Dover, DE, the VRU treated soil containing JP-4 jet fuel, measured as TPHC. At Sand Creek Site, Commerce City, CO, the feed soil at this site was contaminated with two pesticides: heptachlor and dieldrin. Less than 10 percent of these pesticides remained in the treated coarse soil fractions
Christelle Pau Ping Wong
2015-10-01
Full Text Available Textile industries consume large volumes of water for dye processing, leading to undesirable toxic dyes in water bodies. Dyestuffs are harmful to human health and aquatic life, and such illnesses as cholera, dysentery, hepatitis A, and hinder the photosynthetic activity of aquatic plants. To overcome this environmental problem, the advanced oxidation process is a promising technique to mineralize a wide range of dyes in water systems. In this work, reduced graphene oxide (rGO was prepared via an advanced chemical reduction route, and its photocatalytic activity was tested by photodegrading Reactive Black 5 (RB5 dye in aqueous solution. rGO was synthesized by dispersing the graphite oxide into the water to form a graphene oxide (GO solution followed by the addition of hydrazine. Graphite oxide was prepared using a modified Hummers’ method by using potassium permanganate and concentrated sulphuric acid. The resulted rGO nanoparticles were characterized using ultraviolet-visible spectrophotometry (UV-Vis, X-ray powder diffraction (XRD, Raman, and Scanning Electron Microscopy (SEM to further investigate their chemical properties. A characteristic peak of rGO-48 h (275 cm−1 was observed in the UV spectrum. Further, the appearance of a broad peak (002, centred at 2θ = 24.1°, in XRD showing that graphene oxide was reduced to rGO. Based on our results, it was found that the resulted rGO-48 h nanoparticles achieved 49% photodecolorization of RB5 under UV irradiation at pH 3 in 60 min. This was attributed to the high and efficient electron transport behaviors of rGO between aromatic regions of rGO and RB5 molecules.
Zhang, Yingying; Zhuang, Yao; Geng, Jinju; Ren, Hongqiang; Xu, Ke; Ding, Lili
2016-04-15
This study investigated the reduction of antibiotic resistance genes (ARGs), intI1 and 16S rRNA genes, by advanced oxidation processes (AOPs), namely Fenton oxidation (Fe(2+)/H2O2) and UV/H2O2 process. The ARGs include sul1, tetX, and tetG from municipal wastewater effluent. The results indicated that the Fenton oxidation and UV/H2O2 process could reduce selected ARGs effectively. Oxidation by the Fenton process was slightly better than that of the UV/H2O2 method. Particularly, for the Fenton oxidation, under the optimal condition wherein Fe(2+)/H2O2 had a molar ratio of 0.1 and a H2O2 concentration of 0.01molL(-1) with a pH of 3.0 and reaction time of 2h, 2.58-3.79 logs of target genes were removed. Under the initial effluent pH condition (pH=7.0), the removal was 2.26-3.35 logs. For the UV/H2O2 process, when the pH was 3.5 with a H2O2 concentration of 0.01molL(-1) accompanied by 30min of UV irradiation, all ARGs could achieve a reduction of 2.8-3.5 logs, and 1.55-2.32 logs at a pH of 7.0. The Fenton oxidation and UV/H2O2 process followed the first-order reaction kinetic model. The removal of target genes was affected by many parameters, including initial Fe(2+)/H2O2 molar ratios, H2O2 concentration, solution pH, and reaction time. Among these factors, reagent concentrations and pH values are the most important factors during AOPs. PMID:26815295
Spectral variance of aeroacoustic data
Rao, K. V.; Preisser, J. S.
1981-01-01
An asymptotic technique for estimating the variance of power spectra is applied to aircraft flyover noise data. The results are compared with directly estimated variances and they are in reasonable agreement. The basic time series need not be Gaussian for asymptotic theory to apply. The asymptotic variance formulae can be useful tools both in the design and analysis phase of experiments of this type.
Introduction to variance estimation
Wolter, Kirk M
2007-01-01
We live in the information age. Statistical surveys are used every day to determine or evaluate public policy and to make important business decisions. Correct methods for computing the precision of the survey data and for making inferences to the target population are absolutely essential to sound decision making. Now in its second edition, Introduction to Variance Estimation has for more than twenty years provided the definitive account of the theory and methods for correct precision calculations and inference, including examples of modern, complex surveys in which the methods have been used successfully. The book provides instruction on the methods that are vital to data-driven decision making in business, government, and academe. It will appeal to survey statisticians and other scientists engaged in the planning and conduct of survey research, and to those analyzing survey data and charged with extracting compelling information from such data. It will appeal to graduate students and university faculty who...
Advances of Ag, Cu, and Ag-Cu alloy nanoparticles synthesized via chemical reduction route
Tan, Kim Seah; Cheong, Kuan Yew, E-mail: cheong@eng.usm.my [Universiti Sains Malaysia, Electronic Materials Research Group, School of Materials and Mineral Resources Engineering (Malaysia)
2013-04-15
Silver (Ag) and copper (Cu) nanoparticles have shown great potential in variety applications due to their excellent electrical and thermal properties resulting high demand in the market. Decreasing in size to nanometer scale has shown distinct improvement in these inherent properties due to larger surface-to-volume ratio. Ag and Cu nanoparticles are also shown higher surface reactivity, and therefore being used to improve interfacial and catalytic process. Their melting points have also dramatically decreased compared with bulk and thus can be processed at relatively low temperature. Besides, regularly alloying Ag into Cu to create Ag-Cu alloy nanoparticles could be used to improve fast oxidizing property of Cu nanoparticles. There are varieties methods have been reported on the synthesis of Ag, Cu, and Ag-Cu alloy nanoparticles. This review aims to cover chemical reduction means for synthesis of those nanoparticles. Advances of this technique utilizing different reagents namely metal salt precursors, reducing agents, and stabilizers, as well as their effects on respective nanoparticles have been systematically reviewed. Other parameters such as pH and temperature that have been considered as an important factor influencing the quality of those nanoparticles have also been reviewed thoroughly.
A Broadband Beamformer Using Controllable Constraints and Minimum Variance
Karimian-Azari, Sam; Benesty, Jacob; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
The minimum variance distortionless response (MVDR) and the linearly constrained minimum variance (LCMV) beamformers are two optimal approaches in the sense of noise reduction. The LCMV beamformer can also reject interferers using linear constraints at the expense of reducing the degree of freedom...
Saedi, Mehdi; Wolk, Jared
2012-01-01
This paper compares a standard GARCH model with a Constant Elasticity of Variance GARCH model across three major currency pairs and the S&P 500 index. We discuss the advantages and disadvantages of using a more sophisticated model designed to estimate the variance of variance instead of assuming it to be a linear function of the conditional variance. The current stochastic volatility and GARCH analogues rest upon this linear assumption. We are able to confirm through empirical estimation ...
Accurate feedwater iron control for dose rate reduction by advanced resin cleaning system in Tokai-2
Dose rate reduction of out-of-core piping is one of main issues in Boiling Water Nuclear Power Plant (BWR). Main source of the out-of-core piping dose rate is 60Co which adhered to the piping and it is influenced by feedwater iron concentration. A relationship between feedwater iron concentration and amount of iron and cobalt, 60Co which deposited on fuel surface had been evaluated at Tokai-2 (1,100 MWe BWR, operated by The Japan Atomic Power Company, commercial operation started on 1978). As the results, it was demonstrated that to keep the amount of deposited iron on fuel surface around 2000μg/cm2 to reduce Co radioactivation. And, when feedwater iron concentration is around 0.5 ppb, that was achieved. But, when feedwater iron becomes less than 0.5 ppb, soluble 60Co concentration in reactor coolant increases and that makes out-of-core piping dose rate increase. So, necessity to control feedwater iron is shown from these behaviors. At Tokai-2, condensate water iron is removed by only condensate demineralizer resin, because Tokai-2 has no condensate filter. That is, iron removal performance of condensate demineralizer resin affects feedwater iron concentration directly. And, iron removal performance of condensate demineralizer resin is caused by resin cleanness. The resin has been cleaned by a resin cleaning method named 'backwash'. But iron on the surface of the resin could not be removed efficiently by the backwash. As the result, feedwater iron could not be reduced to 0.5 ppb. So, Advanced Resin Cleaning System (ARCS) which can remove almost the iron on the resin was retrofitted to Tokai-2, in October 2005 (21nd outage), to reduce feedwater iron. After applying ARCS, resin cleanness was improved, and feedwater iron decreased to around 0.5 ppb same as that of BWR plants with condensate filter. Also, feedwater iron concentration was maintained in around 0.5 ppb by changing frequency of resin cleaning. By using these results, an optimum control method of
One-way analysis of variance with unequal variances.
Rice, W R; Gaines, S. D.
1989-01-01
We have designed a statistical test that eliminates the assumption of equal group variances from one-way analysis of variance. This test is preferable to the standard technique of trial-and-error transformation and can be shown to be an extension of the Behrens-Fisher T test to the case of three or more means. We suggest that this procedure be used in most applications where the one-way analysis of variance has traditionally been applied to biological data.
Minimum Variance Hedging and Stock Index Market Efficiency
Carol Alexander; Andreza Barbosa
2006-01-01
This empirical study examines the impact of both advanced electronic trading platforms and index exchange traded funds (ETFs) on the minimum variance hedging of stock indices with futures. Our findings show that minimum variance hedging may provide an out-of-sample hedging performance that is superior to that of the one-one futures hedge, but only in markets without active trading of ETFs and advanced development of electronic communications networks. However there is no evidence to suggest t...
Wang, Zhi-Hua; Zhou, Jun-Hu; Zhang, Yan-Wei; Lu, Zhi-Min; Fan, Jian-Ren; Cen, Ke-Fa
2005-03-01
Pulverized coal reburning, ammonia injection and advanced reburning in a pilot scale drop tube furnace were investigated. Premix of petroleum gas, air and NH3 were burned in a porous gas burner to generate the needed flue gas. Four kinds of pulverized coal were fed as reburning fuel at constant rate of 1g/min. The coal reburning process parameters including 15% approximately 25% reburn heat input, temperature range from 1100 degrees C to 1400 degrees C and also the carbon in fly ash, coal fineness, reburn zone stoichiometric ratio, etc. were investigated. On the condition of 25% reburn heat input, maximum of 47% NO reduction with Yanzhou coal was obtained by pure coal reburning. Optimal temperature for reburning is about 1300 degrees C and fuel-rich stoichiometric ratio is essential; coal fineness can slightly enhance the reburning ability. The temperature window for ammonia injection is about 700 degrees C approximately 1100 degrees C. CO can improve the NH3 ability at lower temperature. During advanced reburning, 72.9% NO reduction was measured. To achieve more than 70% NO reduction, Selective Non-catalytic NO(x) Reduction (SNCR) should need NH3/NO stoichiometric ratio larger than 5, while advanced reburning only uses common dose of ammonia as in conventional SNCR technology. Mechanism study shows the oxidization of CO can improve the decomposition of H2O, which will rich the radical pools igniting the whole reactions at lower temperatures. PMID:15682503
Modelling volatility by variance decomposition
Amado, Cristina; Teräsvirta, Timo
2011-01-01
In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the conditional and unconditional variances where the transition between regimes over time is smooth. The main focus is on the multiplicative decomposition that decomposes the variance into an unconditional and...
Budget variance analysis using RVUs.
Berlin, M F; Budzynski, M R
1998-01-01
This article details the use of the variance analysis as management tool to evaluate the financial health of the practice. A common financial tool for administrators has been a simple calculation measuring the difference between actual financials vs. budget financials. Standard cost accounting provides a methodology known as variance analysis to better understand the actual vs. budgeted financial streams. The standard variance analysis has been modified by applying relative value units (RVUs) as standards for the practice. PMID:10387247
Volatility investing with variance swaps
Härdle, Wolfgang Karl; Silyakova, Elena
2010-01-01
Traditionally volatility is viewed as a measure of variability, or risk, of an underlying asset. However recently investors began to look at volatility from a different angle. It happened due to emergence of a market for new derivative instruments - variance swaps. In this paper first we introduse the general idea of the volatility trading using variance swaps. Then we describe valuation and hedging methodology for vanilla variance swaps as well as for the 3-rd generation volatility derivativ...
Fixed effects analysis of variance
Fisher, Lloyd; Birnbaum, Z W; Lukacs, E
1978-01-01
Fixed Effects Analysis of Variance covers the mathematical theory of the fixed effects analysis of variance. The book discusses the theoretical ideas and some applications of the analysis of variance. The text then describes topics such as the t-test; two-sample t-test; the k-sample comparison of means (one-way analysis of variance); the balanced two-way factorial design without interaction; estimation and factorial designs; and the Latin square. Confidence sets, simultaneous confidence intervals, and multiple comparisons; orthogonal and nonorthologonal designs; and multiple regression analysi
Park TS
2015-07-01
Full Text Available Tai Sun Park,1 Yoonki Hong,2 Jae Seung Lee,1 Sang Young Oh,3 Sang Min Lee,3 Namkug Kim,3 Joon Beom Seo,3 Yeon-Mok Oh,1 Sang-Do Lee,1 Sei Won Lee1 1Department of Pulmonary and Critical Care Medicine and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; 2Department of Internal Medicine, College of Medicine, Kangwon National University, Chuncheon, Korea; 3Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea Purpose: Endobronchial valve (EBV therapy is increasingly being seen as a therapeutic option for advanced emphysema, but its clinical utility in Asian populations, who may have different phenotypes to other ethnic populations, has not been assessed.Patients and methods: This prospective open-label single-arm clinical trial examined the clinical efficacy and the safety of EBV in 43 consecutive patients (mean age 68.4±7.5, forced expiratory volume in 1 second [FEV1] 24.5%±10.7% predicted, residual volume 208.7%±47.9% predicted with severe emphysema with complete fissure and no collateral ventilation in a tertiary referral hospital in Korea.Results: Compared to baseline, the patients exhibited significant improvements 6 months after EBV therapy in terms of FEV1 (from 0.68±0.26 L to 0.92±0.40 L; P<0.001, 6-minute walk distance (from 233.5±114.8 m to 299.6±87.5 m; P=0.012, modified Medical Research Council dyspnea scale (from 3.7±0.6 to 2.4±1.2; P<0.001, and St George’s Respiratory Questionnaire (from 65.59±13.07 to 53.76±11.40; P=0.028. Nine patients (20.9% had a tuberculosis scar, but these scars did not affect target lobe volume reduction or pneumothorax frequency. Thirteen patients had adverse events, ten (23.3% developed pneumothorax, which included one death due to tension pneumothorax.Conclusion: EBV therapy was as effective and safe in Korean
Trotter, Michael A.; Hopkins, Peter M.
2014-01-01
Advanced chronic obstructive pulmonary disease (COPD) is a significant cause of morbidity. Treatment options beyond conventional medical therapies are limited to a minority of patients. Lung volume reduction surgery (LVRS) although effective in selected subgroups of patients is not commonly undertaken. Morbidity associated with the procedure has contributed to this low utilisation. In response to this, less invasive bronchoscopic lung volume techniques are being developed to attempt to mitiga...
Variance Adjusted Actor Critic Algorithms
Tamar, Aviv; Mannor, Shie
2013-01-01
We present an actor-critic framework for MDPs where the objective is the variance-adjusted expected return. Our critic uses linear function approximation, and we extend the concept of compatible features to the variance-adjusted setting. We present an episodic actor-critic algorithm and show that it converges almost surely to a locally optimal point of the objective function.
Background: Computed tomography (CT) of the brain is performed with high local doses due to high demands on low contrast resolution. Advanced algorithms for noise reduction might be able to preserve critical image information when reducing radiation dose. Purpose: To evaluate the effect of advanced noise filtering on image quality in brain CT acquired with reduced radiation dose. Material and Methods: Thirty patients referred for non-enhanced CT of the brain were examined with two helical protocols: normal dose (ND, CTDIvol 57 mGy) and low dose (LD, CTDIvol 40 mGy) implying a 30% radiation dose reduction. Images from the LD examinations were also post processed with a noise reduction software with non-linear filters (SharpView CT), creating filtered low dose images (FLD) for each patient. The three image stacks for each patient were presented side by side in randomized order. Five radiologists, blinded for dose level and filtering, ranked these three axial image stacks (ND, LD, FLD) as best to poorest (1 to 3) regarding three image quality criteria. Measurements of mean Hounsfield units (HU) and standard deviation (SD) of the HU were calculated for large region of interest in the centrum semiovale as a measure for noise. Results: Ranking results in pooled data showed that the advanced noise filtering significantly improved the image quality in FLD as compared to LD images for all tested criteria. No significant differences in image quality were found between ND examinations and FLD. However, there was a notable inter-reader spread of the ranking. SD values were 15% higher for LD as compared to ND and FLD. Conclusion: The advanced noise filtering clearly improves image quality of CT examinations of the brain. This effect can be used to significantly lower radiation dose.
Boyages, John; Kastanias, Katrina; Koelmeyer, Louise A.; Winch, Caleb J.; Lam, Thomas C.; Sherman, Kerry A.; Munnoch, David Alex; Brorson, Håkan; Ngo, Quan D.; Heydon-White, Asha; Magnussen, John S.; Mackie, Helen
2015-01-01
Purpose This research describes and evaluates a liposuction surgery and multidisciplinary rehabilitation approach for advanced lymphedema of the upper and lower extremities. Methods A prospective clinical study was conducted at an Advanced Lymphedema Assessment Clinic (ALAC) comprised of specialists in plastic surgery, rehabilitation, imaging, oncology, and allied health, at Macquarie University, Australia. Between May 2012 and 31 May 2014, a total of 104 patients attended the ALAC. Eligibili...
Advanced Glycation End Products in Foods and a Practical Guide to Their Reduction in the Diet
URIBARRI, JAIME; WOODRUFF, SANDRA; Goodman, Susan; Cai, Weijing; Chen, Xue; Pyzik, Renata; YONG, ANGIE; STRIKER, GARY E.; Vlassara, Helen
2010-01-01
Modern diets are largely heat-processed and as a result contain high levels of advanced glycation end products (AGEs). Dietary advanced glycation end products (dAGEs) are known to contribute to increased oxidant stress and inflammation, which are linked to the recent epidemics of diabetes and cardiovascular disease. This report significantly expands the available dAGE database, validates the dAGE testing methodology, compares cooking procedures and inhibitory agents on new dAGE formation, and...
Modelling volatility by variance decomposition
Amado, Cristina; Teräsvirta, Timo
In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the...... conditional and unconditional variances where the transition between regimes over time is smooth. The main focus is on the multiplicative decomposition that decomposes the variance into an unconditional and conditional component. A modelling strategy for the time-varying GARCH model based on the...... multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspecification tests. Finite-sample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns...
Trotter, Michael A; Hopkins, Peter M
2014-11-01
Advanced chronic obstructive pulmonary disease (COPD) is a significant cause of morbidity. Treatment options beyond conventional medical therapies are limited to a minority of patients. Lung volume reduction surgery (LVRS) although effective in selected subgroups of patients is not commonly undertaken. Morbidity associated with the procedure has contributed to this low utilisation. In response to this, less invasive bronchoscopic lung volume techniques are being developed to attempt to mitigate some of the risks and costs associated with surgery. Of these, endobronchial valve therapy is the most comprehensively studied although the presence of collateral ventilation in a significant proportion of patients has compromised its widespread utility. Bronchial thermal vapour ablation and lung volume reduction (LVR) coils are not dependent on collateral ventilation. These techniques have shown promise in early clinical trials; ongoing work will establish whether they have a role in the management of advanced COPD. Lung transplantation, although effective in selected patients for palliation of symptoms and improving survival, is limited by donor organ availability and economic constraint. Reconditioning marginal organs previously declined for transplantation with ex vivo lung perfusion (EVLP) is one potential strategy in improving the utilisation of donor organs. By increasing the donor pool, it is hoped lung transplantation might be more accessible for patients with advanced COPD into the future. PMID:25478204
Variance approximation under balanced sampling
Deville, Jean-Claude; Tillé, Yves
2016-01-01
A balanced sampling design has the interesting property that Horvitz–Thompson estimators of totals for a set of balancing variables are equal to the totals we want to estimate, therefore the variance of Horvitz–Thompson estimators of variables of interest are reduced in function of their correlations with the balancing variables. Since it is hard to derive an analytic expression for the joint inclusion probabilities, we derive a general approximation of variance based on a residual technique....
Advanced RF-KO slow-extraction method for the reduction of spill ripple
Noda, K; Shibuya, S; Uesugi, T; Muramatsu, M; Kanazawa, M; Takada, E; Yamada, S
2002-01-01
Two advanced RF-knockout (RF-KO) slow-extraction methods have been developed at HIMAC in order to reduce the spill ripple for accurate heavy-ion cancer therapy: the dual frequency modulation (FM) method and the separated function method. As a result of simulations and experiments, it was verified that the spill ripple could be considerably reduced using these advanced methods, compared with the ordinary RF-KO method. The dual FM method and the separated function method bring about a low spill ripple within standard deviations of around 25% and of 15% during beam extraction within around 2 s, respectively, which are in good agreement with the simulation results.
Mesoscale Gravity Wave Variances from AMSU-A Radiances
Wu, Dong L.
2004-01-01
A variance analysis technique is developed here to extract gravity wave (GW) induced temperature fluctuations from NOAA AMSU-A (Advanced Microwave Sounding Unit-A) radiance measurements. By carefully removing the instrument/measurement noise, the algorithm can produce reliable GW variances with the minimum detectable value as small as 0.1 K2. Preliminary analyses with AMSU-A data show GW variance maps in the stratosphere have very similar distributions to those found with the UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder). However, the AMSU-A offers better horizontal and temporal resolution for observing regional GW variability, such as activity over sub-Antarctic islands.
Roden, E.E.; Urrutia, M.M.
1997-07-01
'The authors have made considerable progress toward a number of project objectives during the first several months of activity on the project. An exhaustive analysis was made of the growth rate and biomass yield (both derived from measurements of cell protein production) of two representative strains of Fe(III)-reducing bacteria (Shewanellaalga strain BrY and Geobactermetallireducens) growing with different forms of Fe(III) as an electron acceptor. These two fundamentally different types of Fe(III)-reducing bacteria (FeRB) showed comparable rates of Fe(III) reduction, cell growth, and biomass yield during reduction of soluble Fe(III)-citrate and solid-phase amorphous hydrous ferric oxide (HFO). Intrinsic growth rates of the two FeRB were strongly influenced by whether a soluble or a solid-phase source of Fe(III) was provided: growth rates on soluble Fe(III) were 10--20 times higher than those on solid-phase Fe(III) oxide. Intrinsic FeRB growth rates were comparable during reduction of HF0 and a synthetic crystalline Fe(III) oxide (goethite). A distinct lag phase for protein production was observed during the first several days of incubation in solid-phase Fe(III) oxide medium, even though Fe(III) reduction proceeded without any lag. No such lag between protein production and Fe(III) reduction was observed during growth with soluble Fe(III). This result suggested that protein synthesis coupled to solid-phase Fe(III) oxide reduction in batch culture requires an initial investment of energy (generated by Fe(III) reduction), which is probably needed for synthesis of materials (e.g. extracellular polysaccharides) required for attachment of the cells to oxide surfaces. This phenomenon may have important implications for modeling the growth of FeRB in subsurface sedimentary environments, where attachment and continued adhesion to solid-phase materials will be required for maintenance of Fe(III) reduction activity. Despite considerable differences in the rate and
Variance Risk Premiums and Predictive Power of Alternative Forward Variances in the Corn Market
Zhiguang Wang; Scott W. Fausti; Qasmi, Bashir A.
2010-01-01
We propose a fear index for corn using the variance swap rate synthesized from out-of-the-money call and put options as a measure of implied variance. Previous studies estimate implied variance based on Black (1976) model or forecast variance using the GARCH models. Our implied variance approach, based on variance swap rate, is model independent. We compute the daily 60-day variance risk premiums based on the difference between the realized variance and implied variance for the period from 19...
Marincean, Simona; Smith, Sheila R.; Fritz, Michael; Lee, Byung Joo; Rizk, Zeinab
2012-01-01
An upper-division laboratory project has been developed as a collaborative investigation of a reaction routinely taught in organic chemistry courses: the reduction of carbonyl compounds by borohydride reagents. Determination of several trends regarding structure-activity relationship was possible because each student contributed his or her results…
An investigation into reservoir NOM reduction by UV photolysis and advanced oxidation processes.
Goslan, Emma H; Gurses, Filiz; Banks, Jenny; Parsons, Simon A
2006-11-01
A comparison of four treatment technologies for reduction of natural organic matter (NOM) in a reservoir water was made. The work presented here is a laboratory based evaluation of NOM treatment by UV-C photolysis, UV/H(2)O(2), Fenton's reagent (FR) and photo-Fenton's reagent (PFR). The work investigated ways of reducing the organic load on water treatment works (WTWs) with a view to treating 'in-reservoir' or 'in-pipe' before the water reaches the WTW. The efficiency of each process in terms of NOM removal was determined by measuring UV absorbance at 254 nm (UV(254)) and dissolved organic carbon (DOC). In terms of DOC reduction PFR was the most effective (88% removal after 1 min) however there were interferences when measuring UV(254) which was reduced to a lesser extent (31% after 1 min). In the literature, pH 3 is reported to be the optimal pH for oxidation with FR but here the reduction of UV(254) and DOC was found to be insensitive to pH in the range 3-7. The treatment that was identified as the most effective in terms of NOM reduction and cost effectiveness was PFR. PMID:16765416
Hughes, Christoper E.; Gazzaniga, John A.
2013-01-01
A wind tunnel experiment was conducted in the NASA Glenn Research Center anechoic 9- by 15-Foot Low-Speed Wind Tunnel to investigate two new advanced noise reduction technologies in support of the NASA Fundamental Aeronautics Program Subsonic Fixed Wing Project. The goal of the experiment was to demonstrate the noise reduction potential and effect on fan model performance of the two noise reduction technologies in a scale model Ultra-High Bypass turbofan at simulated takeoff and approach aircraft flight speeds. The two novel noise reduction technologies are called Over-the-Rotor acoustic treatment and Soft Vanes. Both technologies were aimed at modifying the local noise source mechanisms of the fan tip vortex/fan case interaction and the rotor wake-stator interaction. For the Over-the-Rotor acoustic treatment, two noise reduction configurations were investigated. The results showed that the two noise reduction technologies, Over-the-Rotor and Soft Vanes, were able to reduce the noise level of the fan model, but the Over-the-Rotor configurations had a significant negative impact on the fan aerodynamic performance; the loss in fan aerodynamic efficiency was between 2.75 to 8.75 percent, depending on configuration, compared to the conventional solid baseline fan case rubstrip also tested. Performance results with the Soft Vanes showed that there was no measurable change in the corrected fan thrust and a 1.8 percent loss in corrected stator vane thrust, which resulted in a total net thrust loss of approximately 0.5 percent compared with the baseline reference stator vane set.
Littleton, Harry; Griffin, John
2011-07-31
This project was a subtask of Energy Saving Melting and Revert Reduction Technology (Energy SMARRT) Program. Through this project, technologies, such as computer modeling, pattern quality control, casting quality control and marketing tools, were developed to advance the Lost Foam Casting process application and provide greater energy savings. These technologies have improved (1) production efficiency, (2) mechanical properties, and (3) marketability of lost foam castings. All three reduce energy consumption in the metals casting industry. This report summarizes the work done on all tasks in the period of January 1, 2004 through June 30, 2011. Current (2011) annual energy saving estimates based on commercial introduction in 2011 and a market penetration of 97% by 2020 is 5.02 trillion BTU's/year and 6.46 trillion BTU's/year with 100% market penetration by 2023. Along with these energy savings, reduction of scrap and improvement in casting yield will result in a reduction of the environmental emissions associated with the melting and pouring of the metal which will be saved as a result of this technology. The average annual estimate of CO2 reduction per year through 2020 is 0.03 Million Metric Tons of Carbon Equivalent (MM TCE).
External Magnetic Field Reduction Techniques for the Advanced Stirling Radioisotope Generator
Niedra, Janis M.; Geng, Steven M.
2013-01-01
Linear alternators coupled to high efficiency Stirling engines are strong candidates for thermal-to-electric power conversion in space. However, the magnetic field emissions, both AC and DC, of these permanent magnet excited alternators can interfere with sensitive instrumentation onboard a spacecraft. Effective methods to mitigate the AC and DC electromagnetic interference (EMI) from solenoidal type linear alternators (like that used in the Advanced Stirling Convertor) have been developed for potential use in the Advanced Stirling Radioisotope Generator. The methods developed avoid the complexity and extra mass inherent in data extraction from multiple sensors or the use of shielding. This paper discusses these methods, and also provides experimental data obtained during breadboard testing of both AC and DC external magnetic field devices.
Development of Head-end Pyrochemical Reduction Process for Advanced Oxide Fuels
Park, B. H.; Seo, C. S.; Hur, J. M.; Jeong, S. M.; Hong, S. S.; Choi, I. K.; Choung, W. M.; Kwon, K. C.; Lee, I. W. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2008-12-15
The development of an electrolytic reduction technology for spent fuels in the form of oxide is of essence to introduce LWR SFs to a pyroprocessing. In this research, the technology was investigated to scale a reactor up, the electrochemical behaviors of FPs were studied to understand the process and a reaction rate data by using U{sub 3}O{sub 8} was obtained with a bench scale reactor. In a scale of 20 kgHM/batch reactor, U{sub 3}O{sub 8} and Simfuel were successfully reduced into metals. Electrochemical characteristics of LiBr, LiI and Li{sub 2}Se were measured in a bench scale reactor and an electrolytic reduction cell was modeled by a computational tool.
Krakowski, R.A., Bathke, C.G.
1997-12-31
The potential for reducing plutonium inventories in the civilian nuclear fuel cycle through recycle in LWRs of a variety of mixed oxide forms is examined by means of a cost based plutonium flow systems model. This model emphasizes: (1) the minimization of separated plutonium; (2) the long term reduction of spent fuel plutonium; (3) the optimum utilization of uranium resources; and (4) the reduction of (relative) proliferation risks. This parametric systems study utilizes a globally aggregated, long term (approx. 100 years) nuclear energy model that interprets scenario consequences in terms of material inventories, energy costs, and relative proliferation risks associated with the civilian fuel cycle. The impact of introducing nonfertile fuels (NFF,e.g., plutonium oxide in an oxide matrix that contains no uranium) into conventional (LWR) reactors to reduce net plutonium generation, to increase plutonium burnup, and to reduce exo- reactor plutonium inventories also is examined.
ADVANCEMENT OF NUCLEIC ACID-BASED TOOLS FOR MONITORING IN SITU REDUCTIVE DECHLORINATION
Vangelas, K; ELIZABETH EDWARDS, E; FRANK LOFFLER, F; Brian02 Looney, B
2006-11-17
Regulatory protocols generally recognize that destructive processes are the most effective mechanisms that support natural attenuation of chlorinated solvents. In many cases, these destructive processes will be biological processes and, for chlorinated compounds, will often be reductive processes that occur under anaerobic conditions. The existing EPA guidance (EPA, 1998) provides a list of parameters that provide indirect evidence of reductive dechlorination processes. In an effort to gather direct evidence of these processes, scientists have identified key microorganisms and are currently developing tools to measure the abundance and activity of these organisms in subsurface systems. Drs. Edwards and Luffler are two recognized leaders in this field. The research described herein continues their development efforts to provide a suite of tools to enable direct measures of biological processes related to the reductive dechlorination of TCE and PCE. This study investigated the strengths and weaknesses of the 16S rRNA gene-based approach to characterizing the natural attenuation capabilities in samples. The results suggested that an approach based solely on 16S rRNA may not provide sufficient information to document the natural attenuation capabilities in a system because it does not distinguish between strains of organisms that have different biodegradation capabilities. The results of the investigations provided evidence that tools focusing on relevant enzymes for functionally desired characteristics may be useful adjuncts to the 16SrRNA methods.
Sarhadi, Ali; Burn, Donald H.; Yang, Ge; Ghodsi, Ali
2016-05-01
One of the main challenges in climate change studies is accurate projection of the global warming impacts on the probabilistic behaviour of hydro-climate processes. Due to the complexity of climate-associated processes, identification of predictor variables from high dimensional atmospheric variables is considered a key factor for improvement of climate change projections in statistical downscaling approaches. For this purpose, the present paper adopts a new approach of supervised dimensionality reduction, which is called "Supervised Principal Component Analysis (Supervised PCA)" to regression-based statistical downscaling. This method is a generalization of PCA, extracting a sequence of principal components of atmospheric variables, which have maximal dependence on the response hydro-climate variable. To capture the nonlinear variability between hydro-climatic response variables and projectors, a kernelized version of Supervised PCA is also applied for nonlinear dimensionality reduction. The effectiveness of the Supervised PCA methods in comparison with some state-of-the-art algorithms for dimensionality reduction is evaluated in relation to the statistical downscaling process of precipitation in a specific site using two soft computing nonlinear machine learning methods, Support Vector Regression and Relevance Vector Machine. The results demonstrate a significant improvement over Supervised PCA methods in terms of performance accuracy.
A variance-based sensitivity index function for factor prioritization
Among the many uses for sensitivity analysis is factor prioritization—that is, the determination of which factor, once fixed to its true value, on average leads to the greatest reduction in the variance of an output. A key assumption is that a given factor can, through further research, be fixed to some point on its domain. In general, this is an optimistic assumption, which can lead to inappropriate resource allocation. This research develops an original method that apportions output variance as a function of the amount of variance reduction that can be achieved for a particular factor. This variance-based sensitivity index function provides a main effect sensitivity index for a given factor as a function of the amount of variance of that factor that can be reduced. An aggregate measure of which factors would on average cause the greatest reduction in output variance given future research is also defined and assumes the portion of a particular factors variance that can be reduced is a random variable. An average main effect sensitivity index is then calculated by taking the mean of the variance-based sensitivity index function. A key aspect of the method is that the analysis is performed directly on the samples that were generated during a global sensitivity analysis using rejection sampling. The method is demonstrated on the Ishigami function and an additive function, where the rankings for future research are shown to be different than those of a traditional global sensitivity analysis. - Highlights: ► A sensitivity index function that apportions output variance as a function of the variance reduction that can be achieved for a given factor. ► A main effect sensitivity index that assumes the portion of a particular factor's variance that can be reduced is a random variable. ► The proposed indices are estimated directly from samples generated during a global sensitivity analysis using rejection sampling. ► Methods are demonstrated on the Ishigami
Comprehensive Study on the Estimation of the Variance Components of Traverse Nets
无
2003-01-01
This paper advances a new simplified formula for estimating variance components ,sums up the basic law to calculate the weights of observed values and a circulation method using the increaments of weights when estimating the variance components of traverse nets,advances the charicteristic roots method to estimate the variance components of traveres nets and presents a practical method to make two real and symmetric matrices two diagonal ones.
Explaining the Variance of Price Dividend Ratios
Cochrane, John H.
1989-01-01
This paper presents a bound on the variance of the price-dividend ratio and a decomposition of the variance of the price-dividend ratio into components that reflect variation in expected future discount rates and variation in expected future dividend growth. Unobserved discount rates needed to make the variance bound and variance decomposition hold are characterized, and the variance bound and variance decomposition are tested for several discount rate models, including the consumption based ...
The purpose of the Advanced Alarm Processing (AAP) is to extract only the most important and the most relevant data out of large amount of available information. It should be noted that the integrity of the knowledge base is the most critical in developing a reliable AAP. This paper proposes a new approach to an AAP by using Event-Condition-Action(ECA) rules that can be automatically triggered by an active database. Also this paper proposed a knowledge acquisition method using data mining techniques to obtain the integrity of the alarm knowledge
Wang, Zhi-Hua; Zhou, Jun-hu; Zhang, Yan-Wei; Lu, Zhi-Min; Fan, Jian-ren; Cen, Ke-fa
2005-01-01
Pulverized coal reburning, ammonia injection and advanced reburning in a pilot scale drop tube furnace were investigated. Premix of petroleum gas, air and NH3 were burned in a porous gas burner to generate the needed flue gas. Four kinds of pulverized coal were fed as reburning fuel at constant rate of 1g/min. The coal reburning process parameters including 15%~25% reburn heat input, temperature range from 1100 °C to 1400 °C and also the carbon in fly ash, coal fineness, reburn zone stoichiom...
Satake, Kenji
2014-12-01
The December 2004 Indian Ocean tsunami was the worst tsunami disaster in the world's history with more than 200,000 casualties. This disaster was attributed to giant size (magnitude M ~ 9, source length >1000 km) of the earthquake, lacks of expectation of such an earthquake, tsunami warning system, knowledge and preparedness for tsunamis in the Indian Ocean countries. In the last ten years, seismology and tsunami sciences as well as tsunami disaster risk reduction have significantly developed. Progress in seismology includes implementation of earthquake early warning, real-time estimation of earthquake source parameters and tsunami potential, paleoseismological studies on past earthquakes and tsunamis, studies of probable maximum size, recurrence variability, and long-term forecast of large earthquakes in subduction zones. Progress in tsunami science includes accurate modeling of tsunami source such as contribution of horizontal components or "tsunami earthquakes", development of new types of offshore and deep ocean tsunami observation systems such as GPS buoys or bottom pressure gauges, deployments of DART gauges in the Pacific and other oceans, improvements in tsunami propagation modeling, and real-time inversion or data assimilation for the tsunami warning. These developments have been utilized for tsunami disaster reduction in the forms of tsunami early warning systems, tsunami hazard maps, and probabilistic tsunami hazard assessments. Some of the above scientific developments helped to reveal the source characteristics of the 2011 Tohoku earthquake, which caused devastating tsunami damage in Japan and Fukushima Dai-ichi Nuclear Power Station accident. Toward tsunami disaster risk reduction, interdisciplinary and trans-disciplinary approaches are needed for scientists with other stakeholders.
Analysis of Variance: Variably Complex
Drummond, Gordon B.; Vowler, Sarah L.
2012-01-01
These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution of…
Kawatoko, Toshiharu; Murai, Koichiro; Ibayashi, Setsurou; Tsuji, Hiroshi; Nomiyama, Kensuke; Sadoshima, Seizo; Eujishima, Masatoshi; Kuwabara, Yasuo; Ichiya, Yuichi (Kyushu Univ., Fukuoka (Japan). Faculty of Medicine)
1992-01-01
Regional cerebral blood flow (rCBF), cerebral metabolic rate of oxygen (rCMRO{sub 2}), and oxygen extraction fraction (rOEF) were measured using positron emission tomography (PET) in four patients with cirrhosis (two males and two females, aged 57 to 69 years) in comparison with those in five age matched controls with previous transient global amnesia. PET studies were carried out when the patients were fully alert and oriented after the episodes of encephalopathy. In the patients, rCBF tended to be lower, while rCMRO{sub 2} was significantly lowered in almost all hemisphere cortices, more markedly in the frontal cortex. Our results suggest that the brain oxygen metabolism is diffusely impaired in patients with advanced cirrhosis, and the frontal cortex seems to be more susceptible to the systemic metabolic derangements induced by chronic liver disease. (author).
Marked reduction of cerebral oxygen metabolism in patients with advanced cirrhosis
Regional cerebral blood flow (rCBF), cerebral metabolic rate of oxygen (rCMRO2), and oxygen extraction fraction (rOEF) were measured using positron emission tomography (PET) in four patients with cirrhosis (two males and two females, aged 57 to 69 years) in comparison with those in five age matched controls with previous transient global amnesia. PET studies were carried out when the patients were fully alert and oriented after the episodes of encephalopathy. In the patients, rCBF tended to be lower, while rCMRO2 was significantly lowered in almost all hemisphere cortices, more markedly in the frontal cortex. Our results suggest that the brain oxygen metabolism is diffusely impaired in patients with advanced cirrhosis, and the frontal cortex seems to be more susceptible to the systemic metabolic derangements induced by chronic liver disease. (author)
Advanced Monitoring of Trace Metals Applied to Contamination Reduction of Silicon Device Processing
Maillot, P.; Martin, C.; Planchais, A.
2011-11-01
The detrimental effects of metallic on certain key electrical parameters of silicon devices mandates the use of state-of-the-art characterization and metrology tools as well as appropriate control plans. Historically, this has been commonly achieved in-line on monitor wafers through a combination of Total Reflectance X-Ray Fluorescence (TXRF) and post anneal Surface Photo Voltage (SPV). On the other hand, VPD (Vapor Phase Decomposition) combined with ICP-MS (Inductively Coupled Mass Spectrometry) or TXRF is known to provide both identification and quantification of surface trace metals at lower detection limits. Based on these considerations the description of an advanced monitoring scheme using SPV, TXRF and automated VPD ICP-MS is described.
Practice reduces task relevant variance modulation and forms nominal trajectory
Osu, Rieko; Morishige, Ken-Ichi; Nakanishi, Jun; Miyamoto, Hiroyuki; Kawato, Mitsuo
2015-12-01
Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.
ADVANCED BYPRODUCT RECOVERY: DIRECT CATALYTIC REDUCTION OF SO2 TO ELEMENTAL SULFUR
Robert S. Weber
1999-05-01
Arthur D. Little, Inc., together with its commercialization partner, Engelhard Corporation, and its university partner Tufts, investigated a single-step process for direct, catalytic reduction of sulfur dioxide from regenerable flue gas desulfurization processes to the more valuable elemental sulfur by-product. This development built on recently demonstrated SO{sub 2}-reduction catalyst performance at Tufts University on a DOE-sponsored program and is, in principle, applicable to processing of regenerator off-gases from all regenerable SO{sub 2}-control processes. In this program, laboratory-scale catalyst optimization work at Tufts was combined with supported catalyst formulation work at Engelhard, bench-scale supported catalyst testing at Arthur D. Little and market assessments, also by Arthur D. Little. Objectives included identification and performance evaluation of a catalyst which is robust and flexible with regard to choice of reducing gas. The catalyst formulation was improved significantly over the course of this work owing to the identification of a number of underlying phenomena that tended to reduce catalyst selectivity. The most promising catalysts discovered in the bench-scale tests at Tufts were transformed into monolith-supported catalysts at Engelhard. These catalyst samples were tested at larger scale at Arthur D. Little, where the laboratory-scale results were confirmed, namely that the catalysts do effectively reduce sulfur dioxide to elemental sulfur when operated under appropriate levels of conversion and in conditions that do not contain too much water or hydrogen. Ways to overcome those limitations were suggested by the laboratory results. Nonetheless, at the end of Phase I, the catalysts did not exhibit the very stringent levels of activity or selectivity that would have permitted ready scale-up to pilot or commercial operation. Therefore, we chose not to pursue Phase II of this work which would have included further bench-scale testing
Advanced oxidation and reduction processes: Closed-loop applications for mixed waste
At Los Alamos we are engaged in applying innovative oxidation and reduction technologies to the destruction of hazardous organics. Non thermal plasmas and relativistic electron-beams both involve the generation of free radicals and are applicable to a wide variety of mixed waste as closed-loop designs can be easily engineered. Silent discharge plasmas (SDP), long used for the generation of ozone, have been demonstrated in the laboratory to be effective in destroying hazardous organic compounds and offer an altemative to existing post-incineration and off-gas treatments. SDP generates very energetic electrons which efficiently create reactive free radicals, without adding the enthalpy associated with very high gas temperatures. A SDP cell has been used as a second stage to a LANL designed, packed-bed reactor (PBR) and has demonstrated DREs as high as 99.9999% for a variety of combustible liquid and gas-based waste streams containing scintillation fluids, nitrates, PCB surrogates, and both chlorinated and fluorinated solvents. Radiolytic treatment of waste using electron-beams and/or bremsstrahlung can be applied to a wide range of waste media (liquids, sludges, and solids). The efficacy and economy of these systems has been demonstrated for aqueous waste through both laboratory and pilot scale studies. We win present recent experimental and theoretical results for systems using stand alone SDP, combined PBR/SDP, and electron-beam treatment methods
Advanced and developmental technologies for treatment and volume reduction of dry active wastes
The nuclear power industry processes Dry Active Wastes (DAW) to achieve cost-effective volume reduction and/or to produce a residue that is more compatible with final disposal criteria. The two principal processes currently used by the industry are compaction and incineration. Although incineration is often considered the process of choice, capital and operating cost are often high, and in some countries, public opposition and lengthy permitting processes result in expensive delays to bringing the process to operation. Therefore, alternative treatment options (mechanical, thermal, chemical, and biological) are being investigated to provide timely, cost-effective options for industry use. An overview of those developmental processes considered applicable to processing DAW is presented. In each category, open-quotes establishedclose quotes processes are mentioned and/or referenced, but the focus is on open-quotes potentialclose quotes technologies and the status of their development. The emphasis is on processing DAW, and therefore, those developmental processes that primarily treat solids in aqueous streams and melting/sintering technologies, both of lesser applicability to nuclear utility wastes, have been omitted. Included are those developmental technologies that appear to have a potential for radioactive waste application based on development on demonstration programs
2014 U.S. Offshore Wind Market Report: Industry Trends, Technology Advancement, and Cost Reduction
Smith, Aaron; Stehly, Tyler; Walter Musial
2015-09-29
2015 has been an exciting year for the U.S. offshore wind market. After more than 15 years of development work, the U.S. has finally hit a crucial milestone; Deepwater Wind began construction on the 30 MW Block Island Wind Farm (BIWF) in April. A number of other promising projects, however, have run into economic, legal, and political headwinds, generating much speculation about the future of the industry. This slow, and somewhat painful, start to the industry is not without precedent; each country in northern Europe began with pilot-scale, proof-of-concept projects before eventually moving to larger commercial scale installations. Now, after more than a decade of commercial experience, the European industry is set to achieve a new deployment record, with more than 4 GW expected to be commissioned in 2015, with demonstrable progress towards industry-wide cost reduction goals. DWW is leveraging 25 years of European deployment experience; the BIWF combines state-of-the-art technologies such as the Alstom 6 MW turbine with U.S. fabrication and installation competencies. The successful deployment of the BIWF will provide a concrete showcase that will illustrate the potential of offshore wind to contribute to state, regional, and federal goals for clean, reliable power and lasting economic development. It is expected that this initial project will launch the U.S. industry into a phase of commercial development that will position offshore wind to contribute significantly to the electric systems in coastal states by 2030.
Luo, Yuehao; Yuan, Lu; Li, Jianhua; Wang, Jianshe
2015-12-01
Nature has supplied the inexhaustible resources for mankind, and at the same time, it has also progressively developed into the school for scientists and engineers. Through more than four billions years of rigorous and stringent evolution, different creatures in nature gradually exhibit their own special and fascinating biological functional surfaces. For example, sharkskin has the potential drag-reducing effect in turbulence, lotus leaf possesses the self-cleaning and anti-foiling function, gecko feet have the controllable super-adhesion surfaces, the flexible skin of dolphin can accelerate its swimming velocity. Great profits of applying biological functional surfaces in daily life, industry, transportation and agriculture have been achieved so far, and much attention from all over the world has been attracted and focused on this field. In this overview, the bio-inspired drag-reducing mechanism derived from sharkskin is explained and explored comprehensively from different aspects, and then the main applications in different fluid engineering are demonstrated in brief. This overview will inevitably improve the comprehension of the drag reduction mechanism of sharkskin surface and better understand the recent applications in fluid engineering. PMID:26348428
2010-01-01
... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Variances. 307.22 Section 307.22....22 Variances. EDA may approve variances to the requirements contained in this subpart, provided such variances: (a) Are consistent with the goals of the Economic Adjustment Assistance program and with an...
2010-07-01
... 29 Labor 7 2010-07-01 2010-07-01 false Variances. 1920.2 Section 1920.2 Labor Regulations Relating...' COMPENSATION ACT § 1920.2 Variances. (a) Variances from standards in parts 1915 through 1918 of this chapter may be granted in the same circumstances in which variances may be granted under sections 6(b)...
10 CFR 851.31 - Variance process.
2010-01-01
... 10 Energy 4 2010-01-01 2010-01-01 false Variance process. 851.31 Section 851.31 Energy DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.31 Variance process. (a) Application. Contractors desiring a variance from a safety and health standard, or portion thereof, may submit a...
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Variance. 59.106 Section 59.106... Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated entity... control may apply in writing to the Administrator for a temporary variance. The variance application...
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Variances. 59.206 Section 59.206... Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who cannot... control may apply in writing to the Administrator for a variance. The variance application shall...
Variance decomposition in stochastic simulators
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 based OFDM frame synchronization
Z. Fedra
2012-04-01
Full Text Available The paper deals with a new frame synchronization scheme for OFDM systems and calculates the complexity of this scheme. The scheme is based on the computing of the detection window variance. The variance is computed in two delayed times, so a modified Early-Late loop is used for the frame position detection. The proposed algorithm deals with different variants of OFDM parameters including guard interval, cyclic prefix, and has good properties regarding the choice of the algorithm's parameters since the parameters may be chosen within a wide range without having a high influence on system performance. The verification of the proposed algorithm functionality has been performed on a development environment using universal software radio peripheral (USRP hardware.
Variance decomposition in stochastic simulators
Le Maître, O. P.
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.
Variance Risk Premiums in Foreign Exchange Markets
Ammann, Manuel; Buesser, Ralf
2013-01-01
Based on the theory of static replication of variance swaps we assess the sign and magnitude of variance risk premiums in foreign exchange markets. We find significantly negative risk premiums when realized variance is computed from intraday data with low frequency. As a likely consequence of microstructure effects however, the evidence is ambiguous when realized variance is based on high-frequency data. Common to all estimates, variance risk premiums are highly time-varying and inversely rel...
An alternative analysis of variance
Longford, Nicholas T.
2008-01-01
The one-way analysis of variance is a staple of elementary statistics courses. The hypothesis test of homogeneity of the means encourages the use of the selected-model based estimators which are usually assessed without any regard for the uncertainty about the outcome of the test. We expose the weaknesses of such estimators when the uncertainty is taken into account, as it should be, and propose synthetic estimators as an alternative.
Yang Li; Pirvu, Traian A
2011-01-01
This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.
Estimating the Modified Allan Variance
Greenhall, Charles
1995-01-01
The third-difference approach to modified Allan variance (MVAR) leads to a tractable formula for a measure of MVAR estimator confidence, the equivalent degrees of freedom (edf), in the presence of power-law phase noise. The effect of estimation stride on edf is tabulated. A simple approximation for edf is given, and its errors are tabulated. A theorem allowing conservative estimates of edf in the presence of compound noise processes is given.
Vertical velocity variances and Reynold stresses at Brookhaven
Busch, Niels E.; Brown, R.M.; Frizzola, J.A.
1970-01-01
Results of wind tunnel tests of the Brookhaven annular bivane are presented. The energy transfer functions describing the instrument response and the numerical filter employed in the data reduction process have been used to obtain corrected values of the normalized variance of the vertical wind...
Analytic variance estimates of Swank and Fano factors
Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank, E-mail: frank.samuelson@fda.hhs.gov [US Food and Drug Administration, Silver Spring, Maryland 20993 (United States)
2014-07-15
Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.
Sorge, J.N.; Larrimore, C.L.; Slatsky, M.D.; Menzies, W.R.; Smouse, S.M.; Stallings, J.W.
1997-12-31
This paper discusses the technical progress of a US Department of Energy Innovative Clean Coal Technology project demonstrating advanced wall-fired combustion techniques for the reduction of nitrogen oxide (NOx) emissions from coal-fired boilers. The primary objectives of the demonstration is to determine the long-term NOx reduction performance of advanced overfire air (AOFA), low NOx burners (LNB), and advanced digital control optimization methodologies applied in a stepwise fashion to a 500 MW boiler. The focus of this paper is to report (1) on the installation of three on-line carbon-in-ash monitors and (2) the design and results to date from the advanced digital control/optimization phase of the project.
Variance optimal stopping for geometric Levy processes
Gad, Kamille Sofie Tågholt; Pedersen, Jesper Lund
2015-01-01
The main result of this paper is the solution to the optimal stopping problem of maximizing the variance of a geometric Lévy process. We call this problem the variance problem. We show that, for some geometric Lévy processes, we achieve higher variances by allowing randomized stopping. Furthermore......, for some geometric Lévy processes, the problem has a solution only if randomized stopping is allowed. When randomized stopping is allowed, we give a solution to the variance problem. We identify the Lévy processes for which the allowance of randomized stopping times increases the maximum variance....... When it does, we also solve the variance problem without randomized stopping....
A multi-variance analysis in the time domain
Walter, Todd
1993-01-01
Recently a new technique for characterizing the noise processes affecting oscillators was introduced. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique was applied to both simulated and real data with excellent results.
Levine's guide to SPSS for analysis of variance
Braver, Sanford L; Page, Melanie
2003-01-01
A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor desi
Neutrino mass without cosmic variance
LoVerde, Marilena
2016-01-01
Measuring the absolute scale of the neutrino masses is one of the most exciting opportunities available with near-term cosmological datasets. Two quantities that are sensitive to neutrino mass, scale-dependent halo bias $b(k)$ and the linear growth parameter $f(k)$ inferred from redshift-space distortions, can be measured without cosmic variance. Unlike the amplitude of the matter power spectrum, which always has a finite error, the error on $b(k)$ and $f(k)$ continues to decrease as the number density of tracers increases. This paper presents forecasts for statistics of galaxy and lensing fields that are sensitive to neutrino mass via $b(k)$ and $f(k)$. The constraints on neutrino mass from the auto- and cross-power spectra of spectroscopic and photometric galaxy samples are weakened by scale-dependent bias unless a very high density of tracers is available. In the high density limit, using multiple tracers allows cosmic-variance to be beaten and the forecasted errors on neutrino mass shrink dramatically. In...
Variance analysis. Part I, Extending flexible budget variance analysis to acuity.
Finkler, S A
1991-01-01
The author reviews the concepts of flexible budget variance analysis, including the price, quantity, and volume variances generated by that technique. He also introduces the concept of acuity variance and provides direction on how such a variance measure can be calculated. Part II in this two-part series on variance analysis will look at how personal computers can be useful in the variance analysis process. PMID:1870002
Mean-variance relation : a sentimental affair
Ascenso, Rui
2015-01-01
This work documents the role investor sentiment plays on the market’s mean-variance tradeoff. We find that, during high-sentiment periods, investor sentiment undermines an otherwise positive mean-variance tradeoff. In low-sentiment periods, the common understanding holds that investors should obtain a compensation for bearing variance risk. These findings are robust to different stock return indices, variances estimates and sentiment measures. We also provide international evidence for five o...
Variance risk premia in energy commodities
Trolle, Anders; Eduardo S. Schwartz
2010-01-01
This paper investigates variance risk premia in energy commodities, particularly crude oil and natural gas, using a robust model-independent approach. Over a period of 11 years, we find that the average variance risk premia are significantly negative for both energy commodities. However, it is difficult to explain the level and variation in energy variance risk premia with systematic or commodity specific factors. The return profile of a natural gas variance swap resembles that of a call opti...
Yaovi Holade
2015-03-01
Full Text Available The oxygen reduction reaction (ORR is the oldest studied and most challenging of the electrochemical reactions. Due to its sluggish kinetics, ORR became the major contemporary technological hurdle for electrochemists, as it hampers the commercialization of fuel cell (FC technologies. Downsizing the metal particles to nanoscale introduces unexpected fundamental modifications compared to the corresponding bulk state. To address these fundamental issues, various synthetic routes have been developed in order to provide more versatile carbon-supported low platinum catalysts. Consequently, the approach of using nanocatalysts may overcome the drawbacks encountered in massive materials for energy conversion. This review paper aims at summarizing the recent important advances in carbon-supported metal nanoparticles preparation from colloidal methods (microemulsion, polyol, impregnation, Bromide Anion Exchange… as cathode material in low temperature FCs. Special attention is devoted to the correlation of the structure of the nanoparticles and their catalytic properties. The influence of the synthesis method on the electrochemical properties of the resulting catalysts is also discussed. Emphasis on analyzing data from theoretical models to address the intrinsic and specific electrocatalytic properties, depending on the synthetic method, is incorporated throughout. The synthesis process-nanomaterials structure-catalytic activity relationships highlighted herein, provide ample new rational, convenient and straightforward strategies and guidelines toward more effective nanomaterials design for energy conversion.
Natural Exponential Families with Quadratic Variance Functions
Morris, Carl N.
1982-01-01
The normal, Poisson, gamma, binomial, and negative binomial distributions are univariate natural exponential families with quadratic variance functions (the variance is at most a quadratic function of the mean). Only one other such family exists. Much theory is unified for these six natural exponential families by appeal to their quadratic variance property, including infinite divisibility, cumulants, orthogonal polynomials, large deviations, and limits in distribution.
2010-04-01
... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Variances. 1010.4 Section 1010.4 Food and Drugs... PERFORMANCE STANDARDS FOR ELECTRONIC PRODUCTS: GENERAL General Provisions § 1010.4 Variances. (a) Criteria for variances. (1) Upon application by a manufacturer (including an assembler), the Director, Center for...
40 CFR 142.41 - Variance request.
2010-07-01
... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Variance request. 142.41 Section 142...) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of...
2010-04-01
... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Variances. 654.402 Section 654.402 Employees... EMPLOYMENT SERVICE SYSTEM Housing for Agricultural Workers Purpose and Applicability § 654.402 Variances. (a) An employer may apply for a permanent, structural variance from a specific standard(s) in...
40 CFR 52.2183 - Variance provision.
2010-07-01
... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Variance provision. 52.2183 Section 52...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) South Dakota § 52.2183 Variance provision. The revisions to the variance provisions in Chapter 74:26:01:31.01 of the South Dakota Air...
2010-02-08
... Paperwork Reduction Act of 1995 (44 U.S.C. 3506 et seq.) and Secretary of Labor's Order No. 5-2007 (72 FR... Occupational Safety and Health Administration Information Collection Requirements for the Variance Regulations..., experimental, permanent, and national defense variances. DATES: Comments must be submitted...
Global variance reduction for Monte Carlo reactor physics calculations
Over the past few decades, hybrid Monte-Carlo-Deterministic (MC-DT) techniques have been mostly focusing on the development of techniques primarily with shielding applications in mind, i.e. problems featuring a limited number of responses. This paper focuses on the application of a new hybrid MC-DT technique: the SUBSPACE method, for reactor analysis calculation. The SUBSPACE method is designed to overcome the lack of efficiency that hampers the application of MC methods in routine analysis calculations on the assembly level where typically one needs to execute the flux solver in the order of 103-105 times. It places high premium on attaining high computational efficiency for reactor analysis application by identifying and capitalizing on the existing correlations between responses of interest. This paper places particular emphasis on using the SUBSPACE method for preparing homogenized few-group cross section sets on the assembly level for subsequent use in full-core diffusion calculations. A BWR assembly model is employed to calculate homogenized few-group cross sections for different burn-up steps. It is found that using the SUBSPACE method significant speedup can be achieved over the state of the art FW-CADIS method. While the presented speed-up alone is not sufficient to render the MC method competitive with the DT method, we believe this work will become a major step on the way of leveraging the accuracy of MC calculations for assembly calculations. (authors)
ADVANTG An Automated Variance Reduction Parameter Generator, Rev. 1
Mosher, Scott W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Johnson, Seth R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bevill, Aaron M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ibrahim, Ahmad M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Daily, Charles R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Evans, Thomas M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wagner, John C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Johnson, Jeffrey O. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Grove, Robert E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2015-08-01
The primary objective of ADVANTG is to reduce both the user effort and the computational time required to obtain accurate and precise tally estimates across a broad range of challenging transport applications. ADVANTG has been applied to simulations of real-world radiation shielding, detection, and neutron activation problems. Examples of shielding applications include material damage and dose rate analyses of the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source and High Flux Isotope Reactor (Risner and Blakeman 2013) and the ITER Tokamak (Ibrahim et al. 2011). ADVANTG has been applied to a suite of radiation detection, safeguards, and special nuclear material movement detection test problems (Shaver et al. 2011). ADVANTG has also been used in the prediction of activation rates within light water reactor facilities (Pantelias and Mosher 2013). In these projects, ADVANTG was demonstrated to significantly increase the tally figure of merit (FOM) relative to an analog MCNP simulation. The ADVANTG-generated parameters were also shown to be more effective than manually generated geometry splitting parameters.
Seasonal variance in P system models for metapopulations
Daniela Besozzi; Paolo Cazzaniga; Dario Pescini; Giancarlo Mauri
2007-01-01
Metapopulations are ecological models describing the interactions and the behavior of populations living in fragmented habitats. In this paper, metapopulations are modelled by means of dynamical probabilistic P systems, where additional structural features have been defined (e. g., a weighted graph associated with the membrane structure and the reduction of maximal parallelism). In particular, we investigate the influence of stochastic and periodic resource feeding processes, owing to seasonal variance, on emergent metapopulation dynamics.
The Correct Kriging Variance Estimated by Bootstrapping
den Hertog, D.; Kleijnen, J.P.C.; Siem, A.Y.D.
2004-01-01
The classic Kriging variance formula is widely used in geostatistics and in the design and analysis of computer experiments.This paper proves that this formula is wrong.Furthermore, it shows that the formula underestimates the Kriging variance in expectation.The paper develops parametric bootstrapping to estimate the Kriging variance.The new method is tested on several artificial examples and a real-life case study.These results demonstrate that the classic formula underestimates the true Kri...
Variance Swaps and Intertemporal Asset Pricing
Nieto, Belén; Novales Cinca, Alfonso; Rubio, Gonzalo
2011-01-01
This paper proposes an ICAPM in which the risk premium embedded in variance swaps is the factor mimicking portfolio for hedging exposure to changes in future investment conditions. Recent empirical evidence shows that the fears by investors to deviations from Normality in the distribution of returns are able to explain time-varying financial and macroeconomic risks in addition to being a determinant of the variance risk premium. Moreover, variance swaps hedges unfavorable changes in the stoch...
Generalized analysis of molecular variance.
Caroline M Nievergelt
2007-04-01
Full Text Available Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA, requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by
Variance components for body weight in Japanese quails (Coturnix japonica
RO Resende
2005-03-01
Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.
Analysis of variance for model output
Jansen, M.J.W.
1999-01-01
A scalar model output Y is assumed to depend deterministically on a set of stochastically independent input vectors of different dimensions. The composition of the variance of Y is considered; variance components of particular relevance for uncertainty analysis are identified. Several analysis of va
On testing variance components in ANOVA models
Hartung, Joachim; Knapp, Guido
2000-01-01
In this paper we derive asymptotic x 2 - tests for general linear hypotheses on variance components using repeated variance components models. In two examples, the two-way nested classification model and the two-way crossed classification model with interaction, we explicitly investigate the properties of the asymptotic tests in small sample sizes.
2010-01-01
... such an action) DOE shall document the emergency actions in accordance with NEPA procedures at 10 CFR... 10 Energy 4 2010-01-01 2010-01-01 false Variances. 1022.16 Section 1022.16 Energy DEPARTMENT OF... Procedures for Floodplain and Wetland Reviews § 1022.16 Variances. (a) Emergency actions. DOE may...
2010-01-01
... Procedures § 1021.343 Variances. (a) Emergency actions. DOE may take an action without observing all provisions of this part or the CEQ Regulations, in accordance with 40 CFR 1506.11, in emergency situations... 10 Energy 4 2010-01-01 2010-01-01 false Variances. 1021.343 Section 1021.343 Energy DEPARTMENT...
2010-04-01
... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Variances. 1304.408 Section 1304.408 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY APPROVAL OF... § 1304.408 Variances. The Vice President or the designee thereof is authorized, following...
Nonlinear Epigenetic Variance: Review and Simulations
Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.
2010-01-01
We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…
Nonlinear epigenetic variance: review and simulations
K.J. Kan; A. Ploeger; M.E.J. Raijmakers; C.V. Dolan; H.L.J. van der Maas
2010-01-01
We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addit
Portfolio optimization with mean-variance model
Hoe, Lam Weng; Siew, Lam Weng
2016-06-01
Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.
Influence of Family Structure on Variance Decomposition
Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter
Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained...... genetic variance. However, in Holstein cattle, a group of genes that explained close to none of the genetic variance could also have a high likelihood ratio. This is still a good separation of signal and noise, but instead of capturing the genetic signal in the marker set being tested, we are instead...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...
Encoding of natural sounds by variance of the cortical local field potential.
Ding, Nai; Simon, Jonathan Z; Shamma, Shihab A; David, Stephen V
2016-06-01
Neural encoding of sensory stimuli is typically studied by averaging neural signals across repetitions of the same stimulus. However, recent work has suggested that the variance of neural activity across repeated trials can also depend on sensory inputs. Here we characterize how intertrial variance of the local field potential (LFP) in primary auditory cortex of awake ferrets is affected by continuous natural sound stimuli. We find that natural sounds often suppress the intertrial variance of low-frequency LFP (<16 Hz). However, the amount of the variance reduction is not significantly correlated with the amplitude of the mean response at the same recording site. Moreover, the variance changes occur with longer latency than the mean response. Although the dynamics of the mean response and intertrial variance differ, spectro-temporal receptive field analysis reveals that changes in LFP variance have frequency tuning similar to multiunit activity at the same recording site, suggesting a local origin for changes in LFP variance. In summary, the spectral tuning of LFP intertrial variance and the absence of a correlation with the amplitude of the mean evoked LFP suggest substantial heterogeneity in the interaction between spontaneous and stimulus-driven activity across local neural populations in auditory cortex. PMID:26912594
Portfolio optimization using median-variance approach
Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli
2013-04-01
Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.
The term structure of variance swap rates and optimal variance swap investments
Egloff, Daniel; Leippold, Markus; Liuren WU
2010-01-01
This paper performs specification analysis on the term structure of variance swap rates on the S&P 500 index and studies the optimal investment decision on the variance swaps and the stock index. The analysis identifies two stochastic variance risk factors, which govern the short and long end of the variance swap term structure variation, respectively. The highly negative estimate for the market price of variance risk makes it optimal for an investor to take short positions in a short-term va...
Prices and Asymptotics for Discrete Variance Swaps
Carole Bernard; Zhenyu Cui
2013-01-01
We study the fair strike of a discrete variance swap for a general time-homogeneous stochastic volatility model. In the special cases of Heston, Hull-White and Schobel-Zhu stochastic volatility models we give simple explicit expressions (improving Broadie and Jain (2008a) in the case of the Heston model). We give conditions on parameters under which the fair strike of a discrete variance swap is higher or lower than that of the continuous variance swap. The interest rate and the correlation b...
On Normal Variance-Mean Mixtures
Yu, Yaming
2011-01-01
Normal variance-mean mixtures encompass a large family of useful distributions such as the generalized hyperbolic distribution, which itself includes the Student t, Laplace, hyperbolic, normal inverse Gaussian, and variance gamma distributions as special cases. We study shape properties of normal variance-mean mixtures, in both the univariate and multivariate cases, and determine conditions for unimodality and log-concavity of the density functions. This leads to a short proof of the unimodality of all generalized hyperbolic densities. We also interpret such results in practical terms and discuss discrete analogues.
A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made. (paper)
Lyashenko, A. V.; Breskin, A.; Chechik, R.; Veloso, J. F. C. A.; Santos, J. M. F. dos; Amaro, F. D.
2006-01-01
A new concept is presented for the reduction of ion back-flow in GEM-based cascaded gaseous electron multipliers, by incorporating Micro-Hole & Strip Plate (MHSP) elements operating in reversed-bias mode (R-MHSP). About an order of magnitude reduction in ion back-flow is achieved by diverting back-drifting ions from their original path. A R-MHSP/2GEM/MHSP cascaded multiplier operated at total gain of ~1.5*10^5 yielded ion back-flow fractions of 0.0015 and 0.0004, at drift fields of 0.5 and 0....
Grammatical and lexical variance in English
Quirk, Randolph
2014-01-01
Written by one of Britain's most distinguished linguists, this book is concerned with the phenomenon of variance in English grammar and vocabulary across regional, social, stylistic and temporal space.
A Mean variance analysis of arbitrage portfolios
Fang, Shuhong
2007-03-01
Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.
Kalman filtering techniques for reducing variance of digital speckle displacement measurement noise
Donghui Li; Li Guo
2006-01-01
@@ Target dynamics are assumed to be known in measuring digital speckle displacement. Use is made of a simple measurement equation, where measurement noise represents the effect of disturbances introduced in measurement process. From these assumptions, Kalman filter can be designed to reduce variance of measurement noise. An optical and analysis system was set up, by which object motion with constant displacement and constant velocity is experimented with to verify validity of Kalman filtering techniques for reduction of measurement noise variance.
The spatial variation of radon concentration within the building of the preparatory year located in Riyadh was studied. Nuclear track detectors (CR-39) were used to measure radon concentration for two consecutive six month periods in more than 40 rooms of the surveyed building. Coefficient of variation (CV) was calculated as a measure of relative variation of radon concentration between floors and between rooms on the same floor. Floor mean ratios, with ground floor as a reference level, were calculated also in order to study the correlation between radon concentration and floor levels in case of using advanced Italian granite building material. All the results of this study were investigated and compared with usual Indian granite building material and it was found that the knowledgement buildingis a healthy work place which may be due to uses of advanced building materials.
Singh, R.; Mahajan, V.
2014-07-01
In the present work surface hardness investigations have been made on acrylonitrile butadiene styrene (ABS) pattern based investment castings after advancements in shell moulding for replication of biomedical implants. For the present study, a hip joint, made of ABS material, was fabricated as a master pattern by fused deposition modelling (FDM). After preparation of master pattern, mold was prepared by deposition of primary (1°), secondary (2°) and tertiary (3°) coatings with the addition of nylon fibre (1-2 cm in length of 1.5D). This study outlines the surface hardness mechanism for cast component prepared from ABS master pattern after advancement in shell moulding. The results of study highlight that during shell production, fibre modified shells have a much reduced drain time. Further the results are supported by cooling rate and micro structure analysis of casting.
[ADVANCE-ON Trial; How to Achieve Maximum Reduction of Mortality in Patients With Type 2 Diabetes].
Kanorskiĭ, S G
2015-01-01
Of 10,261 patients with type 2 diabetes who survived to the end of a randomized ADVANCE trial 83% were included in the ADVANCE-ON project for observation for 6 years. The difference in the level of blood pressure which had been achieved during 4.5 years of within trial treatment with fixed perindopril/indapamide combination quickly vanished but significant decrease of total and cardiovascular mortality in the group of patients treated with this combination for 4.5 years was sustained during 6 years of post-trial follow-up. The results can be related to gradually weakening protective effect of perindopril/indapamide combination on cardiovascular system, and are indicative of the expedience of long-term use of this antihypertensive therapy for maximal lowering of mortality of patients with diabetes. PMID:26164995
Reduced Variance for Material Sources in Implicit Monte Carlo
Urbatsch, Todd J. [Los Alamos National Laboratory
2012-06-25
Implicit Monte Carlo (IMC), a time-implicit method due to Fleck and Cummings, is used for simulating supernovae and inertial confinement fusion (ICF) systems where x-rays tightly and nonlinearly interact with hot material. The IMC algorithm represents absorption and emission within a timestep as an effective scatter. Similarly, the IMC time-implicitness splits off a portion of a material source directly into the radiation field. We have found that some of our variance reduction and particle management schemes will allow large variances in the presence of small, but important, material sources, as in the case of ICF hot electron preheat sources. We propose a modification of our implementation of the IMC method in the Jayenne IMC Project. Instead of battling the sampling issues associated with a small source, we bypass the IMC implicitness altogether and simply deterministically update the material state with the material source if the temperature of the spatial cell is below a user-specified cutoff. We describe the modified method and present results on a test problem that show the elimination of variance for small sources.
42 CFR 456.522 - Content of request for variance.
2010-10-01
... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section..., and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time Requirements § 456.522 Content of request for variance. The agency's request for a variance must include—...
Grossman, M.; Norton, H W
1981-01-01
An approximate minimum-variance estimate of heritability (h2) is proposed, using the sire and dam components of variance from a hierarchical analysis of variance. The minimum sampling variance is derived for unbalanced data. Optimum structures for the estimation of h2 are given for the balanced case. The degree to which ĥ2 is more precise than the equally weighted estimate ĥ2S+D is a function of the size and structure of the sample used. However, computer simulation reveals that ĥ2 has less d...
Arnetz, B B
1996-01-01
There is a void of studies concerning occupational health aspects from working with the most advanced forms of information technologies techniques such as are found in some of the world-renowned telecommunication systems development laboratories. However, many of these techniques will later be applied in the regular office environment. We wanted to identify some of the major stressors perceived by advanced telecommunication systems design employees and develop a valid and reliable instrument by which to monitor such stressors. We were also interested in assessing the impact of a controlled prospective stress-reduction program on perceived mental stress and specific psychophysiological parameters. A total of 116 employees were recruited. Sixty-one were offered to participate in one of three stress-reduction training programs (intervention group). The additional 50 functioned as a reference group. After a detailed baseline assessment, including a comprehensive questionnaire and psychophysiological measurements, new assessments were made at the end of the formal training program (+ 3 months) and after an additional 5-month period. Results reveal a significant improvement in the intervention group with regard to circulating levels of the stress-sensitive hormone prolactin as well as an attenuation in mental strain. Cardiovascular risk indicators were also improved. Circulating thrombocytes decreased in the intervention group. Type of stress-reduction programs chosen and intensity of participation did not significantly impact results. Coping style was not affected and no beneficial effects were observed with regard to the psychological characteristics of the work, eg intellectual discretion and control over work processes. The survey instrument is now being used in the continuous improvement of work processes and strategic leadership of occupational health issues. The results suggest that prior psychophysiological stress research, based on low- and medium-skill, rather
Inhomogeneity-induced variance of cosmological parameters
Wiegand, Alexander
2011-01-01
Modern cosmology relies on the assumption of large-scale isotropy and homogeneity of the Universe. However, locally the Universe is inhomogeneous and anisotropic. So, how can local measurements (at the 100 Mpc scale) be used to determine global cosmological parameters (defined at the 10 Gpc scale)? We use Buchert's averaging formalism and determine a set of locally averaged cosmological parameters in the context of the flat Lambda cold dark matter model. We calculate their ensemble means (i.e. their global values) and variances (i.e. their cosmic variances). We apply our results to typical survey geometries and focus on the study of the effects of local fluctuations of the curvature parameter. By this means we show, that in the linear regime cosmological backreaction and averaging can be reformulated as the issue of cosmic variance. The cosmic variance is found largest for the curvature parameter and discuss some of its consequences. We further propose to use the observed variance of cosmological parameters t...
Guimarães, José Roberto; Franco, Regina Maura Bueno; Guadagnini, Regiane Aparecida; Santos, Luciana Urbano dos
2014-01-01
This study evaluated the effect of peroxidation assisted by ultraviolet radiation (H2O2/UV), which is an advanced oxidation process (AOP), on Giardia duodenalis cysts. The cysts were inoculated in synthetic and surface water using a concentration of 12 g H2O2 L−1 and a UV dose (λ=254 nm) of 5,480 mJcm−2. The aqueous solutions were concentrated using membrane filtration, and the organisms were observed using a direct immunofluorescence assay (IFA). The AOP was effective in reducing the number ...
Genomic prediction of breeding values using previously estimated SNP variances
Calus, M.P.L.; Schrooten, C.; Veerkamp, R.F.
2014-01-01
Background Genomic prediction requires estimation of variances of effects of single nucleotide polymorphisms (SNPs), which is computationally demanding, and uses these variances for prediction. We have developed models with separate estimation of SNP variances, which can be applied infrequently, and
Estimating quadratic variation using realized variance
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2002-01-01
This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process is a...... rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....
Graphical abstract: N-doped graphene/Co nanocomposites were synthesized through one-step pyrolysis process and the product exhibits high performance for ORR and excellent stability in alkaline medium. - Highlights: • N-doped graphene/Co nano-composite is directly synthesized by a one-step method from Co(NO3)2∙6H2O, glucose and dicyandiamide (DCDA). • The electrocatalytic performance of as-prepared NG/Co-0.5 shows the peak potential positively shifts about 10 mV than commercial Pt/C electrode. • The material shows an excellent stability and tolerance to methanol poisoning effects in alkaline medium. - Abstract: N-doped graphene/Co nanocomposites (NG/Co NPs) have been prepared by a simple one-step pyrolysis of Co(NO3)2∙6H2O, glucose and dicyandiamide (DCDA). The products with nitrogen doped and suitable graphitic degree perform high electrocatalytic activity (with the reduction peak at −0.099 V vs Ag/AgCl) and near four-electron selectivity for the oxygen reduction reaction (ORR), with excellent stability and durability in alkaline medium comparable to a commercial Pt/C catalyst. Owing to the superb ORR performance, low cost and facile preparation, the catalysts of NG/Co NPs have great potential applications in fuel cells, metal-air batteries and ORR-related electrochemical industries
Integrating Variances into an Analytical Database
Sanchez, Carlos
2010-01-01
For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.
Inhomogeneity-induced variance of cosmological parameters
Wiegand, A.; Schwarz, D. J.
2012-02-01
Context. Modern cosmology relies on the assumption of large-scale isotropy and homogeneity of the Universe. However, locally the Universe is inhomogeneous and anisotropic. This raises the question of how local measurements (at the ~102 Mpc scale) can be used to determine the global cosmological parameters (defined at the ~104 Mpc scale)? Aims: We connect the questions of cosmological backreaction, cosmic averaging and the estimation of cosmological parameters and show how they relate to the problem of cosmic variance. Methods: We used Buchert's averaging formalism and determined a set of locally averaged cosmological parameters in the context of the flat Λ cold dark matter model. We calculated their ensemble means (i.e. their global value) and variances (i.e. their cosmic variance). We applied our results to typical survey geometries and focused on the study of the effects of local fluctuations of the curvature parameter. Results: We show that in the context of standard cosmology at large scales (larger than the homogeneity scale and in the linear regime), the question of cosmological backreaction and averaging can be reformulated as the question of cosmic variance. The cosmic variance is found to be highest in the curvature parameter. We propose to use the observed variance of cosmological parameters to measure the growth factor. Conclusions: Cosmological backreaction and averaging are real effects that have been measured already for a long time, e.g. by the fluctuations of the matter density contrast averaged over spheres of a certain radius. Backreaction and averaging effects from scales in the linear regime, as considered in this work, are shown to be important for the precise measurement of cosmological parameters.
Decomposition of variance for spatial Cox processes
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
2013-01-01
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with...... additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees....
A Simple Algorithm for Approximating Confidence on the Modified Allan Variance and the Time Variance
Weiss, Marc A.; Greenhall, Charles A.
1996-01-01
An approximating algorithm for computing equvalent degrees of freedom of the Modified Allan Variance and its square root, the Modified Allan Deviation (MVAR and MDEV), and the Time Variance and Time Deviation (TVAR and TDEV) is presented, along with an algorithm for approximating the inverse chi-square distribution.
Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander;
2013-01-01
variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...
O' Connor, Patrick [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rugani, Kelsey [Kearns & West, Inc., San Francisco, CA (United States); West, Anna [Kearns & West, Inc., San Francisco, CA (United States)
2016-03-01
On behalf of the U.S. Department of Energy (DOE) Wind and Water Power Technology Office (WWPTO), Oak Ridge National Laboratory (ORNL), hosted a day and half long workshop on November 5 and 6, 2015 in the Washington, D.C. metro area to discuss cost reduction opportunities in the development of hydropower projects. The workshop had a further targeted focus on the costs of small, low-head1 facilities at both non-powered dams (NPDs) and along undeveloped stream reaches (also known as New Stream-Reach Development or “NSD”). Workshop participants included a cross-section of seasoned experts, including project owners and developers, engineering and construction experts, conventional and next-generation equipment manufacturers, and others to identify the most promising ways to reduce costs and achieve improvements for hydropower projects.
Formative Use of Intuitive Analysis of Variance
Trumpower, David L.
2013-01-01
Students' informal inferential reasoning (IIR) is often inconsistent with the normative logic underlying formal statistical methods such as Analysis of Variance (ANOVA), even after instruction. In two experiments reported here, student's IIR was assessed using an intuitive ANOVA task at the beginning and end of a statistics course. In…
Multivariate Analysis of Variance Using Spatial Ranks
KYUNGMEE CHOI; JOHN MARDEN
2002-01-01
The authors consider multivariate analysis of variance procedures based on the multivariate spatial ranks. Two models are considered: the location-family model and the fully nonparametric model. Procedures for testing main and interaction effects are given for the 2 × 2 layout.
Realized Variance and Market Microstructure Noise
Hansen, Peter R.; Lunde, Asger
2006-01-01
We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel-b...
Broadband Minimum Variance Beamforming for Ultrasound Imaging
Holfort, Iben Kraglund; Gran, Fredrik; Jensen, Jørgen Arendt
2009-01-01
A minimum variance (MV) approach for near-field beamforming of broadband data is proposed. The approach is implemented in the frequency domain, and it provides a set of adapted, complex apodization weights for each frequency subband. The performance of the proposed MV beamformer is tested on...
Strengthened Chernoff-type variance bounds
Afendras, G.; Papadatos, N.
2014-01-01
Let $X$ be an absolutely continuous random variable from the integrated Pearson family and assume that $X$ has finite moments of any order. Using some properties of the associated orthonormal polynomial system, we provide a class of strengthened Chernoff-type variance bounds.
The Variance of Language in Different Contexts
申一宁
2012-01-01
language can be quite different (here referring to the meaning) in different contexts. And there are 3 categories of context: the culture, the situation and the cotext. In this article, we will analysis the variance of language in each of the 3 aspects. This article is written for the purpose of making people understand the meaning of a language under specific better.
Decomposition of variance for spatial Cox processes
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...
Decomposition of variance for spatial Cox processes
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with...
LOCAL MEDIAN ESTIMATION OF VARIANCE FUNCTION
杨瑛
2004-01-01
This paper considers local median estimation in fixed design regression problems. The proposed method is employed to estimate the median function and the variance function of a heteroscedastic regression model. Strong convergence rates of the proposed estimators are obtained. Simulation results are given to show the performance of the proposed methods.
ROBUST ESTIMATION OF VARIANCE COMPONENTS MODEL
无
1999-01-01
Classical least squares estimation consists of minimizing the sum of the squared residuals of observation. Many authors have produced more robust versions of this estimation by replacing the square by something else, such as the absolute value. These approaches have been generalized, and their robust estimations and influence functions of variance components have been presented. The results may have wide practical and theoretical value.
Expected Stock Returns and Variance Risk Premia
Bollerslev, Tim; Tauchen, George; Zhou, Hao
Motivated by the implications from a stylized self-contained general equilibrium model incorporating the effects of time-varying economic uncertainty, we show that the difference between implied and realized variation, or the variance risk premium, is able to explain a non-trivial fraction of the...
Expected Stock Returns and Variance Risk Premia
Bollerslev, Tim; Zhou, Hao
We find that the difference between implied and realized variation, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high (low) premia predi...
Lorenz Dominance and the Variance of Logarithms.
Ok, Efe A.; Foster, James
1997-01-01
The variance of logarithms is a widely used inequality measure which is well known to disagree with the Lorenz criterion. Up to now, the extent and likelihood of this inconsistency were thought to be vanishingly small. We find that this view is mistaken : the extent of the disgreement can be extremely large; the likelihood is far from negligible.
Variance Component Testing in Multilevel Models
Berkhof, J.; Snijders, T.A.B.
2001-01-01
Available variance component tests are reviewed and three new score tests are presented In the first score test, the asymptotic normal distribution of the test statistic is used as a reference distribution. In the other two score tests, a Satterthwaite approximation is used for the null distribution
Linear transformations of variance/covariance matrices
Parois, P.J.A.; Lutz, M.
2011-01-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance
Bias and variance in continuous EDA
Teytaud, Fabien; Teytaud, Olivier
2009-01-01
Estimation of Distribution Algorithms are based on statistical estimates. We show that when combining classical tools from statistics, namely bias/variance decomposition, reweighting and quasi-randomization, we can strongly improve the convergence rate. All modiﬁcations are easy, compliant with most algorithms, and experimentally very eﬃcient in particular in the parallel case (large oﬀsprings).
A study on effect of point-of-use filters on defect reduction for advanced 193nm processes
Vitorino, Nelson; Wolfer, Elizabeth; Cao, Yi; Lee, DongKwan; Wu, Aiwen
2009-03-01
Bottom Anti-Reflective Coatings (BARCs) have been widely used in the lithography process for decades. BARCs play important roles in controlling reflections and therefore improving swing ratios, CD variations, reflective notching, and standing waves. The implementation of BARC processes in 193nm dry and immersion lithography has been accompanied by defect reduction challenges on fine patterns. Point-of-Use filters are well known among the most critical components on a track tool ensuring low wafer defects by providing particle-free coatings on wafers. The filters must have very good particle retention to remove defect-causing particulate and gels while not altering the delicate chemical formulation of photochemical materials. This paper describes a comparative study of the efficiency and performance of various Point-of-Use filters in reducing defects observed in BARC materials. Multiple filter types with a variety of pore sizes, membrane materials, and filter designs were installed on an Entegris Intelligent(R) Mini dispense pump which is integrated in the coating module of a clean track. An AZ(R) 193nm organic BARC material was spin-coated on wafers through various filter media. Lithographic performance of filtered BARCs was examined and wafer defect analysis was performed. By this study, the effect of filter properties on BARC process related defects can be learned and optimum filter media and design can be selected for BARC material to yield the lowest defects on a coated wafer.
An event of station blackout (SBO) can result in severe core damage and undesirable consequences to the public and the environment. To cope with an SBO, nuclear reactors are provided with protection systems that automatically shut down the reactor, and with safety systems to remove the core residual heat. In order to reduce core damage frequency, the design of new reactors incorporates passive systems that rely only on natural forces to operate. This paper presents an evaluation of the SBO core damage frequency of a PWR reactor being designed in Brazil. The reactor has two core residual heat removal systems - an AC dependent system, and a passive system. Probabilistic safety assessment is applied to identify failure scenarios leading to SBO core damage. The SBO is treated as an initiating event, and fault trees are developed to model those systems required to operate in SBO conditions. Event trees are developed to assist in the evaluation of the possible combinations of success or failure of the systems required to cope with an SBO. The evaluation is performed using SAPHIRE, as the software for reliability and risk assessment. It is shown that a substantial reduction in the core damage frequency can be achieved by implementing the passive system proposed for the LABGENE reactor design. Keywords: Station blackout, passive safety system, core damage frequency. (author)
NONE
1997-12-31
The team of Arthur D. Little, Tufts University and Engelhard Corporation are conducting Phase 1 of a four and a half year, two-phase effort to develop and scale-up an advanced byproduct recovery technology that is a direct, single-stage, catalytic process for converting sulfur dioxide to elemental sulfur. This catalytic process reduces SO{sub 2} over a fluorite-type oxide (such as ceria and zirconia). The catalytic activity can be significantly promoted by active transition metals, such as copper. More than 95% elemental sulfur yield, corresponding to almost complete sulfur dioxide conversion, was obtained over a Cu-Ce-O oxide catalyst as part of an on-going DOE-sponsored, University Coal Research Program. This type of mixed metal oxide catalyst has stable activity, high selectivity for sulfur production, and is resistant to water and carbon dioxide poisoning. Tests with CO and CH{sub 4} reducing gases indicate that the catalyst has the potential for flexibility with regard to the composition of the reducing gas, making it attractive for utility use. The performance of the catalyst is consistently good over a range of SO{sub 2} inlet concentration (0.1 to 10%) indicating its flexibility in treating SO{sub 2} tail gases as well as high concentration streams. The principal objective of the Phase 1 program is to identify and evaluate the performance of a catalyst which is robust and flexible with regard to choice of reducing gas. In order to achieve this goal, the authors have planned a structured program including: Market/process/cost/evaluation; Lab-scale catalyst preparation/optimization studies; Lab-scale, bulk/supported catalyst kinetic studies; Bench-scale catalyst/process studies; and Utility review. Progress is reported from all three organizations.
10 CFR 851.32 - Action on variance requests.
2010-01-01
... 10 Energy 4 2010-01-01 2010-01-01 false Action on variance requests. 851.32 Section 851.32 Energy DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.32 Action on variance requests. (a... approval of a variance application, the Chief Health, Safety and Security Officer must forward to the...
2010-07-01
... 41 Public Contracts and Property Management 1 2010-07-01 2010-07-01 true Variances. 50-204.1a... and Application § 50-204.1a Variances. (a) Variances from standards in this part may be granted in the same circumstances in which variances may be granted under sections 6(b)(6)(A) or 6(d) of the...
A Critical Note on the Forecast Error Variance Decomposition
Seymen, Atilim
2008-01-01
The paper questions the reasonability of using forecast error variance decompositions for assessing the role of different structural shocks in business cycle fluctuations. It is shown that the forecast error variance decomposition is related to a dubious definition of the business cycle. A historical variance decomposition approach is proposed to overcome the problems related to the forecast error variance decomposition.
42 CFR 456.525 - Request for renewal of variance.
2010-10-01
... 42 Public Health 4 2010-10-01 2010-10-01 false Request for renewal of variance. 456.525 Section..., and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time Requirements § 456.525 Request for renewal of variance. (a) The agency must submit a request for renewal of...
42 CFR 456.521 - Conditions for granting variance requests.
2010-10-01
... 42 Public Health 4 2010-10-01 2010-10-01 false Conditions for granting variance requests. 456.521..., and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time Requirements § 456.521 Conditions for granting variance requests. (a) Except as described under paragraph...