Vanmarcke, Erik
1983-03-01
Random variation over space and time is one of the few attributes that might safely be predicted as characterizing almost any given complex system. Random fields or "distributed disorder systems" confront astronomers, physicists, geologists, meteorologists, biologists, and other natural scientists. They appear in the artifacts developed by electrical, mechanical, civil, and other engineers. They even underlie the processes of social and economic change. The purpose of this book is to bring together existing and new methodologies of random field theory and indicate how they can be applied to these diverse areas where a "deterministic treatment is inefficient and conventional statistics insufficient." Many new results and methods are included. After outlining the extent and characteristics of the random field approach, the book reviews the classical theory of multidimensional random processes and introduces basic probability concepts and methods in the random field context. It next gives a concise amount of the second-order analysis of homogeneous random fields, in both the space-time domain and the wave number-frequency domain. This is followed by a chapter on spectral moments and related measures of disorder and on level excursions and extremes of Gaussian and related random fields. After developing a new framework of analysis based on local averages of one-, two-, and n-dimensional processes, the book concludes with a chapter discussing ramifications in the important areas of estimation, prediction, and control. The mathematical prerequisite has been held to basic college-level calculus.
Crampin, A C; Mwinuka, V; Malema, S S; Glynn, J R; Fine, P E
2001-01-01
Selection bias, particularly of controls, is common in case-control studies and may materially affect the results. Methods of control selection should be tailored both for the risk factors and disease under investigation and for the population being studied. We present here a control selection method devised for a case-control study of tuberculosis in rural Africa (Karonga, northern Malawi) that selects an age/sex frequency-matched random sample of the population, with a geographical distribution in proportion to the population density. We also present an audit of the selection process, and discuss the potential of this method in other settings.
Simuta-Champo, R.; Herrera-Zamarrón, G. S.
2010-01-01
The Monte Carlo technique provides a natural method for evaluating uncertainties. The uncertainty is represented by a probability distribution or by related quantities such as statistical moments. When the groundwater flow and transport governing equations are solved and the hydraulic conductivity field is treated as a random spatial function, the hydraulic head, velocities and concentrations also become random spatial functions. When that is the case, for the stochastic simulation of groundw...
Blocked Randomization with Randomly Selected Block Sizes
Directory of Open Access Journals (Sweden)
Jimmy Efird
2010-12-01
Full Text Available When planning a randomized clinical trial, careful consideration must be given to how participants are selected for various arms of a study. Selection and accidental bias may occur when participants are not assigned to study groups with equal probability. A simple random allocation scheme is a process by which each participant has equal likelihood of being assigned to treatment versus referent groups. However, by chance an unequal number of individuals may be assigned to each arm of the study and thus decrease the power to detect statistically significant differences between groups. Block randomization is a commonly used technique in clinical trial design to reduce bias and achieve balance in the allocation of participants to treatment arms, especially when the sample size is small. This method increases the probability that each arm will contain an equal number of individuals by sequencing participant assignments by block. Yet still, the allocation process may be predictable, for example, when the investigator is not blind and the block size is fixed. This paper provides an overview of blocked randomization and illustrates how to avoid selection bias by using random block sizes.
International Nuclear Information System (INIS)
Itzykson, C.
1983-10-01
We review the formulation of field theory and statistical mechanics on a Poissonian random lattice. Topics discussed include random geometry, the construction of field equations for arbitrary spin, the free field spectrum and the question of localization illustrated in the one dimensional case
Random walks, random fields, and disordered systems
Černý, Jiří; Kotecký, Roman
2015-01-01
Focusing on the mathematics that lies at the intersection of probability theory, statistical physics, combinatorics and computer science, this volume collects together lecture notes on recent developments in the area. The common ground of these subjects is perhaps best described by the three terms in the title: Random Walks, Random Fields and Disordered Systems. The specific topics covered include a study of Branching Brownian Motion from the perspective of disordered (spin-glass) systems, a detailed analysis of weakly self-avoiding random walks in four spatial dimensions via methods of field theory and the renormalization group, a study of phase transitions in disordered discrete structures using a rigorous version of the cavity method, a survey of recent work on interacting polymers in the ballisticity regime and, finally, a treatise on two-dimensional loop-soup models and their connection to conformally invariant systems and the Gaussian Free Field. The notes are aimed at early graduate students with a mod...
Bell inequalities for random fields
Energy Technology Data Exchange (ETDEWEB)
Morgan, Peter [Physics Department, Yale University, CT 06520 (United States)
2006-06-09
The assumptions required for the derivation of Bell inequalities are not satisfied for random field models in which there are any thermal or quantum fluctuations, in contrast to the general satisfaction of the assumptions for classical two point particle models. Classical random field models that explicitly include the effects of quantum fluctuations on measurement are possible for experiments that violate Bell inequalities.
Bell inequalities for random fields
Morgan, Peter
2004-01-01
The assumptions required for the derivation of Bell inequalities are not usually satisfied for random fields in which there are any thermal or quantum fluctuations, in contrast to the general satisfaction of the assumptions for classical two point particle models. Classical random field models that explicitly include the effects of quantum fluctuations on measurement are possible for experiments that violate Bell inequalities.
Ellis, Jeremy
On temporal, spatial and spectral scales which are small enough, all fields are fully polarized. In the optical regime, however, instantaneous fields can rarely be examined, and, instead, only average quantities are accessible. The study of polarimetry is concerned with both the description of electromagnetic fields and the characterization of media a field has interacted with. The polarimetric information is conventionally presented in terms of second order field correlations which are averaged over the ensemble of field realizations. Motivated by the deficiencies of classical polarimetry in dealing with specific practical situations, this dissertation expands the traditional polarimetric approaches to include higher order field correlations and the description of fields fluctuating in three dimensions. In relation to characterization of depolarizing media, a number of fourth-order correlations are introduced in this dissertation. Measurements of full polarization distributions, and the subsequent evaluation of Stokes vector element correlations and Complex Degree of Mutual Polarization demonstrate the use of these quantities for material discrimination and characterization. Recent advancements in detection capabilities allow access to fields near their sources and close to material boundaries, where a unique direction of propagation is not evident. Similarly, there exist classical situations such as overlapping beams, focusing, or diffusive scattering in which there is no unique transverse direction. In this dissertation, the correlation matrix formalism is expanded to describe three dimensional electromagnetic fields, providing a definition for the degree of polarization of such a field. It is also shown that, because of the dimensionality of the problem, a second parameter is necessary to fully describe the polarimetric properties of three dimensional fields. Measurements of second-order correlations of a three dimensional field are demonstrated, allowing the
Efficient robust conditional random fields.
Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A
2015-10-01
Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.
Random scalar fields and hyperuniformity
Ma, Zheng; Torquato, Salvatore
2017-06-01
Disordered many-particle hyperuniform systems are exotic amorphous states of matter that lie between crystals and liquids. Hyperuniform systems have attracted recent attention because they are endowed with novel transport and optical properties. Recently, the hyperuniformity concept has been generalized to characterize two-phase media, scalar fields, and random vector fields. In this paper, we devise methods to explicitly construct hyperuniform scalar fields. Specifically, we analyze spatial patterns generated from Gaussian random fields, which have been used to model the microwave background radiation and heterogeneous materials, the Cahn-Hilliard equation for spinodal decomposition, and Swift-Hohenberg equations that have been used to model emergent pattern formation, including Rayleigh-Bénard convection. We show that the Gaussian random scalar fields can be constructed to be hyperuniform. We also numerically study the time evolution of spinodal decomposition patterns and demonstrate that they are hyperuniform in the scaling regime. Moreover, we find that labyrinth-like patterns generated by the Swift-Hohenberg equation are effectively hyperuniform. We show that thresholding (level-cutting) a hyperuniform Gaussian random field to produce a two-phase random medium tends to destroy the hyperuniformity of the progenitor scalar field. We then propose guidelines to achieve effectively hyperuniform two-phase media derived from thresholded non-Gaussian fields. Our investigation paves the way for new research directions to characterize the large-structure spatial patterns that arise in physics, chemistry, biology, and ecology. Moreover, our theoretical results are expected to guide experimentalists to synthesize new classes of hyperuniform materials with novel physical properties via coarsening processes and using state-of-the-art techniques, such as stereolithography and 3D printing.
Minimization over randomly selected lines
Directory of Open Access Journals (Sweden)
Ismet Sahin
2013-07-01
Full Text Available This paper presents a population-based evolutionary optimization method for minimizing a given cost function. The mutation operator of this method selects randomly oriented lines in the cost function domain, constructs quadratic functions interpolating the cost function at three different points over each line, and uses extrema of the quadratics as mutated points. The crossover operator modifies each mutated point based on components of two points in population, instead of one point as is usually performed in other evolutionary algorithms. The stopping criterion of this method depends on the number of almost degenerate quadratics. We demonstrate that the proposed method with these mutation and crossover operations achieves faster and more robust convergence than the well-known Differential Evolution and Particle Swarm algorithms.
Variational Infinite Hidden Conditional Random Fields
Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin
2015-01-01
Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of
Xu, Ganggang; Genton, Marc G.
2016-01-01
We propose a new class of trans-Gaussian random fields named Tukey g-and-h (TGH) random fields to model non-Gaussian spatial data. The proposed TGH random fields have extremely flexible marginal distributions, possibly skewed and/or heavy-tailed, and, therefore, have a wide range of applications. The special formulation of the TGH random field enables an automatic search for the most suitable transformation for the dataset of interest while estimating model parameters. Asymptotic properties of the maximum likelihood estimator and the probabilistic properties of the TGH random fields are investigated. An efficient estimation procedure, based on maximum approximated likelihood, is proposed and an extreme spatial outlier detection algorithm is formulated. Kriging and probabilistic prediction with TGH random fields are developed along with prediction confidence intervals. The predictive performance of TGH random fields is demonstrated through extensive simulation studies and an application to a dataset of total precipitation in the south east of the United States.
Xu, Ganggang
2016-07-15
We propose a new class of trans-Gaussian random fields named Tukey g-and-h (TGH) random fields to model non-Gaussian spatial data. The proposed TGH random fields have extremely flexible marginal distributions, possibly skewed and/or heavy-tailed, and, therefore, have a wide range of applications. The special formulation of the TGH random field enables an automatic search for the most suitable transformation for the dataset of interest while estimating model parameters. Asymptotic properties of the maximum likelihood estimator and the probabilistic properties of the TGH random fields are investigated. An efficient estimation procedure, based on maximum approximated likelihood, is proposed and an extreme spatial outlier detection algorithm is formulated. Kriging and probabilistic prediction with TGH random fields are developed along with prediction confidence intervals. The predictive performance of TGH random fields is demonstrated through extensive simulation studies and an application to a dataset of total precipitation in the south east of the United States.
High Entropy Random Selection Protocols
H. Buhrman (Harry); M. Christandl (Matthias); M. Koucky (Michal); Z. Lotker (Zvi); B. Patt-Shamir; M. Charikar; K. Jansen; O. Reingold; J. Rolim
2007-01-01
textabstractIn this paper, we construct protocols for two parties that do not trust each other, to generate random variables with high Shannon entropy. We improve known bounds for the trade off between the number of rounds, length of communication and the entropy of the outcome.
Efficient Training Methods for Conditional Random Fields
National Research Council Canada - National Science Library
Sutton, Charles A
2008-01-01
.... In this thesis, I investigate efficient training methods for conditional random fields with complex graphical structure, focusing on local methods which avoid propagating information globally along the graph...
Taradaj, Jakub; Ozon, Marcin; Dymarek, Robert; Bolach, Bartosz; Walewicz, Karolina; Rosińczuk, Joanna
2018-03-23
Interdisciplinary physical therapy together with pharmacological treatment constitute conservative treatment strategies related to low back pain (LBP). There is still a lack of high quality studies aimed at an objective evaluation of physiotherapeutic procedures according to their effectiveness in LBP. The aim of this study is to carry out a prospective, randomized, single-blinded, and placebocontrolled clinical trial to evaluate the effectiveness of magnetic fields in discopathy-related LBP. A group of 177 patients was assessed for eligibility based on inclusion and exclusion criteria. In the end, 106 patients were randomly assigned into 5 comparative groups: A (n = 23; magnetic therapy: 10 mT, 50 Hz); B (n = 23; magnetic therapy: 5 mT, 50 Hz); C (n = 20; placebo magnetic therapy); D (n = 20; magnetic stimulation: 49.2 μT, 195 Hz); and E (n = 20; placebo magnetic stimulation). All patients were assessed using tests for pain intensity, degree of disability and range of motion. Also, postural stability was assessed using a stabilographic platform. In this study, positive changes in all clinical outcomes were demonstrated in group A (p 0.05). It was determined that the application of magnetic therapy (10 mT, 50 Hz, 20 min) significantly reduces pain symptoms and leads to an improvement of functional ability in patients with LBP.
Vacuum instability in a random electric field
International Nuclear Information System (INIS)
Krive, I.V.; Pastur, L.A.
1984-01-01
The reaction of the vacuum on an intense spatially homogeneous random electric field is investigated. It is shown that a stochastic electric field always causes a breakdown of the boson vacuum, and the number of pairs of particles which are created by the electric field increases exponentially in time. For the choice of potential field in the form of a dichotomic random process we find in explicit form the dependence of the average number of pairs of particles on the time of the action of the source of the stochastic field. For the fermion vacuum the average number of pairs of particles which are created by the field in the lowest order of perturbation theory in the amplitude of the random field is independent of time
Uniqueness conditions for finitely dependent random fields
International Nuclear Information System (INIS)
Dobrushin, R.L.; Pecherski, E.A.
1981-01-01
The authors consider a random field for which uniqueness and some additional conditions guaranteeing that the correlations between the variables of the field decrease rapidly enough with the distance between the values of the parameter occur. The main result of the paper states that in such a case uniqueness is true for any other field with transition probabilities sufficiently close to those of the original field. Then they apply this result to some ''degenerate'' classes of random fields for which one can check this condition of correlation to decay, and thus obtain some new conditions of uniqueness. (Auth.)
Markov Random Field Surface Reconstruction
DEFF Research Database (Denmark)
Paulsen, Rasmus Reinhold; Bærentzen, Jakob Andreas; Larsen, Rasmus
2010-01-01
) and knowledge about data (the observation model) in an orthogonal fashion. Local models that account for both scene-specific knowledge and physical properties of the scanning device are described. Furthermore, how the optimal distance field can be computed is demonstrated using conjugate gradients, sparse...
Random Assignment: Practical Considerations from Field Experiments.
Dunford, Franklyn W.
1990-01-01
Seven qualitative issues associated with randomization that have the potential to weaken or destroy otherwise sound experimental designs are reviewed and illustrated via actual field experiments. Issue areas include ethics and legality, liability risks, manipulation of randomized outcomes, hidden bias, design intrusiveness, case flow, and…
Solitons in a random force field
International Nuclear Information System (INIS)
Bass, F.G.; Konotop, V.V.; Sinitsyn, Y.A.
1985-01-01
We study the dynamics of a soliton of the sine-Gordon equation in a random force field in the adiabatic approximation. We obtain an Einstein-Fokker equation and find the distribution function for the soliton parameters which we use to evaluate its statistical characteristics. We derive an equation for the averaged functions of the soliton parameters. We determine the limits of applicability of the delta-correlated in time random field approximation
Entropy estimates for simple random fields
DEFF Research Database (Denmark)
Forchhammer, Søren; Justesen, Jørn
1995-01-01
We consider the problem of determining the maximum entropy of a discrete random field on a lattice subject to certain local constraints on symbol configurations. The results are expected to be of interest in the analysis of digitized images and two dimensional codes. We shall present some examples...... of binary and ternary fields with simple constraints. Exact results on the entropies are known only in a few cases, but we shall present close bounds and estimates that are computationally efficient...
Selection of 3013 Containers for Field Surveillance
International Nuclear Information System (INIS)
Larry Peppers; Elizabeth Kelly; James McClard; Gary Friday; Theodore Venetz; Jerry Stakebade
2007-01-01
This report revises and combines three earlier reports dealing with the binning, statistical sampling, and sample selection of 3013 containers for field surveillance. It includes changes to the binning specification resulting from completion of the Savannah River Site packaging campaign and new information from the shelf-life program and field surveillance activities. The revised bin assignments result in changes to the random sample specification. These changes are necessary to meet the statistical requirements of the surveillance program. This report will be reviewed regularly and revised as needed. Section 1 of this report summarizes the results of an extensive effort to assign all of the current and projected 3013 containers in the Department of Energy (DOE) inventory to one of three bins (Innocuous, Pressure and Corrosion, or Pressure) based on potential failure mechanisms. Grouping containers into bins provides a framework to make a statistical selection of individual containers from the entire population for destructive and nondestructive field surveillance. The binning process consisted of three main steps. First, the packaged containers were binned using information in the Integrated Surveillance Program database and a decision tree. The second task was to assign those containers that could not be binned using the decision tree to a specific bin using container-by-container engineering review. The final task was to evaluate containers not yet packaged and assign them to bins using process knowledge. The technical basis for the decisions made during the binning process is included in Section 1. A composite decision tree and a summary table show all of the containers projected to be in the DOE inventory at the conclusion of packaging at all sites. Decision trees that provide an overview of the binning process and logic are included for each site. Section 2 of this report describes the approach to the statistical selection of containers for surveillance and
Markov Random Fields on Triangle Meshes
DEFF Research Database (Denmark)
Andersen, Vedrana; Aanæs, Henrik; Bærentzen, Jakob Andreas
2010-01-01
In this paper we propose a novel anisotropic smoothing scheme based on Markov Random Fields (MRF). Our scheme is formulated as two coupled processes. A vertex process is used to smooth the mesh by displacing the vertices according to a MRF smoothness prior, while an independent edge process label...
Digital servo control of random sound fields
Nakich, R. B.
1973-01-01
It is necessary to place number of sensors at different positions in sound field to determine actual sound intensities to which test object is subjected. It is possible to determine whether specification is being met adequately or exceeded. Since excitation is of random nature, signals are essentially coherent and it is impossible to obtain true average.
47 CFR 1.1603 - Conduct of random selection.
2010-10-01
... 47 Telecommunication 1 2010-10-01 2010-10-01 false Conduct of random selection. 1.1603 Section 1.1603 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1603 Conduct of random selection. The...
47 CFR 1.1602 - Designation for random selection.
2010-10-01
... 47 Telecommunication 1 2010-10-01 2010-10-01 false Designation for random selection. 1.1602 Section 1.1602 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1602 Designation for random selection...
An efficient estimator for Gibbs random fields
Czech Academy of Sciences Publication Activity Database
Janžura, Martin
2014-01-01
Roč. 50, č. 6 (2014), s. 883-895 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : Gibbs random field * efficient estimator * empirical estimator Subject RIV: BA - General Mathematics Impact factor: 0.541, year: 2014 http://library.utia.cas.cz/separaty/2015/SI/janzura-0441325.pdf
Role of random electric fields in relaxors
Phelan, Daniel; Stock, Christopher; Rodriguez-Rivera, Jose A.; Chi, Songxue; Leão, Juscelino; Long, Xifa; Xie, Yujuan; Bokov, Alexei A.; Ye, Zuo-Guang; Ganesh, Panchapakesan; Gehring, Peter M.
2014-01-01
PbZr1–xTixO3 (PZT) and Pb(Mg1/3Nb2/3)1–xTixO3 (PMN-xPT) are complex lead-oxide perovskites that display exceptional piezoelectric properties for pseudorhombohedral compositions near a tetragonal phase boundary. In PZT these compositions are ferroelectrics, but in PMN-xPT they are relaxors because the dielectric permittivity is frequency dependent and exhibits non-Arrhenius behavior. We show that the nanoscale structure unique to PMN-xPT and other lead-oxide perovskite relaxors is absent in PZT and correlates with a greater than 100% enhancement of the longitudinal piezoelectric coefficient in PMN-xPT relative to that in PZT. By comparing dielectric, structural, lattice dynamical, and piezoelectric measurements on PZT and PMN-xPT, two nearly identical compounds that represent weak and strong random electric field limits, we show that quenched (static) random fields establish the relaxor phase and identify the order parameter. PMID:24449912
Analysis, Simulation and Prediction of Multivariate Random Fields with Package RandomFields
Directory of Open Access Journals (Sweden)
Martin Schlather
2015-02-01
Full Text Available Modeling of and inference on multivariate data that have been measured in space, such as temperature and pressure, are challenging tasks in environmental sciences, physics and materials science. We give an overview over and some background on modeling with cross- covariance models. The R package RandomFields supports the simulation, the parameter estimation and the prediction in particular for the linear model of coregionalization, the multivariate Matrn models, the delay model, and a spectrum of physically motivated vector valued models. An example on weather data is considered, illustrating the use of RandomFields for parameter estimation and prediction.
Testing, Selection, and Implementation of Random Number Generators
National Research Council Canada - National Science Library
Collins, Joseph C
2008-01-01
An exhaustive evaluation of state-of-the-art random number generators with several well-known suites of tests provides the basis for selection of suitable random number generators for use in stochastic simulations...
Statistics of peaks of Gaussian random fields
International Nuclear Information System (INIS)
Bardeen, J.M.; Bond, J.R.; Kaiser, N.; Szalay, A.S.; Stanford Univ., CA; California Univ., Berkeley; Cambridge Univ., England; Fermi National Accelerator Lab., Batavia, IL)
1986-01-01
A set of new mathematical results on the theory of Gaussian random fields is presented, and the application of such calculations in cosmology to treat questions of structure formation from small-amplitude initial density fluctuations is addressed. The point process equation is discussed, giving the general formula for the average number density of peaks. The problem of the proper conditional probability constraints appropriate to maxima are examined using a one-dimensional illustration. The average density of maxima of a general three-dimensional Gaussian field is calculated as a function of heights of the maxima, and the average density of upcrossing points on density contour surfaces is computed. The number density of peaks subject to the constraint that the large-scale density field be fixed is determined and used to discuss the segregation of high peaks from the underlying mass distribution. The machinery to calculate n-point peak-peak correlation functions is determined, as are the shapes of the profiles about maxima. 67 references
Dynamics of the Random Field Ising Model
Xu, Jian
The Random Field Ising Model (RFIM) is a general tool to study disordered systems. Crackling noise is generated when disordered systems are driven by external forces, spanning a broad range of sizes. Systems with different microscopic structures such as disordered mag- nets and Earth's crust have been studied under the RFIM. In this thesis, we investigated the domain dynamics and critical behavior in two dipole-coupled Ising ferromagnets Nd2Fe14B and LiHoxY 1-xF4. With Tc well above room temperature, Nd2Fe14B has shown reversible disorder when exposed to an external transverse field and crosses between two universality classes in the strong and weak disorder limits. Besides tunable disorder, LiHoxY1-xF4 has shown quantum tunneling effects arising from quantum fluctuations, providing another mechanism for domain reversal. Universality within and beyond power law dependence on avalanche size and energy were studied in LiHo0.65Y0.35 F4.
Baryon-to-dark matter ratio from random angular fields
International Nuclear Information System (INIS)
McDonald, John
2013-01-01
We consider the baryon-to-dark matter ratio in models where the dark matter and baryon densities depend on angular fields θ d and θ b according to ρ d ∝θ d α and ρ b ∝θ b β , with all values of θ d and θ b being equally probable in a given randomly-selected domain. Under the assumption that anthropic selection depends primarily on the baryon density in galaxies at spherical collapse, we show that the probability density function for the baryon-to-dark matter ratio r = Ω B /Ω DM is purely statistical in nature and is independent of anthropic selection. We compute the probability density function for r as a function of α and β and show that the observed value of the baryon-to-dark matter ratio, r ≈ 1/5, is natural in this framework
Unmixing hyperspectral images using Markov random fields
International Nuclear Information System (INIS)
Eches, Olivier; Dobigeon, Nicolas; Tourneret, Jean-Yves
2011-01-01
This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm.
Random effect selection in generalised linear models
DEFF Research Database (Denmark)
Denwood, Matt; Houe, Hans; Forkman, Björn
We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...
Magnetic field line random walk in non-axisymmetric turbulence
International Nuclear Information System (INIS)
Tautz, R.C.; Lerche, I.
2011-01-01
Including a random component of a magnetic field parallel to an ambient field introduces a mean perpendicular motion to the average field line. This effect is normally not discussed because one customarily chooses at the outset to ignore such a field component in discussing random walk and diffusion of field lines. A discussion of the basic effect is given, indicating that any random magnetic field with a non-zero helicity will lead to such a non-zero perpendicular mean motion. Several exact analytic illustrations are given of the effect as well as a simple numerical illustration. -- Highlights: → For magnetic field line random walk all magnetic field components are important. → Non-vanishing magnetic helicity leads to mean perpendicular motion. → Analytically exact stream functions illustrate that the novel transverse effect exists.
On plasma stability under anisotropic random electric field influence
International Nuclear Information System (INIS)
Rabich, L.N.; Sosenko, P.P.
1987-01-01
The influence of anisotropic random field on plasma stability is studied. The thresholds and instability increments are obtained. The stabilizing influence of frequency missmatch and external magnetic field is pointed out
Interference-aware random beam selection for spectrum sharing systems
Abdallah, Mohamed M.; Sayed, Mostafa M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.
2012-01-01
. In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary
Simulation of random walks in field theory
International Nuclear Information System (INIS)
Rensburg, E.J.J. van
1988-01-01
The numerical simulation of random walks is considered using the Monte Carlo method previously proposed. The algorithm is tested and then generalised to generate Edwards random walks. The renormalised masses of the Edwards model are calculated and the results are compared with those obtained from a simple perturbation theory calculation for small values of the bare coupling constant. The efficiency of this algorithm is discussed and compared with an alternative approach. (author)
Efficient Incorporation of Markov Random Fields in Change Detection
DEFF Research Database (Denmark)
Aanæs, Henrik; Nielsen, Allan Aasbjerg; Carstensen, Jens Michael
2009-01-01
of noise, implying that the pixel-wise classifier is also noisy. There is thus a need for incorporating local homogeneity constraints into such a change detection framework. For this modelling task Markov Random Fields are suitable. Markov Random Fields have, however, previously been plagued by lack...
The potts chain in a random field: an exact solution
International Nuclear Information System (INIS)
Riera, R.; Chaves, C.M.G.F.; Santos, Raimundo R. dos.
1984-01-01
An exact solution is presented for the one-dimensional q-state Potts model in a quenched random field. The ferromagnetic phase is unstable against any small random field perturbation. The correlation function and the Edwards-Anderson order parameter Q are discussed. For finite q only the phase with Q ≠ 0 is present. (Author) [pt
Level sets and extrema of random processes and fields
Azais, Jean-Marc
2009-01-01
A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book provides a unified and accessible approach to these two topics and their relationship to classical theory and Gaussian processes and fields, and the most modern research findings are also discussed. The authors begin with an introduction to the basic concepts of stochastic processes, including a modern review of Gaussian fields and their classical inequalities. Subsequent chapters are devoted to Rice formulas, regularity properties, and recent results on the tails of the distribution of the maximum. Finally, applications of random fields to various areas of mathematics a...
Generating functionals for quantum field theories with random potentials
International Nuclear Information System (INIS)
Jain, Mudit; Vanchurin, Vitaly
2016-01-01
We consider generating functionals for computing correlators in quantum field theories with random potentials. Examples of such theories include cosmological systems in context of the string theory landscape (e.g. cosmic inflation) or condensed matter systems with quenched disorder (e.g. spin glass). We use the so-called replica trick to define two different generating functionals for calculating correlators of the quantum fields averaged over a given distribution of random potentials. The first generating functional is appropriate for calculating averaged (in-out) amplitudes and involves a single replica of fields, but the replica limit is taken to an (unphysical) negative one number of fields outside of the path integral. When the number of replicas is doubled the generating functional can also be used for calculating averaged probabilities (squared amplitudes) using the in-in construction. The second generating functional involves an infinite number of replicas, but can be used for calculating both in-out and in-in correlators and the replica limits are taken to only a zero number of fields. We discuss the formalism in details for a single real scalar field, but the generalization to more fields or to different types of fields is straightforward. We work out three examples: one where the mass of scalar field is treated as a random variable and two where the functional form of interactions is random, one described by a Gaussian random field and the other by a Euclidean action in the field configuration space.
Supplementary Material for: Tukey g-and-h Random Fields
Xu, Ganggang
2016-01-01
We propose a new class of transGaussian random fields named Tukey g-and-h (TGH) random fields to model non-Gaussian spatial data. The proposed TGH random fields have extremely flexible marginal distributions, possibly skewed and/or heavy-tailed, and, therefore, have a wide range of applications. The special formulation of the TGH random field enables an automatic search for the most suitable transformation for the dataset of interest while estimating model parameters. Asymptotic properties of the maximum likelihood estimator and the probabilistic properties of the TGH random fields are investigated. An efficient estimation procedure, based on maximum approximated likelihood, is proposed and an extreme spatial outlier detection algorithm is formulated. Kriging and probabilistic prediction with TGH random fields are developed along with prediction confidence intervals. The predictive performance of TGH random fields is demonstrated through extensive simulation studies and an application to a dataset of total precipitation in the south east of the United States. Supplementary materials for this article are available online.
Receptive fields selection for binary feature description.
Fan, Bin; Kong, Qingqun; Trzcinski, Tomasz; Wang, Zhiheng; Pan, Chunhong; Fua, Pascal
2014-06-01
Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning-based methods for designing local descriptor become more and more popular because of their good performance and data-driven property. This paper proposes a novel data-driven method for designing binary feature descriptor, which we call receptive fields descriptor (RFD). Technically, RFD is constructed by thresholding responses of a set of receptive fields, which are selected from a large number of candidates according to their distinctiveness and correlations in a greedy way. Using two different kinds of receptive fields (namely rectangular pooling area and Gaussian pooling area) for selection, we obtain two binary descriptors RFDR and RFDG .accordingly. Image matching experiments on the well-known patch data set and Oxford data set demonstrate that RFD significantly outperforms the state-of-the-art binary descriptors, and is comparable with the best float-valued descriptors at a fraction of processing time. Finally, experiments on object recognition tasks confirm that both RFDR and RFDG successfully bridge the performance gap between binary descriptors and their floating-point competitors.
Positive random fields for modeling material stiffness and compliance
DEFF Research Database (Denmark)
Hasofer, Abraham Michael; Ditlevsen, Ove Dalager; Tarp-Johansen, Niels Jacob
1998-01-01
Positive random fields with known marginal properties and known correlation function are not numerous in the literature. The most prominent example is the log\\-normal field for which the complete distribution is known and for which the reciprocal field is also lognormal. It is of interest to supp...
Random wave fields and scintillated beams
CSIR Research Space (South Africa)
Roux, FS
2009-01-01
Full Text Available F. Stef Roux CSIR National Laser Centre PO Box 395, Pretoria 0001, South Africa CSIR National Laser Centre – p.1/29 Contents . Scintillated beams and adaptive optics . Detecting a vortex — Shack-Hartmann . Remove optical vortices . Random vortex... beam. CSIR National Laser Centre – p.3/29 Weak scintillation If the scintillation is weak the resulting phase function of the optical beam is still continuous. Such a weakly scintillated beam can be corrected by an adaptive optical system. CSIR National...
Selectivity and sparseness in randomly connected balanced networks.
Directory of Open Access Journals (Sweden)
Cengiz Pehlevan
Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.
The random field Blume-Capel model revisited
Santos, P. V.; da Costa, F. A.; de Araújo, J. M.
2018-04-01
We have revisited the mean-field treatment for the Blume-Capel model under the presence of a discrete random magnetic field as introduced by Kaufman and Kanner (1990). The magnetic field (H) versus temperature (T) phase diagrams for given values of the crystal field D were recovered in accordance to Kaufman and Kanner original work. However, our main goal in the present work was to investigate the distinct structures of the crystal field versus temperature phase diagrams as the random magnetic field is varied because similar models have presented reentrant phenomenon due to randomness. Following previous works we have classified the distinct phase diagrams according to five different topologies. The topological structure of the phase diagrams is maintained for both H - T and D - T cases. Although the phase diagrams exhibit a richness of multicritical phenomena we did not found any reentrant effect as have been seen in similar models.
The use of random walk in field theory
International Nuclear Information System (INIS)
Brydges, D.
1984-01-01
Ferromagnetic spin systems and gauge theories where the gauge group is topologically a sphere, e.g. Z 2 , U(1) and SU(2) are related to the theory of random walk and random surfaces respectively. I survey some applications of this theme to the phi 4 field theories. (orig.)
Subquantum nonlocal correlations induced by the background random field
Energy Technology Data Exchange (ETDEWEB)
Khrennikov, Andrei, E-mail: Andrei.Khrennikov@lnu.s [International Center for Mathematical Modelling in Physics and Cognitive Sciences, Linnaeus University, Vaexjoe (Sweden); Institute of Information Security, Russian State University for Humanities, Moscow (Russian Federation)
2011-10-15
We developed a purely field model of microphenomena-prequantum classical statistical field theory (PCSFT). This model not only reproduces important probabilistic predictions of quantum mechanics (QM) including correlations for entangled systems, but also gives a possibility to go beyond QM, i.e. to make predictions of phenomena that could be observed at the subquantum level. In this paper, we discuss one such prediction-the existence of nonlocal correlations between prequantum random fields corresponding to all quantum systems. (And by PCSFT, quantum systems are represented by classical Gaussian random fields and quantum observables by quadratic forms of these fields.) The source of these correlations is the common background field. Thus all prequantum random fields are 'entangled', but in the sense of classical signal theory. On the one hand, PCSFT demystifies quantum nonlocality by reducing it to nonlocal classical correlations based on the common random background. On the other hand, it demonstrates total generality of such correlations. They exist even for distinguishable quantum systems in factorizable states (by PCSFT terminology-for Gaussian random fields with covariance operators corresponding to factorizable quantum states).
Subquantum nonlocal correlations induced by the background random field
International Nuclear Information System (INIS)
Khrennikov, Andrei
2011-01-01
We developed a purely field model of microphenomena-prequantum classical statistical field theory (PCSFT). This model not only reproduces important probabilistic predictions of quantum mechanics (QM) including correlations for entangled systems, but also gives a possibility to go beyond QM, i.e. to make predictions of phenomena that could be observed at the subquantum level. In this paper, we discuss one such prediction-the existence of nonlocal correlations between prequantum random fields corresponding to all quantum systems. (And by PCSFT, quantum systems are represented by classical Gaussian random fields and quantum observables by quadratic forms of these fields.) The source of these correlations is the common background field. Thus all prequantum random fields are 'entangled', but in the sense of classical signal theory. On the one hand, PCSFT demystifies quantum nonlocality by reducing it to nonlocal classical correlations based on the common random background. On the other hand, it demonstrates total generality of such correlations. They exist even for distinguishable quantum systems in factorizable states (by PCSFT terminology-for Gaussian random fields with covariance operators corresponding to factorizable quantum states).
The signature of positive selection at randomly chosen loci.
Przeworski, Molly
2002-01-01
In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequ...
The reliability of randomly selected final year pharmacy students in ...
African Journals Online (AJOL)
Employing ANOVA, factorial experimental analysis, and the theory of error, reliability studies were conducted on the assessment of the drug product chloroquine phosphate tablets. The G–Study employed equal numbers of the factors for uniform control, and involved three analysts (randomly selected final year Pharmacy ...
Properties and simulation of α-permanental random fields
DEFF Research Database (Denmark)
Møller, Jesper; Rubak, Ege Holger
An α-permanental random field is briefly speaking a model for a collection of random variables with positive associations, where α is a positive number and the probability generating function is given in terms of a covariance or more general function so that density and moment expressions are given...... by certain α-permanents. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields and their potential applications. The purpose of this paper is first to summarize useful probabilistic results using the simplest possible setting......, and second to study stochastic constructions and simulation techniques, which should provide a useful basis for discussing the statistical aspects in future work. The paper also discusses some examples of α-permanental random fields....
Shape Modelling Using Markov Random Field Restoration of Point Correspondences
DEFF Research Database (Denmark)
Paulsen, Rasmus Reinhold; Hilger, Klaus Baggesen
2003-01-01
A method for building statistical point distribution models is proposed. The novelty in this paper is the adaption of Markov random field regularization of the correspondence field over the set of shapes. The new approach leads to a generative model that produces highly homogeneous polygonized sh...
ANALYTIC WORD RECOGNITION WITHOUT SEGMENTATION BASED ON MARKOV RANDOM FIELDS
Coisy, C.; Belaid, A.
2004-01-01
In this paper, a method for analytic handwritten word recognition based on causal Markov random fields is described. The words models are HMMs where each state corresponds to a letter; each letter is modelled by a NSHPHMM (Markov field). Global models are build dynamically, and used for recognition
Local randomization in neighbor selection improves PRM roadmap quality
McMahon, Troy
2012-10-01
Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K\\'), that first computes the K\\' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K\\'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.
Local randomization in neighbor selection improves PRM roadmap quality
McMahon, Troy; Jacobs, Sam; Boyd, Bryan; Tapia, Lydia; Amato, Nancy M.
2012-01-01
Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K'), that first computes the K' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.
Random walks, critical phenomena, and triviality in quantum field theory
International Nuclear Information System (INIS)
Fernandez, R.; Froehlich, J.; Sokal, A.D.
1992-01-01
The subject of this book is equilibrium statistical mechanics - in particular the theory of critical phenomena - and quantum field theory. A general review of the theory of critical phenomena in spin systems, field theories, and random-walk and random-surface models is presented. Among the more technical topics treated in this book, the central theme is the use of random-walk representations as a tool to derive correlation inequalities. The consequences of these inequalities for critical-exponent theory and the triviality question in quantum field theory are expounded in detail. The book contains some previously unpublished results. It addresses both the researcher and the graduate student in modern statistical mechanics and quantum field theory. (orig.)
Selection for altruism through random drift in variable size populations
Directory of Open Access Journals (Sweden)
Houchmandzadeh Bahram
2012-05-01
Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.
The intermittency of vector fields and random-number generators
Kalinin, A. O.; Sokoloff, D. D.; Tutubalin, V. N.
2017-09-01
We examine how well natural random-number generators can reproduce the intermittency phenomena that arise in the transfer of vector fields in random media. A generator based on the analysis of financial indices is suggested as the most promising random-number generator. Is it shown that even this generator, however, fails to reproduce the phenomenon long enough to confidently detect intermittency, while the C++ generator successfully solves this problem. We discuss the prospects of using shell models of turbulence as the desired generator.
Pose-invariant face recognition using Markov random fields.
Ho, Huy Tho; Chellappa, Rama
2013-04-01
One of the key challenges for current face recognition techniques is how to handle pose variations between the probe and gallery face images. In this paper, we present a method for reconstructing the virtual frontal view from a given nonfrontal face image using Markov random fields (MRFs) and an efficient variant of the belief propagation algorithm. In the proposed approach, the input face image is divided into a grid of overlapping patches, and a globally optimal set of local warps is estimated to synthesize the patches at the frontal view. A set of possible warps for each patch is obtained by aligning it with images from a training database of frontal faces. The alignments are performed efficiently in the Fourier domain using an extension of the Lucas-Kanade algorithm that can handle illumination variations. The problem of finding the optimal warps is then formulated as a discrete labeling problem using an MRF. The reconstructed frontal face image can then be used with any face recognition technique. The two main advantages of our method are that it does not require manually selected facial landmarks or head pose estimation. In order to improve the performance of our pose normalization method in face recognition, we also present an algorithm for classifying whether a given face image is at a frontal or nonfrontal pose. Experimental results on different datasets are presented to demonstrate the effectiveness of the proposed approach.
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
Phase transitions in the random field Ising model in the presence of a transverse field
Energy Technology Data Exchange (ETDEWEB)
Dutta, A.; Chakrabarti, B.K. [Saha Institute of Nuclear Physics, Bidhannagar, Calcutta (India); Stinchcombe, R.B. [Saha Institute of Nuclear Physics, Bidhannagar, Calcutta (India); Department of Physics, Oxford (United Kingdom)
1996-09-07
We have studied the phase transition behaviour of the random field Ising model in the presence of a transverse (or tunnelling) field. The mean field phase diagram has been studied in detail, and in particular the nature of the transition induced by the tunnelling (transverse) field at zero temperature. Modified hyper-scaling relation for the zero-temperature transition has been derived using the Suzuki-Trotter formalism and a modified 'Harris criterion'. Mapping of the model to a randomly diluted antiferromagnetic Ising model in uniform longitudinal and transverse field is also given. (author)
Infinite conditional random fields for human behavior analysis
Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja
Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF
Random field assessment of nanoscopic inhomogeneity of bone.
Dong, X Neil; Luo, Qing; Sparkman, Daniel M; Millwater, Harry R; Wang, Xiaodu
2010-12-01
Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to represent the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. Copyright © 2010 Elsevier Inc. All rights reserved.
Numerical solution of field theories using random walks
International Nuclear Information System (INIS)
Barnes, T.; Daniell, G.J.
1985-01-01
We show how random walks in function space can be employed to evaluate field theoretic vacuum expectation values numerically. Specific applications which we study are the two-point function, mass gap, magnetization and classical solutions. This technique offers the promise of faster calculations using less computer memory than current methods. (orig.)
Energy conservation law for randomly fluctuating electromagnetic fields
International Nuclear Information System (INIS)
Gbur, G.; Wolf, E.; James, D.
1999-01-01
An energy conservation law is derived for electromagnetic fields generated by any random, statistically stationary, source distribution. It is shown to provide insight into the phenomenon of correlation-induced spectral changes. The results are illustrated by an example. copyright 1999 The American Physical Society
The dilute random field Ising model by finite cluster approximation
International Nuclear Information System (INIS)
Benyoussef, A.; Saber, M.
1987-09-01
Using the finite cluster approximation, phase diagrams of bond and site diluted three-dimensional simple cubic Ising models with a random field have been determined. The resulting phase diagrams have the same general features for both bond and site dilution. (author). 7 refs, 4 figs
Interference-aware random beam selection for spectrum sharing systems
Abdallah, Mohamed M.
2012-09-01
Spectrum sharing systems have been introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary transmitter equipped with multiple antennas, our schemes select a random beam, among a set of power- optimized orthogonal random beams, that maximizes the capacity of the secondary link while satisfying the interference constraint at the primary receiver for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the signal-to-noise and interference ratio (SINR) statistics as well as the capacity of the secondary link. Finally, we present numerical results that study the effect of system parameters including number of beams and the maximum transmission power on the capacity of the secondary link attained using the proposed schemes. © 2012 IEEE.
Magnetic field correlations in random flow with strong steady shear
International Nuclear Information System (INIS)
Kolokolov, I. V.; Lebedev, V. V.; Sizov, G. A.
2011-01-01
We analyze the magnetic kinematic dynamo in a conducting fluid where a stationary shear flow is accompanied by relatively weak random velocity fluctuations. The diffusionless and diffusion regimes are described. The growth rates of the magnetic field moments are related to the statistical characteristics of the flow describing divergence of the Lagrangian trajectories. The magnetic field correlation functions are examined, and their growth rates and scaling behavior are established. General assertions are illustrated by the explicit solution of a model where the velocity field is short-correlated in time.
Correlation diagnostics of random spatially nonuniform optical fields
International Nuclear Information System (INIS)
Angel'skii, O.V.
1992-01-01
This review examines some questions concerning the capabilities of interference and polarization-interference correlation diagnostics of the amplitude-phase characteristics of random optical fields for the purpose of identifying these fields and then studying the corresponding objects. The diagnostics of random phase objects is discussed separately in the case in which the phase dispersion of the inhomogeneities is less than and greater than one. The outlook is promising for the use of the correlation dimensionality of chaos in a field as a diagnostic parameter. It is also shown that the use of interference principles for a parallel processing of large data files can substantially increase the speed of processing systems. 32 refs., 8 figs
Nonstationary random acoustic and electromagnetic fields as wave diffusion processes
International Nuclear Information System (INIS)
Arnaut, L R
2007-01-01
We investigate the effects of relatively rapid variations of the boundaries of an overmoded cavity on the stochastic properties of its interior acoustic or electromagnetic field. For quasi-static variations, this field can be represented as an ideal incoherent and statistically homogeneous isotropic random scalar or vector field, respectively. A physical model is constructed showing that the field dynamics can be characterized as a generalized diffusion process. The Langevin-It o-hat and Fokker-Planck equations are derived and their associated statistics and distributions for the complex analytic field, its magnitude and energy density are computed. The energy diffusion parameter is found to be proportional to the square of the ratio of the standard deviation of the source field to the characteristic time constant of the dynamic process, but is independent of the initial energy density, to first order. The energy drift vanishes in the asymptotic limit. The time-energy probability distribution is in general not separable, as a result of nonstationarity. A general solution of the Fokker-Planck equation is obtained in integral form, together with explicit closed-form solutions for several asymptotic cases. The findings extend known results on statistics and distributions of quasi-stationary ideal random fields (pure diffusions), which are retrieved as special cases
Random selection of items. Selection of n1 samples among N items composing a stratum
International Nuclear Information System (INIS)
Jaech, J.L.; Lemaire, R.J.
1987-02-01
STR-224 provides generalized procedures to determine required sample sizes, for instance in the course of a Physical Inventory Verification at Bulk Handling Facilities. The present report describes procedures to generate random numbers and select groups of items to be verified in a given stratum through each of the measurement methods involved in the verification. (author). 3 refs
Statistical analysis of the ratio of electric and magnetic fields in random fields generators
Serra, R.; Nijenhuis, J.
2013-01-01
In this paper we present statistical models of the ratio of random electric and magnetic fields in mode-stirred reverberation chambers. This ratio is based on the electric and magnetic field statistics derived for ideal reverberation conditions. It provides a further performance indicator for
The signature of positive selection at randomly chosen loci.
Przeworski, Molly
2002-03-01
In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.
A ferromagnetic chain in a random weak field
Avgin, I.
1996-10-01
The harmonic magnon modes in a Heisenberg ferromagnetic chain in a random weak field are studied. The Lyapunov exponent for the uniform ( k = 0) mode is computed using the coherent potential approximation (CPA) in the weak-disorder limit. The CPA results are compared with the numerical and weak-disorder expansions of various random systems. We have found that the inverse localization length and the integrated density of states have anomalous power law behaviour as reported earlier. The CPA also reproduces the dispersion law for the same system, calculated by Pimentel and Stinchcombe using the real space renormalization scaling technique. A brief comment is also made for the uniform weak-field case.
Random field Ising chain and neutral networks with synchronous dynamics
International Nuclear Information System (INIS)
Skantzos, N.S.; Coolen, A.C.C.
2001-01-01
We first present an exact solution of the one-dimensional random-field Ising model in which spin-updates are made fully synchronously, i.e. in parallel (in contrast to the more conventional Glauber-type sequential rules). We find transitions where the support of local observables turns from a continuous interval into a Cantor set and we show that synchronous and sequential random-field models lead asymptotically to the same physical states. We then proceed to an application of these techniques to recurrent neural networks where 1D short-range interactions are combined with infinite-range ones. Due to the competing interactions these models exhibit phase diagrams with first-order transitions and regions with multiple locally stable solutions for the macroscopic order parameters
Thomas, D.L.; Johnson, D.; Griffith, B.
2006-01-01
Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a
Efficient approximation of random fields for numerical applications
Harbrecht, Helmut; Peters, Michael; Siebenmorgen, Markus
2015-01-01
We consider the rapid computation of separable expansions for the approximation of random fields. We compare approaches based on techniques from the approximation of non-local operators on the one hand and based on the pivoted Cholesky decomposition on the other hand. We provide an a-posteriori error estimate for the pivoted Cholesky decomposition in terms of the trace. Numerical examples validate and quantify the considered methods.
On the Tsallis Entropy for Gibbs Random Fields
Czech Academy of Sciences Publication Activity Database
Janžura, Martin
2014-01-01
Roč. 21, č. 33 (2014), s. 59-69 ISSN 1212-074X R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional research plan: CEZ:AV0Z1075907 Keywords : Tsallis entropy * Gibbs random fields * phase transitions * Tsallis entropy rate Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/SI/janzura-0441885.pdf
Efficient approximation of random fields for numerical applications
Harbrecht, Helmut
2015-01-07
We consider the rapid computation of separable expansions for the approximation of random fields. We compare approaches based on techniques from the approximation of non-local operators on the one hand and based on the pivoted Cholesky decomposition on the other hand. We provide an a-posteriori error estimate for the pivoted Cholesky decomposition in terms of the trace. Numerical examples validate and quantify the considered methods.
Joint Conditional Random Field Filter for Multi-Object Tracking
Directory of Open Access Journals (Sweden)
Luo Ronghua
2011-03-01
Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.
Blind Measurement Selection: A Random Matrix Theory Approach
Elkhalil, Khalil
2016-12-14
This paper considers the problem of selecting a set of $k$ measurements from $n$ available sensor observations. The selected measurements should minimize a certain error function assessing the error in estimating a certain $m$ dimensional parameter vector. The exhaustive search inspecting each of the $n\\\\choose k$ possible choices would require a very high computational complexity and as such is not practical for large $n$ and $k$. Alternative methods with low complexity have recently been investigated but their main drawbacks are that 1) they require perfect knowledge of the measurement matrix and 2) they need to be applied at the pace of change of the measurement matrix. To overcome these issues, we consider the asymptotic regime in which $k$, $n$ and $m$ grow large at the same pace. Tools from random matrix theory are then used to approximate in closed-form the most important error measures that are commonly used. The asymptotic approximations are then leveraged to select properly $k$ measurements exhibiting low values for the asymptotic error measures. Two heuristic algorithms are proposed: the first one merely consists in applying the convex optimization artifice to the asymptotic error measure. The second algorithm is a low-complexity greedy algorithm that attempts to look for a sufficiently good solution for the original minimization problem. The greedy algorithm can be applied to both the exact and the asymptotic error measures and can be thus implemented in blind and channel-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also presented and sustain the efficiency of the proposed blind methods in reaching the performances of channel-aware algorithms.
International Nuclear Information System (INIS)
Ovchinnikov, O. S.; Jesse, S.; Kalinin, S. V.; Bintacchit, P.; Trolier-McKinstry, S.
2009-01-01
An approach for the direct identification of disorder type and strength in physical systems based on recognition analysis of hysteresis loop shape is developed. A large number of theoretical examples uniformly distributed in the parameter space of the system is generated and is decorrelated using principal component analysis (PCA). The PCA components are used to train a feed-forward neural network using the model parameters as targets. The trained network is used to analyze hysteresis loops for the investigated system. The approach is demonstrated using a 2D random-bond-random-field Ising model, and polarization switching in polycrystalline ferroelectric capacitors.
Efficacy of selected herbicide formulations on sugarcane field weeds ...
African Journals Online (AJOL)
In continuation for the search of appropriate weed control strategy for sugarcane field weeds at the Unilorin Sugar Research Institute (USRI), Ilorin located at 8o 030' N; 4o 32' E , Nigeria. Field trials were laid out in a randomized complete block design during 2012 and 2013 growing seasons to evaluate four herbicide ...
Materials selection for oxide-based resistive random access memories
International Nuclear Information System (INIS)
Guo, Yuzheng; Robertson, John
2014-01-01
The energies of atomic processes in resistive random access memories (RRAMs) are calculated for four typical oxides, HfO 2 , TiO 2 , Ta 2 O 5 , and Al 2 O 3 , to define a materials selection process. O vacancies have the lowest defect formation energy in the O-poor limit and dominate the processes. A band diagram defines the operating Fermi energy and O chemical potential range. It is shown how the scavenger metal can be used to vary the O vacancy formation energy, via controlling the O chemical potential, and the mean Fermi energy. The high endurance of Ta 2 O 5 RRAM is related to its more stable amorphous phase and the adaptive lattice rearrangements of its O vacancy
Primitive polynomials selection method for pseudo-random number generator
Anikin, I. V.; Alnajjar, Kh
2018-01-01
In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.
Materials selection for oxide-based resistive random access memories
Energy Technology Data Exchange (ETDEWEB)
Guo, Yuzheng; Robertson, John [Engineering Department, Cambridge University, Cambridge CB2 1PZ (United Kingdom)
2014-12-01
The energies of atomic processes in resistive random access memories (RRAMs) are calculated for four typical oxides, HfO{sub 2}, TiO{sub 2}, Ta{sub 2}O{sub 5}, and Al{sub 2}O{sub 3}, to define a materials selection process. O vacancies have the lowest defect formation energy in the O-poor limit and dominate the processes. A band diagram defines the operating Fermi energy and O chemical potential range. It is shown how the scavenger metal can be used to vary the O vacancy formation energy, via controlling the O chemical potential, and the mean Fermi energy. The high endurance of Ta{sub 2}O{sub 5} RRAM is related to its more stable amorphous phase and the adaptive lattice rearrangements of its O vacancy.
Optimizing Event Selection with the Random Grid Search
Energy Technology Data Exchange (ETDEWEB)
Bhat, Pushpalatha C. [Fermilab; Prosper, Harrison B. [Florida State U.; Sekmen, Sezen [Kyungpook Natl. U.; Stewart, Chip [Broad Inst., Cambridge
2017-06-29
The random grid search (RGS) is a simple, but efficient, stochastic algorithm to find optimal cuts that was developed in the context of the search for the top quark at Fermilab in the mid-1990s. The algorithm, and associated code, have been enhanced recently with the introduction of two new cut types, one of which has been successfully used in searches for supersymmetry at the Large Hadron Collider. The RGS optimization algorithm is described along with the recent developments, which are illustrated with two examples from particle physics. One explores the optimization of the selection of vector boson fusion events in the four-lepton decay mode of the Higgs boson and the other optimizes SUSY searches using boosted objects and the razor variables.
Selective decontamination in pediatric liver transplants. A randomized prospective study.
Smith, S D; Jackson, R J; Hannakan, C J; Wadowsky, R M; Tzakis, A G; Rowe, M I
1993-06-01
Although it has been suggested that selective decontamination of the digestive tract (SDD) decreases postoperative aerobic Gram-negative and fungal infections in orthotopic liver transplantation (OLT), no controlled trials exist in pediatric patients. This prospective, randomized controlled study of 36 pediatric OLT patients examines the effect of short-term SDD on postoperative infection and digestive tract flora. Patients were randomized into two groups. The control group received perioperative parenteral antibiotics only. The SDD group received in addition polymyxin E, tobramycin, and amphotericin B enterally and by oropharyngeal swab postoperatively until oral intake was tolerated (6 +/- 4 days). Indications for operation, preoperative status, age, and intensive care unit and hospital length of stay were no different in SDD (n = 18) and control (n = 18) groups. A total of 14 Gram-negative infections (intraabdominal abscess 7, septicemia 5, pneumonia 1, urinary tract 1) developed in the 36 patients studied. Mortality was not significantly different in the two groups. However, there were significantly fewer patients with Gram-negative infections in the SDD group: 3/18 patients (11%) vs. 11/18 patients (50%) in the control group, P < 0.001. There was also significant reduction in aerobic Gram-negative flora in the stool and pharynx in patients receiving SDD. Gram-positive and anaerobic organisms were unaffected. We conclude that short-term postoperative SDD significantly reduces Gram-negative infections in pediatric OLT patients.
Phase conjugation with random fields and with deterministic and random scatterers
International Nuclear Information System (INIS)
Gbur, G.; Wolf, E.
1999-01-01
The theory of distortion correction by phase conjugation, developed since the discovery of this phenomenon many years ago, applies to situations when the field that is conjugated is monochromatic and the medium with which it interacts is deterministic. In this Letter a generalization of the theory is presented that applies to phase conjugation of partially coherent waves interacting with either deterministic or random weakly scattering nonabsorbing media. copyright 1999 Optical Society of America
Statistical mechanics and stability of random lattice field theory
International Nuclear Information System (INIS)
Baskaran, G.
1984-01-01
The averaging procedure in the random lattice field theory is studied by viewing it as a statistical mechanics of a system of classical particles. The corresponding thermodynamic phase is shown to determine the random lattice configuration which contributes dominantly to the generating function. The non-abelian gauge theory in four (space plus time) dimensions in the annealed and quenched averaging versions is shown to exist as an ideal classical gas, implying that macroscopically homogeneous configurations dominate the configurational averaging. For the free massless scalar field theory with O(n) global symmetry, in the annealed average, the pressure becomes negative for dimensions greater than two when n exceeds a critical number. This implies that macroscopically inhomogeneous collapsed configurations contribute dominantly. In the quenched averaging, the collapse of the massless scalar field theory is prevented and the system becomes an ideal gas which is at infinite temperature. Our results are obtained using exact scaling analysis. We also show approximately that SU(N) gauge theory collapses for dimensions greater than four in the annealed average. Within the same approximation, the collapse is prevented in the quenched average. We also obtain exact scaling differential equations satisfied by the generating function and physical quantities. (orig.)
Deep recurrent conditional random field network for protein secondary prediction
DEFF Research Database (Denmark)
Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae
2017-01-01
Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...
Extremes in random fields a theory and its applications
Yakir, Benjamin
2013-01-01
Presents a useful new technique for analyzing the extreme-value behaviour of random fields Modern science typically involves the analysis of increasingly complex data. The extreme values that emerge in the statistical analysis of complex data are often of particular interest. This book focuses on the analytical approximations of the statistical significance of extreme values. Several relatively complex applications of the technique to problems that emerge in practical situations are presented. All the examples are difficult to analyze using classical methods, and as a result, the author pr
A note on moving average models for Gaussian random fields
DEFF Research Database (Denmark)
Hansen, Linda Vadgård; Thorarinsdottir, Thordis L.
The class of moving average models offers a flexible modeling framework for Gaussian random fields with many well known models such as the Matérn covariance family and the Gaussian covariance falling under this framework. Moving average models may also be viewed as a kernel smoothing of a Lévy...... basis, a general modeling framework which includes several types of non-Gaussian models. We propose a new one-parameter spatial correlation model which arises from a power kernel and show that the associated Hausdorff dimension of the sample paths can take any value between 2 and 3. As a result...
Pediatric selective mutism therapy: a randomized controlled trial.
Esposito, Maria; Gimigliano, Francesca; Barillari, Maria R; Precenzano, Francesco; Ruberto, Maria; Sepe, Joseph; Barillari, Umberto; Gimigliano, Raffaele; Militerni, Roberto; Messina, Giovanni; Carotenuto, Marco
2017-10-01
Selective mutism (SM) is a rare disease in children coded by DSM-5 as an anxiety disorder. Despite the disabling nature of the disease, there is still no specific treatment. The aims of this study were to verify the efficacy of six-month standard psychomotor treatment and the positive changes in lifestyle, in a population of children affected by SM. Randomized controlled trial registered in the European Clinical Trials Registry (EuDract 2015-001161-36). University third level Centre (Child and Adolescent Neuropsychiatry Clinic). Study population was composed by 67 children in group A (psychomotricity treatment) (35 M, mean age 7.84±1.15) and 71 children in group B (behavioral and educational counseling) (37 M, mean age 7.75±1.36). Psychomotor treatment was administered by trained child therapists in residential settings three times per week. Each child was treated for the whole period by the same therapist and all the therapists shared the same protocol. The standard psychomotor session length is of 45 minutes. At T0 and after 6 months (T1) of treatments, patients underwent a behavioral and SM severity assessment. To verify the effects of the psychomotor management, the Child Behavior Checklist questionnaire (CBCL) and Selective Mutism Questionnaire (SMQ) were administered to the parents. After 6 months of psychomotor treatment SM children showed a significant reduction among CBCL scores such as in social relations, anxious/depressed, social problems and total problems (Pselective mutism, even if further studies are needed. The present study identifies in psychomotricity a safe and efficacy therapy for pediatric selective mutism.
Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base
Directory of Open Access Journals (Sweden)
Chuan Gu
2015-01-01
Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.
Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons.
Sadeh, Sadra; Cardanobile, Stefano; Rotter, Stefan
2014-01-01
Mechanisms underlying the emergence of orientation selectivity in the primary visual cortex are highly debated. Here we study the contribution of inhibition-dominated random recurrent networks to orientation selectivity, and more generally to sensory processing. By simulating and analyzing large-scale networks of spiking neurons, we investigate tuning amplification and contrast invariance of orientation selectivity in these networks. In particular, we show how selective attenuation of the common mode and amplification of the modulation component take place in these networks. Selective attenuation of the baseline, which is governed by the exceptional eigenvalue of the connectivity matrix, removes the unspecific, redundant signal component and ensures the invariance of selectivity across different contrasts. Selective amplification of modulation, which is governed by the operating regime of the network and depends on the strength of coupling, amplifies the informative signal component and thus increases the signal-to-noise ratio. Here, we perform a mean-field analysis which accounts for this process.
Quantum Coherence and Random Fields at Mesoscopic Scales
International Nuclear Information System (INIS)
Rosenbaum, Thomas F.
2016-01-01
We seek to explore and exploit model, disordered and geometrically frustrated magnets where coherent spin clusters stably detach themselves from their surroundings, leading to extreme sensitivity to finite frequency excitations and the ability to encode information. Global changes in either the spin concentration or the quantum tunneling probability via the application of an external magnetic field can tune the relative weights of quantum entanglement and random field effects on the mesoscopic scale. These same parameters can be harnessed to manipulate domain wall dynamics in the ferromagnetic state, with technological possibilities for magnetic information storage. Finally, extensions from quantum ferromagnets to antiferromagnets promise new insights into the physics of quantum fluctuations and effective dimensional reduction. A combination of ac susceptometry, dc magnetometry, noise measurements, hole burning, non-linear Fano experiments, and neutron diffraction as functions of temperature, magnetic field, frequency, excitation amplitude, dipole concentration, and disorder address issues of stability, overlap, coherence, and control. We have been especially interested in probing the evolution of the local order in the progression from spin liquid to spin glass to long-range-ordered magnet.
Quantum Coherence and Random Fields at Mesoscopic Scales
Energy Technology Data Exchange (ETDEWEB)
Rosenbaum, Thomas F. [Univ. of Chicago, IL (United States)
2016-03-01
We seek to explore and exploit model, disordered and geometrically frustrated magnets where coherent spin clusters stably detach themselves from their surroundings, leading to extreme sensitivity to finite frequency excitations and the ability to encode information. Global changes in either the spin concentration or the quantum tunneling probability via the application of an external magnetic field can tune the relative weights of quantum entanglement and random field effects on the mesoscopic scale. These same parameters can be harnessed to manipulate domain wall dynamics in the ferromagnetic state, with technological possibilities for magnetic information storage. Finally, extensions from quantum ferromagnets to antiferromagnets promise new insights into the physics of quantum fluctuations and effective dimensional reduction. A combination of ac susceptometry, dc magnetometry, noise measurements, hole burning, non-linear Fano experiments, and neutron diffraction as functions of temperature, magnetic field, frequency, excitation amplitude, dipole concentration, and disorder address issues of stability, overlap, coherence, and control. We have been especially interested in probing the evolution of the local order in the progression from spin liquid to spin glass to long-range-ordered magnet.
Open-field behavior of house mice selectively bred for high voluntary wheel-running.
Bronikowski, A M; Carter, P A; Swallow, J G; Girard, I A; Rhodes, J S; Garland, T
2001-05-01
Open-field behavioral assays are commonly used to test both locomotor activity and emotionality in rodents. We performed open-field tests on house mice (Mus domesticus) from four replicate lines genetically selected for high voluntary wheel-running for 22 generations and from four replicate random-bred control lines. Individual mice were recorded by video camera for 3 min in a 1-m2 open-field arena on 2 consecutive days. Mice from selected lines showed no statistical differences from control mice with respect to distance traveled, defecation, time spent in the interior, or average distance from the center of the arena during the trial. Thus, we found little evidence that open-field behavior, as traditionally defined, is genetically correlated with wheel-running behavior. This result is a useful converse test of classical studies that report no increased wheel-running in mice selected for increased open-field activity. However, mice from selected lines turned less in their travel paths than did control-line mice, and females from selected lines had slower travel times (longer latencies) to reach the wall. We discuss these results in the context of the historical open-field test and newly defined measures of open-field activity.
Conditional Random Fields for Morphological Analysis of Wireless ECG Signals
Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin
2015-01-01
Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321
Random fields, topology, and the Imry-Ma argument.
Proctor, Thomas C; Garanin, Dmitry A; Chudnovsky, Eugene M
2014-03-07
We consider an n-component fixed-length order parameter interacting with a weak random field in d=1, 2, 3 dimensions. Relaxation from the initially ordered state and spin-spin correlation functions are studied on lattices containing hundreds of millions of sites. At n ≤ d the presence of topological defects leads to strong metastability and glassy behavior, with the final state depending on the initial condition. At n=d+1, when topological structures are nonsingular, the system possesses a weak metastability. At n>d+1, when topological objects are absent, the final, lowest-energy state is independent of the initial condition. It is characterized by the exponential decay of correlations that agrees quantitatively with the theory based upon the Imry-Ma argument.
Cover estimation and payload location using Markov random fields
Quach, Tu-Thach
2014-02-01
Payload location is an approach to find the message bits hidden in steganographic images, but not necessarily their logical order. Its success relies primarily on the accuracy of the underlying cover estimators and can be improved if more estimators are used. This paper presents an approach based on Markov random field to estimate the cover image given a stego image. It uses pairwise constraints to capture the natural two-dimensional statistics of cover images and forms a basis for more sophisticated models. Experimental results show that it is competitive against current state-of-the-art estimators and can locate payload embedded by simple LSB steganography and group-parity steganography. Furthermore, when combined with existing estimators, payload location accuracy improves significantly.
A Markov random field approach for microstructure synthesis
International Nuclear Information System (INIS)
Kumar, A; Nguyen, L; DeGraef, M; Sundararaghavan, V
2016-01-01
We test the notion that many microstructures have an underlying stationary probability distribution. The stationary probability distribution is ubiquitous: we know that different windows taken from a polycrystalline microstructure are generally ‘statistically similar’. To enable computation of such a probability distribution, microstructures are represented in the form of undirected probabilistic graphs called Markov Random Fields (MRFs). In the model, pixels take up integer or vector states and interact with multiple neighbors over a window. Using this lattice structure, algorithms are developed to sample the conditional probability density for the state of each pixel given the known states of its neighboring pixels. The sampling is performed using reference experimental images. 2D microstructures are artificially synthesized using the sampled probabilities. Statistical features such as grain size distribution and autocorrelation functions closely match with those of the experimental images. The mechanical properties of the synthesized microstructures were computed using the finite element method and were also found to match the experimental values. (paper)
5th Seminar on Stochastic Processes, Random Fields and Applications
Russo, Francesco; Dozzi, Marco
2008-01-01
This volume contains twenty-eight refereed research or review papers presented at the 5th Seminar on Stochastic Processes, Random Fields and Applications, which took place at the Centro Stefano Franscini (Monte Verità) in Ascona, Switzerland, from May 30 to June 3, 2005. The seminar focused mainly on stochastic partial differential equations, random dynamical systems, infinite-dimensional analysis, approximation problems, and financial engineering. The book will be a valuable resource for researchers in stochastic analysis and professionals interested in stochastic methods in finance. Contributors: Y. Asai, J.-P. Aubin, C. Becker, M. Benaïm, H. Bessaih, S. Biagini, S. Bonaccorsi, N. Bouleau, N. Champagnat, G. Da Prato, R. Ferrière, F. Flandoli, P. Guasoni, V.B. Hallulli, D. Khoshnevisan, T. Komorowski, R. Léandre, P. Lescot, H. Lisei, J.A. López-Mimbela, V. Mandrekar, S. Méléard, A. Millet, H. Nagai, A.D. Neate, V. Orlovius, M. Pratelli, N. Privault, O. Raimond, M. Röckner, B. Rüdiger, W.J. Runggaldi...
Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields
Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.
1994-01-01
To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.
Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields
Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.
1994-07-01
To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.
Discriminative Random Field Models for Subsurface Contamination Uncertainty Quantification
Arshadi, M.; Abriola, L. M.; Miller, E. L.; De Paolis Kaluza, C.
2017-12-01
Application of flow and transport simulators for prediction of the release, entrapment, and persistence of dense non-aqueous phase liquids (DNAPLs) and associated contaminant plumes is a computationally intensive process that requires specification of a large number of material properties and hydrologic/chemical parameters. Given its computational burden, this direct simulation approach is particularly ill-suited for quantifying both the expected performance and uncertainty associated with candidate remediation strategies under real field conditions. Prediction uncertainties primarily arise from limited information about contaminant mass distributions, as well as the spatial distribution of subsurface hydrologic properties. Application of direct simulation to quantify uncertainty would, thus, typically require simulating multiphase flow and transport for a large number of permeability and release scenarios to collect statistics associated with remedial effectiveness, a computationally prohibitive process. The primary objective of this work is to develop and demonstrate a methodology that employs measured field data to produce equi-probable stochastic representations of a subsurface source zone that capture the spatial distribution and uncertainty associated with key features that control remediation performance (i.e., permeability and contamination mass). Here we employ probabilistic models known as discriminative random fields (DRFs) to synthesize stochastic realizations of initial mass distributions consistent with known, and typically limited, site characterization data. Using a limited number of full scale simulations as training data, a statistical model is developed for predicting the distribution of contaminant mass (e.g., DNAPL saturation and aqueous concentration) across a heterogeneous domain. Monte-Carlo sampling methods are then employed, in conjunction with the trained statistical model, to generate realizations conditioned on measured borehole data
Polynomial selection in number field sieve for integer factorization
Directory of Open Access Journals (Sweden)
Gireesh Pandey
2016-09-01
Full Text Available The general number field sieve (GNFS is the fastest algorithm for factoring large composite integers which is made up by two prime numbers. Polynomial selection is an important step of GNFS. The asymptotic runtime depends on choice of good polynomial pairs. In this paper, we present polynomial selection algorithm that will be modelled with size and root properties. The correlations between polynomial coefficient and number of relations have been explored with experimental findings.
Blind Measurement Selection: A Random Matrix Theory Approach
Elkhalil, Khalil; Kammoun, Abla; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also
Natural selection on immune defense: A field experiment.
Langeloh, Laura; Behrmann-Godel, Jasminca; Seppälä, Otto
2017-02-01
Predicting the evolution of phenotypic traits requires an understanding of natural selection on them. Despite its indispensability in the fight against parasites, selection on host immune defense has remained understudied. Theory predicts immune traits to be under stabilizing selection due to associated trade-offs with other fitness-related traits. Empirical studies, however, report mainly positive directional selection. This discrepancy could be caused by low phenotypic variation in the examined individuals and/or variation in host resource level that confounds trade-offs in empirical studies. In a field experiment where we maintained Lymnaea stagnalis snails individually in cages in a lake, we investigated phenotypic selection on two immune defense traits, phenoloxidase (PO)-like activity and antibacterial activity, in hemolymph. We used a diverse laboratory population and manipulated snail resource level by limiting their food supply. For six weeks, we followed immune activity, growth, and two fitness components, survival and fecundity of snails. We found that PO-like activity and growth were under stabilizing selection, while antibacterial activity was under positive directional selection. Selection on immune traits was mainly driven by variation in survival. The form of selection on immune defense apparently depends on the particular trait, possibly due to its importance for countering the present parasite community. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.
A Markov Random Field Groupwise Registration Framework for Face Recognition.
Liao, Shu; Shen, Dinggang; Chung, Albert C S
2014-04-01
In this paper, we propose a new framework for tackling face recognition problem. The face recognition problem is formulated as groupwise deformable image registration and feature matching problem. The main contributions of the proposed method lie in the following aspects: (1) Each pixel in a facial image is represented by an anatomical signature obtained from its corresponding most salient scale local region determined by the survival exponential entropy (SEE) information theoretic measure. (2) Based on the anatomical signature calculated from each pixel, a novel Markov random field based groupwise registration framework is proposed to formulate the face recognition problem as a feature guided deformable image registration problem. The similarity between different facial images are measured on the nonlinear Riemannian manifold based on the deformable transformations. (3) The proposed method does not suffer from the generalizability problem which exists commonly in learning based algorithms. The proposed method has been extensively evaluated on four publicly available databases: FERET, CAS-PEAL-R1, FRGC ver 2.0, and the LFW. It is also compared with several state-of-the-art face recognition approaches, and experimental results demonstrate that the proposed method consistently achieves the highest recognition rates among all the methods under comparison.
Branched flow and caustics in random media with magnetic fields
Metzger, Jakob; Fleischmann, Ragnar; Geisel, Theo
2009-03-01
Classical particles as well as quantum mechanical waves exhibit complex behaviour when propagating through random media. One of the dominant features of the dynamics in correlated, weak disorder potentials is the branching of the flow. This can be observed in several physical systems, most notably in the electron flow in two-dimensional electron gases [1], and has also been used to describe the formation of freak waves [2]. We present advances in the theoretical understanding and numerical simulation of classical branched flows in magnetic fields. In particular, we study branching statistics and branch density profiles. Our results have direct consequences for experiments which measure transport properties in electronic systems [3].[1] e.g. M. A. Topinka et al., Nature 410, 183 (2001), M. P. Jura et al., Nature Physics 3, 841 (2007)[2] E. J. Heller, L. Kaplan and A. Dahlen, J. Geophys. Res., 113, C09023 (2008)[3] J. J. Metzger, R. Fleischmann and T. Geisel, in preparation
Infinite hidden conditional random fields for human behavior analysis.
Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja
2013-01-01
Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.
IMAGE SEGMENTATION BASED ON MARKOV RANDOM FIELD AND WATERSHED TECHNIQUES
Institute of Scientific and Technical Information of China (English)
纳瑟; 刘重庆
2002-01-01
This paper presented a method that incorporates Markov Random Field(MRF), watershed segmentation and merging techniques for performing image segmentation and edge detection tasks. MRF is used to obtain an initial estimate of x regions in the image under process where in MRF model, gray level x, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The process needs an initial segmented result. An initial segmentation is got based on K-means clustering technique and the minimum distance, then the region process in modeled by MRF to obtain an image contains different intensity regions. Starting from this we calculate the gradient values of that image and then employ a watershed technique. When using MRF method it obtains an image that has different intensity regions and has all the edge and region information, then it improves the segmentation result by superimpose closed and an accurate boundary of each region using watershed algorithm. After all pixels of the segmented regions have been processed, a map of primitive region with edges is generated. Finally, a merge process based on averaged mean values is employed. The final segmentation and edge detection result is one closed boundary per actual region in the image.
Markov random field based automatic image alignment for electron tomography.
Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark
2008-03-01
We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.
Conditional Random Fields for Pattern Recognition Applied to Structured Data
Directory of Open Access Journals (Sweden)
Tom Burr
2015-07-01
Full Text Available Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building or “natural” (such as a tree. Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs model structured data using the conditional distribution P(Y|X = x, without specifying a model for P(X, and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches in the output domain. Second, we identify research topics and present numerical examples.
GAUSSIAN RANDOM FIELD: PHYSICAL ORIGIN OF SERSIC PROFILES
International Nuclear Information System (INIS)
Cen, Renyue
2014-01-01
While the Sersic profile family provides adequate fits for the surface brightness profiles of observed galaxies, its physical origin is unknown. We show that if the cosmological density field is seeded by random Gaussian fluctuations, as in the standard cold dark matter model, galaxies with steep central profiles have simultaneously extended envelopes of shallow profiles in the outskirts, whereas galaxies with shallow central profiles are accompanied by steep density profiles in the outskirts. These properties are in accord with those of the Sersic profile family. Moreover, galaxies with steep central profiles form their central regions in smaller denser subunits that possibly merge subsequently, which naturally leads to the formation of bulges. In contrast, galaxies with shallow central profiles form their central regions in a coherent fashion without significant substructure, a necessary condition for disk galaxy formation. Thus, the scenario is self-consistent with respect to the correlation between observed galaxy morphology and the Sersic index. We further predict that clusters of galaxies should display a similar trend, which should be verifiable observationally
Rigorously testing multialternative decision field theory against random utility models.
Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg
2014-06-01
Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Field site selection: getting it right first time around
Malcolm, Colin A.; El Sayed, Badria; Babiker, Ahmed; Girod, Romain; Fontenille, Didier; Knols, Bart G. J.; Nugud, Abdel Hameed; Benedict, Mark Q.
2009-01-01
The selection of suitable field sites for integrated control of Anopheles mosquitoes using the sterile insect technique (SIT) requires consideration of the full gamut of factors facing most proposed control strategies, but four criteria identify an ideal site: 1) a single malaria vector, 2) an
Which Is More Consequential: Fields of Study or Institutional Selectivity?
Ma, Yingyi; Savas, Gokhan
2014-01-01
The persisting gender pay gap favoring men among college graduates is a puzzle given women's remarkable success in postsecondary education. This article examines income disparities among recent college graduates by intersecting gender and social class and evaluating the relative importance of fields of study and institutional selectivity.…
On polynomial selection for the general number field sieve
Kleinjung, Thorsten
2006-12-01
The general number field sieve (GNFS) is the asymptotically fastest algorithm for factoring large integers. Its runtime depends on a good choice of a polynomial pair. In this article we present an improvement of the polynomial selection method of Montgomery and Murphy which has been used in recent GNFS records.
Role Appropriateness of Educational Fields: Bias in Selection.
Smith, Elizabeth P.; And Others
Bias towards women exists in the selection of applicants to professional and other positions. This research investigated the effects of two rater variables--sex and attitude toward women--and three applicant variables--sex, field (engineering-dietetics), and attributes--(feminine-masculine) upon ratings of competency and personal charm. Analyses…
Strategyproof Peer Selection using Randomization, Partitioning, and Apportionment
Aziz, Haris; Lev, Omer; Mattei, Nicholas; Rosenschein, Jeffrey S.; Walsh, Toby
2016-01-01
Peer review, evaluation, and selection is a fundamental aspect of modern science. Funding bodies the world over employ experts to review and select the best proposals of those submitted for funding. The problem of peer selection, however, is much more general: a professional society may want to give a subset of its members awards based on the opinions of all members; an instructor for a MOOC or online course may want to crowdsource grading; or a marketing company may select ideas from group b...
The mean field theory in EM procedures for blind Markov random field image restoration.
Zhang, J
1993-01-01
A Markov random field (MRF) model-based EM (expectation-maximization) procedure for simultaneously estimating the degradation model and restoring the image is described. The MRF is a coupled one which provides continuity (inside regions of smooth gray tones) and discontinuity (at region boundaries) constraints for the restoration problem which is, in general, ill posed. The computational difficulty associated with the EM procedure for MRFs is resolved by using the mean field theory from statistical mechanics. An orthonormal blur decomposition is used to reduce the chances of undesirable locally optimal estimates. Experimental results on synthetic and real-world images show that this approach provides good blur estimates and restored images. The restored images are comparable to those obtained by a Wiener filter in mean-square error, but are most visually pleasing.
Bearing Fault Classification Based on Conditional Random Field
Directory of Open Access Journals (Sweden)
Guofeng Wang
2013-01-01
Full Text Available Condition monitoring of rolling element bearing is paramount for predicting the lifetime and performing effective maintenance of the mechanical equipment. To overcome the drawbacks of the hidden Markov model (HMM and improve the diagnosis accuracy, conditional random field (CRF model based classifier is proposed. In this model, the feature vectors sequences and the fault categories are linked by an undirected graphical model in which their relationship is represented by a global conditional probability distribution. In comparison with the HMM, the main advantage of the CRF model is that it can depict the temporal dynamic information between the observation sequences and state sequences without assuming the independence of the input feature vectors. Therefore, the interrelationship between the adjacent observation vectors can also be depicted and integrated into the model, which makes the classifier more robust and accurate than the HMM. To evaluate the effectiveness of the proposed method, four kinds of bearing vibration signals which correspond to normal, inner race pit, outer race pit and roller pit respectively are collected from the test rig. And the CRF and HMM models are built respectively to perform fault classification by taking the sub band energy features of wavelet packet decomposition (WPD as the observation sequences. Moreover, K-fold cross validation method is adopted to improve the evaluation accuracy of the classifier. The analysis and comparison under different fold times show that the accuracy rate of classification using the CRF model is higher than the HMM. This method brings some new lights on the accurate classification of the bearing faults.
Variable Selection in Time Series Forecasting Using Random Forests
Directory of Open Access Journals (Sweden)
Hristos Tyralis
2017-10-01
Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.
Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields
Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.
1992-12-01
During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards
Lauterbach, S.; Fina, M.; Wagner, W.
2018-04-01
Since structural engineering requires highly developed and optimized structures, the thickness dependency is one of the most controversially debated topics. This paper deals with stability analysis of lightweight thin structures combined with arbitrary geometrical imperfections. Generally known design guidelines only consider imperfections for simple shapes and loading, whereas for complex structures the lower-bound design philosophy still holds. Herein, uncertainties are considered with an empirical knockdown factor representing a lower bound of existing measurements. To fully understand and predict expected bearable loads, numerical investigations are essential, including geometrical imperfections. These are implemented into a stand-alone program code with a stochastic approach to compute random fields as geometric imperfections that are applied to nodes of the finite element mesh of selected structural examples. The stochastic approach uses the Karhunen-Loève expansion for the random field discretization. For this approach, the so-called correlation length l_c controls the random field in a powerful way. This parameter has a major influence on the buckling shape, and also on the stability load. First, the impact of the correlation length is studied for simple structures. Second, since most structures for engineering devices are more complex and combined structures, these are intensively discussed with the focus on constrained random fields for e.g. flange-web-intersections. Specific constraints for those random fields are pointed out with regard to the finite element model. Further, geometrical imperfections vanish where the structure is supported.
Wampler, Peter J; Rediske, Richard R; Molla, Azizur R
2013-01-18
A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only rarely was local knowledge required to identify and locate households. This
Directory of Open Access Journals (Sweden)
Wampler Peter J
2013-01-01
Full Text Available Abstract Background A remote sensing technique was developed which combines a Geographic Information System (GIS; Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. Methods The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. Results A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. Conclusions The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only
An application of random field theory to analysis of electron trapping sites in disordered media
International Nuclear Information System (INIS)
Hilczer, M.; Bartczak, W.M.
1993-01-01
The potential energy surface in a disordered medium is considered a random field and described using the concepts of the mathematical theory of random fields. The preexisting traps for excess electrons are identified with certain regions of excursion (extreme regions) of the potential field. The theory provides an analytical method of statistical analysis of these regions. Parameters of the cavity-averaged potential field, which are provided by computer simulation of a given medium, serve as input data for the analysis. The statistics of preexisting traps are obtained for liquid methanol as a numerical example of the random field method. 26 refs., 6 figs
Random-walk simulation of selected aspects of dissipative collisions
International Nuclear Information System (INIS)
Toeke, J.; Gobbi, A.; Matulewicz, T.
1984-11-01
Internuclear thermal equilibrium effects and shell structure effects in dissipative collisions are studied numerically within the framework of the model of stochastic exchanges by applying the random-walk technique. Effective blocking of the drift through the mass flux induced by the temperature difference, while leaving the variances of the mass distributions unaltered is found possible, provided an internuclear potential barrier is present. Presence of the shell structure is found to lead to characteristic correlations between the consecutive exchanges. Experimental evidence for the predicted effects is discussed. (orig.)
Exact simulation of Brown-Resnick random fields at a finite number of locations
DEFF Research Database (Denmark)
Dieker, Ton; Mikosch, Thomas Valentin
2015-01-01
We propose an exact simulation method for Brown-Resnick random fields, building on new representations for these stationary max-stable fields. The main idea is to apply suitable changes of measure.......We propose an exact simulation method for Brown-Resnick random fields, building on new representations for these stationary max-stable fields. The main idea is to apply suitable changes of measure....
Application of random effects to the study of resource selection by animals.
Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L
2006-07-01
1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions
Reduction of the Random Variables of the Turbulent Wind Field
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.
2012-01-01
.e. Importance Sampling (IS) or Subset Simulation (SS), will be deteriorated on problems with many random variables. The problem with PDEM is that a multidimensional integral has to be carried out over the space defined by the random variables of the system. The numerical procedure requires discretization......Applicability of the Probability Density Evolution Method (PDEM) for realizing evolution of the probability density for the wind turbines has rather strict bounds on the basic number of the random variables involved in the model. The efficiency of most of the Advanced Monte Carlo (AMC) methods, i...... of the integral domain; this becomes increasingly difficult as the dimensions of the integral domain increase. On the other hand efficiency of the AMC methods is closely dependent on the design points of the problem. Presence of many random variables may increase the number of the design points, hence affects...
Electron traps in polar liquids. An application of the formalism of the random field theory
International Nuclear Information System (INIS)
Hilczer, M.; Bartczak, W.M.
1992-01-01
The potential energy surface in a disordered medium is described, using the concepts of the mathematical theory of random fields. The statistics of trapping sites (the regions of an excursion of the random field) is obtained for liquid methanol as a numerical example of the theory. (author). 15 refs, 4 figs
A test for stationarity of spatio-temporal random fields on planar and spherical domains
Jun, Mikyoung; Genton, Marc G.
2012-01-01
A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method
Specific heat of the Ising linear chain in a Random field
International Nuclear Information System (INIS)
Silva, P.R.; Sa Barreto, F.C. de
1984-01-01
Starting from correlation identities for the Ising model the effect of a random field on the one dimension version of the model is studied. Explicit results for the magnetization, the two-particle correlation function and the specific heat are obtained for an uncorrelated distribution of the random fields. (Author) [pt
Interference-aware random beam selection schemes for spectrum sharing systems
Abdallah, Mohamed; Qaraqe, Khalid; Alouini, Mohamed-Slim
2012-01-01
users. In this work, we develop interference-aware random beam selection schemes that provide enhanced performance for the secondary network under the condition that the interference observed by the receivers of the primary network is below a
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...
Global mean-field phase diagram of the spin-1 Ising ferromagnet in a random crystal field
Borelli, M. E. S.; Carneiro, C. E. I.
1996-02-01
We study the phase diagram of the mean-field spin-1 Ising ferromagnet in a uniform magnetic field H and a random crystal field Δi, with probability distribution P( Δi) = pδ( Δi - Δ) + (1 - p) δ( Δi). We analyse the effects of randomness on the first-order surfaces of the Δ- T- H phase diagram for different values of the concentration p and show how these surfaces are affected by the dilution of the crystal field.
Diffusion in the kicked quantum rotator by random corrections to a linear and sine field
International Nuclear Information System (INIS)
Hilke, M.; Flores, J.C.
1992-01-01
We discuss the diffusion in momentum space, of the kicked quantum rotator, by introducing random corrections to a linear and sine external field. For the linear field we obtain a linear diffusion behavior identical to the case with zero average in the external field. But for the sine field, accelerator modes with quadratic diffusion are found for particular values of the kicking period. (orig.)
Kleinman, Alan
2016-12-20
The random mutation and natural selection phenomenon act in a mathematically predictable behavior, which when understood leads to approaches to reduce and prevent the failure of the use of these selection pressures when treating infections and cancers. The underlying principle to impair the random mutation and natural selection phenomenon is to use combination therapy, which forces the population to evolve to multiple selection pressures simultaneously that invoke the multiplication rule of probabilities simultaneously as well. Recently, it has been seen that combination therapy for the treatment of malaria has failed to prevent the emergence of drug-resistant variants. Using this empirical example and the principles of probability theory, the derivation of the equations describing this treatment failure is carried out. These equations give guidance as to how to use combination therapy for the treatment of cancers and infectious diseases and prevent the emergence of drug resistance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Acceptance sampling using judgmental and randomly selected samples
Energy Technology Data Exchange (ETDEWEB)
Sego, Landon H.; Shulman, Stanley A.; Anderson, Kevin K.; Wilson, John E.; Pulsipher, Brent A.; Sieber, W. Karl
2010-09-01
We present a Bayesian model for acceptance sampling where the population consists of two groups, each with different levels of risk of containing unacceptable items. Expert opinion, or judgment, may be required to distinguish between the high and low-risk groups. Hence, high-risk items are likely to be identifed (and sampled) using expert judgment, while the remaining low-risk items are sampled randomly. We focus on the situation where all observed samples must be acceptable. Consequently, the objective of the statistical inference is to quantify the probability that a large percentage of the unsampled items in the population are also acceptable. We demonstrate that traditional (frequentist) acceptance sampling and simpler Bayesian formulations of the problem are essentially special cases of the proposed model. We explore the properties of the model in detail, and discuss the conditions necessary to ensure that required samples sizes are non-decreasing function of the population size. The method is applicable to a variety of acceptance sampling problems, and, in particular, to environmental sampling where the objective is to demonstrate the safety of reoccupying a remediated facility that has been contaminated with a lethal agent.
Metastability of Reversible Random Walks in Potential Fields
Landim, C.; Misturini, R.; Tsunoda, K.
2015-09-01
Let be an open and bounded subset of , and let be a twice continuously differentiable function. Denote by the discretization of , , and denote by the continuous-time, nearest-neighbor, random walk on which jumps from to at rate . We examine in this article the metastable behavior of among the wells of the potential F.
40 CFR 761.308 - Sample selection by random number generation on any two-dimensional square grid.
2010-07-01
... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sample selection by random number... Â§ 761.79(b)(3) § 761.308 Sample selection by random number generation on any two-dimensional square... area created in accordance with paragraph (a) of this section, select two random numbers: one each for...
Radiography by selective detection of scatter field velocity components
Jacobs, Alan M. (Inventor); Dugan, Edward T. (Inventor); Shedlock, Daniel (Inventor)
2007-01-01
A reconfigurable collimated radiation detector, system and related method includes at least one collimated radiation detector. The detector has an adjustable collimator assembly including at least one feature, such as a fin, optically coupled thereto. Adjustments to the adjustable collimator selects particular directions of travel of scattered radiation emitted from an irradiated object which reach the detector. The collimated detector is preferably a collimated detector array, where the collimators are independently adjustable. The independent motion capability provides the capability to focus the image by selection of the desired scatter field components. When an array of reconfigurable collimated detectors is provided, separate image data can be obtained from each of the detectors and the respective images cross-correlated and combined to form an enhanced image.
Phase diagram and tricritical behavior of an metamagnet in uniform and random fields
International Nuclear Information System (INIS)
Liang Yaqiu; Wei Guozhu; Xu Xiaojuan; Song Guoli
2010-01-01
A two-sublattice Ising metamagnet in both uniform and random fields is studied within the mean-field approach based on Bogoliubov's inequality for the Gibbs free energy. We show that the qualitative features of the phase diagrams are dependent on the parameters of the model and the uniform field values. The tricritical point and reentrant phenomenon can be observed on the phase diagram. The reentrance is due to the competition between uniform and random interactions.
Critical behavior in a random field classical Heisenberg model for amorphous systems
International Nuclear Information System (INIS)
Albuquerque, Douglas F. de; Alves, Sandro Roberto L.; Arruda, Alberto S. de
2005-01-01
By using the differential operator technique and the effective field theory scheme, the critical behavior of amorphous classical Heisenberg ferromagnet of spin-1/2 in a random field is studied. The phase diagram in the T-H and T-α planes on a simple cubic lattice for a cluster with two spins is obtained. Tricritical points, reentrant phenomena and influence of the random field and amorphization on the transition temperature are discussed
Prediction of Geological Subsurfaces Based on Gaussian Random Field Models
Energy Technology Data Exchange (ETDEWEB)
Abrahamsen, Petter
1997-12-31
During the sixties, random functions became practical tools for predicting ore reserves with associated precision measures in the mining industry. This was the start of the geostatistical methods called kriging. These methods are used, for example, in petroleum exploration. This thesis reviews the possibilities for using Gaussian random functions in modelling of geological subsurfaces. It develops methods for including many sources of information and observations for precise prediction of the depth of geological subsurfaces. The simple properties of Gaussian distributions make it possible to calculate optimal predictors in the mean square sense. This is done in a discussion of kriging predictors. These predictors are then extended to deal with several subsurfaces simultaneously. It is shown how additional velocity observations can be used to improve predictions. The use of gradient data and even higher order derivatives are also considered and gradient data are used in an example. 130 refs., 44 figs., 12 tabs.
Random errors in the magnetic field coefficients of superconducting magnets
International Nuclear Information System (INIS)
Herrera, J.; Hogue, R.; Prodell, A.; Wanderer, P.; Willen, E.
1985-01-01
Random errors in the multipole magnetic coefficients of superconducting magnet have been of continuing interest in accelerator research. The Superconducting Super Collider (SSC) with its small magnetic aperture only emphasizes this aspect of magnet design, construction, and measurement. With this in mind, we present a magnet model which mirrors the structure of a typical superconducting magnet. By taking advantage of the basic symmetries of a dipole magnet, we use this model to fit the measured multipole rms widths. The fit parameters allow us then to predict the values of the rms multipole errors expected for the SSC dipole reference design D, SSC-C5. With the aid of first-order perturbation theory, we then give an estimate of the effect of these random errors on the emittance growth of a proton beam stored in an SSC. 10 refs., 6 figs., 2 tabs
Supplementary Material for: Tukey g-and-h Random Fields
Xu, Ganggang; Genton, Marc G.
2016-01-01
We propose a new class of transGaussian random fields named Tukey g-and-h (TGH) random fields to model non-Gaussian spatial data. The proposed TGH random fields have extremely flexible marginal distributions, possibly skewed and/or heavy-tailed, and, therefore, have a wide range of applications. The special formulation of the TGH random field enables an automatic search for the most suitable transformation for the dataset of interest while estimating model parameters. Asymptotic properties of the maximum likelihood estimator and the probabilistic properties of the TGH random fields are investigated. An efficient estimation procedure, based on maximum approximated likelihood, is proposed and an extreme spatial outlier detection algorithm is formulated. Kriging and probabilistic prediction with TGH random fields are developed along with prediction confidence intervals. The predictive performance of TGH random fields is demonstrated through extensive simulation studies and an application to a dataset of total precipitation in the south east of the United States. Supplementary materials for this article are available online.
Charged Particle Diffusion in Isotropic Random Magnetic Fields
Energy Technology Data Exchange (ETDEWEB)
Subedi, P.; Matthaeus, W. H.; Chuychai, P.; Parashar, T. N.; Chhiber, R. [Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716 (United States); Sonsrettee, W. [Faculty of Engineering and Technology, Panyapiwat Institute of Management, Nonthaburi 11120 (Thailand); Blasi, P. [INAF/Osservatorio Astrofisico di Arcetri, Largo E. Fermi, 5—I-50125 Firenze (Italy); Ruffolo, D. [Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400 (Thailand); Montgomery, D. [Department of Physics and Astronomy, Dartmouth College, Hanover, NH 03755 (United States); Dmitruk, P. [Departamento de Física Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires Ciudad Universitaria, 1428 Buenos Aires (Argentina); Wan, M. [Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055 (China)
2017-03-10
The investigation of the diffusive transport of charged particles in a turbulent magnetic field remains a subject of considerable interest. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here we consider the diffusion of charged particles in fully three-dimensional isotropic turbulent magnetic fields with no mean field, which may be pertinent to many astrophysical situations. We identify different ranges of particle energy depending upon the ratio of Larmor radius to the characteristic outer length scale of turbulence. Two different theoretical models are proposed to calculate the diffusion coefficient, each applicable to a distinct range of particle energies. The theoretical results are compared to those from computer simulations, showing good agreement.
Analysis of tree stand horizontal structure using random point field methods
Directory of Open Access Journals (Sweden)
O. P. Sekretenko
2015-06-01
Full Text Available This paper uses the model approach to analyze the horizontal structure of forest stands. The main types of models of random point fields and statistical procedures that can be used to analyze spatial patterns of trees of uneven and even-aged stands are described. We show how modern methods of spatial statistics can be used to address one of the objectives of forestry – to clarify the laws of natural thinning of forest stand and the corresponding changes in its spatial structure over time. Studying natural forest thinning, we describe the consecutive stages of modeling: selection of the appropriate parametric model, parameter estimation and generation of point patterns in accordance with the selected model, the selection of statistical functions to describe the horizontal structure of forest stands and testing of statistical hypotheses. We show the possibilities of a specialized software package, spatstat, which is designed to meet the challenges of spatial statistics and provides software support for modern methods of analysis of spatial data. We show that a model of stand thinning that does not consider inter-tree interaction can project the size distribution of the trees properly, but the spatial pattern of the modeled stand is not quite consistent with observed data. Using data of three even-aged pine forest stands of 25, 55, and 90-years old, we demonstrate that the spatial point process models are useful for combining measurements in the forest stands of different ages to study the forest stand natural thinning.
Cross-talk free selective reconstruction of individual objects from multiplexed optical field data
Zea, Alejandro Velez; Barrera, John Fredy; Torroba, Roberto
2018-01-01
In this paper we present a data multiplexing method for simultaneous storage in a single package composed by several optical fields of tridimensional (3D) objects, and their individual cross-talk free retrieval. Optical field data are extracted from off axis Fourier holograms, and then sampled by multiplying them with random binary masks. The resulting sampled optical fields can be used to reconstruct the original objects. Sampling causes a loss of quality that can be controlled by the number of white pixels in the binary masks and by applying a padding procedure on the optical field data. This process can be performed using a different binary mask for each optical field, and then added to form a multiplexed package. With the adequate choice of sampling and padding, we can achieve a volume reduction in the multiplexed package over the addition of all individual optical fields. Moreover, the package can be multiplied by a binary mask to select a specific optical field, and after the reconstruction procedure, the corresponding 3D object is recovered without any cross-talk. We demonstrate the effectiveness of our proposal for data compression with a comparison with discrete cosine transform filtering. Experimental results confirm the validity of our proposal.
Selected Tools and Methods from Quality Management Field
Directory of Open Access Journals (Sweden)
Kateřina BRODECKÁ
2009-06-01
Full Text Available Following paper describes selected tools and methods from Quality management field and their practical applications on defined examples. Solved examples were elaborated in the form of electronic support. This in detail elaborated electronic support provides students opportunity to thoroughly practice specific issues, help them to prepare for exams and consequently will lead to education improvement. Especially students of combined study form will appreciate this support. The paper specifies project objectives, subjects that will be covered by mentioned support, target groups, structure and the way of elaboration of electronic exercise book in view. The emphasis is not only on manual solution of selected examples that may help students to understand the principles and relationships, but also on solving and results interpreting of selected examples using software support. Statistic software Statgraphics Plus v 5.0 is used while working support, because it is free to use for all students of the faculty. Exemplary example from the subject Basic Statistical Methods of Quality Management is also part of this paper.
Mice selectively bred for open-field thigmotaxis: life span and stability of the selection trait.
Leppänen, Pia K; Ewalds-Kvist, S Béatrice M; Selander, Ritva-Kajsa
2005-04-01
In 2 experiments, the authors examined 69 mice selectively bred for high or low levels of open-field (OF) thigmotactic behavior (high open-field thigmotaxis [HOFT] and low open-field thigmotaxis [LOFT], respectively). They found that the strains differed in defecation during the 60-min exposure to the OF. Furthermore, the strains differed with regard to their life spans: The more thigmotactic HOFT mice lived longer than the LOFT mice. The strains were not differentiated by food intake or excretion. The strain difference in thigmotaxis was not age dependent, and it persisted in the home-cage condition as well. Neither the location (center or wall) of the starting point nor the shape (circular or square) of the OF arena affected the difference in wall-seeking behavior between the two strains. The authors concluded that the difference in thigmotaxis (or emotionality) between the HOFT and LOFT mice is a stable and robust feature of these animals.
Generalized Whittle-Matern random field as a model of correlated fluctuations
International Nuclear Information System (INIS)
Lim, S C; Teo, L P
2009-01-01
This paper considers a generalization of the Gaussian random field with covariance function of the Whittle-Matern family. Such a random field can be obtained as the solution to the fractional stochastic differential equation with two fractional orders. Asymptotic properties of the covariance functions belonging to this generalized Whittle-Matern family are studied, which are used to deduce the sample path properties of the random field. The Whittle-Matern field has been widely used in modeling geostatistical data such as sea beam data, wind speed, field temperature and soil data. In this paper we show that the generalized Whittle-Matern field provides a more flexible model for wind speed data
Külske, C
2003-01-01
We derive useful general concentration inequalities for functions of Gibbs fields in the uniqueness regime. We also consider expectations of random Gibbs measures that depend on an additional disorder field, and prove concentration w.r.t the disorder field. Both fields are assumed to be in the uniqueness regime, allowing in particular for non-independent disorder field. The modification of the bounds compared to the case of an independent field can be expressed in terms of constants that resemble the Dobrushin contraction coefficient, and are explicitly computable. On the basis of these inequalities, we obtain bounds on the deviation of a diffraction pattern created by random scatterers located on a general discrete point set in the Euclidean space, restricted to a finite volume. Here we also allow for thermal dislocations of the scatterers around their equilibrium positions. Extending recent results for independent scatterers, we give a universal upper bound on the probability of a deviation of the random sc...
Body fixed frame, rigid gauge rotations and large N random fields in QCD
International Nuclear Information System (INIS)
Levit, S.
1995-01-01
The ''body fixed frame'' with respect to local gauge transformations is introduced. Rigid gauge ''rotations'' in QCD and their Schroedinger equation are studied for static and dynamic quarks. Possible choices of the rigid gauge field configuration corresponding to a non-vanishing static colormagnetic field in the ''body fixed'' frame are discussed. A gauge invariant variational equation is derived in this frame. For large number N of colors the rigid gauge field configuration is regarded as random with maximally random probability distribution under constraints on macroscopic-like quantities. For the uniform magnetic field the joint probability distribution of the field components is determined by maximizing the appropriate entropy under the area law constraint for the Wilson loop. In the quark sector the gauge invariance requires the rigid gauge field configuration to appear not only as a background but also as inducing an instantaneous quark-quark interaction. Both are random in the large N limit. (orig.)
On Closely Coupled Dipoles in a Random Field
DEFF Research Database (Denmark)
Andersen, Jørgen Bach; Vincent, L.
2006-01-01
Reception of partially correlated fields by two closely coupled electrical dipoles is discussed as a function of load impedances and open-circuit correlations. Two local maxima of the power may be achieved for two different load impedances, but in those cases the output correlations are high...
Cross-covariance functions for multivariate random fields based on latent dimensions
Apanasovich, T. V.; Genton, M. G.
2010-01-01
The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable
Modulation of electromagnetic fields by a depolarizer of random polarizer array
DEFF Research Database (Denmark)
Ma, Ning; Hanson, Steen Grüner; Wang, Wei
2016-01-01
The statistical properties of the electric fields with random changes of the polarization state in space generated by a depolarizer are investigated on the basis of the coherence matrix. The depolarizer is a polarizer array composed of a multitude of contiguous square cells of polarizers with ran......The statistical properties of the electric fields with random changes of the polarization state in space generated by a depolarizer are investigated on the basis of the coherence matrix. The depolarizer is a polarizer array composed of a multitude of contiguous square cells of polarizers...... with randomly distributed polarization angles, where the incident fields experience a random polarization modulation after passing through the depolarizer. The propagation of the modulated electric fields through any quadratic optical system is examined within the framework of the complex ABCD matrix to show...
Diffusion of charged particles in strong large-scale random and regular magnetic fields
International Nuclear Information System (INIS)
Mel'nikov, Yu.P.
2000-01-01
The nonlinear collision integral for the Green's function averaged over a random magnetic field is transformed using an iteration procedure taking account of the strong random scattering of particles on the correlation length of the random magnetic field. Under this transformation the regular magnetic field is assumed to be uniform at distances of the order of the correlation length. The single-particle Green's functions of the scattered particles in the presence of a regular magnetic field are investigated. The transport coefficients are calculated taking account of the broadening of the cyclotron and Cherenkov resonances as a result of strong random scattering. The mean-free path lengths parallel and perpendicular to the regular magnetic field are found for a power-law spectrum of the random field. The analytical results obtained are compared with the experimental data on the transport ranges of solar and galactic cosmic rays in the interplanetary magnetic field. As a result, the conditions for the propagation of cosmic rays in the interplanetary space and a more accurate idea of the structure of the interplanetary magnetic field are determined
Restoration of dimensional reduction in the random-field Ising model at five dimensions
Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas
2017-04-01
The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D equality at all studied dimensions.
Resource selection for an interdisciplinary field: a methodology.
Jacoby, Beth E; Murray, Jane; Alterman, Ina; Welbourne, Penny
2002-10-01
The Health Sciences and Human Services Library of the University of Maryland developed and implemented a methodology to evaluate print and digital resources for social work. Although this methodology was devised for the interdisciplinary field of social work, the authors believe it may lend itself to resource selection in other interdisciplinary fields. The methodology was developed in response to the results of two separate surveys conducted in late 1999, which indicated improvement was needed in the library's graduate-level social work collections. Library liaisons evaluated the print collection by identifying forty-five locally relevant Library of Congress subject headings and then using these subjects or synonymous terms to compare the library's titles to collections of peer institutions, publisher catalogs, and Amazon.com. The collection also was compared to social work association bibliographies, ISI Journal Citation Reports, and major social work citation databases. An approval plan for social work books was set up to assist in identifying newly published titles. The library acquired new print and digital social work resources as a result of the evaluation, thus improving both print and digital collections for its social work constituents. Visibility of digital resources was increased by cataloging individual titles in aggregated electronic journal packages and listing each title on the library Web page.
Kinetic Theory of Electronic Transport in Random Magnetic Fields
Lucas, Andrew
2018-03-01
We present the theory of quasiparticle transport in perturbatively small inhomogeneous magnetic fields across the ballistic-to-hydrodynamic crossover. In the hydrodynamic limit, the resistivity ρ generically grows proportionally to the rate of momentum-conserving electron-electron collisions at large enough temperatures T . In particular, the resulting flow of electrons provides a simple scenario where viscous effects suppress conductance below the ballistic value. This new mechanism for ρ ∝T2 resistivity in a Fermi liquid may describe low T transport in single-band SrTiO3 .
Revisiting Boltzmann learning: parameter estimation in Markov random fields
DEFF Research Database (Denmark)
Hansen, Lars Kai; Andersen, Lars Nonboe; Kjems, Ulrik
1996-01-01
This article presents a generalization of the Boltzmann machine that allows us to use the learning rule for a much wider class of maximum likelihood and maximum a posteriori problems, including both supervised and unsupervised learning. Furthermore, the approach allows us to discuss regularization...... and generalization in the context of Boltzmann machines. We provide an illustrative example concerning parameter estimation in an inhomogeneous Markov field. The regularized adaptation produces a parameter set that closely resembles the “teacher” parameters, hence, will produce segmentations that closely reproduce...
International Nuclear Information System (INIS)
Bertschinger, E.
1987-01-01
Path integrals may be used to describe the statistical properties of a random field such as the primordial density perturbation field. In this framework the probability distribution is given for a Gaussian random field subjected to constraints such as the presence of a protovoid or supercluster at a specific location in the initial conditions. An algorithm has been constructed for generating samples of a constrained Gaussian random field on a lattice using Monte Carlo techniques. The method makes possible a systematic study of the density field around peaks or other constrained regions in the biased galaxy formation scenario, and it is effective for generating initial conditions for N-body simulations with rare objects in the computational volume. 21 references
Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi
2017-09-01
It has been a common idea to produce multiscale segmentations to represent the various geographic objects in high-spatial resolution remote sensing (HR) images. However, it remains a great challenge to automatically select the proper segmentation scale(s) just according to the image information. In this study, we propose a novel way of information fusion at object level by combining hierarchical multiscale segmentations with existed thematic information produced by classification or recognition. The tree Markov random field (T-MRF) model is designed for the multiscale combination framework, through which the object type is determined as close as the existed thematic information. At the same time, the object boundary is jointly determined by the thematic labels and the multiscale segments through the minimization of the energy function. The benefits of the proposed T-MRF combination model include: (1) reducing the dependence of segmentation scale selection when utilizing multiscale segmentations; (2) exploring the hierarchical context naturally imbedded in the multiscale segmentations. The HR images in both urban and rural areas are used in the experiments to show the effectiveness of the proposed combination framework on these two aspects.
Replica field theory for a polymer in random media
International Nuclear Information System (INIS)
Goldschmidt, Yadin Y.
2000-01-01
In this paper we revisit the problem of a (non-self-avoiding) polymer chain in a random medium which was previously investigated by Edwards and Muthukumar (EM) [J. Chem. Phys. 89, 2435 (1988)]. As noticed by Cates and Ball (CB) [J. Phys. (France) 49, 2009 (1988)] there is a discrepancy between the predictions of the replica calculation of EM and the expectation that in an infinite medium the quenched and annealed results should coincide (for a chain that is free to move) and a long polymer should always collapse. CB argued that only in a finite volume one might see a ''localization transition'' (or crossover) from a stretched to a collapsed chain in three spatial dimensions. Here we carry out the replica calculation in the presence of an additional confining harmonic potential that mimics the effect of a finite volume. Using a variational scheme with five variational parameters we derive analytically for d -1/(4-d) ∼(g ln V) -1/(4-d) , where R is the radius of gyration, g is the strength of the disorder, μ is the spring constant associated with the confining potential, and V is the associated effective volume of the system. Thus the EM result is recovered with their constant replaced by ln V as argued by CB. We see that in the strict infinite volume limit the polymer always collapses, but for finite volume a transition from a stretched to a collapsed form might be observed as a function of the strength of the disorder. For d V ' ∼exp(g 2/(2-d) L (4-d)/(2-d) ) the annealed results are recovered and R∼(Lg) 1/(d-2) , where L is the length of the polymer. Hence the polymer also collapses in the large L limit. The one-step replica symmetry breaking solution is crucial for obtaining the above results. (c) 2000 The American Physical Society
First steps towards a state classification in the random-field Ising model
International Nuclear Information System (INIS)
Basso, Vittorio; Magni, Alessandro; Bertotti, Giorgio
2006-01-01
The properties of locally stable states of the random-field Ising model are studied. A map is defined for the dynamics driven by the field starting from a locally stable state. The fixed points of the map are connected with the limit hysteresis loops that appear in the classification of the states
Selection of Infective Arbuscular Mycorrhizal Fungal Isolates for Field Inoculation
Directory of Open Access Journals (Sweden)
Elisa Pellegrino
2010-09-01
Full Text Available Arbuscular mycorrhizal (AM fungi play a key role in host plant growth and health, nutrient and water uptake, plant community diversity and dynamics. AM fungi differ in their symbiotic performance, which is the result of the interaction of two fungal characters, infectivity and efficiency. Infectivity is the ability of a fungal isolate to establish rapidly an extensive mycorrhizal symbiosis and is correlated with pre-symbiotic steps of fungal life cycle, such as spore germination and hyphal growth. Here, different AM fungal isolates were tested, with the aim of selecting infective endophytes for field inoculation. Greenhouse and microcosm experiments were performed in order to assess the ability of 12 AM fungal isolates to produce spores, colonize host roots and to perform initial steps of symbiosis establishment, such as spore germination and hyphal growth. AM fungal spore production and root colonization were significantly different among AM fungal isolates. Spore and sporocarp densities ranged from 0.8 to 7.4 and from 0.6 to 2.0 per gram of soil, respectively, whereas root colonization ranged from 2.9 to 72.2%. Percentage of spore or sporocarp germination ranged from 5.8 to 53.3% and hyphal length from 4.7 to 79.8 mm. The ordination analysis (Redundancy Analysis, RDA showed that environmental factors explained about 60% of the whole variance and their effect on fungal infectivity variables was significant (P = 0.002. The biplot clearly showed that variables which might be used to detect infective AM fungal isolates were hyphal length and root colonization. Such analysis may allow the detection of the best parameters to select efficient AM fungal isolates to be used in agriculture.
Segmentation of RGB-D indoor scenes by stacking random forests and conditional random fields
DEFF Research Database (Denmark)
Thøgersen, Mikkel; Guerrero, Sergio Escalera; Gonzàlez, Jordi
2016-01-01
Depth images have granted new possibilities to computer vision researchers across the field. A prominent task is scene understanding and segmentation on which the present work is concerned. In this paper, we present a procedure combining well known methods in a unified learning framework based on...
Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe
2018-06-01
In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.
International Nuclear Information System (INIS)
Braginsky, V.B.; Kardashev, N.S.; Polnarev, A.G.; Novikov, I.D.
1989-12-01
Propagation of an electromagnetic wave in the field of gravitational waves is considered. Attention is given to the principal difference between the electromagnetic wave propagation in the field of random gravitational waves and the electromagnetic wave propagation in a medium with a randomly-inhomogeneous refraction index. It is shown that in the case of the gravitation wave field the phase shift of an electromagnetic wave does not increase with distance. The capability of space radio interferometry to detect relic gravitational waves as well as gravitational wave bursts of non cosmological origin are analyzed. (author). 64 refs, 2 figs
Non-random mating for selection with restricted rates of inbreeding and overlapping generations
Sonesson, A.K.; Meuwissen, T.H.E.
2002-01-01
Minimum coancestry mating with a maximum of one offspring per mating pair (MC1) is compared with random mating schemes for populations with overlapping generations. Optimum contribution selection is used, whereby $\\\\\\\\Delta F$ is restricted. For schemes with $\\\\\\\\Delta F$ restricted to 0.25% per
Applications of random forest feature selection for fine-scale genetic population assignment.
Sylvester, Emma V A; Bentzen, Paul; Bradbury, Ian R; Clément, Marie; Pearce, Jon; Horne, John; Beiko, Robert G
2018-02-01
Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F ST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon ( Salmo salar ) and a published SNP data set for Alaskan Chinook salmon ( Oncorhynchus tshawytscha ). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than F ST -selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F ST -selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.
40 CFR 761.306 - Sampling 1 meter square surfaces by random selection of halves.
2010-07-01
... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sampling 1 meter square surfaces by...(b)(3) § 761.306 Sampling 1 meter square surfaces by random selection of halves. (a) Divide each 1 meter square portion where it is necessary to collect a surface wipe test sample into two equal (or as...
Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex
Lindsay, Grace W.
2017-01-01
Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (
Directory of Open Access Journals (Sweden)
Tan Nhat Nguyen
2016-01-01
Full Text Available In this paper, we evaluate performances of various user selection protocols under impact of hardware impairments. In the considered protocols, a Base Station (BS selects one of available Users (US to serve, while the remaining USs harvest the energy from the Radio Frequency (RF transmitted by the BS. We assume that all of the US randomly appear around the BS. In the Random Selection Protocol (RAN, the BS randomly selects a US to transmit the data. In the second proposed protocol, named Minimum Distance Protocol (MIND, the US that is nearest to the BS will be chosen. In the Optimal Selection Protocol (OPT, the US providing the highest channel gain between itself and the BS will be served. For performance evaluation, we derive exact and asymptotic closed-form expressions of average Outage Probability (OP over Rayleigh fading channels. We also consider average harvested energy per a US. Finally, Monte-Carlo simulations are then performed to verify the theoretical results.
Simulated Performance Evaluation of a Selective Tracker Through Random Scenario Generation
DEFF Research Database (Denmark)
Hussain, Dil Muhammad Akbar
2006-01-01
performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the proposed selective track splitting algorithm using Kalman filters is investigated through a number of performance parameters which gives the activity profile of the tracking scenario...... The paper presents a simulation study on the performance of a target tracker using selective track splitting filter algorithm through a random scenario implemented on a digital signal processor. In a typical track splitting filter all the observation which fall inside a likelihood ellipse...... are used for update, however, in our proposed selective track splitting filter less number of observations are used for track update. Much of the previous performance work [1] has been done on specific (deterministic) scenarios. One of the reasons for considering the specific scenarios, which were...
TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD
Directory of Open Access Journals (Sweden)
A. Shamsoddini
2017-09-01
Full Text Available Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.
Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method
Shamsoddini, A.; Aboodi, M. R.; Karami, J.
2017-09-01
Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.
Continuous-Time Mean-Variance Portfolio Selection with Random Horizon
International Nuclear Information System (INIS)
Yu, Zhiyong
2013-01-01
This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right
Continuous-Time Mean-Variance Portfolio Selection with Random Horizon
Energy Technology Data Exchange (ETDEWEB)
Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)
2013-12-15
This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.
A test for stationarity of spatio-temporal random fields on planar and spherical domains
Jun, Mikyoung
2012-01-01
A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method can be applied to univariate or to multivariate random fields. Our test is based on the asymptotic normality of certain statistics that are functions of estimators of covariances at certain spatial and temporal lags under weak stationarity. Simulation results for spatial as well as spatio-temporal cases on the two types of spatial domains are reported. We describe the results of testing the stationarity of Pacific wind data, and of testing the axial symmetry of climate model errors for surface temperature using the NOAA GFDL model outputs and the observations from the Climate Research Unit in East Anglia and the Hadley Centre.
Properties of a random bond Ising chain in a magnetic field
International Nuclear Information System (INIS)
Landau, D.P.; Blume, M.
1976-01-01
The Ising chain with random bonds in a magnetic field H = -Σ/sub i/J/sub i/sigma/sub i/sigma/sub i + l/ - hΣ/sub i/sigma/sub i/, where J/sub i/ = +- 1 at random, and Σ/sub i/J/sub i/ = 0, represents a model of a magnetic glass, or of heteropolymer melting. Calculations of the thermodynamic properties of the chain as a function of field strength and temperature have been performed by Monte Carlo techniques. These results are compared with perturbation calculations for small and large values of h/T. The Monte Carlo results show, in agreement with the perturbation calculations, that the field-induced magnetization is generally smaller for the random bond model than for a chain of noninteracting spins. As T → 0 the magnetization approaches the result for noninteracting spins
Random errors in the magnetic field coefficients of superconducting quadrupole magnets
International Nuclear Information System (INIS)
Herrera, J.; Hogue, R.; Prodell, A.; Thompson, P.; Wanderer, P.; Willen, E.
1987-01-01
The random multipole errors of superconducting quadrupoles are studied. For analyzing the multipoles which arise due to random variations in the size and locations of the current blocks, a model is outlined which gives the fractional field coefficients from the current distributions. With this approach, based on the symmetries of the quadrupole magnet, estimates are obtained of the random multipole errors for the arc quadrupoles envisioned for the Relativistic Heavy Ion Collider and for a single-layer quadrupole proposed for the Superconducting Super Collider
A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model
Directory of Open Access Journals (Sweden)
Apisit Eiumnoh
2013-10-01
Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.
Selection of 3013 containers for field surveillance: LA-14310, Revision 1
International Nuclear Information System (INIS)
Peppers, Larry; Kelly, Elizabeth; McClard, James; Friday, Gary; Venetz, Theodore; Stakebake, Jerry
2009-01-01
This document is the fifth in a series of reports that document the binning, statistical sampling, and sample selection of 3013 containers for field surveillance. 1,2,3,39 Revisions to binning assignments documented in this report are primarily a result of new prompt gamma data. This report also documents changes to the random sample specification resulting from these binning changes and identifies and provides the rationale for the engineering judgment sample items for Fiscal Year (FY) 2008 and 2009. This revision also updates the changes to the previous surveillance sample resulting from changes to the order that specific containers undergo surveillance. This report will continue to be reviewed regularly and revised as needed to meet the requirements of the surveillance program.
Ding, Jian; Li, Li
2018-06-01
We initiate the study on chemical distances of percolation clusters for level sets of two-dimensional discrete Gaussian free fields as well as loop clusters generated by two-dimensional random walk loop soups. One of our results states that the chemical distance between two macroscopic annuli away from the boundary for the random walk loop soup at the critical intensity is of dimension 1 with positive probability. Our proof method is based on an interesting combination of a theorem of Makarov, isomorphism theory, and an entropic repulsion estimate for Gaussian free fields in the presence of a hard wall.
Suppression of thermal noise in a non-Markovian random velocity field
International Nuclear Information System (INIS)
Ueda, Masahiko
2016-01-01
We study the diffusion of Brownian particles in a Gaussian random velocity field with short memory. By extending the derivation of an effective Fokker–Planck equation for the Lanvegin equation with weakly colored noise to a random velocity-field problem, we find that the effect of thermal noise on particles is suppressed by the existence of memory. We also find that the renormalization effect for the relative diffusion of two particles is stronger than that for single-particle diffusion. The results are compared with those of molecular dynamics simulations. (paper: classical statistical mechanics, equilibrium and non-equilibrium)
Emergence of multilevel selection in the prisoner's dilemma game on coevolving random networks
International Nuclear Information System (INIS)
Szolnoki, Attila; Perc, Matjaz
2009-01-01
We study the evolution of cooperation in the prisoner's dilemma game, whereby a coevolutionary rule is introduced that molds the random topology of the interaction network in two ways. First, existing links are deleted whenever a player adopts a new strategy or its degree exceeds a threshold value; second, new links are added randomly after a given number of game iterations. These coevolutionary processes correspond to the generic formation of new links and deletion of existing links that, especially in human societies, appear frequently as a consequence of ongoing socialization, change of lifestyle or death. Due to the counteraction of deletions and additions of links the initial heterogeneity of the interaction network is qualitatively preserved, and thus cannot be held responsible for the observed promotion of cooperation. Indeed, the coevolutionary rule evokes the spontaneous emergence of a powerful multilevel selection mechanism, which despite the sustained random topology of the evolving network, maintains cooperation across the whole span of defection temptation values.
SAR Subsets for Selected Field Sites, 2007-2010
National Aeronautics and Space Administration — ABSTRACT: This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks...
SAR Subsets for Selected Field Sites, 2007-2010
National Aeronautics and Space Administration — This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including...
Evaluation of completeness of selected poison control center data fields.
Jaramillo, Jeanie E; Marchbanks, Brenda; Willis, Branch; Forrester, Mathias B
2010-08-01
Poison control center data are used in research and surveillance. Due to the large volume of information, these efforts are dependent on data being recorded in machine readable format. However, poison center records include non-machine readable text fields and machine readable coded fields, some of which are duplicative. Duplicating this data increases the chance of inaccurate/incomplete coding. For surveillance efforts to be effective, coding should be complete and accurate. Investigators identified a convenience sample of 964 records and reviewed the substance code determining if it matched its text field. They also reviewed the coded clinical effects and treatments determining if they matched the notes text field. The substance code matched its text field for 91.4% of the substances. The clinical effects and treatments codes matched their text field for 72.6% and 82.4% of occurrences respectively. This under-reporting of clinical effects and treatments has surveillance and public health implications.
Topology-selective jamming of fully-connected, code-division random-access networks
Polydoros, Andreas; Cheng, Unjeng
1990-01-01
The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.
Directory of Open Access Journals (Sweden)
R Alexander Bentley
Full Text Available The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.
Bentley, R Alexander
2008-08-27
The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.
Study of Landau spectrum for a two-dimensional random magnetic field
International Nuclear Information System (INIS)
Furtlehner, C.
1997-01-01
This thesis deals with the two-dimensional problem of a charged particle coupled to a random magnetic field. Various situations are considered, according to the relative importance of the mean value of field and random component. The last one is conceived as a distribution of magnetic impurities (punctual vortex), having various statistical properties (local or non-local correlations, Poisson distribution, etc). The study of this system has led to two distinct situations: - the case of the charged particle feeling the influence of mean field that manifests its presence in the spectrum of broadened Landau levels; - the disordered situation in which the spectrum can be distinguished from the free one only by a low energy Lifshits behaviour. Additional properties are occurring in the limit of 'strong' mean field, namely a non-conventional low energy behaviour (in contrast to Lifshits behaviour) which was interpreted in terms of localized states. (author)
Natural Selection in the Field and the Classroom
Andrews, Tessa Marie
2012-01-01
This dissertation examined natural selection in westslope cutthroat trout ("Oncorhynchus clarkii lewisi") and undergraduate learning in the subject area natural selection. Translocation--moving individuals to a new habitat to establish, re-establish or supplement a population--is a crucial management strategy for cutthroat trout. One of…
International Nuclear Information System (INIS)
Perez, J.F.; Pontin, L.F.; Segundo, J.A.B.
1985-01-01
Using a method proposed by van Hemmen the free energy of the Curie-Weiss version of the site-dilute antiferromagnetic Ising model is computed, in the presence of an uniform magnetic field. The solution displays an exact correspondence between this model and the Curie-Weiss version of the Ising model in the presence of a random magnetic field. The phase diagrams are discussed and a tricritical point is shown to exist. (Author) [pt
On the unlikeliness of multi-field inflation: bounded random potentials and our vacuum
International Nuclear Information System (INIS)
Battefeld, Diana; Battefeld, Thorsten; Schulz, Sebastian
2012-01-01
Based on random matrix theory, we compute the likelihood of saddles and minima in a class of random potentials that are softly bounded from above and below, as required for the validity of low energy effective theories. Imposing this bound leads to a random mass matrix with non-zero mean of its entries. If the dimensionality of field-space is large, inflation is rare, taking place near a saddle point (if at all), since saddles are more likely than minima or maxima for common values of the potential. Due to the boundedness of the potential, the latter become more ubiquitous for rare low/large values respectively. Based on the observation of a positive cosmological constant, we conclude that the dimensionality of field-space after (and most likely during) inflation has to be low if no anthropic arguments are invoked, since the alternative, encountering a metastable deSitter vacuum by chance, is extremely unlikely
Wolde, Mistire; Tarekegn, Getahun; Kebede, Tedla
2018-05-01
Point-of-care glucometer (PoCG) devices play a significant role in self-monitoring of the blood sugar level, particularly in the follow-up of high blood sugar therapeutic response. The aim of this study was to evaluate blood glucose test results performed with four randomly selected glucometers on diabetes and control subjects versus standard wet chemistry (hexokinase) methods in Addis Ababa, Ethiopia. A prospective cross-sectional study was conducted on randomly selected 200 study participants (100 participants with diabetes and 100 healthy controls). Four randomly selected PoCG devices (CareSens N, DIAVUE Prudential, On Call Extra, i-QARE DS-W) were evaluated against hexokinase method and ISO 15197:2003 and ISO 15197:2013 standards. The minimum and maximum blood sugar values were recorded by CareSens N (21 mg/dl) and hexokinase method (498.8 mg/dl), respectively. The mean sugar values of all PoCG devices except On Call Extra showed significant differences compared with the reference hexokinase method. Meanwhile, all four PoCG devices had strong positive relationship (>80%) with the reference method (hexokinase). On the other hand, none of the four PoCG devices fulfilled the minimum accuracy measurement set by ISO 15197:2003 and ISO 15197:2013 standards. In addition, the linear regression analysis revealed that all four selected PoCG overestimated the glucose concentrations. The overall evaluation of the selected four PoCG measurements were poorly correlated with standard reference method. Therefore, before introducing PoCG devices to the market, there should be a standardized evaluation platform for validation. Further similar large-scale studies on other PoCG devices also need to be undertaken.
Random fields of initial out of straightness leading to column buckling
DEFF Research Database (Denmark)
Kala, Zdeněk; Valeš, Jan; Jönsson, Jeppe
2017-01-01
The elastic load-carrying capacity and buckling trajectory of steel columns under compression with open and hollow cross-sections, whose axis is curved by spatial random fields, are studied in the article. As a result of the spatial curvature of the axis the cross-sections are subjected to compre...
van Kasteren, T.L.M.; Noulas, A.K.; Kröse, B.J.A.; Smit, G.J.M.; Epema, D.H.J.; Lew, M.S.
2008-01-01
Conditional Random Fields are a discriminative probabilistic model which recently gained popularity in applications that require modeling nonindependent observation sequences. In this work, we present the basic advantages of this model over generative models and argue about its suitability in the
Bayesian structure learning for Markov Random Fields with a spike and slab prior
Chen, Y.; Welling, M.; de Freitas, N.; Murphy, K.
2012-01-01
In recent years a number of methods have been developed for automatically learning the (sparse) connectivity structure of Markov Random Fields. These methods are mostly based on L1-regularized optimization which has a number of disadvantages such as the inability to assess model uncertainty and
Integrals of random fields treated by the model correction factor method
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...
Joint modeling of ChIP-seq data via a Markov random field model
Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C
Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein-binding sites. In this paper, we present a Markov random field model for the joint analysis of multiple ChIP-seq experiments. The proposed model naturally accounts for
Random model of two-level atoms interacting with electromagnetic field
International Nuclear Information System (INIS)
Kireev, A.N.; Meleshko, A.N.
1983-12-01
A phase transition has been studied in a random system of two-level atoms interacting with an electromagnetic field. It is shown that superradiation can arise when there is short-range order in a spin-subsystem. The existence of long-range order is irrelevant for this phase transition
The limiting behavior of the estimated parameters in a misspecified random field regression model
DEFF Research Database (Denmark)
Dahl, Christian Møller; Qin, Yu
This paper examines the limiting properties of the estimated parameters in the random field regression model recently proposed by Hamilton (Econometrica, 2001). Though the model is parametric, it enjoys the flexibility of the nonparametric approach since it can approximate a large collection of n...
DEFF Research Database (Denmark)
Wang, W.; Hanson, Steen Grüner; Miyamoto, Y.
2005-01-01
We present the first direct experimental evidence of the local properties of optical vortices in a random laser speckle field. We have observed the Berry anisotropy ellipse describing the anisotropic squeezing of phase lines close to vortex cores and quantitatively verified the Dennis angular mom...
New constraints on modelling the random magnetic field of the MW
Energy Technology Data Exchange (ETDEWEB)
Beck, Marcus C.; Nielaba, Peter [Department of Physics, University of Konstanz, Universitätsstr. 10, D-78457 Konstanz (Germany); Beck, Alexander M.; Dolag, Klaus [University Observatory Munich, Scheinerstr. 1, D-81679 Munich (Germany); Beck, Rainer [Max Planck Institute for Radioastronomy, Auf dem Hügel 69, D-53121 Bonn (Germany); Strong, Andrew W., E-mail: marcus.beck@uni-konstanz.de, E-mail: abeck@usm.uni-muenchen.de, E-mail: rbeck@mpifr-bonn.mpg.de, E-mail: dolag@usm.uni-muenchen.de, E-mail: aws@mpe.mpg.de, E-mail: peter.nielaba@uni-konstanz.de [Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, D-85748 Garching (Germany)
2016-05-01
We extend the description of the isotropic and anisotropic random component of the small-scale magnetic field within the existing magnetic field model of the Milky Way from Jansson and Farrar, by including random realizations of the small-scale component. Using a magnetic-field power spectrum with Gaussian random fields, the NE2001 model for the thermal electrons and the Galactic cosmic-ray electron distribution from the current GALPROP model we derive full-sky maps for the total and polarized synchrotron intensity as well as the Faraday rotation-measure distribution. While previous work assumed that small-scale fluctuations average out along the line-of-sight or which only computed ensemble averages of random fields, we show that these fluctuations need to be carefully taken into account. Comparing with observational data we obtain not only good agreement with 408 MHz total and WMAP7 22 GHz polarized intensity emission maps, but also an improved agreement with Galactic foreground rotation-measure maps and power spectra, whose amplitude and shape strongly depend on the parameters of the random field. We demonstrate that a correlation length of 0≈22 pc (05 pc being a 5σ lower limit) is needed to match the slope of the observed power spectrum of Galactic foreground rotation-measure maps. Using multiple realizations allows us also to infer errors on individual observables. We find that previously-used amplitudes for random and anisotropic random magnetic field components need to be rescaled by factors of ≈0.3 and 0.6 to account for the new small-scale contributions. Our model predicts a rotation measure of −2.8±7.1 rad/m{sup 2} and 04.4±11. rad/m{sup 2} for the north and south Galactic poles respectively, in good agreement with observations. Applying our model to deflections of ultra-high-energy cosmic rays we infer a mean deflection of ≈3.5±1.1 degree for 60 EeV protons arriving from CenA.
Selection bias and subject refusal in a cluster-randomized controlled trial
Directory of Open Access Journals (Sweden)
Rochelle Yang
2017-07-01
Full Text Available Abstract Background Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. Methods The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. Results There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1
Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach
Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar
2010-10-01
To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.
MULTITEMPORAL CROP TYPE CLASSIFICATION USING CONDITIONAL RANDOM FIELDS AND RAPIDEYE DATA
Directory of Open Access Journals (Sweden)
T. Hoberg
2012-09-01
Full Text Available The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM. These approaches do not model temporal dependencies in an explicit way. Existing approaches that make use of temporal dependencies are in most cases quite simple and based on rules. Approaches that integrate temporal dependencies to statistical models are very rare and at an early stage of development. Here our approach CRFmulti, based on conditional random fields (CRF, should make a contribution. Conditional random fields consider context knowledge among neighboring primitives in the same way as Markov random fields (MRF do. Furthermore conditional random fields handle the feature vectors of the neighboring primitives and not only the class labels. Additional to taking spatial context into account, we present an approach for multitemporal data processing where a temporal association potential has been integrated to the common CRF approach to model temporal dependencies. The classification works on pixel ‐level using spectral image features, whereas all available single images are taken separately. For our experiments a high resolution RapidEye satellite data set of 2010 consisting of 4 images made during the whole vegetation period from April to October is taken. Six crop type categories are distinguished, namely grassland, corn, winter crop, rapeseed, root crops and other crops. To evaluate the potential of the new conditional random field approach the classification result is compared to a manual reference on pixel‐ and on object‐level. Additional a SVM approach is applied under the same conditions and should serve as a benchmark.
Raghav, Kanwal Pratap Singh; Mahajan, Sminil; Yao, James C.; Hobbs, Brian P.; Berry, Donald A.; Pentz, Rebecca D.; Tam, Alda; Hong, Waun K.; Ellis, Lee M.; Abbruzzese, James; Overman, Michael J.
2015-01-01
Purpose The decision by journals to append protocols to published reports of randomized trials was a landmark event in clinical trial reporting. However, limited information is available on how this initiative effected transparency and selective reporting of clinical trial data. Methods We analyzed 74 oncology-based randomized trials published in Journal of Clinical Oncology, the New England Journal of Medicine, and The Lancet in 2012. To ascertain integrity of reporting, we compared published reports with their respective appended protocols with regard to primary end points, nonprimary end points, unplanned end points, and unplanned analyses. Results A total of 86 primary end points were reported in 74 randomized trials; nine trials had greater than one primary end point. Nine trials (12.2%) had some discrepancy between their planned and published primary end points. A total of 579 nonprimary end points (median, seven per trial) were planned, of which 373 (64.4%; median, five per trial) were reported. A significant positive correlation was found between the number of planned and nonreported nonprimary end points (Spearman r = 0.66; P < .001). Twenty-eight studies (37.8%) reported a total of 65 unplanned end points; 52 (80.0%) of which were not identified as unplanned. Thirty-one (41.9%) and 19 (25.7%) of 74 trials reported a total of 52 unplanned analyses involving primary end points and 33 unplanned analyses involving nonprimary end points, respectively. Studies reported positive unplanned end points and unplanned analyses more frequently than negative outcomes in abstracts (unplanned end points odds ratio, 6.8; P = .002; unplanned analyses odd ratio, 8.4; P = .007). Conclusion Despite public and reviewer access to protocols, selective outcome reporting persists and is a major concern in the reporting of randomized clinical trials. To foster credible evidence-based medicine, additional initiatives are needed to minimize selective reporting. PMID:26304898
Impact of electromagnetic field on the pathogenicity of selected ...
African Journals Online (AJOL)
Rhipicephalus decoloratus) to variable intensities of electromagnetic field for different periods of time was examined on their pathogenicity on tick. Some bacterial isolates from the macerate of tick cadavers were used in the infection of healthy engorged ...
3D vector distribution of the electro-magnetic fields on a random gold film
Canneson, Damien; Berini, Bruno; Buil, Stéphanie; Hermier, Jean-Pierre; Quélin, Xavier
2018-05-01
The 3D vector distribution of the electro-magnetic fields at the very close vicinity of the surface of a random gold film is studied. Such films are well known for their properties of light confinement and large fluctuations of local density of optical states. Using Finite-Difference Time-Domain simulations, we show that it is possible to determine the local orientation of the electro-magnetic fields. This allows us to obtain a complete characterization of the fields. Large fluctuations of their amplitude are observed as previously shown. Here, we demonstrate large variations of their direction depending both on the position on the random gold film, and on the distance to it. Such characterization could be useful for a better understanding of applications like the coupling of point-like dipoles to such films.
Maximizing Entropy of Pickard Random Fields for 2x2 Binary Constraints
DEFF Research Database (Denmark)
Søgaard, Jacob; Forchhammer, Søren
2014-01-01
This paper considers the problem of maximizing the entropy of two-dimensional (2D) Pickard Random Fields (PRF) subject to constraints. We consider binary Pickard Random Fields, which provides a 2D causal finite context model and use it to define stationary probabilities for 2x2 squares, thus...... allowing us to calculate the entropy of the field. All possible binary 2x2 constraints are considered and all constraints are categorized into groups according to their properties. For constraints which can be modeled by a PRF approach and with positive entropy, we characterize and provide statistics...... of the maximum PRF entropy. As examples, we consider the well known hard square constraint along with a few other constraints....
Optimization of the Dutch Matrix Test by Random Selection of Sentences From a Preselected Subset
Directory of Open Access Journals (Sweden)
Rolph Houben
2015-04-01
Full Text Available Matrix tests are available for speech recognition testing in many languages. For an accurate measurement, a steep psychometric function of the speech materials is required. For existing tests, it would be beneficial if it were possible to further optimize the available materials by increasing the function’s steepness. The objective is to show if the steepness of the psychometric function of an existing matrix test can be increased by selecting a homogeneous subset of recordings with the steepest sentence-based psychometric functions. We took data from a previous multicenter evaluation of the Dutch matrix test (45 normal-hearing listeners. Based on half of the data set, first the sentences (140 out of 311 with a similar speech reception threshold and with the steepest psychometric function (≥9.7%/dB were selected. Subsequently, the steepness of the psychometric function for this selection was calculated from the remaining (unused second half of the data set. The calculation showed that the slope increased from 10.2%/dB to 13.7%/dB. The resulting subset did not allow the construction of enough balanced test lists. Therefore, the measurement procedure was changed to randomly select the sentences during testing. Random selection may interfere with a representative occurrence of phonemes. However, in our material, the median phonemic occurrence remained close to that of the original test. This finding indicates that phonemic occurrence is not a critical factor. The work highlights the possibility that existing speech tests might be improved by selecting sentences with a steep psychometric function.
Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models
Directory of Open Access Journals (Sweden)
Hui Wang
2017-10-01
Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.
Raghav, Kanwal Pratap Singh; Mahajan, Sminil; Yao, James C; Hobbs, Brian P; Berry, Donald A; Pentz, Rebecca D; Tam, Alda; Hong, Waun K; Ellis, Lee M; Abbruzzese, James; Overman, Michael J
2015-11-01
The decision by journals to append protocols to published reports of randomized trials was a landmark event in clinical trial reporting. However, limited information is available on how this initiative effected transparency and selective reporting of clinical trial data. We analyzed 74 oncology-based randomized trials published in Journal of Clinical Oncology, the New England Journal of Medicine, and The Lancet in 2012. To ascertain integrity of reporting, we compared published reports with their respective appended protocols with regard to primary end points, nonprimary end points, unplanned end points, and unplanned analyses. A total of 86 primary end points were reported in 74 randomized trials; nine trials had greater than one primary end point. Nine trials (12.2%) had some discrepancy between their planned and published primary end points. A total of 579 nonprimary end points (median, seven per trial) were planned, of which 373 (64.4%; median, five per trial) were reported. A significant positive correlation was found between the number of planned and nonreported nonprimary end points (Spearman r = 0.66; P medicine, additional initiatives are needed to minimize selective reporting. © 2015 by American Society of Clinical Oncology.
Field performance of selected mutants of sorghum and rice. Field evaluation review
International Nuclear Information System (INIS)
1996-10-01
Agricultural research conducted in Mali by the Institute Polytechnique Rural (IPR) and the Institute d'Economie Rural (IER), from improvement of sorghum and African rice (Oryza glaberrima) with some Agency support, resulted in several advanced generations of sorghum and African rice with improved characteristics, including high yield. Project MLI/5/014 aims at further supporting both institutions to advance these promising results, particularly by supporting multi-location field trials to select high yielding plant varieties, and by adding capability in tissue culture techniques for advanced mutation breeding as well as in the use of nuclear techniques in soil studies. The project was approved in 1995, as a model project and the current budget for the Agency's input amounts to $469,300 until 1997. The disbursements up to April 1996 amount to $168,991. The present mid-term evaluation aims at assessing the progress of the project towards its intended objectives and overall goal and the evaluation methodology applied was based on the Logical Framework Approach for project design. Figs, tabs
Validity of selected cardiovascular field-based test among Malaysian ...
African Journals Online (AJOL)
Based on emerge obese problem among Malaysian, this research is formulated to validate published tests among healthy female adult. Selected test namely; 20 meter multi-stage shuttle run, 2.4km run test, 1 mile walk test and Harvard Step test were correlated with laboratory test (Bruce protocol) to find the criterion validity ...
Frisch, H.; Anusha, L. S.; Sampoorna, M.; Nagendra, K. N.
2009-07-01
Context: The Hanle effect is used to determine weak turbulent magnetic fields in the solar atmosphere, usually assuming that the angular distribution is isotropic, the magnetic field strength constant, and that micro-turbulence holds, i.e. that the magnetic field correlation length is much less than a photon mean free path. Aims: To examine the sensitivity of turbulent magnetic field measurements to these assumptions, we study the dependence of Hanle effect on the magnetic field correlation length, its angular, and strength distributions. Methods: We introduce a fairly general random magnetic field model characterized by a correlation length and a magnetic field vector distribution. Micro-turbulence is recovered when the correlation length goes to zero and macro-turbulence when it goes to infinity. Radiative transfer equations are established for the calculation of the mean Stokes parameters and they are solved numerically by a polarized approximate lambda iteration method. Results: We show that optically thin spectral lines and optically very thick ones are insensitive to the correlation length of the magnetic field, while spectral lines with intermediate optical depths (around 10-100) show some sensitivity to this parameter. The result is interpreted in terms of the mean number of scattering events needed to create the surface polarization. It is shown that the single-scattering approximation holds good for thin and thick lines but may fail for lines with intermediate thickness. The dependence of the polarization on the magnetic field vector probability density function (PDF) is examined in the micro-turbulent limit. A few PDFs with different angular and strength distributions, but equal mean value of the magnetic field, are considered. It is found that the polarization is in general quite sensitive to the shape of the magnetic field strength PDF and somewhat to the angular distribution. Conclusions: The mean field derived from Hanle effect analysis of
Effect of magnetic field on selectivity of three-step photoionization
International Nuclear Information System (INIS)
Lim, Chang Hwan; Rho, Si Pyo; Ko, Kwang Hoon; Kim, Chul Joong; Izawa, Yasukazu
2001-01-01
Effect of magnetic field on selectivity by linearly polarized lasers was analyzed by formulating the density matrix equations. To investigate the effect of magnetic field on the selectivity of AVLIS, we proposed a general Hamiltonian for multilevel atomic system in magnetic field. The population dynamics of magnetic sublevels have been observed by solving the Liouville equation. Mixing between magnetic sublevels was observed in each state during the laser excitations when the magnetic field perpendicular to the quantization axis was applied to the atomic system. The magnetic field dependence on ionization rate of even isotopes was also discussed. In the magnetic field dependence, two ionization peaks were appeared because of the interference between Rabi and Larmor frequency during the ionization process. The permissible intensities of magnetic field were predicted to obtain enough selectivity for the target isotopes of zirconium and gadolinium in the AVLIS process based on the polarization selection rule
Field development. Concept selection in deep water environment offshore Angola
Energy Technology Data Exchange (ETDEWEB)
Guenot, A.; Berger, J.C.; Limet, N. [TotalFinaElf, la Defense 6, Rosa-Lirio Project Group, 92 - Courbevoie (France)
2002-10-01
The significant oil discoveries made at the end of the 90's in the deep water environment offshore the coast of Angola, has led to a considerable amount of development activities. The first field in production was the turnkey development of the Kuito field on the Block 14 operated by Chevron. More recently the Girassol field has been put successfully in production on the Block 17, operated by TotalFinaElf. Both developments are making use of sub-sea wells connected to a moored dedicated FPSO. On the western side of the Girassol field, several discoveries have been made. They are known as the Rosa Lirio pole, from the names of two of the main channels. Values for water depth are in the same range than on Girassol (1300- 1400 m). A project group has been established in 1999 to evaluate the development of these discoveries. The purpose of this paper is to present the conceptual work which as been carried out, and in particular to show that even if many different concepts have been evaluated, the final choice has been also to make use of sub-sea trees. (authors)
Energy Technology Data Exchange (ETDEWEB)
Zaim, N.; Zaim, A., E-mail: ah_zaim@yahoo.fr; Kerouad, M., E-mail: kerouad@fs-umi.ac.ma
2017-02-15
In this work, the magnetic behavior of the cylindrical nanowire, consisting of a ferromagnetic core of spin-1 atoms surrounded by a ferromagnetic shell of spin-1 atoms is studied in the presence of a random crystal field interaction. Based on Metropolis algorithm, the Monte Carlo simulation has been used to investigate the effects of the concentration of the random crystal field p, the crystal field D and the shell exchange interaction J{sub s} on the phase diagrams and the hysteresis behavior of the system. Some characteristic behaviors have been found, such as the first and second-order phase transitions joined by tricritical point for appropriate values of the system parameters, triple and isolated critical points can be also found. Depending on the Hamiltonian parameters, single, double and para hysteresis regions are explicitly determined. - Highlights: • Phase diagrams of a ferromagnetic nanowire are examined by the Monte Carlo simulation. • Different types of the phase diagrams are obtained. • The effect of the random crystal field on the hysteresis loops is studied. • Single, double and para hysteresis regions are explicitly determined.
On theoretical models of gene expression evolution with random genetic drift and natural selection.
Directory of Open Access Journals (Sweden)
Osamu Ogasawara
2009-11-01
Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.
International Nuclear Information System (INIS)
Artaud, J.F.
1994-01-01
The main themes of this thesis are: review of superconductivity principles; critical current in a random orientation magnetic field; the MHD model applied to superconductors (with comprehensive calculation of the field in a plate type conductor); the magnetization created by a variation of a random orientation magnetic field; the electric field in a superconductor in steady or quasi-steady state (MHD displacement, pinning and thermal effects). 145 figs., 166 refs
Risk Attitudes, Sample Selection and Attrition in a Longitudinal Field Experiment
DEFF Research Database (Denmark)
Harrison, Glenn W.; Lau, Morten Igel
with respect to risk attitudes. Our design builds in explicit randomization on the incentives for participation. We show that there are significant sample selection effects on inferences about the extent of risk aversion, but that the effects of subsequent sample attrition are minimal. Ignoring sample...... selection leads to inferences that subjects in the population are more risk averse than they actually are. Correcting for sample selection and attrition affects utility curvature, but does not affect inferences about probability weighting. Properly accounting for sample selection and attrition effects leads...... to findings of temporal stability in overall risk aversion. However, that stability is around different levels of risk aversion than one might naively infer without the controls for sample selection and attrition we are able to implement. This evidence of “randomization bias” from sample selection...
Selective data analysis for diamond detectors in neutron fields
Directory of Open Access Journals (Sweden)
Weiss Christina
2017-01-01
Full Text Available Detectors based on synthetic chemical vapor deposition diamond gain importance in various neutron applications. The superior thermal robustness and the excellent radiation hardness of diamond as well as its excellent electronic properties make this material uniquely suited for rough environments, such as nuclear fission and fusion reactors. The intrinsic electronic properties of single-crystal diamond sensors allow distinguishing various interactions in the detector. This can be used to successfully suppress background of γ-rays and charged particles in different neutron experiments, such as neutron flux measurements in thermal nuclear reactors or cross-section measurements in fast neutron fields. A novel technique of distinguishing background reactions in neutron experiments with diamond detectors will be presented. A proof of principle will be given on the basis of experimental results in thermal and fast neutron fields.
Endogenous fields enhanced stochastic resonance in a randomly coupled neuronal network
International Nuclear Information System (INIS)
Deng, Bin; Wang, Lin; Wang, Jiang; Wei, Xi-le; Yu, Hai-tao
2014-01-01
Highlights: • We study effects of endogenous fields on stochastic resonance in a neural network. • Stochastic resonance can be notably enhanced by endogenous field feedback. • Endogenous field feedback delay plays a vital role in stochastic resonance. • The parameters of low-passed filter play a subtle role in SR. - Abstract: Endogenous field, evoked by structured neuronal network activity in vivo, is correlated with many vital neuronal processes. In this paper, the effects of endogenous fields on stochastic resonance (SR) in a randomly connected neuronal network are investigated. The network consists of excitatory and inhibitory neurons and the axonal conduction delays between neurons are also considered. Numerical results elucidate that endogenous field feedback results in more rhythmic macroscope activation of the network for proper time delay and feedback coefficient. The response of the network to the weak periodic stimulation can be notably enhanced by endogenous field feedback. Moreover, the endogenous field feedback delay plays a vital role in SR. We reveal that appropriately tuned delays of the feedback can either induce the enhancement of SR, appearing at every integer multiple of the weak input signal’s oscillation period, or the depression of SR, appearing at every integer multiple of half the weak input signal’s oscillation period for the same feedback coefficient. Interestingly, the parameters of low-passed filter which is used in obtaining the endogenous field feedback signal play a subtle role in SR
Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H
2017-07-01
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in
A Modified FCM Classifier Constrained by Conditional Random Field Model for Remote Sensing Imagery
Directory of Open Access Journals (Sweden)
WANG Shaoyu
2016-12-01
Full Text Available Remote sensing imagery has abundant spatial correlation information, but traditional pixel-based clustering algorithms don't take the spatial information into account, therefore the results are often not good. To this issue, a modified FCM classifier constrained by conditional random field model is proposed. Adjacent pixels' priori classified information will have a constraint on the classification of the center pixel, thus extracting spatial correlation information. Spectral information and spatial correlation information are considered at the same time when clustering based on second order conditional random field. What's more, the global optimal inference of pixel's classified posterior probability can be get using loopy belief propagation. The experiment shows that the proposed algorithm can effectively maintain the shape feature of the object, and the classification accuracy is higher than traditional algorithms.
Quantum correlations and dynamics from classical random fields valued in complex Hilbert spaces
International Nuclear Information System (INIS)
Khrennikov, Andrei
2010-01-01
One of the crucial differences between mathematical models of classical and quantum mechanics (QM) is the use of the tensor product of the state spaces of subsystems as the state space of the corresponding composite system. (To describe an ensemble of classical composite systems, one uses random variables taking values in the Cartesian product of the state spaces of subsystems.) We show that, nevertheless, it is possible to establish a natural correspondence between the classical and the quantum probabilistic descriptions of composite systems. Quantum averages for composite systems (including entangled) can be represented as averages with respect to classical random fields. It is essentially what Albert Einstein dreamed of. QM is represented as classical statistical mechanics with infinite-dimensional phase space. While the mathematical construction is completely rigorous, its physical interpretation is a complicated problem. We present the basic physical interpretation of prequantum classical statistical field theory in Sec. II. However, this is only the first step toward real physical theory.
Analysis of family-wise error rates in statistical parametric mapping using random field theory.
Flandin, Guillaume; Friston, Karl J
2017-11-01
This technical report revisits the analysis of family-wise error rates in statistical parametric mapping-using random field theory-reported in (Eklund et al. []: arXiv 1511.01863). Contrary to the understandable spin that these sorts of analyses attract, a review of their results suggests that they endorse the use of parametric assumptions-and random field theory-in the analysis of functional neuroimaging data. We briefly rehearse the advantages parametric analyses offer over nonparametric alternatives and then unpack the implications of (Eklund et al. []: arXiv 1511.01863) for parametric procedures. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Random crystal field effects on the integer and half-integer mixed-spin system
Yigit, Ali; Albayrak, Erhan
2018-05-01
In this work, we have focused on the random crystal field effects on the phase diagrams of the mixed spin-1 and spin-5/2 Ising system obtained by utilizing the exact recursion relations (ERR) on the Bethe lattice (BL). The distribution function P(Di) = pδ [Di - D(1 + α) ] +(1 - p) δ [Di - D(1 - α) ] is used to randomize the crystal field.The phase diagrams are found to exhibit second- and first-order phase transitions depending on the values of α, D and p. It is also observed that the model displays tricritical point, isolated point, critical end point and three compensation temperatures for suitable values of the system parameters.
The phase diagrams of a ferromagnetic thin film in a random magnetic field
Energy Technology Data Exchange (ETDEWEB)
Zaim, N.; Zaim, A., E-mail: ah_zaim@yahoo.fr; Kerouad, M., E-mail: m.kerouad@fs-umi.ac.ma
2016-10-07
In this paper, the magnetic properties and the phase diagrams of a ferromagnetic thin film with a thickness N in a random magnetic field (RMF) are investigated by using the Monte Carlo simulation technique based on the Metropolis algorithm. The effects of the RMF and the surface exchange interaction on the critical behavior are studied. A variety of multicritical points such as tricritical points, isolated critical points, and triple points are obtained. It is also found that the double reentrant phenomenon can appear for appropriate values of the system parameters. - Highlights: • Phase diagrams of a ferromagnetic thin film are examined by the Monte Carlo simulation. • The effect of the random magnetic field on the magnetic properties is studied. • Different types of the phase diagrams are obtained. • The dependence of the magnetization and susceptibility on the temperature are investigated.
Bit selection using field drilling data and mathematical investigation
Momeni, M. S.; Ridha, S.; Hosseini, S. J.; Meyghani, B.; Emamian, S. S.
2018-03-01
A drilling process will not be complete without the usage of a drill bit. Therefore, bit selection is considered to be an important task in drilling optimization process. To select a bit is considered as an important issue in planning and designing a well. This is simply because the cost of drilling bit in total cost is quite high. Thus, to perform this task, aback propagation ANN Model is developed. This is done by training the model using several wells and it is done by the usage of drilling bit records from offset wells. In this project, two models are developed by the usage of the ANN. One is to find predicted IADC bit code and one is to find Predicted ROP. Stage 1 was to find the IADC bit code by using all the given filed data. The output is the Targeted IADC bit code. Stage 2 was to find the Predicted ROP values using the gained IADC bit code in Stage 1. Next is Stage 3 where the Predicted ROP value is used back again in the data set to gain Predicted IADC bit code value. The output is the Predicted IADC bit code. Thus, at the end, there are two models that give the Predicted ROP values and Predicted IADC bit code values.
Magnetoresistance of a two-dimensional electron gas in a random magnetic field
DEFF Research Database (Denmark)
Smith, Anders; Taboryski, Rafael Jozef; Hansen, Luise Theil
1994-01-01
We report magnetoresistance measurements on a two-dimensional electron gas made from a high-mobility GaAs/AlxGa1-xAs heterostructure, where the externally applied magnetic field was expelled from regions of the semiconductor by means of superconducting lead grains randomly distributed on the surf...... on the surface of the sample. A theoretical explanation in excellent agreement with the experiment is given within the framework of the semiclassical Boltzmann equation. © 1994 The American Physical Society...
Prediction of the spatial occurrence of fire induced spalling in concrete slabs using random fields
Directory of Open Access Journals (Sweden)
Van Coile R.
2013-09-01
Full Text Available As the loss of concrete cover can significantly influence the reliability of concrete elements during fire, spalling should be taken into account when performing reliability calculations. However, the occurrence and spatial variation of spalling are highly uncertain. A first step towards a probabilistic analysis of spalling is made by combining existing deterministic models with a stochastic representation of the concrete tensile strength and by using random fields to model the tensile strength spatial variation.
Application of the random field theory in PET imaging - injection dose optimization
Czech Academy of Sciences Publication Activity Database
Dvořák, Jiří; Boldyš, Jiří; Skopalová, M.; Bělohlávek, O.
2013-01-01
Roč. 49, č. 2 (2013), s. 280-300 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572 Institutional support: RVO:67985556 Keywords : random field theory * Euler characteristic * PET imaging * PET image quality Subject RIV: BD - Theory of Information Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/boldys-0397176.pdf
Extreme of random field over rectangle with application to concrete rupture stresses
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2000-01-01
to time consuming simulation procedures. This paperrevives a conceptually simple approach that gives surprisingly good results in particular for wide band typesof random processes and fields. The closed form formulas obtained for smooth Gaussian fieldsover rectangles contain size effects both with respect...... to the area of the rectangle and the side lengths of therectangle. Published rupture stress data for plain concrete beams illustrate the applicability of the derivedclosed form extreme value distributions as models for distributions of rupture stresses related to weakest linkmechanisms....
Boruch, R F; Mcsweeny, A J; Soderstrom, E J
1978-11-01
This bibliography lists references to over 300 field experiments undertaken in schools, hospitals, prisons, and other social settings, mainly in the U.S. The list is divided into 10 major categories corresponding to the type of program under examination. They include: criminal and civil justice programs, mental health, training and education, mass media, information collection, utilization, commerce and industry, welfare, health, and family planning. The main purpose of the bibliography is to provide evidence on feasibility and scope of randomized field tests, since despite their advantages, it is not always clear from managerial, political, and other constraints on research that they can be mounted. Dates of publications range from 1944 to 1978.
Statistical Shape Modelling and Markov Random Field Restoration (invited tutorial and exercise)
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen
This tutorial focuses on statistical shape analysis using point distribution models (PDM) which is widely used in modelling biological shape variability over a set of annotated training data. Furthermore, Active Shape Models (ASM) and Active Appearance Models (AAM) are based on PDMs and have proven...... deformation field between shapes. The tutorial demonstrates both generative active shape and appearance models, and MRF restoration on 3D polygonized surfaces. ''Exercise: Spectral-Spatial classification of multivariate images'' From annotated training data this exercise applies spatial image restoration...... using Markov random field relaxation of a spectral classifier. Keywords: the Ising model, the Potts model, stochastic sampling, discriminant analysis, expectation maximization....
A Unified 3D Mesh Segmentation Framework Based on Markov Random Field
Z.F. Shi; L.Y. Lu; D. Le; X.M. Niu
2012-01-01
3D Mesh segmentation has become an important research field in computer graphics during the past decades. Many geometry based and semantic oriented approaches for 3D mesh segmentation has been presented. In this paper, we present a definition of mesh segmentation according to labeling problem. Inspired by the Markov Random Field (MRF) based image segmentation, we propose a new framework of 3D mesh segmentation based on MRF and use graph cuts to solve it. Any features of 3D mesh can be integra...
Lifetime, turnover time, and fast magnetic field regeneration in random flows
International Nuclear Information System (INIS)
Tanner, S. E. M.
2007-01-01
The fast dynamo is thought to be relevant in the regeneration of magnetic fields in astrophysics where the value of the magnetic Reynolds number (Rm) is immense. The fast dynamo picture is one in which chaotic flows provide a mechanism for the stretching of magnetic field lines. Furthermore, a cascade of energy down to small scales results in intermittent regions of a small-scale, intense magnetic field. Given this scenario it is natural to invoke the use of kinematic random flows in order to understand field regeneration mechanisms better. Here a family of random flows is used to study the effects that L, the lifetime of the cell, and τ, the turnover time of the cell, may have on magnetic field regeneration. Defining the parameter Γ=L/τ, it has been varied according to Γ>1, Γ<1, Γ∼O(1). In the kinematic regime, dynamo growth rates and Lyapunov exponents are examined at varying values of Rm. The possibility of fast dynamo action is considered. In the nonlinear regime, magnetic and kinetic energies are examined. Results indicate that there does appear to be a relationship between Γ and dynamo efficiency. In particular, the most efficient dynamos seem to operate at lower values of Γ
Anomalous diffusion and Levy random walk of magnetic field lines in three dimensional turbulence
International Nuclear Information System (INIS)
Zimbardo, G.; Veltri, P.; Basile, G.; Principato, S.
1995-01-01
The transport of magnetic field lines is studied numerically where three dimensional (3-D) magnetic fluctuations, with a power law spectrum, and periodic over the simulation box are superimposed on an average uniform magnetic field. The weak and the strong turbulence regime, δB∼B 0 , are investigated. In the weak turbulence case, magnetic flux tubes are separated from each other by percolating layers in which field lines undergo a chaotic motion. In this regime the field lines may exhibit Levy, rather than Gaussian, random walk, changing from Levy flights to trapped motion. The anomalous diffusion laws left-angle Δx 2 i right-angle ∝s α with α>1 and α<1, are obtained for a number of cases, and the non-Gaussian character of the field line random walk is pointed out by computing the kurtosis. Increasing the fluctuation level, and, therefore stochasticity, normal diffusion (α congruent 1) is recovered and the kurtoses reach their Gaussian value. However, the numerical results show that neither the quasi-linear theory nor the two dimensional percolation theory can be safely extrapolated to the considered 3-D strong turbulence regime. copyright 1995 American Institute of Physics
Earl, James A.
1992-01-01
When charged particles spiral along a large constant magnetic field, their trajectories are scattered by any random field components that are superposed on the guiding field. If the random field configuration embodies helicity, the scattering is asymmetrical with respect to a plane perpendicular to the guiding field, for particles moving into the forward hemisphere are scattered at different rates from those moving into the backward hemisphere. This asymmetry gives rise to new terms in the transport equations that describe propagation of charged particles. Helicity has virtually no impact on qualitative features of the diffusive mode of propagation. However, characteristic velocities of the coherent modes that appear after a highly anisotropic injection exhibit an asymmetry related to helicity. Explicit formulas, which embody the effects of helicity, are given for the anisotropies, the coefficient diffusion, and the coherent velocities. Predictions derived from these expressions are in good agreement with Monte Carlo simulations of particle transport, but the simulations reveal certain phenomena whose explanation calls for further analytical work.
Bone metastasis: review and critical analysis of random allocation trials of local field treatment
International Nuclear Information System (INIS)
Ratanatharathorn, Vaneerat; Powers, William E.; Moss, William T.; Perez, Carlos A.
1999-01-01
Purpose: Compare and contrast reports of random allocation clinical trials of local field radiation therapy of metastases to bone to determine the techniques producing the best results (frequency, magnitude, and duration of benefit), and relate these to the goals of complete relief of pain and prevention of disability for the remaining life of the patient. Methods and Materials: Review all published reports of random allocation clinical trials, and perform a systematic analysis of the processes and outcomes of the several trial reports. Results: All trials were performed on selected populations of patients with symptomatic metastases and most studies included widely diverse groups with regard to: (a) site of primary tumor, (b) location, extent, size, and nature of metastases, (c) duration of survival after treatment. All trial reports lack sufficient detail for full and complete analysis. Much collected information is not now available for reanalysis and many important data sets were apparently never collected. Several of the variations in patient and tumor characteristics were found to be much more important than treatment dose in the outcome results. Treatment planning and delivery techniques were unsophisticated and probably resulted in a systematic delivery of less than the assigned dose to some metastases. In general the use and benefit of retreatment was greater in those patients who initially received lower doses but the basis and dose of retreatment was not documented. Follow-up of patients was varied with a large proportion of surviving patients lost to follow-up in several studies. The greatest difference in the reports is the method of calculation of results. The applicability of Kaplan-Meier actuarial analysis, censoring the lost and dead patients, as used in studies with loss to follow-up of a large number of patients is questionable. The censoring involved is 'informative' (the processes of loss relate to the outcome) and not acceptable since it
Hong, Liang
2013-10-01
The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.
Analysis and applications of a frequency selective surface via a random distribution method
International Nuclear Information System (INIS)
Xie Shao-Yi; Huang Jing-Jian; Yuan Nai-Chang; Liu Li-Guo
2014-01-01
A novel frequency selective surface (FSS) for reducing radar cross section (RCS) is proposed in this paper. This FSS is based on the random distribution method, so it can be called random surface. In this paper, the stacked patches serving as periodic elements are employed for RCS reduction. Previous work has demonstrated the efficiency by utilizing the microstrip patches, especially for the reflectarray. First, the relevant theory of the method is described. Then a sample of a three-layer variable-sized stacked patch random surface with a dimension of 260 mm×260 mm is simulated, fabricated, and measured in order to demonstrate the validity of the proposed design. For the normal incidence, the 8-dB RCS reduction can be achieved both by the simulation and the measurement in 8 GHz–13 GHz. The oblique incidence of 30° is also investigated, in which the 7-dB RCS reduction can be obtained in a frequency range of 8 GHz–14 GHz. (condensed matter: electronic structure, electrical, magnetic, and optical properties)
Directory of Open Access Journals (Sweden)
Zhao D
2015-07-01
Full Text Available Di Zhao,1,* Jian Song,2,* Xuan Gao,3 Fei Gao,4 Yupeng Wu,2 Yingying Lu,5 Kai Hou1 1Department of Neurosurgery, The First Hospital of Hebei Medical University, 2Department of Neurosurgery, 3Department of Neurology, The Second Hospital of Hebei Medical University, 4Hebei Provincial Procurement Centers for Medical Drugs and Devices, 5Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang People’s Republic of China *These authors contributed equally to this work Background: Selective digestive decontamination (SDD and selective oropharyngeal decontamination (SOD are associated with reduced mortality and infection rates among patients in intensive care units (ICUs; however, whether SOD has a superior effect than SDD remains uncertain. Hence, we conducted a meta-analysis of randomized controlled trials (RCTs to compare SOD with SDD in terms of clinical outcomes and antimicrobial resistance rates in patients who were critically ill. Methods: RCTs published in PubMed, Embase, and Web of Science were systematically reviewed to compare the effects of SOD and SDD in patients who were critically ill. Outcomes included day-28 mortality, length of ICU stay, length of hospital stay, duration of mechanical ventilation, ICU-acquired bacteremia, and prevalence of antibiotic-resistant Gram-negative bacteria. Results were expressed as risk ratio (RR with 95% confidence intervals (CIs, and weighted mean differences (WMDs with 95% CIs. Pooled estimates were performed using a fixed-effects model or random-effects model, depending on the heterogeneity among studies. Results: A total of four RCTs involving 23,822 patients met the inclusion criteria and were included in this meta-analysis. Among patients whose admitting specialty was surgery, cardiothoracic surgery (57.3% and neurosurgery (29.7% were the two main types of surgery being performed. Pooled results showed that SOD had similar effects as SDD in day-28 mortality (RR =1
Coaxial monitoring of temperature field in selective pulsed laser melting
Liu, Che; Chen, Zhongyun; Cao, Hongzhong; Zhou, Jianhong
2017-10-01
Selective Laser Melting is a rapid manufacturing technology which produces complex parts layer by layer. The presence of thermal stress and thermal strain in the forming process often leads to defects in the formed parts. In order to detect fabricate errors and avoid failure which caused by thermal gradient in time. An infrared thermal imager and a high speed CCD camera were applied to build a coaxial optical system for real-time monitoring the temperature distribution and changing trend of laser affected zone in SLM forming process. Molten tracks were fabricated by SLM under different laser parameters such as frequency, pulse width. And the relationship between the laser parameters and the temperature distribution were all obtained and analyzed.
Directory of Open Access Journals (Sweden)
Ramoni Marco F
2007-03-01
Full Text Available Abstract Background Recent studies have shown that when individuals are grouped on the basis of genetic similarity, group membership corresponds closely to continental origin. There has been considerable debate about the implications of these findings in the context of larger debates about race and the extent of genetic variation between groups. Some have argued that clustering according to continental origin demonstrates the existence of significant genetic differences between groups and that these differences may have important implications for differences in health and disease. Others argue that clustering according to continental origin requires the use of large amounts of genetic data or specifically chosen markers and is indicative only of very subtle genetic differences that are unlikely to have biomedical significance. Results We used small numbers of randomly selected single nucleotide polymorphisms (SNPs from the International HapMap Project to train naïve Bayes classifiers for prediction of ancestral continent of origin. Predictive accuracy was tested on two independent data sets. Genetically similar groups should be difficult to distinguish, especially if only a small number of genetic markers are used. The genetic differences between continentally defined groups are sufficiently large that one can accurately predict ancestral continent of origin using only a minute, randomly selected fraction of the genetic variation present in the human genome. Genotype data from only 50 random SNPs was sufficient to predict ancestral continent of origin in our primary test data set with an average accuracy of 95%. Genetic variations informative about ancestry were common and widely distributed throughout the genome. Conclusion Accurate characterization of ancestry is possible using small numbers of randomly selected SNPs. The results presented here show how investigators conducting genetic association studies can use small numbers of arbitrarily
Directory of Open Access Journals (Sweden)
Thandi Kapwata
2016-11-01
Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.
Sadeh, Sadra; Rotter, Stefan
2014-01-01
Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.
Interference-aware random beam selection schemes for spectrum sharing systems
Abdallah, Mohamed
2012-10-19
Spectrum sharing systems have been recently introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this work, we develop interference-aware random beam selection schemes that provide enhanced performance for the secondary network under the condition that the interference observed by the receivers of the primary network is below a predetermined/acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a primary link composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes select a beam, among a set of power-optimized random beams, that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the SINR statistics as well as the capacity and bit error rate (BER) of the secondary link.
Abdallah, Mohamed M.
2013-11-01
In this work, we develop joint interference-aware random beam and spectrum selection scheme that provide enhanced performance for the secondary network under the condition that the interference observed at the primary receiver is below a predetermined acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a set of primary links composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes jointly select a beam, among a set of power-optimized random beams, as well as the primary spectrum that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint. In particular, we consider the case where the interference level is described by a q-bit description of its magnitude, whereby we propose a technique to find the optimal quantizer thresholds in a mean square error (MSE) sense. © 2013 IEEE.
Abdallah, Mohamed M.; Sayed, Mostafa M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.
2013-01-01
In this work, we develop joint interference-aware random beam and spectrum selection scheme that provide enhanced performance for the secondary network under the condition that the interference observed at the primary receiver is below a predetermined acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a set of primary links composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes jointly select a beam, among a set of power-optimized random beams, as well as the primary spectrum that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint. In particular, we consider the case where the interference level is described by a q-bit description of its magnitude, whereby we propose a technique to find the optimal quantizer thresholds in a mean square error (MSE) sense. © 2013 IEEE.
Selected Track and Field Articles. Sports Articles Reprint Series. First Edition.
Harkins, Dorothy, Ed.
This is a collection of articles from the 1962-70 DGWS Track and Field Guides and from National Institute Proceedings on the subject of girl's track and field activity. Included among the selections are articles on teaching outlines for track and field; distance running for girls and women; athletic injuries; hurdling for girls and women; adaption…
The quantum transverse spin-2 Ising model with a bimodal random-field in the pair approximation
International Nuclear Information System (INIS)
Canko, O.; Albayrak, E.; Keskin, M.
2005-01-01
In this paper, we have investigated the bimodal random-field spin-2 Ising system in a transverse field by combining the pair approximation with the discretized path-integral representation. The exact equations for the second-order phase transition lines and tricritical points are obtained in terms of the random field H, the transverse field G and the coordination number z. It is found that there are some critical values for H and G where the tricritical points disappear for given z. We have also observed that the system presents reentrant behavior which may be caused by the quantum effects and randomness. The phase diagram with respect to the random field and the second-order phase transition temperature are studied extensively for given values of the transverse field and the coordination number
Field selection of chemical protective clothing and respiratory protection
International Nuclear Information System (INIS)
Pinette, S.; Dodgen, C.; Morley, M.
1991-01-01
Safety professionals who must choose appropriate personal protective equipment for hazardous substance response or hazardous waste sites require useable information about the effectiveness of the various products available. Each hazardous waste operation involves a unique combination of chemical hazards requiring a unique combination of protective apparel. A chemical protective suit or respirator must be chosen for each site and each operation on the site. No single protective suit is effective against all chemical hazards. No single respirator is the best choice in every situation. Various sources of information on the effectiveness of protective clothing products will be discussed. Site-specific permeation testing of the proposed protective clothing options will also be discussed. It is both possible and practical to obtain specific information about the degree of protection afforded by a particular suit against a particular chemical mixture. It is also important to know how long the suit will last. Choosing adequate respiratory protection is a complex process. Respirator cartridge performance depends on various environmental factors as well as upon the combination and concentration of chemicals in the air. Once characterization of the air at a site has been accomplished, it may be appropriate to select an alternative to airline respirators and SCBAs. Respirator cartridges can be tested against specific chemical mixtures using worse case environmental factors. The results can be used to predict both the effectiveness and duration of protection afforded by respirator cartridges which can reduce costs and worker fatigue
Random source generating far field with elliptical flat-topped beam profile
International Nuclear Information System (INIS)
Zhang, Yongtao; Cai, Yangjian
2014-01-01
Circular and rectangular multi-Gaussian Schell-model (MGSM) sources which generate far fields with circular and rectangular flat-topped beam profiles were introduced just recently (Sahin and Korotkova 2012 Opt. Lett. 37 2970; Korotkova 2014 Opt. Lett. 39 64). In this paper, a random source named an elliptical MGSM source is introduced. An analytical expression for the propagation factor of an elliptical MGSM beam is derived. Furthermore, an analytical propagation formula for an elliptical MGSM beam passing through a stigmatic ABCD optical system is derived, and its propagation properties in free space are studied. It is interesting to find that an elliptical MGSM source generates a far field with an elliptical flat-topped beam profile, being qualitatively different from that of circular and rectangular MGSM sources. The ellipticity and the flatness of the elliptical flat-topped beam profile in the far field are determined by the initial coherence widths and the beam index, respectively. (paper)
Vector solution for the mean electromagnetic fields in a layer of random particles
Lang, R. H.; Seker, S. S.; Levine, D. M.
1986-01-01
The mean electromagnetic fields are found in a layer of randomly oriented particles lying over a half space. A matrix-dyadic formulation of Maxwell's equations is employed in conjunction with the Foldy-Lax approximation to obtain equations for the mean fields. A two variable perturbation procedure, valid in the limit of small fractional volume, is then used to derive uncoupled equations for the slowly varying amplitudes of the mean wave. These equations are solved to obtain explicit expressions for the mean electromagnetic fields in the slab region in the general case of arbitrarily oriented particles and arbitrary polarization of the incident radiation. Numerical examples are given for the application to remote sensing of vegetation.
Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves.
Ma, Yunbei; Zhou, Xiao-Hua
2017-02-01
For time-to-event data in a randomized clinical trial, we proposed two new methods for selecting an optimal treatment for a patient based on the covariate-specific treatment effect curve, which is used to represent the clinical utility of a predictive biomarker. To select an optimal treatment for a patient with a specific biomarker value, we proposed pointwise confidence intervals for each covariate-specific treatment effect curve and the difference between covariate-specific treatment effect curves of two treatments. Furthermore, to select an optimal treatment for a future biomarker-defined subpopulation of patients, we proposed confidence bands for each covariate-specific treatment effect curve and the difference between each pair of covariate-specific treatment effect curve over a fixed interval of biomarker values. We constructed the confidence bands based on a resampling technique. We also conducted simulation studies to evaluate finite-sample properties of the proposed estimation methods. Finally, we illustrated the application of the proposed method in a real-world data set.
Integrated Behavior Therapy for Selective Mutism: a randomized controlled pilot study.
Bergman, R Lindsey; Gonzalez, Araceli; Piacentini, John; Keller, Melody L
2013-10-01
To evaluate the feasibility, acceptability, and preliminary efficacy of a novel behavioral intervention for reducing symptoms of selective mutism and increasing functional speech. A total of 21 children ages 4 to 8 with primary selective mutism were randomized to 24 weeks of Integrated Behavior Therapy for Selective Mutism (IBTSM) or a 12-week Waitlist control. Clinical outcomes were assessed using blind independent evaluators, parent-, and teacher-report, and an objective behavioral measure. Treatment recipients completed a three-month follow-up to assess durability of treatment gains. Data indicated increased functional speaking behavior post-treatment as rated by parents and teachers, with a high rate of treatment responders as rated by blind independent evaluators (75%). Conversely, children in the Waitlist comparison group did not experience significant improvements in speaking behaviors. Children who received IBTSM also demonstrated significant improvements in number of words spoken at school compared to baseline, however, significant group differences did not emerge. Treatment recipients also experienced significant reductions in social anxiety per parent, but not teacher, report. Clinical gains were maintained over 3 month follow-up. IBTSM appears to be a promising new intervention that is efficacious in increasing functional speaking behaviors, feasible, and acceptable to parents and teachers. Copyright © 2013 Elsevier Ltd. All rights reserved.
Two-year Randomized Clinical Trial of Self-etching Adhesives and Selective Enamel Etching.
Pena, C E; Rodrigues, J A; Ely, C; Giannini, M; Reis, A F
2016-01-01
The aim of this randomized, controlled prospective clinical trial was to evaluate the clinical effectiveness of restoring noncarious cervical lesions with two self-etching adhesive systems applied with or without selective enamel etching. A one-step self-etching adhesive (Xeno V(+)) and a two-step self-etching system (Clearfil SE Bond) were used. The effectiveness of phosphoric acid selective etching of enamel margins was also evaluated. Fifty-six cavities were restored with each adhesive system and divided into two subgroups (n=28; etch and non-etch). All 112 cavities were restored with the nanohybrid composite Esthet.X HD. The clinical effectiveness of restorations was recorded in terms of retention, marginal integrity, marginal staining, caries recurrence, and postoperative sensitivity after 3, 6, 12, 18, and 24 months (modified United States Public Health Service). The Friedman test detected significant differences only after 18 months for marginal staining in the groups Clearfil SE non-etch (p=0.009) and Xeno V(+) etch (p=0.004). One restoration was lost during the trial (Xeno V(+) etch; p>0.05). Although an increase in marginal staining was recorded for groups Clearfil SE non-etch and Xeno V(+) etch, the clinical effectiveness of restorations was considered acceptable for the single-step and two-step self-etching systems with or without selective enamel etching in this 24-month clinical trial.
Directory of Open Access Journals (Sweden)
Mingjie Wang
2016-01-01
Full Text Available For the frequency response analysis of acoustic field with random and interval parameters, a nonintrusive uncertain analysis method named Polynomial Chaos Response Surface (PCRS method is proposed. In the proposed method, the polynomial chaos expansion method is employed to deal with the random parameters, and the response surface method is used to handle the interval parameters. The PCRS method does not require efforts to modify model equations due to its nonintrusive characteristic. By means of the PCRS combined with the existing interval analysis method, the lower and upper bounds of expectation, variance, and probability density function of the frequency response can be efficiently evaluated. Two numerical examples are conducted to validate the accuracy and efficiency of the approach. The results show that the PCRS method is more efficient compared to the direct Monte Carlo simulation (MCS method based on the original numerical model without causing significant loss of accuracy.
Transverse spin correlations of the random transverse-field Ising model
Iglói, Ferenc; Kovács, István A.
2018-03-01
The critical behavior of the random transverse-field Ising model in finite-dimensional lattices is governed by infinite disorder fixed points, several properties of which have already been calculated by the use of the strong disorder renormalization-group (SDRG) method. Here we extend these studies and calculate the connected transverse-spin correlation function by a numerical implementation of the SDRG method in d =1 ,2 , and 3 dimensions. At the critical point an algebraic decay of the form ˜r-ηt is found, with a decay exponent being approximately ηt≈2 +2 d . In d =1 the results are related to dimer-dimer correlations in the random antiferromagnetic X X chain and have been tested by numerical calculations using free-fermionic techniques.
Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks
DEFF Research Database (Denmark)
Heide, J; Zhang, Qi; Fitzek, F H P
2013-01-01
This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...... reduction in the number of transmitted packets can be achieved. However, NC introduces additional computations and potentially a non-negligible transmission overhead, both of which depend on the chosen coding parameters. Therefore it is necessary to consider the trade-off that these coding parameters...... present in order to obtain the lowest energy consumption per transmitted bit. This problem is analyzed and suitable coding parameters are determined for the popular Tmote Sky platform. Compared to the use of traditional RLNC, these parameters enable a reduction in the energy spent per bit which grows...
Energy Technology Data Exchange (ETDEWEB)
Chandonia, John-Marc; Brenner, Steven E.
2004-07-14
The structural genomics project is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy which is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the Pfam5000 strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These include including complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at EBI. Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68 percent of all prokaryotic proteins (covering 59 percent of residues) and 61 percent of eukaryotic proteins (40 percent of residues). More fine-grained coverage which would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: a significant fraction (about 30-40 percent of the proteins, and 40-60 percent of the residues) of each proteome is classified in small
Day-ahead load forecast using random forest and expert input selection
International Nuclear Information System (INIS)
Lahouar, A.; Ben Hadj Slama, J.
2015-01-01
Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar
Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums
DEFF Research Database (Denmark)
Ding, Shilin; Cong, Gao; Lin, Chin-Yew
2008-01-01
Online forum discussions often contain vast amounts of questions that are the focuses of discussions. Extracting contexts and answers together with the questions will yield not only a coherent forum summary but also a valuable QA knowledge base. In this paper, we propose a general framework based...... on Conditional Random Fields (CRFs) to detect the contexts and answers of questions from forum threads. We improve the basic framework by Skip-chain CRFs and 2D CRFs to better accommodate the features of forums for better performance. Experimental results show that our techniques are very promising....
A heuristic for the distribution of point counts for random curves over a finite field.
Achter, Jeffrey D; Erman, Daniel; Kedlaya, Kiran S; Wood, Melanie Matchett; Zureick-Brown, David
2015-04-28
How many rational points are there on a random algebraic curve of large genus g over a given finite field Fq? We propose a heuristic for this question motivated by a (now proven) conjecture of Mumford on the cohomology of moduli spaces of curves; this heuristic suggests a Poisson distribution with mean q+1+1/(q-1). We prove a weaker version of this statement in which g and q tend to infinity, with q much larger than g. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
International Nuclear Information System (INIS)
Watanabe, Shuichi; Kudo, Hiroyuki; Saito, Tsuneo
1993-01-01
In this paper, we propose a new reconstruction algorithm based on MAP (maximum a posteriori probability) estimation principle for emission tomography. To improve noise suppression properties of the conventional ML-EM (maximum likelihood expectation maximization) algorithm, direct three-dimensional reconstruction that utilizes intensity correlations between adjacent transaxial slices is introduced. Moreover, to avoid oversmoothing of edges, a priori knowledge of RI (radioisotope) distribution is represented by using a doubly-stochastic image model called the compound Gauss-Markov random field. The a posteriori probability is maximized by using the iterative GEM (generalized EM) algorithm. Computer simulation results are shown to demonstrate validity of the proposed algorithm. (author)
Reduced Wiener Chaos representation of random fields via basis adaptation and projection
Energy Technology Data Exchange (ETDEWEB)
Tsilifis, Panagiotis, E-mail: tsilifis@usc.edu [Department of Mathematics, University of Southern California, Los Angeles, CA 90089 (United States); Department of Civil Engineering, University of Southern California, Los Angeles, CA 90089 (United States); Ghanem, Roger G., E-mail: ghanem@usc.edu [Department of Civil Engineering, University of Southern California, Los Angeles, CA 90089 (United States)
2017-07-15
A new characterization of random fields appearing in physical models is presented that is based on their well-known Homogeneous Chaos expansions. We take advantage of the adaptation capabilities of these expansions where the core idea is to rotate the basis of the underlying Gaussian Hilbert space, in order to achieve reduced functional representations that concentrate the induced probability measure in a lower dimensional subspace. For a smooth family of rotations along the domain of interest, the uncorrelated Gaussian inputs are transformed into a Gaussian process, thus introducing a mesoscale that captures intermediate characteristics of the quantity of interest.
Light absorption in disordered semiconductors with a random coulomb-type field
International Nuclear Information System (INIS)
Arbuzov, Yu.D.; Evdokimov, V.M.; Kolenkin, M.Yu.
1988-01-01
A method is proposed for the formulation of an asymptotic series for the light absorption coefficient in disordered semiconductors with a random field of the Coulomb type. It is shown that the series is obtained by expanding the exponent of an exponential function in powers of a parameter proportional to (E g - ℎω) -1/3 , where E g is the band gap of the semiconductor, and ℎω is the photon energy. The first three terms of the series are calculated in explicit form
Colour and rotation invariant textural features based on Markov random fields
Czech Academy of Sciences Publication Activity Database
Vácha, Pavel; Haindl, Michal; Suk, Tomáš
2011-01-01
Roč. 32, č. 6 (2011), s. 771-779 ISSN 0167-8655 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Image modelling * colour texture * Illumination invariance * Markov random field * rotation invariance Subject RIV: BD - Theory of Information Impact factor: 1.034, year: 2011 http://library.utia.cas.cz/separaty/2011/RO/vacha-0357314.pdf
Directory of Open Access Journals (Sweden)
Pablo Gregori
2014-03-01
Full Text Available This paper represents a survey of recent advances in modeling of space or space-time Gaussian Random Fields (GRF, tools of Geostatistics at hand for the understanding of special cases of noise in image analysis. They can be used when stationarity or isotropy are unrealistic assumptions, or even when negative covariance between some couples of locations are evident. We show some strategies in order to escape from these restrictions, on the basis of rich classes of well known stationary or isotropic non negative covariance models, and through suitable operations, like linear combinations, generalized means, or with particular Fourier transforms.
International Nuclear Information System (INIS)
Kiskis, J.; Narayanan, R.; Vranas, P.
1993-01-01
The authors study the random walk representation of the two-point function in statistical mechanics models near the critical point. Using standard scaling arguments, the authors show that the critical exponent v describing the vanishing of the physical mass at the critical point is equal to v θ /d w , where d w is the Hausdorff dimension of the walk, and v θ = var-phi, where var-phi is the crossover exponent known in the context of field theory. This implies that the Hausdorff dimension of the walk is var-phi/v for O(N) models. 3 refs
Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection
Elfers, Carsten; Horstmann, Mirko; Sohr, Karsten; Herzog, Otthein
Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine learning techniques have been proposed. However, one critical issue is that the amount of reference data that contains serious intrusions is very sparse. In this paper we present an inference process with linear chain conditional random fields that aims to solve this problem by using domain knowledge about the alerts of different intrusion sensors represented in an ontology.
Sharp Trapping Boundaries in the Random Walk of Interplanetary Magnetic Field Lines
Ruffolo, D.; Chuychai, P.; Meechai, J.; Pongkitiwanichkul, P.; Kimpraphan, N.; Matthaeus, W. H.; Rowlands, G.
2004-05-01
Although magnetic field lines in space are believed to undergo a diffusive random walk in the long-distance limit, observed dropouts of solar energetic particles, as well as computer simulations, indicate sharply defined filaments in which interplanetary magnetic field lines have been temporarily trapped. We identify mechanisms that can explain such sharp boundaries in the framework of 2D+slab turbulence, a model that provides a good explanation of solar wind turbulence spectra and the parallel transport of solar energetic particles. Local trapping boundaries (LTBs) are empirically defined as trajectories of 2D turbulence where the mean 2D field is a local maximum. In computer simulations, the filaments (or ``islands'' in the two dimensions perpendicular to the mean field) that are most resistant to slab diffusion correspond closely to the mathematically defined LTBs, that is, there is a mathematical prescription for defining the trapping regions. Furthermore, we provide computational evidence and a theoretical explanation that strong 2D turbulence can inhibit diffusion due to the slab component. Therefore, while these filaments are basically defined by the small-scale topology of 2D turbulence, there can be sharp trapping boundaries where the 2D field is strongest. This work was supported by the Thailand Research Fund, the Rachadapisek Sompoj Fund of Chulalongkorn University, and NASA Grant NAG5-11603. G.R. thanks Mahidol University for its hospitality and the Thailand Commission for Higher Education for travel support.
Markov random field and Gaussian mixture for segmented MRI-based partial volume correction in PET
International Nuclear Information System (INIS)
Bousse, Alexandre; Thomas, Benjamin A; Erlandsson, Kjell; Hutton, Brian F; Pedemonte, Stefano; Ourselin, Sébastien; Arridge, Simon
2012-01-01
In this paper we propose a segmented magnetic resonance imaging (MRI) prior-based maximum penalized likelihood deconvolution technique for positron emission tomography (PET) images. The model assumes the existence of activity classes that behave like a hidden Markov random field (MRF) driven by the segmented MRI. We utilize a mean field approximation to compute the likelihood of the MRF. We tested our method on both simulated and clinical data (brain PET) and compared our results with PET images corrected with the re-blurred Van Cittert (VC) algorithm, the simplified Guven (SG) algorithm and the region-based voxel-wise (RBV) technique. We demonstrated our algorithm outperforms the VC algorithm and outperforms SG and RBV corrections when the segmented MRI is inconsistent (e.g. mis-segmentation, lesions, etc) with the PET image. (paper)
Experimental vibroacoustic testing of plane panels using synthesized random pressure fields.
Robin, Olivier; Berry, Alain; Moreau, Stéphane
2014-06-01
The experimental reproduction of random pressure fields on a plane panel and corresponding induced vibrations is studied. An open-loop reproduction strategy is proposed that uses the synthetic array concept, for which a small array element is moved to create a large array by post-processing. Three possible approaches are suggested to define the complex amplitudes to be imposed to the reproduction sources distributed on a virtual plane facing the panel to be tested. Using a single acoustic monopole, a scanning laser vibrometer and a baffled simply supported aluminum panel, experimental vibroacoustic indicators such as the Transmission Loss for Diffuse Acoustic Field, high-speed subsonic and supersonic Turbulent Boundary Layer excitations are obtained. Comparisons with simulation results obtained using a commercial software show that the Transmission Loss estimation is possible under both excitations. Moreover and as a complement to frequency domain indicators, the vibroacoustic behavior of the panel can be studied in the wave number domain.
Magnetic field line random walk in two-dimensional dynamical turbulence
Wang, J. F.; Qin, G.; Ma, Q. M.; Song, T.; Yuan, S. B.
2017-08-01
The field line random walk (FLRW) of magnetic turbulence is one of the important topics in plasma physics and astrophysics. In this article, by using the field line tracing method, the mean square displacement (MSD) of FLRW is calculated on all possible length scales for pure two-dimensional turbulence with the damping dynamical model. We demonstrate that in order to describe FLRW with the damping dynamical model, a new dimensionless quantity R is needed to be introduced. On different length scales, dimensionless MSD shows different relationships with the dimensionless quantity R. Although the temporal effect affects the MSD of FLRW and even changes regimes of FLRW, it does not affect the relationship between the dimensionless MSD and dimensionless quantity R on all possible length scales.
Baumgarten, Daniel; Eichardt, Roland; Crevecoeur, Guillaume; Supriyanto, Eko; Haueisen, Jens
2013-01-01
Biomedical applications of magnetic nanoparticles require a precise knowledge of their biodistribution. From multi-channel magnetorelaxometry measurements, this distribution can be determined by means of inverse methods. It was recently shown that the combination of sequential inhomogeneous excitation fields in these measurements is favorable regarding the reconstruction accuracy when compared to homogeneous activation . In this paper, approaches for the determination of activation sequences for these measurements are investigated. Therefor, consecutive activation of single coils, random activation patterns and families of m-sequences are examined in computer simulations involving a sample measurement setup and compared with respect to the relative condition number of the system matrix. We obtain that the values of this condition number decrease with larger number of measurement samples for all approaches. Random sequences and m-sequences reveal similar results with a significant reduction of the required number of samples. We conclude that the application of pseudo-random sequences for sequential activation in the magnetorelaxometry imaging of magnetic nanoparticles considerably reduces the number of required sequences while preserving the relevant measurement information.
Modified random hinge transport mechanics and multiple scattering step-size selection in EGS5
International Nuclear Information System (INIS)
Wilderman, S.J.; Bielajew, A.F.
2005-01-01
The new transport mechanics in EGS5 allows for significantly longer electron transport step sizes and hence shorter computation times than required for identical problems in EGS4. But as with all Monte Carlo electron transport algorithms, certain classes of problems exhibit step-size dependencies even when operating within recommended ranges, sometimes making selection of step-sizes a daunting task for novice users. Further contributing to this problem, because of the decoupling of multiple scattering and continuous energy loss in the dual random hinge transport mechanics of EGS5, there are two independent step sizes in EGS5, one for multiple scattering and one for continuous energy loss, each of which influences speed and accuracy in a different manner. Further, whereas EGS4 used a single value of fractional energy loss (ESTEPE) to determine step sizes at all energies, to increase performance by decreasing the amount of effort expended simulating lower energy particles, EGS5 permits the fractional energy loss values which are used to determine both the multiple scattering and continuous energy loss step sizes to vary with energy. This results in requiring the user to specify four fractional energy loss values when optimizing computations for speed. Thus, in order to simplify step-size selection and to mitigate step-size dependencies, a method has been devised to automatically optimize step-size selection based on a single material dependent input related to the size of problem tally region. In this paper we discuss the new transport mechanics in EGS5 and describe the automatic step-size optimization algorithm. (author)
Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure
International Nuclear Information System (INIS)
Yang Xuhua; Sun Bao; Wang Bo; Sun Youxian
2010-01-01
Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper. (general)
Dynamical effects and the critical behavior of random-field systems (invited)
International Nuclear Information System (INIS)
Shapir, Y.
1985-01-01
A variety of phenomena is observed experimentally in random-field (RF) systems realized by the application of an external field to diluted antiferromagnets. At low temperatures, infinitely long hysteretic effects are manifested by the history dependence of the final states: long-range order is observed if the field is applied after cooling, while domain states are reached when field cooled. While no indications for critical fluctuations are detected in 2-D systems, scaling behavior, for both the correlation length and the specific heat, is observed in 3-D systems over an intermediate range of temperatures. The related critical properties seem to be well described by the corresponding ones in the 2-D pure Ising model. The renormalization-group approach, which yields for the equilibrium critical exponents their values of the pure model in d-2 dimensions, is reviewed. A generalization of the dimensional-reduction approach, which accounts self-consistently for renormalized responses of the RF system, is presented. The dynamical effects are implicitly incorporated through the variation in the critical response between the local and the global regimes, associated with short- and long-time scales, respectively. In both regimes the lower critical dimension is found to be d = 2 in accordance with stability arguments. The short-time critical behavior indicates a dimensional reduction by one for the 3-D thermal exponents, in agreement with the experimental results
Dynamical effects and the critical behavior of random-field systems
International Nuclear Information System (INIS)
Shapir, Y.
1985-01-01
A variety of phenomena is observed experimentally in random-field (RF) systems realized by the application of an external field to diluted antiferromagnets. At low temperatures, infinitely long hysteretic effects are manifested by the history dependence of the final states: long-range order is observed if the field is applied after cooling, while domain states are reached when field cooled. While no indications for critical fluctuations are detected in 2-D systems, scaling behavior, for both the correlation length and the specific heat, is observed in 3-D systems over an intermediate range of temperatures. The related critical properties seem to be well described by the corresponding ones in the 2-D pure Ising model. The renormalization-group approach, which yields for the equilibrium critical exponents their values of the pure model in d-2 dimensions, is reviewed. A generalization of the dimensional-reduction approach, which accounts self-consistently for renormalized responses of the RF system, is presented. The dynamical effects are implicitly incorporated through the variation in the critical response between the local and the global regimes, associated with short- and long-time scales, respectively. In both regimes the lower critical dimension is found to be d = 2 in accordance with stability arguments. The short-time critical behavior indicates a dimensional reduction by one for the 3-D thermal exponents, in agreement with the experimental results. 37 references
The time-dependent relativistic mean-field theory and the random phase approximation
International Nuclear Information System (INIS)
Ring, P.; Ma, Zhong-yu; Van Giai, Nguyen; Vretenar, D.; Wandelt, A.; Cao, Li-gang
2001-01-01
The Relativistic Random Phase Approximation (RRPA) is derived from the Time-Dependent Relativistic Mean-Field (TD RMF) theory in the limit of small amplitude oscillations. In the no-sea approximation of the RMF theory, the RRPA configuration space includes not only the usual particle-hole ph-states, but also αh-configurations, i.e. pairs formed from occupied states in the Fermi sea and empty negative-energy states in the Dirac sea. The contribution of the negative-energy states to the RRPA matrices is examined in a schematic model, and the large effect of Dirac-sea states on isoscalar strength distributions is illustrated for the giant monopole resonance in 116 Sn. It is shown that, because the matrix elements of the time-like component of the vector-meson fields which couple the αh-configurations with the ph-configurations are strongly reduced with respect to the corresponding matrix elements of the isoscalar scalar meson field, the inclusion of states with unperturbed energies more than 1.2 GeV below the Fermi energy has a pronounced effect on giant resonances with excitation energies in the MeV region. The influence of nuclear magnetism, i.e. the effect of the spatial components of the vector fields is examined, and the difference between the nonrelativistic and relativistic RPA predictions for the nuclear matter compression modulus is explained
The adverse effect of selective cyclooxygenase-2 inhibitor on random skin flap survival in rats.
Directory of Open Access Journals (Sweden)
Haiyong Ren
Full Text Available BACKGROUND: Cyclooxygenase-2(COX-2 inhibitors provide desired analgesic effects after injury or surgery, but evidences suggested they also attenuate wound healing. The study is to investigate the effect of COX-2 inhibitor on random skin flap survival. METHODS: The McFarlane flap model was established in 40 rats and evaluated within two groups, each group gave the same volume of Parecoxib and saline injection for 7 days. The necrotic area of the flap was measured, the specimens of the flap were stained with haematoxylin-eosin(HE for histologic analysis. Immunohistochemical staining was performed to analyse the level of VEGF and COX-2 . RESULTS: 7 days after operation, the flap necrotic area ratio in study group (66.65 ± 2.81% was significantly enlarged than that of the control group(48.81 ± 2.33%(P <0.01. Histological analysis demonstrated angiogenesis with mean vessel density per mm(2 being lower in study group (15.4 ± 4.4 than in control group (27.2 ± 4.1 (P <0.05. To evaluate the expression of COX-2 and VEGF protein in the intermediate area II in the two groups by immunohistochemistry test .The expression of COX-2 in study group was (1022.45 ± 153.1, and in control group was (2638.05 ± 132.2 (P <0.01. The expression of VEGF in the study and control groups were (2779.45 ± 472.0 vs (4938.05 ± 123.6(P <0.01.In the COX-2 inhibitor group, the expressions of COX-2 and VEGF protein were remarkably down-regulated as compared with the control group. CONCLUSION: Selective COX-2 inhibitor had adverse effect on random skin flap survival. Suppression of neovascularization induced by low level of VEGF was supposed to be the biological mechanism.
Application of random coherence order selection in gradient-enhanced multidimensional NMR
International Nuclear Information System (INIS)
Bostock, Mark J.; Nietlispach, Daniel
2016-01-01
Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1 -norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1 -norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended
Collection of ions in a plasma by magnetic field acceleration with selective polarization
International Nuclear Information System (INIS)
Forsen, H.K.
1976-01-01
Method and apparatus are described for generating and accelerating ions in a vapor by use of relatively polarized laser radiation and a magnetic field. As applied to uranium isotope enrichment, a flowing uranium vapor has particles of the 235 U isotope type selectively ionized by laser radiation and the ionized flow is subjected to a transverse gradient in a magnetic field. The magnetic field gradient induces an acceleration on the ionized particles of 235 U which deflects them from their normal flow path toward a collecting structure. High magnetic field and corresponding high ion accelerations are achieved without loss in ionization selectivity by maintaining a polarization between the applied laser radiation and magnetic field which minimizes Zeeman splitting of the uranium energy states
Wetting and layering transitions of a spin-1/2 Ising model in a random transverse field
International Nuclear Information System (INIS)
Bahmad, L.; Benyoussef, A.; El-Kenz, A.; Ez-Zahraouy, H.
2000-09-01
The effect of a random transverse field (RTF) on the wetting and layering transitions of a spin-1/2 Ising model, in the presence of bulk and surface fields, is studied within an effective field theory by using the differential operator technique. Indeed, the dependencies of the wetting temperature and wetting transverse field on the probability of the presence of a transverse field are established. For specific values of the surface field we show the existence of a critical probability p, above which wetting and layering transitions disappear. (author)
Random genetic drift, natural selection, and noise in human cranial evolution.
Roseman, Charles C
2016-08-01
This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Anderson, David A.; Paradis, Eric G.; Raithel, Georg
2018-01-01
We present a hybrid atomic sensor that realizes radio-frequency electric field detection with intrinsic field amplification and polarization selectivity for robust high-sensitivity field measurement. The hybrid sensor incorporates a passive resonator element integrated with an atomic vapor cell that provides amplification and polarization selectivity for detection of incident radio-frequency fields. The amplified intra-cavity radio-frequency field is measured by atoms using a quantum-optical ...
Polarization dynamics and polarization time of random three-dimensional electromagnetic fields
International Nuclear Information System (INIS)
Voipio, Timo; Setaelae, Tero; Shevchenko, Andriy; Friberg, Ari T.
2010-01-01
We investigate the polarization dynamics of random, stationary three-dimensional (3D) electromagnetic fields. For analyzing the time evolution of the instantaneous polarization state, two intensity-normalized polarization autocorrelation functions are introduced, one based on a geometric approach with the Poincare vectors and the other on energy considerations with the Jones vectors. Both approaches lead to the same conclusions on the rate and strength of the polarization dynamics and enable the definition of a polarization time over which the state of polarization remains essentially unchanged. For fields obeying Gaussian statistics, the two correlation functions are shown to be expressible in terms of quantities characterizing partial 3D polarization and electromagnetic coherence. The 3D degree of polarization is found to have the same meaning in the 3D polarization dynamics as the usual two-dimensional (2D) degree of polarization does with planar fields. The formalism is demonstrated with several examples, and it is expected to be useful in applications dealing with polarization fluctuations of 3D light.
Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.
Wang, Xiao; Li, Guo-Zheng
2013-03-12
Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.
Technical Note: Response measurement for select radiation detectors in magnetic fields
Energy Technology Data Exchange (ETDEWEB)
Reynolds, M., E-mail: michaelreynolds@ualberta.net [Department of Oncology, Medical Physics Division, University of Alberta, 11560 University Avenue, Edmonton, Alberta T6G 1Z2 (Canada); Fallone, B. G. [Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada and Departments of Oncology and Physics, University of Alberta, 11560 University Avenue, Edmonton, Alberta T6G 1Z2 (Canada); Rathee, S. [Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada and Department of Oncology, Medical Physics Division,University of Alberta, 11560 University Avenue, Edmonton, Alberta T6G 1Z2 (Canada)
2015-06-15
Purpose: Dose response to applied magnetic fields for ion chambers and solid state detectors has been investigated previously for the anticipated use in linear accelerator–magnetic resonance devices. In this investigation, the authors present the measured response of selected radiation detectors when the magnetic field is applied in the same direction as the radiation beam, i.e., a longitudinal magnetic field, to verify previous simulation only data. Methods: The dose response of a PR06C ion chamber, PTW60003 diamond detector, and IBA PFD diode detector is measured in a longitudinal magnetic field. The detectors are irradiated with buildup caps and their long axes either parallel or perpendicular to the incident photon beam. In each case, the magnetic field dose response is reported as the ratio of detector signals with to that without an applied longitudinal magnetic field. The magnetic field dose response for each unique orientation as a function of magnetic field strength was then compared to the previous simulation only studies. Results: The measured dose response of each detector in longitudinal magnetic fields shows no discernable response up to near 0.21 T. This result was expected and matches the previously published simulation only results, showing no appreciable dose response with magnetic field. Conclusions: Low field longitudinal magnetic fields have been shown to have little or no effect on the dose response of the detectors investigated and further lend credibility to previous simulation only studies.
Selection of 3013 Containers for Field Surveillance. Fiscal Year 2016 Update
Energy Technology Data Exchange (ETDEWEB)
Kelly, Elizabeth J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Berg, John M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cheadle, Jesse [Savannah River Nuclear Solutions, LLC, (SRNS), Aiken, SC (United States); McClard, James [Project Services Group LLC, Suwanee, GA (United States); Veirs, Douglas Kirk [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-04-19
This update is the eighth in a series of reports that document the binning and sample selection of 3013 containers for the Field Surveillance program as part of the Integrated Surveillance Program. This report documents changes made to both the container binning assignments and the sample selection approach. Binning changes documented in this update are a result of changes to the prompt gamma calibration curves and the reassignment of a small number of Hanford items from the Pressure bin to the Pressure and Corrosion (P&C) bin. Field Surveillance sample selection changes are primarily a result of focusing future destructive examinations (DEs) on the potential for stress corrosion cracking in higher moisture containers in the P&C bin. The decision to focus the Field Surveillance program on higher moisture items is based on findings from both the Shelf-life testing program and DEs.
Cross-covariance functions for multivariate random fields based on latent dimensions
Apanasovich, T. V.
2010-02-16
The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable and computationally feasible classes of cross-covariance functions in closed form. We focus on spatio-temporal cross-covariance functions that can be nonseparable, asymmetric and can have different covariance structures, for instance different smoothness parameters, in each component. We discuss estimation of these models and perform a small simulation study to demonstrate our approach. We illustrate our methodology on a trivariate spatio-temporal pollution dataset from California and demonstrate that our cross-covariance performs better than other competing models. © 2010 Biometrika Trust.
Document page structure learning for fixed-layout e-books using conditional random fields
Tao, Xin; Tang, Zhi; Xu, Canhui
2013-12-01
In this paper, a model is proposed to learn logical structure of fixed-layout document pages by combining support vector machine (SVM) and conditional random fields (CRF). Features related to each logical label and their dependencies are extracted from various original Portable Document Format (PDF) attributes. Both local evidence and contextual dependencies are integrated in the proposed model so as to achieve better logical labeling performance. With the merits of SVM as local discriminative classifier and CRF modeling contextual correlations of adjacent fragments, it is capable of resolving the ambiguities of semantic labels. The experimental results show that CRF based models with both tree and chain graph structures outperform the SVM model with an increase of macro-averaged F1 by about 10%.
Anomalous transport in fluid field with random waiting time depending on the preceding jump length
International Nuclear Information System (INIS)
Zhang Hong; Li Guo-Hua
2016-01-01
Anomalous (or non-Fickian) transport behaviors of particles have been widely observed in complex porous media. To capture the energy-dependent characteristics of non-Fickian transport of a particle in flow fields, in the present paper a generalized continuous time random walk model whose waiting time probability distribution depends on the preceding jump length is introduced, and the corresponding master equation in Fourier–Laplace space for the distribution of particles is derived. As examples, two generalized advection-dispersion equations for Gaussian distribution and lévy flight with the probability density function of waiting time being quadratic dependent on the preceding jump length are obtained by applying the derived master equation. (paper)
Finite nucleus Dirac mean field theory and random phase approximation using finite B splines
International Nuclear Information System (INIS)
McNeil, J.A.; Furnstahl, R.J.; Rost, E.; Shepard, J.R.; Department of Physics, University of Maryland, College Park, Maryland 20742; Department of Physics, University of Colorado, Boulder, Colorado 80309)
1989-01-01
We calculate the finite nucleus Dirac mean field spectrum in a Galerkin approach using finite basis splines. We review the method and present results for the relativistic σ-ω model for the closed-shell nuclei 16 O and 40 Ca. We study the convergence of the method as a function of the size of the basis and the closure properties of the spectrum using an energy-weighted dipole sum rule. We apply the method to the Dirac random-phase-approximation response and present results for the isoscalar 1/sup -/ and 3/sup -/ longitudinal form factors of 16 O and 40 Ca. We also use a B-spline spectral representation of the positive-energy projector to evaluate partial energy-weighted sum rules and compare with nonrelativistic sum rule results
Adaptive Markov Random Fields for Example-Based Super-resolution of Faces
Stephenson, Todd A.; Chen, Tsuhan
2006-12-01
Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resolution). For example, hallucination and Markov random field (MRF) methods use examples drawn from the same domain as the image being enhanced to determine what the missing high-frequency information is likely to be. We propose to use even stronger prior information by extending MRF-based super-resolution to use adaptive observation and transition functions, that is, to make these functions region-dependent. We show with face images how we can adapt the modeling for each image patch so as to improve the resolution.
Anomalous transport in fluid field with random waiting time depending on the preceding jump length
Zhang, Hong; Li, Guo-Hua
2016-11-01
Anomalous (or non-Fickian) transport behaviors of particles have been widely observed in complex porous media. To capture the energy-dependent characteristics of non-Fickian transport of a particle in flow fields, in the present paper a generalized continuous time random walk model whose waiting time probability distribution depends on the preceding jump length is introduced, and the corresponding master equation in Fourier-Laplace space for the distribution of particles is derived. As examples, two generalized advection-dispersion equations for Gaussian distribution and lévy flight with the probability density function of waiting time being quadratic dependent on the preceding jump length are obtained by applying the derived master equation. Project supported by the Foundation for Young Key Teachers of Chengdu University of Technology, China (Grant No. KYGG201414) and the Opening Foundation of Geomathematics Key Laboratory of Sichuan Province, China (Grant No. scsxdz2013009).
Zhang, Y.; Li, F.; Zhang, S.; Hao, W.; Zhu, T.; Yuan, L.; Xiao, F.
2017-09-01
In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.
A Coupled Hidden Markov Random Field Model for Simultaneous Face Clustering and Tracking in Videos
Wu, Baoyuan
2016-10-25
Face clustering and face tracking are two areas of active research in automatic facial video processing. They, however, have long been studied separately, despite the inherent link between them. In this paper, we propose to perform simultaneous face clustering and face tracking from real world videos. The motivation for the proposed research is that face clustering and face tracking can provide useful information and constraints to each other, thus can bootstrap and improve the performances of each other. To this end, we introduce a Coupled Hidden Markov Random Field (CHMRF) to simultaneously model face clustering, face tracking, and their interactions. We provide an effective algorithm based on constrained clustering and optimal tracking for the joint optimization of cluster labels and face tracking. We demonstrate significant improvements over state-of-the-art results in face clustering and tracking on several videos.
Evaluating Consumer m-Health Services for Promoting Healthy Eating: A Randomized Field Experiment.
Kato-Lin, Yi-Chin; Padman, Rema; Downs, Julie; Abhishek, Vibhanshu
2015-01-01
Mobile apps have great potential to deliver promising interventions to engage consumers and change their health-related behaviors, such as healthy eating. Currently, the interventions for promoting healthy eating are either too onerous to keep consumers engaged or too restrictive to keep consumers connected with healthcare professionals. In addition, while social media allows individuals to receive information from many sources, it is unclear how peer support interacts with professional support in the context of such interventions. This study proposes and evaluates three mobile-enabled interventions to address these challenges. We examine their effects on user engagement and food choices via a 4-month randomized field experiment. Mixed models provide strong evidence of the positive effect of image-based dietitian support and negative effects of peer support, and moderate evidence of the positive effects of mobile-based visual diary, highlighting the value of mobile apps for delivering advanced interventions to engage users and facilitate behavior change.
Liu, Dan; Liu, Xuejun; Wu, Yiguang
2018-04-24
This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.
Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields
Directory of Open Access Journals (Sweden)
Hee-Deok Yang
2014-12-01
Full Text Available Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D space. In this research, we use 3D depth information from hand motions, generated from Microsoft’s Kinect sensor and apply a hierarchical conditional random field (CRF that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%.
Directory of Open Access Journals (Sweden)
Dan Liu
2018-04-01
Full Text Available This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN and a continuous pairwise Conditional Random Field (CRF model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.
Adaptive Markov Random Fields for Example-Based Super-resolution of Faces
Directory of Open Access Journals (Sweden)
Stephenson Todd A
2006-01-01
Full Text Available Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resolution. For example, hallucination and Markov random field (MRF methods use examples drawn from the same domain as the image being enhanced to determine what the missing high-frequency information is likely to be. We propose to use even stronger prior information by extending MRF-based super-resolution to use adaptive observation and transition functions, that is, to make these functions region-dependent. We show with face images how we can adapt the modeling for each image patch so as to improve the resolution.
Birkelund, Gunn Elisabeth; Chan, Tak Wing; Ugreninov, Elisabeth; Midtbøen, Arnfinn H; Rogstad, Jon
2018-01-24
Terrorist attacks are known to influence public opinion. But do they also change behaviour? We address this question by comparing the results of two identical randomized field experiments on ethnic discrimination in hiring that we conducted in Oslo. The first experiment was conducted before the 2011 terrorist attacks in Norway; the second experiment was conducted after the attacks. In both experiments, applicants with a typical Pakistani name were significantly less likely to get a job interview compared to those with a typical Norwegian name. But the ethnic gap in call-back rates were very similar in the two experiments. Thus, Pakistanis in Norway still experienced the same level of discrimination, despite claims that Norwegians have become more positive about migrants after the far-right, anti-migrant terrorist attacks of 2011. © London School of Economics and Political Science 2018.
High energy X-ray phase and dark-field imaging using a random absorption mask.
Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal
2016-07-28
High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science.
Hidden State Conditional Random Field for Abnormal Activity Recognition in Smart Homes
Directory of Open Access Journals (Sweden)
Yu Tong
2015-03-01
Full Text Available As the number of elderly people has increased worldwide, there has been a surge of research into assistive technologies to provide them with better care by recognizing their normal and abnormal activities. However, existing abnormal activity recognition (AAR algorithms rarely consider sub-activity relations when recognizing abnormal activities. This paper presents an application of the Hidden State Conditional Random Field (HCRF method to detect and assess abnormal activities that often occur in elderly persons’ homes. Based on HCRF, this paper designs two AAR algorithms, and validates them by comparing them with a feature vector distance based algorithm in two experiments. The results demonstrate that the proposed algorithms favorably outperform the competitor, especially when abnormal activities have same sensor type and sensor number as normal activities.
A novel approach to assess the treatment response using Gaussian random field in PET
Energy Technology Data Exchange (ETDEWEB)
Wang, Mengdie [Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China and Center for Advanced Medical Imaging Science, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Guo, Ning [Center for Advanced Medical Imaging Science, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Hu, Guangshu; Zhang, Hui, E-mail: hzhang@mail.tsinghua.edu.cn, E-mail: li.quanzheng@mgh.harvard.edu [Department of Biomedical Engineering, Tsinghua University, Beijing 100084 (China); El Fakhri, Georges; Li, Quanzheng, E-mail: hzhang@mail.tsinghua.edu.cn, E-mail: li.quanzheng@mgh.harvard.edu [Center for Advanced Medical Imaging Science, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114 and Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115 (United States)
2016-02-15
Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128{sup 2} pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response
International Nuclear Information System (INIS)
Ryutova, M.
1990-08-01
Effects of strong and random inhomogeneities of the magnetic fields, plasma density, and temperature in the solar atmosphere on the properties of magnetoacoustic waves of arbitrary amplitudes are studied. The procedure which allows one to obtain the averaged equation containing the nonlinearity of a wave, dispersion properties of a system, and dissipative effects is described. It is shown that depending on the statistical properties of the medium, different scenarios of wave propagation arise: in the predominance of dissipative effects the primary wave is damped away in the linear stage and the efficiency of heating due to inhomogeneities is much greater than that in homogeneous medium. Depending on the interplay of nonlinear and dispersion effects, the process of heating can be afforded through the formation of shocks or through the storing of energy in a system of solitons which are later damped away. Our computer simulation supports and extends the above theoretical investigations. In particular the enhanced dissipation of waves due to the strong and random inhomogeneities is observed and this is more pronounced for shorter waves
Directory of Open Access Journals (Sweden)
Yu-Hsun Hsu
2011-09-01
Full Text Available Nest site quality often affects nest success and the fitness of avian breeders. Vegetation structure and water depth are possible factors evaluated in nest-site selection by ground nesting birds in wetlands. Vegetation structure may affect the predation risk, and water depth is linked to the possibility of being flooded. We examined these two factors in the nest site selection of a wetland bird, the Greater Painted Snipe (Rostratula benghalensis benghalensis, in I-Lan, Taiwan. We found 17 Greater Painted Snipe nests in wet fallow fields. By paired comparisons, we found the breeders tended to nest on sites with higher vegetation coverage and lower water depth than random sites. No significant difference was found in the vegetation height between the nest sites and the paired random sites. Five nests failed to hatch due to flooding or predation. The preference for nest sites with low water depth may be an effort to avoid being flooded and the preference for dense vegetation coverage at nest sites may be a response to predation risk.
International Nuclear Information System (INIS)
Akıncı, Ümit
2012-01-01
The effect of the random magnetic field distribution on the phase diagrams and ground state magnetizations of the Ising nanowire has been investigated with effective field theory with correlations. Gaussian distribution has been chosen as a random magnetic field distribution. The variation of the phase diagrams with that distribution parameters has been obtained and some interesting results have been found such as disappearance of the reentrant behavior and first order transitions which appear in the case of discrete distributions. Also for single and double Gaussian distributions, ground state magnetizations for different distribution parameters have been determined which can be regarded as separate partially ordered phases of the system. - Highlights: ► We give the phase diagrams of the Ising nanowire under the continuous randomly distributed magnetic field. ► Ground state magnetization values obtained. ► Different partially ordered phases observed.
Ion-selective field-effect transitors. A sensor for lithium and calcium
International Nuclear Information System (INIS)
Kharitonov, A.B.; Petrukhin, O.M.; Nad', V.Yh.; Ypivakov, B.Ya.; Myasoedov, B.F.; Otmakhova, O.A.; Tal'roze, R.V.; Plateh, N.A.
1997-01-01
An Li-sensitive sensor based on a field-effect transistor with a tantalum pentoxide gate and a poly(vinyl chloride) membrane based on diethylene glycol bis-o-2-diphenylphosphinylmethyl phenyl ether is developed. THis sensor exhibits analytical characteristics close to those of a lithium-selective electrode analogous in membrane composition; it is insensitive to the concentration of hydrogen ions in the pH range 4.5-8.5. The service life of the sensor is no shorter than four months, which is comparable to the service life of the corresponding ion-selective electrode. A bifunctional sensor for Ca and Li is prepared based on membranes used for preparing the corresponding monofunctional ion-selective field-effect transistors; this sensor exhibits analytical characteristics close to those of ion-selective electrodes and monofunctional sensors. 12 refs., 6 figs., 2 tabs
Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces
Directory of Open Access Journals (Sweden)
Hossein Bashashati
2017-07-01
Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main diﬃculty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.
Stochastic generation of explicit pore structures by thresholding Gaussian random fields
Energy Technology Data Exchange (ETDEWEB)
Hyman, Jeffrey D., E-mail: jhyman@lanl.gov [Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721-0089 (United States); Computational Earth Science, Earth and Environmental Sciences (EES-16), and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87544 (United States); Winter, C. Larrabee, E-mail: winter@email.arizona.edu [Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721-0089 (United States); Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ 85721-0011 (United States)
2014-11-15
We provide a description and computational investigation of an efficient method to stochastically generate realistic pore structures. Smolarkiewicz and Winter introduced this specific method in pores resolving simulation of Darcy flows (Smolarkiewicz and Winter, 2010 [1]) without giving a complete formal description or analysis of the method, or indicating how to control the parameterization of the ensemble. We address both issues in this paper. The method consists of two steps. First, a realization of a correlated Gaussian field, or topography, is produced by convolving a prescribed kernel with an initial field of independent, identically distributed random variables. The intrinsic length scales of the kernel determine the correlation structure of the topography. Next, a sample pore space is generated by applying a level threshold to the Gaussian field realization: points are assigned to the void phase or the solid phase depending on whether the topography over them is above or below the threshold. Hence, the topology and geometry of the pore space depend on the form of the kernel and the level threshold. Manipulating these two user prescribed quantities allows good control of pore space observables, in particular the Minkowski functionals. Extensions of the method to generate media with multiple pore structures and preferential flow directions are also discussed. To demonstrate its usefulness, the method is used to generate a pore space with physical and hydrological properties similar to a sample of Berea sandstone. -- Graphical abstract: -- Highlights: •An efficient method to stochastically generate realistic pore structures is provided. •Samples are generated by applying a level threshold to a Gaussian field realization. •Two user prescribed quantities determine the topology and geometry of the pore space. •Multiple pore structures and preferential flow directions can be produced. •A pore space based on Berea sandstone is generated.
Effects of Force Field Selection on the Computational Ranking of MOFs for CO2 Separations.
Dokur, Derya; Keskin, Seda
2018-02-14
Metal-organic frameworks (MOFs) have been considered as highly promising materials for adsorption-based CO 2 separations. The number of synthesized MOFs has been increasing very rapidly. High-throughput molecular simulations are very useful to screen large numbers of MOFs in order to identify the most promising adsorbents prior to extensive experimental studies. Results of molecular simulations depend on the force field used to define the interactions between gas molecules and MOFs. Choosing the appropriate force field for MOFs is essential to make reliable predictions about the materials' performance. In this work, we performed two sets of molecular simulations using the two widely used generic force fields, Dreiding and UFF, and obtained adsorption data of CO 2 /H 2 , CO 2 /N 2 , and CO 2 /CH 4 mixtures in 100 different MOF structures. Using this adsorption data, several adsorbent evaluation metrics including selectivity, working capacity, sorbent selection parameter, and percent regenerability were computed for each MOF. MOFs were then ranked based on these evaluation metrics, and top performing materials were identified. We then examined the sensitivity of the MOF rankings to the force field type. Our results showed that although there are significant quantitative differences between some adsorbent evaluation metrics computed using different force fields, rankings of the top MOF adsorbents for CO 2 separations are generally similar: 8, 8, and 9 out of the top 10 most selective MOFs were found to be identical in the ranking for CO 2 /H 2 , CO 2 /N 2 , and CO 2 /CH 4 separations using Dreiding and UFF. We finally suggested a force field factor depending on the energy parameters of atoms present in the MOFs to quantify the robustness of the simulation results to the force field selection. This easily computable factor will be highly useful to determine whether the results are sensitive to the force field type or not prior to performing computationally demanding
Dahlberg, Peter D.; Boughter, Christopher T.; Faruk, Nabil F.; Hong, Lu; Koh, Young Hoon; Reyer, Matthew A.; Shaiber, Alon; Sherani, Aiman; Zhang, Jiacheng; Jureller, Justin E.; Hammond, Adam T.
2016-01-01
A standard wide field inverted microscope was converted to a spatially selective spectrally resolved microscope through the addition of a polarizing beam splitter, a pair of polarizers, an amplitude-mode liquid crystal-spatial light modulator, and a USB spectrometer. The instrument is capable of simultaneously imaging and acquiring spectra over user defined regions of interest. The microscope can also be operated in a bright-field mode to acquire absorption spectra of micron scale objects. Th...
Raghavan, Ramanujan T; Joshua, Mati
2017-10-01
We investigated the composition of preparatory activity of frontal eye field (FEF) neurons in monkeys performing a pursuit target selection task. In response to the orthogonal motion of a large and a small reward target, monkeys initiated pursuit biased toward the direction of large reward target motion. FEF neurons exhibited robust preparatory activity preceding movement initiation in this task. Preparatory activity consisted of two components, ramping activity that was constant across target selection conditions, and a flat offset in firing rates that signaled the target selection condition. Ramping activity accounted for 50% of the variance in the preparatory activity and was linked most strongly, on a trial-by-trial basis, to pursuit eye movement latency rather than to its direction or gain. The offset in firing rates that discriminated target selection conditions accounted for 25% of the variance in the preparatory activity and was commensurate with a winner-take-all representation, signaling the direction of large reward target motion rather than a representation that matched the parameters of the upcoming movement. These offer new insights into the role that the frontal eye fields play in target selection and pursuit control. They show that preparatory activity in the FEF signals more strongly when to move rather than where or how to move and suggest that structures outside the FEF augment its contributions to the target selection process. NEW & NOTEWORTHY We used the smooth eye movement pursuit system to link between patterns of preparatory activity in the frontal eye fields and movement during a target selection task. The dominant pattern was a ramping signal that did not discriminate between selection conditions and was linked, on trial-by-trial basis, to movement latency. A weaker pattern was composed of a constant signal that discriminated between selection conditions but was only weakly linked to the movement parameters. Copyright © 2017 the American
Le, Trang T; Simmons, W Kyle; Misaki, Masaya; Bodurka, Jerzy; White, Bill C; Savitz, Jonathan; McKinney, Brett A
2017-09-15
Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed. However, for domains such as bioinformatics, where the number of features is much larger than the number of observations p≫n , these differential privacy methods are susceptible to overfitting. We introduce private Evaporative Cooling, a stochastic privacy-preserving machine learning algorithm that uses Relief-F for feature selection and random forest for privacy preserving classification that also prevents overfitting. We relate the privacy-preserving threshold mechanism to a thermodynamic Maxwell-Boltzmann distribution, where the temperature represents the privacy threshold. We use the thermal statistical physics concept of Evaporative Cooling of atomic gases to perform backward stepwise privacy-preserving feature selection. On simulated data with main effects and statistical interactions, we compare accuracies on holdout and validation sets for three privacy-preserving methods: the reusable holdout, reusable holdout with random forest, and private Evaporative Cooling, which uses Relief-F feature selection and random forest classification. In simulations where interactions exist between attributes, private Evaporative Cooling provides higher classification accuracy without overfitting based on an independent validation set. In simulations without interactions, thresholdout with random forest and private Evaporative Cooling give comparable accuracies. We also apply these privacy methods to human brain resting-state fMRI data from a study of major depressive disorder. Code
IMPLEMENTATION OF THE MARKOV RANDOM FIELD FOR URBAN LAND COVER CLASSIFICATION OF UAV VHIR DATA
Directory of Open Access Journals (Sweden)
Jati Pratomo
2016-10-01
Full Text Available The usage of Unmanned Aerial Vehicle (UAV has grown rapidly in various fields, such as urban planning, search and rescue, and surveillance. Capturing images from UAV has many advantages compared with satellite imagery. For instance, higher spatial resolution and less impact from atmospheric variations can be obtained. However, there are difficulties in classifying urban features, due to the complexity of the urban land covers. The usage of Maximum Likelihood Classification (MLC has limitations since it is based on the assumption of the normal distribution of pixel values, where, in fact, urban features are not normally distributed. There are advantages in using the Markov Random Field (MRF for urban land cover classification as it assumes that neighboring pixels have a higher probability to be classified in the same class rather than a different class. This research aimed to determine the impact of the smoothness (λ and the updating temperature (Tupd on the accuracy result (κ in MRF. We used a UAV VHIR sized 587 square meters, with six-centimetre resolution, taken in Bogor Regency, Indonesia. The result showed that the kappa value (κ increases proportionally with the smoothness (λ until it reaches the maximum (κ, then the value drops. The usage of higher (Tupd has resulted in better (κ although it also led to a higher Standard Deviations (SD. Using the most optimal parameter, MRF resulted in slightly higher (κ compared with MLC.
Field-controlled randomness of colloidal paths on a magnetic bubble lattice
International Nuclear Information System (INIS)
Jungnickel, C; Fischer, Th M; Khattari, Z; Johansen, T H
2011-01-01
Paramagnetic colloidal particles move in the potential energy landscape of a magnetically modulated bubble lattice of a magnetic garnet film. The modulation causes the energy minima to alternate between positions above the centres of the bubbles and interstitial positions. The particles deterministically follow the time-dependent positions of the energy minima until the minima become unstable in one or several directions and allow the particles to hop to a new minimum. We control the time delay between instabilities of the minima in alternative directions by the angle of the external magnetic field with the crystallographic directions of the bubble lattice. When the time delay is large, the particles deterministically hop to the next minimum along the direction that becomes unstable first. When the time delay is short, diffusion of the particle in the marginal potential randomizes the choice of the hopping directions or the choice of the transport network. Gradual changes of the external field direction from 0 0 to 30 0 lead to a continuous crossover from a deterministic to a fully stochastic path of the colloids.
Gong, Zheng; Chen, Tianrun; Ratilal, Purnima; Makris, Nicholas C
2013-11-01
An analytical model derived from normal mode theory for the accumulated effects of range-dependent multiple forward scattering is applied to estimate the temporal coherence of the acoustic field forward propagated through a continental-shelf waveguide containing random three-dimensional internal waves. The modeled coherence time scale of narrow band low-frequency acoustic field fluctuations after propagating through a continental-shelf waveguide is shown to decay with a power-law of range to the -1/2 beyond roughly 1 km, decrease with increasing internal wave energy, to be consistent with measured acoustic coherence time scales. The model should provide a useful prediction of the acoustic coherence time scale as a function of internal wave energy in continental-shelf environments. The acoustic coherence time scale is an important parameter in remote sensing applications because it determines (i) the time window within which standard coherent processing such as matched filtering may be conducted, and (ii) the number of statistically independent fluctuations in a given measurement period that determines the variance reduction possible by stationary averaging.
Multi-fidelity Gaussian process regression for prediction of random fields
Energy Technology Data Exchange (ETDEWEB)
Parussini, L. [Department of Engineering and Architecture, University of Trieste (Italy); Venturi, D., E-mail: venturi@ucsc.edu [Department of Applied Mathematics and Statistics, University of California Santa Cruz (United States); Perdikaris, P. [Department of Mechanical Engineering, Massachusetts Institute of Technology (United States); Karniadakis, G.E. [Division of Applied Mathematics, Brown University (United States)
2017-05-01
We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgers equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.
Multi-fidelity Gaussian process regression for prediction of random fields
International Nuclear Information System (INIS)
Parussini, L.; Venturi, D.; Perdikaris, P.; Karniadakis, G.E.
2017-01-01
We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgers equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.
Multilayer Markov Random Field models for change detection in optical remote sensing images
Benedek, Csaba; Shadaydeh, Maha; Kato, Zoltan; Szirányi, Tamás; Zerubia, Josiane
2015-09-01
In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF) based solutions proposed for change detection in optical remote sensing images, called Multicue MRF, Conditional Mixed Markov model, and Fusion MRF. Our purposes are twofold. On one hand, we highlight the significance of the focused model family and we set them against various state-of-the-art approaches through a thematic analysis and quantitative tests. We discuss the advantages and drawbacks of class comparison vs. direct approaches, usage of training data, various targeted application fields and different ways of Ground Truth generation, meantime informing the Reader in which roles the Multilayer MRFs can be efficiently applied. On the other hand we also emphasize the differences between the three focused models at various levels, considering the model structures, feature extraction, layer interpretation, change concept definition, parameter tuning and performance. We provide qualitative and quantitative comparison results using principally a publicly available change detection database which contains aerial image pairs and Ground Truth change masks. We conclude that the discussed models are competitive against alternative state-of-the-art solutions, if one uses them as pre-processing filters in multitemporal optical image analysis. In addition, they cover together a large range of applications, considering the different usage options of the three approaches.
Meinzer, Caitlyn; Martin, Renee; Suarez, Jose I
2017-09-08
In phase II trials, the most efficacious dose is usually not known. Moreover, given limited resources, it is difficult to robustly identify a dose while also testing for a signal of efficacy that would support a phase III trial. Recent designs have sought to be more efficient by exploring multiple doses through the use of adaptive strategies. However, the added flexibility may potentially increase the risk of making incorrect assumptions and reduce the total amount of information available across the dose range as a function of imbalanced sample size. To balance these challenges, a novel placebo-controlled design is presented in which a restricted Bayesian response adaptive randomization (RAR) is used to allocate a majority of subjects to the optimal dose of active drug, defined as the dose with the lowest probability of poor outcome. However, the allocation between subjects who receive active drug or placebo is held constant to retain the maximum possible power for a hypothesis test of overall efficacy comparing the optimal dose to placebo. The design properties and optimization of the design are presented in the context of a phase II trial for subarachnoid hemorrhage. For a fixed total sample size, a trade-off exists between the ability to select the optimal dose and the probability of rejecting the null hypothesis. This relationship is modified by the allocation ratio between active and control subjects, the choice of RAR algorithm, and the number of subjects allocated to an initial fixed allocation period. While a responsive RAR algorithm improves the ability to select the correct dose, there is an increased risk of assigning more subjects to a worse arm as a function of ephemeral trends in the data. A subarachnoid treatment trial is used to illustrate how this design can be customized for specific objectives and available data. Bayesian adaptive designs are a flexible approach to addressing multiple questions surrounding the optimal dose for treatment efficacy
Directory of Open Access Journals (Sweden)
Y. L. Li
2013-01-01
Full Text Available Cropping fields often have well-defined poor-performing patches due to spatial and temporal variability. In an attempt to increase crop performance on poor patches, spatially selective field operations may be performed by agricultural robotics to apply additional inputs with targeted requirements. This paper addresses the route planning problem for an agricultural robot that has to treat some poor-patches in a field with row crops, with respect to the minimization of the total non-working distance travelled during headland turnings and in-field travel distance. The traversal of patches in the field is expressed as the traversal of a mixed weighted graph, and then the problem of finding an optimal patch sequence is formulated as an asymmetric traveling salesman problem and solved by the partheno-genetic algorithm. The proposed method is applied on a cropping field located in Northwestern China. Research results show that by using optimum patch sequences, the total non-working distance travelled during headland turnings and in-field travel distance can be reduced. But the savings on the non-working distance inside the field interior depend on the size and location of patches in the field, and the introduction of agricultural robotics is beneficial to increase field efficiency.
Energy Technology Data Exchange (ETDEWEB)
Li, Y. L.; Yi, S. P.
2013-05-01
Cropping fields often have well-defined poor-performing patches due to spatial and temporal variability. In an attempt to increase crop performance on poor patches, spatially selective field operations may be performed by agricultural robotics to apply additional inputs with targeted requirements. This paper addresses the route planning problem for an agricultural robot that has to treat some poor-patches in a field with row crops, with respect to the minimization of the total non-working distance travelled during headland turnings and in-field travel distance. The traversal of patches in the field is expressed as the traversal of a mixed weighted graph, and then the problem of finding an optimal patch sequence is formulated as an asymmetric traveling salesman problem and solved by the parthenogenetic algorithm. The proposed method is applied on a cropping field located in Northwestern China. Research results show that by using optimum patch sequences, the total non-working distance travelled during headland turnings and in-field travel distance can be reduced. But the savings on the non-working distance inside the field interior depend on the size and location of patches in the field, and the introduction of agricultural robotics is beneficial to increase field efficiency. (Author) 21 refs.
Mullen, Ann L.; Baker, Jayne
2015-01-01
While women now earn more bachelor's degrees than men in many parts of the world, large gender gaps persist in fields of study, and women remain underrepresented in the most prestigious institutions. This study updates and extends the literature on gender disparities in higher education by comparing the selectivity of the institutions where men…
New membrane materials for potassium-selective ion-sensitive field-effect transistors
van der Wal, P.D.; van der Wal, Peter D.; Skowronska-Ptasinska, Maria; van den Berg, Albert; Bergveld, Piet; Sudholter, Ernst; Sudholter, Ernst J.R.; Reinhoudt, David
1990-01-01
Several polymeric materials were studied as membrane materials for potassium-selective ion-sensitive field-effect transistors (ISFETs) to overcome the problems related with the use of conventional plasticized poly(vinyl chloride) membranes casted on ISFET gate surfaces. Several acrylate materials,
Yuvchenko, S. A.; Ushakova, E. V.; Pavlova, M. V.; Alonova, M. V.; Zimnyakov, D. A.
2018-04-01
We consider the practical realization of a new optical probe method of the random media which is defined as the reference-free path length interferometry with the intensity moments analysis. A peculiarity in the statistics of the spectrally selected fluorescence radiation in laser-pumped dye-doped random medium is discussed. Previously established correlations between the second- and the third-order moments of the intensity fluctuations in the random interference patterns, the coherence function of the probe radiation, and the path difference probability density for the interfering partial waves in the medium are confirmed. The correlations were verified using the statistical analysis of the spectrally selected fluorescence radiation emitted by a laser-pumped dye-doped random medium. Water solution of Rhodamine 6G was applied as the doping fluorescent agent for the ensembles of the densely packed silica grains, which were pumped by the 532 nm radiation of a solid state laser. The spectrum of the mean path length for a random medium was reconstructed.
Random-field Potts model for the polar domains of lead magnesium niobate and lead scandium tantalate
Energy Technology Data Exchange (ETDEWEB)
Qian, H.; Bursill, L.A
1997-06-01
A random filed Potts model is used to establish the spatial relationship between the nanoscale distribution of charges chemical defects and nanoscale polar domains for the perovskite-based relaxor materials lead magnesium niobate (PMN) and lead scandium tantalate (PST). The random fields are not set stochastically but are determined initially by the distribution of B-site cations (Mg, Nb) or (Sc, Ta) generated by Monte Carlo NNNI-model simulations for the chemical defects. An appropriate random field Potts model is derived and algorithms developed for a 2D lattice. It is shown that the local fields are strongly correlated with the chemical domain walls and that polar domains as a function of decreasing temperature is simulated for the two cases of PMN and PST. The dynamics of the polar clusters is also discussed. 33 refs., 9 figs.
Energy Technology Data Exchange (ETDEWEB)
Zentner, I. [IMSIA, UMR EDF-ENSTA-CNRS-CEA 9219, Université Paris-Saclay, 828 Boulevard des Maréchaux, 91762 Palaiseau Cedex (France); Ferré, G., E-mail: gregoire.ferre@ponts.org [CERMICS – Ecole des Ponts ParisTech, 6 et 8 avenue Blaise Pascal, Cité Descartes, Champs sur Marne, 77455 Marne la Vallée Cedex 2 (France); Poirion, F. [Department of Structural Dynamics and Aeroelasticity, ONERA, BP 72, 29 avenue de la Division Leclerc, 92322 Chatillon Cedex (France); Benoit, M. [Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), UMR 7342 (CNRS, Aix-Marseille Université, Ecole Centrale Marseille), 49 rue Frédéric Joliot-Curie, BP 146, 13384 Marseille Cedex 13 (France)
2016-06-01
In this paper, a new method for the identification and simulation of non-Gaussian and non-stationary stochastic fields given a database is proposed. It is based on two successive biorthogonal decompositions aiming at representing spatio–temporal stochastic fields. The proposed double expansion allows to build the model even in the case of large-size problems by separating the time, space and random parts of the field. A Gaussian kernel estimator is used to simulate the high dimensional set of random variables appearing in the decomposition. The capability of the method to reproduce the non-stationary and non-Gaussian features of random phenomena is illustrated by applications to earthquakes (seismic ground motion) and sea states (wave heights).
Cheraghalizadeh, Jafar; Najafi, Morteza N.; Mohammadzadeh, Hossein
2018-05-01
The effect of metallic nano-particles (MNPs) on the electrostatic potential of a disordered 2D dielectric media is considered. The disorder in the media is assumed to be white-noise Coulomb impurities with normal distribution. To realize the correlations between the MNPs we have used the Ising model with an artificial temperature T that controls the number of MNPs as well as their correlations. In the T → 0 limit, one retrieves the Gaussian free field (GFF), and in the finite temperature the problem is equivalent to a GFF in iso-potential islands. The problem is argued to be equivalent to a scale-invariant random surface with some critical exponents which vary with T and correspondingly are correlation-dependent. Two type of observables have been considered: local and global quantities. We have observed that the MNPs soften the random potential and reduce its statistical fluctuations. This softening is observed in the local as well as the geometrical quantities. The correlation function of the electrostatic and its total variance are observed to be logarithmic just like the GFF, i.e. the roughness exponent remains zero for all temperatures, whereas the proportionality constants scale with T - T c . The fractal dimension of iso-potential lines ( D f ), the exponent of the distribution function of the gyration radius ( τ r ), and the loop lengths ( τ l ), and also the exponent of the loop Green function x l change in terms of T - T c in a power-law fashion, with some critical exponents reported in the text. Importantly we have observed that D f ( T) - D f ( T c ) 1/√ ξ( T), in which ξ( T) is the spin correlation length in the Ising model.
ANALYSIS AND VALIDATION OF GRID DEM GENERATION BASED ON GAUSSIAN MARKOV RANDOM FIELD
Directory of Open Access Journals (Sweden)
F. J. Aguilar
2016-06-01
Full Text Available Digital Elevation Models (DEMs are considered as one of the most relevant geospatial data to carry out land-cover and land-use classification. This work deals with the application of a mathematical framework based on a Gaussian Markov Random Field (GMRF to interpolate grid DEMs from scattered elevation data. The performance of the GMRF interpolation model was tested on a set of LiDAR data (0.87 points/m2 provided by the Spanish Government (PNOA Programme over a complex working area mainly covered by greenhouses in Almería, Spain. The original LiDAR data was decimated by randomly removing different fractions of the original points (from 10% to up to 99% of points removed. In every case, the remaining points (scattered observed points were used to obtain a 1 m grid spacing GMRF-interpolated Digital Surface Model (DSM whose accuracy was assessed by means of the set of previously extracted checkpoints. The GMRF accuracy results were compared with those provided by the widely known Triangulation with Linear Interpolation (TLI. Finally, the GMRF method was applied to a real-world case consisting of filling the LiDAR-derived DSM gaps after manually filtering out non-ground points to obtain a Digital Terrain Model (DTM. Regarding accuracy, both GMRF and TLI produced visually pleasing and similar results in terms of vertical accuracy. As an added bonus, the GMRF mathematical framework makes possible to both retrieve the estimated uncertainty for every interpolated elevation point (the DEM uncertainty and include break lines or terrain discontinuities between adjacent cells to produce higher quality DTMs.
Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization.
Jiang, Z; Chen, W; Burkhart, C
2013-11-01
Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.
Transverse eV Ion Heating by Random Electric Field Fluctuations in the Plasmasphere
Artemyev, A. V.; Mourenas, D.; Agapitov, O. V.; Blum, L.
2017-01-01
Charged particle acceleration in the Earth inner magnetosphere is believed to be mainly due to the local resonant wave-particle interaction or particle transport processes. However, the Van Allen Probes have recently provided interesting evidence of a relatively slow transverse heating of eV ions at distances about 2-3 Earth radii during quiet times. Waves that are able to resonantly interact with such very cold ions are generally rare in this region of space, called the plasmasphere. Thus, non-resonant wave-particle interactions are expected to play an important role in the observed ion heating. We demonstrate that stochastic heating by random transverse electric field fluctuations of whistler (and possibly electromagnetic ion cyclotron) waves could explain this weak and slow transverse heating of H+ and O+ ions in the inner magnetosphere. The essential element of the proposed model of ion heating is the presence of trains of random whistler (hiss) wave packets, with significant amplitude modulations produced by strong wave damping, rapid wave growth, or a superposition of wave packets of different frequencies, phases, and amplitudes. Such characteristics correspond to measured characteristics of hiss waves in this region. Using test particle simulations with typical wave and plasma parameters, we demonstrate that the corresponding stochastic transverse ion heating reaches 0.07-0.2 eV/h for protons and 0.007-0.015 eV/h for O+ ions. This global temperature increase of the Maxwellian ion population from an initial Ti approx. 0.3 eV could potentially explain the observations.
Fetal MEG evoked response latency from beamformer with random field theory.
McCubbin, J; Vrba, J; Murphy, P; Temple, J; Eswaran, H; Lowery, C L; Preissl, H
2010-01-01
Analysis of fetal magnetoencephalographic brain recordings is restricted by low signal to noise ratio (SNR) and non-stationarity of the sources. Beamformer techniques have been applied to improve SNR of fetal evoked responses. However, until now the effect of non-stationarity was not taken into account in detail, because the detection of evoked responses is in most cases determined by averaging a large number of trials. We applied a windowing technique to improve the stationarity of the data by using short time segments recorded during a flash-evoked study. In addition, we implemented a random field theory approach for more stringent control of false-positives in the statistical parametric map of the search volume for the beamformer. The search volume was based on detailed individual fetal/maternal biometrics from ultrasound scans and fetal heart localization. Average power over a sliding window within the averaged evoked response against a randomized average background power was used as the test z-statistic. The significance threshold was set at 10% over all members of a contiguous cluster of voxels. There was at least one significant response for 62% of fetal and 95% of newborn recordings with gestational age (GA) between 28 and 45 weeks from 29 subjects. We found that the latency was either substantially unchanged or decreased with increasing GA for most subjects, with a nominal rate of about -11 ms/week. These findings support the anticipated neurophysiological development, provide validation for the beamformer model search as a methodology, and may lead to a clinical test for fetal cognitive development.
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M. Mahdian
2013-09-01
Full Text Available In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF, which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.
Zhang, Hua; Harter, Thomas; Sivakumar, Bellie
2006-06-01
examined, the third moment of the traveltime pdf varies from negatively skewed to strongly positively skewed. We also show that the Markov chain approach may give significantly different traveltime distributions when compared to the more commonly used Gaussian random field approach, even when the first- and second-order moments in the geostatistical distribution of the lnK field are identical. The choice of the appropriate geostatistical model is therefore critical in the assessment of nonpoint source transport, and uncertainty about that choice must be considered in evaluating the results.
Frants, E. A.; Ganchenko, G. S.; Shelistov, V. S.; Amiroudine, S.; Demekhin, E. A.
2018-02-01
Electrokinetics and the movement of charge-selective micro-granules in an electrolyte solution under the influence of an external electric field are investigated theoretically. Straightforward perturbation analysis is applied to a thin electric double layer and a weak external field, while a numerical solution is used for moderate electric fields. The asymptotic solution enables the determination of the salt concentration, electric charge distribution, and electro-osmotic velocity fields. It may also be used to obtain a simple analytical formula for the electrophoretic velocity in the case of quasi-equilibrium electrophoresis (electrophoresis of the first kind). This formula differs from the famous Helmholtz-Smoluchowski relation, which applies to dielectric microparticles, but not to ion-selective granules. Numerical calculations are used to validate the derived formula for weak external electric fields, but for moderate fields, nonlinear effects lead to a significant increase in electrophoretic mobility and to a transition from quasi-equilibrium electrophoresis of the first kind to nonequilibrium electrophoresis of the second kind. Theoretical results are successfully compared with experimental data.
Leppänen, Pia K; Ravaja, N; Ewalds-Kvist, S B M
2006-03-01
We examined: (a) the response to bidirectional selection for open-field (OF) thigmotaxis in mice for 23 generations and (b) the effects of repeated exposure (during 5 days) on different OF behaviors in the selectively bred high OF thigmotaxis (HOFT) and low OF thigmotaxis (LOFT) mice. A total of 2049 mice were used in the study. Prior to the testing in the selection experiment, the mice were exposed to the OF apparatus for approximately 2 min on each of 4 consecutive days. Thus, the selection was based on the scores registered on the 5th day after the four habituation periods. The HOFT mice were more thigmotactic than the LOFT mice in almost each generation. The HOFT mice also tended to rear less than the LOFT mice, which was explained by the inverse relationship between emotionality and exploratory tendencies. The lines did not generally differ in ambulation. Sex differences were found in thigmotaxis, ambulation, and rearing. In the repeated exposure experiment, the development of nine different OF behaviors across the 5 days of testing was addressed. Both lines ambulated, explored, and reared most on the 1st, 4th, and 5th days. Grooming and radial latency decreased and thigmotaxis increased linearly across the testing days. Line differences were found in ambulation, exploration, grooming, and rearing, while sex differences were manifested in ambulation and exploration. The line difference in thigmotaxis was evident only on the 5th day. Temporal changes were partially at variance with the general assumptions. OF thigmotaxis was found to be a powerful characteristic for producing two diverging lines of mice.
Trapping, percolation, and anomalous diffusion of particles in a two-dimensional random field
International Nuclear Information System (INIS)
Avellaneda, M.; Apelian, C.; Elliott, F. Jr.
1993-01-01
The authors analyze the advection of particles in a velocity field with Hamiltonian H(x,y) = bar V 1 y-bar V 2 x + W 1 (y) - W 2 (x), where W i , i=1,2, are random functions with stationary, independent increments. In the absence of molecular diffusion, the particle dynamics are sensitive to the streamline topology, which depends on the mean-to-fluctuations ratio p=max(|bar V 1 |/bar U;|bar V 2 |/bar U), with bar U = [|W' 1 | 2 ] 1/2 = rms fluctuations. The model is exactly solvable for p≥1 and well suited for Monte Carlo simulations for all p. Statistics are considered of streamlines for p=0, deriving power laws for the escape probability and the length of escaping trajectories for a box of size L much-gt 1. Also obtained is a characterization of the statistical topography of the Hamiltonian. The large-scale transport is studied of advected particles with p > 0. For 0 -v/2 [x(t) - (x(t))] and t -v/2 [y(t) - (y(t))]. The large-scale motions are Fickian (v=1) or superdiffusive (v=3/2) with a non-Gaussian coarse-grained probability, according to the direction of the mean velocity relative to the underlying lattice. These results are obtained analytically for p≥1 and extended to the regime 0 1 , bar V 2 ) for which stagnation regions in the flow exist. The results are compared with existing predictions on the topology of streamlines based on percolation theory and with mean-field calculations of effective diffusivities. 29 refs., 15 figs., 7 tabs
Self-consistent Random Phase Approximation applied to a schematic model of the field theory
International Nuclear Information System (INIS)
Bertrand, Thierry
1998-01-01
The self-consistent Random Phase Approximation (SCRPA) is a method allowing in the mean-field theory inclusion of the correlations in the ground and excited states. It has the advantage of not violating the Pauli principle in contrast to RPA, that is based on the quasi-bosonic approximation; in addition, numerous applications in different domains of physics, show a possible variational character. However, the latter should be formally demonstrated. The first model studied with SCRPA is the anharmonic oscillator in the region where one of its symmetries is spontaneously broken. The ground state energy is reproduced by SCRPA more accurately than RPA, with no violation of the Ritz variational principle, what is not the case for the latter approximation. The success of SCRPA is the the same in case of ground state energy for a model mixing bosons and fermions. At the transition point the SCRPA is correcting RPA drastically, but far from this region the correction becomes negligible, both methods being of similar precision. In the deformed region in the case of RPA a spurious mode occurred due to the microscopical character of the model.. The SCRPA may also reproduce this mode very accurately and actually it coincides with an excitation in the exact spectrum
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P. M. A. Diaz
2016-06-01
Full Text Available This paper presents a method to estimate the temporal interaction in a Conditional Random Field (CRF based approach for crop recognition from multitemporal remote sensing image sequences. This approach models the phenology of different crop types as a CRF. Interaction potentials are assumed to depend only on the class labels of an image site at two consecutive epochs. In the proposed method, the estimation of temporal interaction parameters is considered as an optimization problem, whose goal is to find the transition matrix that maximizes the CRF performance, upon a set of labelled data. The objective functions underlying the optimization procedure can be formulated in terms of different accuracy metrics, such as overall and average class accuracy per crop or phenological stages. To validate the proposed approach, experiments were carried out upon a dataset consisting of 12 co-registered LANDSAT images of a region in southeast of Brazil. Pattern Search was used as the optimization algorithm. The experimental results demonstrated that the proposed method was able to substantially outperform estimates related to joint or conditional class transition probabilities, which rely on training samples.
Tao, R.; Tang, H.
Chocolate is one of the most popular food types and flavors in the world. Unfortunately, at present, chocolate products contain too much fat, leading to obesity. For example, a typical molding chocolate has various fat up to 40% in total and chocolate for covering ice cream has fat 50 -60%. Especially, as children are the leading chocolate consumers, reducing the fat level in chocolate products to make them healthier is important and urgent. While this issue was called into attention and elaborated in articles and books decades ago and led to some patent applications, no actual solution was found unfortunately. Why is reducing fat in chocolate so difficult? What is the underlying physical mechanism? We have found that this issue is deeply related to the basic science of soft matters, especially to their viscosity and maximally random jammed (MRJ) density φx. All chocolate productions are handling liquid chocolate, a suspension with cocoa solid particles in melted fat, mainly cocoa butter. The fat level cannot be lower than 1-φxin order to have liquid chocolate to flow. Here we show that that with application of an electric field to liquid chocolate, we can aggregate the suspended particles into prolate spheroids. This microstructure change reduces liquid chocolate's viscosity along the flow direction and increases its MRJ density significantly. Hence the fat level in chocolate can be effectively reduced. We are looking forward to a new class of healthier and tasteful chocolate coming to the market soon. Dept. of Physics, Temple Univ, Philadelphia, PA 19122.
Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin
2018-05-01
Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.
Ben Daya, Ibrahim; Chen, Albert I H; Shafiee, Mohammad Javad; Wong, Alexander; Yeow, John T W
2017-09-06
The row-column method received a lot of attention for 3-D ultrasound imaging. By reducing the number of connections required to address the 2-D array and therefore reducing the amount of data to handle, this addressing method allows for real time 3-D imaging. Row-column still has its limitations: the issues of sparsity, speckle noise inherent to ultrasound, the spatially varying point spread function, and the ghosting artifacts inherent to the row-column method must all be taken into account when building a reconstruction framework. In this research, we build on a previously published system and propose an edge-guided, compensated row-column ultrasound imaging system that incorporates multilayered edge-guided stochastically fully connected conditional random fields to address the limitations of the row-column method. Tests carried out on simulated and real row-column ultrasound images show the effectiveness of our proposed system over other published systems. Visual assessment show our proposed system's potential at preserving edges and reducing speckle. Quantitative analysis shows that our proposed system outperforms previously published systems when evaluated with metrics such as Peak Signal-to-Noise Ratio, Coefficient of Correlation, and Effective Number of Looks. These results show the potential of our proposed system as an effective tool for enhancing 3-D row-column imaging.
Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.
Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping
2014-01-01
The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.
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Hoffmann Nico
2016-09-01
Full Text Available Intraoperative thermal neuroimaging is a novel intraoperative imaging technique for the characterization of perfusion disorders, neural activity and other pathological changes of the brain. It bases on the correlation of (sub-cortical metabolism and perfusion with the emitted heat of the cortical surface. In order to minimize required computational resources and prevent unwanted artefacts in subsequent data analysis workflows foreground detection is a important preprocessing technique to differentiate pixels representing the cerebral cortex from background objects. We propose an efficient classification framework that integrates characteristic dynamic thermal behaviour into this classification task to include additional discriminative features. The first stage of our framework consists of learning this representation of characteristic thermal time-frequency behaviour. This representation models latent interconnections in the time-frequency domain that cover specific, yet a priori unknown, thermal properties of the cortex. In a second stage these features are then used to classify each pixel’s state with conditional random fields. We quantitatively evaluate several approaches to learning high-level features and their impact to the overall prediction accuracy. The introduction of high-level features leads to a significant accuracy improvement compared to a baseline classifier.
Pécot, Thierry; Bouthemy, Patrick; Boulanger, Jérôme; Chessel, Anatole; Bardin, Sabine; Salamero, Jean; Kervrann, Charles
2015-02-01
Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in space and time at the subcellular level. In fluorescence microscopy imaging, the moving tagged structures of interest, such as vesicles, appear as bright spots over a static or nonstatic background. In this paper, we consider the problem of vesicle segmentation and time-varying background estimation at the cellular scale. The main idea is to formulate the joint segmentation-estimation problem in the general conditional random field framework. Furthermore, segmentation of vesicles and background estimation are alternatively performed by energy minimization using a min cut-max flow algorithm. The proposed approach relies on a detection measure computed from intensity contrasts between neighboring blocks in fluorescence microscopy images. This approach permits analysis of either 2D + time or 3D + time data. We demonstrate the performance of the so-called C-CRAFT through an experimental comparison with the state-of-the-art methods in fluorescence video-microscopy. We also use this method to characterize the spatial and temporal distribution of Rab6 transport carriers at the cell periphery for two different specific adhesion geometries.
Oriented Markov random field based dendritic spine segmentation for fluorescence microscopy images.
Cheng, Jie; Zhou, Xiaobo; Miller, Eric L; Alvarez, Veronica A; Sabatini, Bernardo L; Wong, Stephen T C
2010-10-01
Dendritic spines have been shown to be closely related to various functional properties of the neuron. Usually dendritic spines are manually labeled to analyze their morphological changes, which is very time-consuming and susceptible to operator bias, even with the assistance of computers. To deal with these issues, several methods have been recently proposed to automatically detect and measure the dendritic spines with little human interaction. However, problems such as degraded detection performance for images with larger pixel size (e.g. 0.125 μm/pixel instead of 0.08 μm/pixel) still exist in these methods. Moreover, the shapes of detected spines are also distorted. For example, the "necks" of some spines are missed. Here we present an oriented Markov random field (OMRF) based algorithm which improves spine detection as well as their geometric characterization. We begin with the identification of a region of interest (ROI) containing all the dendrites and spines to be analyzed. For this purpose, we introduce an adaptive procedure for identifying the image background. Next, the OMRF model is discussed within a statistical framework and the segmentation is solved as a maximum a posteriori estimation (MAP) problem, whose optimal solution is found by a knowledge-guided iterative conditional mode (KICM) algorithm. Compared with the existing algorithms, the proposed algorithm not only provides a more accurate representation of the spine shape, but also improves the detection performance by more than 50% with regard to reducing both the misses and false detection.
Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model
Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato
2018-02-01
This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.
Language Recognition Using Latent Dynamic Conditional Random Field Model with Phonological Features
Directory of Open Access Journals (Sweden)
Sirinoot Boonsuk
2014-01-01
Full Text Available Spoken language recognition (SLR has been of increasing interest in multilingual speech recognition for identifying the languages of speech utterances. Most existing SLR approaches apply statistical modeling techniques with acoustic and phonotactic features. Among the popular approaches, the acoustic approach has become of greater interest than others because it does not require any prior language-specific knowledge. Previous research on the acoustic approach has shown less interest in applying linguistic knowledge; it was only used as supplementary features, while the current state-of-the-art system assumes independency among features. This paper proposes an SLR system based on the latent-dynamic conditional random field (LDCRF model using phonological features (PFs. We use PFs to represent acoustic characteristics and linguistic knowledge. The LDCRF model was employed to capture the dynamics of the PFs sequences for language classification. Baseline systems were conducted to evaluate the features and methods including Gaussian mixture model (GMM based systems using PFs, GMM using cepstral features, and the CRF model using PFs. Evaluated on the NIST LRE 2007 corpus, the proposed method showed an improvement over the baseline systems. Additionally, it showed comparable result with the acoustic system based on i-vector. This research demonstrates that utilizing PFs can enhance the performance.
Automatic Lung Tumor Segmentation on PET/CT Images Using Fuzzy Markov Random Field Model
Directory of Open Access Journals (Sweden)
Yu Guo
2014-01-01
Full Text Available The combination of positron emission tomography (PET and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice’s similarity coefficient (DSC was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.
A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking.
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Mohammad Javad Shafiee
Full Text Available In this work, we introduce a deep-structured conditional random field (DS-CRF model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering.
Jeong, Chan-Seok; Kim, Dongsup
2016-02-24
Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.
Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.
2017-11-01
Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.
Zhang, Yifan
2016-08-18
For face naming in TV series or movies, a typical way is using subtitles/script alignment to get the time stamps of the names, and tagging them to the faces. We study the problem of face naming in videos when subtitles are not available. To this end, we divide the problem into two tasks: face clustering which groups the faces depicting a certain person into a cluster, and name assignment which associates a name to each face. Each task is formulated as a structured prediction problem and modeled by a hidden conditional random field (HCRF) model. We argue that the two tasks are correlated problems whose outputs can provide prior knowledge of the target prediction for each other. The two HCRFs are coupled in a unified graphical model called coupled HCRF where the joint dependence of the cluster labels and face name association is naturally embedded in the correlation between the two HCRFs. We provide an effective algorithm to optimize the two HCRFs iteratively and the performance of the two tasks on real-world data set can be both improved.
Heinrich, Angela; Szostek, Anne; Meyer, Patric; Nees, Frauke; Rauschenberg, Jaane; Gröbner, Jens; Gilles, Maria; Paslakis, Georgios; Deuschle, Michael; Semmler, Wolfhard; Flor, Herta
2013-01-01
To establish the extent to which representative cognitive functions in subjects undergoing magnetic resonance (MR) imaging are acutely impaired by static magnetic fields of varying field strengths. This study was approved by the local ethics committee, and informed consent was obtained from all subjects. In this single-blind case-crossover study, 41 healthy subjects underwent an extensive neuropsychologic examination while in MR units of differing field strengths (1.5, 3.0, and 7.0 T), including a mock imager with no magnetic field as a control condition. Subjects were blinded to field strength. Tests were performed while subjects were lying still in the MR unit and while the examination table was moved. The tests covered a representative set of cognitive functions, such as memory, eye-hand coordination, attention, reaction time, and visual discrimination. Subjective sensory perceptions were also assessed. Effects were analyzed with a repeated-measures analysis of variance; the within-subject factors were field strength (0, 1.5, 3.0, and 7.0 T) and state (static, dynamic). Static magnetic fields were not found to have a significant effect on cognitive function at any field strength. However, sensory perceptions did vary according to field strength. Dizziness, nystagmus, phosphenes, and head ringing were related to the strength of the static magnetic field. Static magnetic fields as high as 7.0 T did not have a significant effect on cognition. RSNA, 2012
Hong, JaeSub; van den Berg, Maureen; Schlegel, Eric M.; Grindlay, Jonathan E.; Koenig, Xavier; Laycock, Silas; Zhao, Ping
2005-12-01
We describe the X-ray analysis procedure of the ongoing Chandra Multiwavelength Plane (ChaMPlane) Survey and report the initial results from the analysis of 15 selected anti-Galactic center observations (90degusing custom-developed analysis tools appropriate for Galactic sources but also of general use: optimum photometry in crowded fields using advanced techniques for overlapping sources, rigorous astrometry and 95% error circles for combining X-ray images or matching to optical/IR images, and application of quantile analysis for spectral analysis of faint sources. We apply these techniques to 15 anti-Galactic center observations (of 14 distinct fields), in which we have detected 921 X-ray point sources. We present logN-logS distributions and quantile analysis to show that in the hard band (2-8 keV) active galactic nuclei dominate the sources. Complete analysis of all ChaMPlane anti-Galactic center fields will be given in a subsequent paper, followed by papers on sources in the Galactic center and bulge regions.
Spatial Scaling of the Profile of Selective Attention in the Visual Field.
Gannon, Matthew A; Knapp, Ashley A; Adams, Thomas G; Long, Stephanie M; Parks, Nathan A
2016-01-01
Neural mechanisms of selective attention must be capable of adapting to variation in the absolute size of an attended stimulus in the ever-changing visual environment. To date, little is known regarding how attentional selection interacts with fluctuations in the spatial expanse of an attended object. Here, we use event-related potentials (ERPs) to investigate the scaling of attentional enhancement and suppression across the visual field. We measured ERPs while participants performed a task at fixation that varied in its attentional demands (attentional load) and visual angle (1.0° or 2.5°). Observers were presented with a stream of task-relevant stimuli while foveal, parafoveal, and peripheral visual locations were probed by irrelevant distractor stimuli. We found two important effects in the N1 component of visual ERPs. First, N1 modulations to task-relevant stimuli indexed attentional selection of stimuli during the load task and further correlated with task performance. Second, with increased task size, attentional modulation of the N1 to distractor stimuli showed a differential pattern that was consistent with a scaling of attentional selection. Together, these results demonstrate that the size of an attended stimulus scales the profile of attentional selection across the visual field and provides insights into the attentional mechanisms associated with such spatial scaling.
Spatial Scaling of the Profile of Selective Attention in the Visual Field.
Directory of Open Access Journals (Sweden)
Matthew A Gannon
Full Text Available Neural mechanisms of selective attention must be capable of adapting to variation in the absolute size of an attended stimulus in the ever-changing visual environment. To date, little is known regarding how attentional selection interacts with fluctuations in the spatial expanse of an attended object. Here, we use event-related potentials (ERPs to investigate the scaling of attentional enhancement and suppression across the visual field. We measured ERPs while participants performed a task at fixation that varied in its attentional demands (attentional load and visual angle (1.0° or 2.5°. Observers were presented with a stream of task-relevant stimuli while foveal, parafoveal, and peripheral visual locations were probed by irrelevant distractor stimuli. We found two important effects in the N1 component of visual ERPs. First, N1 modulations to task-relevant stimuli indexed attentional selection of stimuli during the load task and further correlated with task performance. Second, with increased task size, attentional modulation of the N1 to distractor stimuli showed a differential pattern that was consistent with a scaling of attentional selection. Together, these results demonstrate that the size of an attended stimulus scales the profile of attentional selection across the visual field and provides insights into the attentional mechanisms associated with such spatial scaling.
The basic science and mathematics of random mutation and natural selection.
Kleinman, Alan
2014-12-20
The mutation and natural selection phenomenon can and often does cause the failure of antimicrobial, herbicidal, pesticide and cancer treatments selection pressures. This phenomenon operates in a mathematically predictable behavior, which when understood leads to approaches to reduce and prevent the failure of the use of these selection pressures. The mathematical behavior of mutation and selection is derived using the principles given by probability theory. The derivation of the equations describing the mutation and selection phenomenon is carried out in the context of an empirical example. Copyright © 2014 John Wiley & Sons, Ltd.
Yan, Yuan
2017-07-13
Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.
DEFF Research Database (Denmark)
Thamsborg, G; Florescu, A; Oturai, P
2005-01-01
OBJECTIVE: The investigation aimed at determining the effectiveness of pulsed electromagnetic fields (PEMF) in the treatment of osteoarthritis (OA) of the knee by conducting a randomized, double-blind, placebo-controlled clinical trial. DESIGN: The trial consisted of 2h daily treatment 5 days per...
Yan, Yuan; Genton, Marc G.
2017-01-01
Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.
Roeser, Robert W.; Schonert-Reichl, Kimberly A.; Jha, Amishi; Cullen, Margaret; Wallace, Linda; Wilensky, Rona; Oberle, Eva; Thomson, Kimberly; Taylor, Cynthia; Harrison, Jessica
2013-01-01
The effects of randomization to mindfulness training (MT) or to a waitlist-control condition on psychological and physiological indicators of teachers' occupational stress and burnout were examined in 2 field trials. The sample included 113 elementary and secondary school teachers (89% female) from Canada and the United States. Measures were…
International Nuclear Information System (INIS)
Dietrich, H.; Mueller-Dethlefs, K.; Baranov, L.Y.
1996-01-01
For the first time fractional Stark state selective electric field ionization of very high-n (n approx-gt 250) molecular Rydberg states is observed. An open-quote open-quote offset close-quote close-quote electric pulse selectively ionizes the more fragile open-quote open-quote red close-quote close-quote (down shifted in energy) Stark states. The more resilient open-quote open-quote bluer close-quote close-quote, or up-shifted, ones survive and are shifted down in energy upon application of a second (open-quote open-quote probe close-quote close-quote) pulse of opposite direction (diabatic Stark states close-quote inversion). Hence, even for smaller probe than offset fields ionization is observed. The offset/probe ratio allows one to control spectral peak shapes in zero-kinetic-energy photoelectron spectroscopy. copyright 1995 The American Physical Society
Symmetry-adaptation and selection rules for effective crystal field Hamiltonians
International Nuclear Information System (INIS)
Tuszynski, J.A.
1986-01-01
The intention of this paper is to systematically derive an effective Hamiltonian in the presence of crystal fields in such a way as to incorporate relativistic effects and higher order perturbation corrections including configuration mixing. This Hamiltonian will then be conveniently represented as a symmetry-adapted series of one- and two-body double tensor operators whose matrix elements will be analyzed for selection rules. 16 references, 4 tables
Leppänen, Pia K; Ravaja, Niklas; Ewalds-Kvist, S Béatrice M
2008-01-01
The authors examined pre- and postpartum open-field (OF) behavior and maternal responsiveness in mice that they bidirectionally selected for OF thigmotaxis. The authors tested 40 female mice under 3 conditions: prepartum OF, postpartum OF, and a pup retrieval test. In both OF conditions, the high OF thigmotaxis (HOFT) mice were more thigmotactic but explored and reared less than the low OF thigmotaxis (LOFT) mice, indicating that the HOFT mice were more emotional. In the postpartum condition, the HOFT mothers also defecated more and ambulated less than the LOFT mothers. The increase in grooming after parturition was more conspicuous among the LOFT mothers than among the HOFT mothers. The LOFT mothers were also more attracted to their pups in the OF, but the retrieval test did not show any substantial line differences. The results suggested that the line difference in emotionality was more pronounced during lactation than during pregnancy, although parturition exerted no effect on thigmotaxis.
Selective control of multiple ferroelectric switching pathways using a trailing flexoelectric field
Park, Sung Min; Wang, Bo; Das, Saikat; Chae, Seung Chul; Chung, Jin-Seok; Yoon, Jong-Gul; Chen, Long-Qing; Yang, Sang Mo; Noh, Tae Won
2018-05-01
Flexoelectricity is an electromechanical coupling between electrical polarization and a strain gradient1 that enables mechanical manipulation of polarization without applying an electrical bias2,3. Recently, flexoelectricity was directly demonstrated by mechanically switching the out-of-plane polarization of a uniaxial system with a scanning probe microscope tip3,4. However, the successful application of flexoelectricity in low-symmetry multiaxial ferroelectrics and therefore active manipulation of multiple domains via flexoelectricity have not yet been achieved. Here, we demonstrate that the symmetry-breaking flexoelectricity offers a powerful route for the selective control of multiple domain switching pathways in multiaxial ferroelectric materials. Specifically, we use a trailing flexoelectric field that is created by the motion of a mechanically loaded scanning probe microscope tip. By controlling the SPM scan direction, we can deterministically select either stable 71° ferroelastic switching or 180° ferroelectric switching in a multiferroic magnetoelectric BiFeO3 thin film. Phase-field simulations reveal that the amplified in-plane trailing flexoelectric field is essential for this domain engineering. Moreover, we show that mechanically switched domains have a good retention property. This work opens a new avenue for the deterministic selection of nanoscale ferroelectric domains in low-symmetry materials for non-volatile magnetoelectric devices and multilevel data storage.
Cohen-Khait, Ruth; Schreiber, Gideon
2018-04-27
Protein-protein interactions mediate the vast majority of cellular processes. Though protein interactions obey basic chemical principles also within the cell, the in vivo physiological environment may not allow for equilibrium to be reached. Thus, in vitro measured thermodynamic affinity may not provide a complete picture of protein interactions in the biological context. Binding kinetics composed of the association and dissociation rate constants are relevant and important in the cell. Therefore, changes in protein-protein interaction kinetics have a significant impact on the in vivo activity of the proteins. The common protocol for the selection of tighter binders from a mutant library selects for protein complexes with slower dissociation rate constants. Here we describe a method to specifically select for variants with faster association rate constants by using pre-equilibrium selection, starting from a large random library. Toward this end, we refine the selection conditions of a TEM1-β-lactamase library against its natural nanomolar affinity binder β-lactamase inhibitor protein (BLIP). The optimal selection conditions depend on the ligand concentration and on the incubation time. In addition, we show that a second sort of the library helps to separate signal from noise, resulting in a higher percent of faster binders in the selected library. Fast associating protein variants are of particular interest for drug development and other biotechnological applications.
International Nuclear Information System (INIS)
Monthus, Cécile; Garel, Thomas
2012-01-01
To avoid the complicated topology of surviving clusters induced by standard strong disorder RG in dimension d > 1, we introduce a modified procedure called ‘boundary strong disorder RG’ where the order of decimations is chosen a priori. We apply this modified procedure numerically to the random transverse field Ising model in dimension d = 2. We find that the location of the critical point, the activated exponent ψ ≃ 0.5 of the infinite-disorder scaling, and the finite-size correlation exponent ν FS ≃ 1.3 are compatible with the values obtained previously using standard strong disorder RG. Our conclusion is thus that strong disorder RG is very robust with respect to changes in the order of decimations. In addition, we analyze the RG flows within the two phases in more detail, to show explicitly the presence of various correlation length exponents: we measure the typical correlation exponent ν typ ≃ 0.64 for the disordered phase (this value is very close to the correlation exponent ν pure Q (d=2)≅0.6 3 of the pure two-dimensional quantum Ising model), and the typical exponent ν h ≃ 1 for the ordered phase. These values satisfy the relations between critical exponents imposed by the expected finite-size scaling properties at infinite-disorder critical points. We also measure, within the disordered phase, the fluctuation exponent ω ≃ 0.35 which is compatible with the directed polymer exponent ω DP (1+1)= 1/3 in (1 + 1) dimensions. (paper)
De-identification of clinical notes via recurrent neural network and conditional random field.
Liu, Zengjian; Tang, Buzhou; Wang, Xiaolong; Chen, Qingcai
2017-11-01
De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-scale and RDOC Individualized Domains (N-GRID) clinical natural language processing (NLP) challenge contains a de-identification track in de-identifying electronic medical records (EMRs) (i.e., track 1). The challenge organizers provide 1000 annotated mental health records for this track, 600 out of which are used as a training set and 400 as a test set. We develop a hybrid system for the de-identification task on the training set. Firstly, four individual subsystems, that is, a subsystem based on bidirectional LSTM (long-short term memory, a variant of recurrent neural network), a subsystem-based on bidirectional LSTM with features, a subsystem based on conditional random field (CRF) and a rule-based subsystem, are used to identify PHI instances. Then, an ensemble learning-based classifiers is deployed to combine all PHI instances predicted by above three machine learning-based subsystems. Finally, the results of the ensemble learning-based classifier and the rule-based subsystem are merged together. Experiments conducted on the official test set show that our system achieves the highest micro F1-scores of 93.07%, 91.43% and 95.23% under the "token", "strict" and "binary token" criteria respectively, ranking first in the 2016 CEGS N-GRID NLP challenge. In addition, on the dataset of 2014 i2b2 NLP challenge, our system achieves the highest micro F1-scores of 96.98%, 95.11% and 98.28% under the "token", "strict" and "binary token" criteria respectively, outperforming other state-of-the-art systems. All these experiments prove the effectiveness of our proposed method. Copyright © 2017. Published by Elsevier Inc.
SAR-based change detection using hypothesis testing and Markov random field modelling
Cao, W.; Martinis, S.
2015-04-01
The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.
Degerman, Alexander; Rinne, Teemu; Särkkä, Anna-Kaisa; Salmi, Juha; Alho, Kimmo
2008-06-01
Event-related brain potentials (ERPs) and magnetic fields (ERFs) were used to compare brain activity associated with selective attention to sound location or pitch in humans. Sixteen healthy adults participated in the ERP experiment, and 11 adults in the ERF experiment. In different conditions, the participants focused their attention on a designated sound location or pitch, or pictures presented on a screen, in order to detect target sounds or pictures among the attended stimuli. In the Attend Location condition, the location of sounds varied randomly (left or right), while their pitch (high or low) was kept constant. In the Attend Pitch condition, sounds of varying pitch (high or low) were presented at a constant location (left or right). Consistent with previous ERP results, selective attention to either sound feature produced a negative difference (Nd) between ERPs to attended and unattended sounds. In addition, ERPs showed a more posterior scalp distribution for the location-related Nd than for the pitch-related Nd, suggesting partially different generators for these Nds. The ERF source analyses found no source distribution differences between the pitch-related Ndm (the magnetic counterpart of the Nd) and location-related Ndm in the superior temporal cortex (STC), where the main sources of the Ndm effects are thought to be located. Thus, the ERP scalp distribution differences between the location-related and pitch-related Nd effects may have been caused by activity of areas outside the STC, perhaps in the inferior parietal regions.
The upper bound of abutment scour defined by selected laboratory and field data
Benedict, Stephen; Caldwell, Andral W.
2015-01-01
The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted a field investigation of abutment scour in South Carolina and used that data to develop envelope curves defining the upper bound of abutment scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with abutment-scour data from other sources and evaluate the upper bound of abutment scour with the larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published abutment-scour data, and selected data, consisting of 446 laboratory and 331 field measurements, were compiled for the analysis. These data encompassed a wide range of laboratory and field conditions and represent field data from 6 states within the United States. The data set was used to evaluate the South Carolina abutment-scour envelope curves. Additionally, the data were used to evaluate a dimensionless abutment-scour envelope curve developed by Melville (1992), highlighting the distinct difference in the upper bound for laboratory and field data. The envelope curves evaluated in this investigation provide simple but useful tools for assessing the potential maximum abutment-scour depth in the field setting.
Lerchner, A; Hertz, J; Ahmadi, M
2004-01-01
We present a complete mean field theory for a balanced state of a simple model of an orientation hypercolumn. The theory is complemented by a description of a numerical procedure for solving the mean-field equations quantitatively. With our treatment, we can determine self-consistently both the firing rates and the firing correlations, without being restricted to specific neuron models. Here, we solve the analytically derived mean-field equations numerically for integrate-and-fire neurons. Several known key properties of orientation selective cortical neurons emerge naturally from the description: Irregular firing with statistics close to -- but not restricted to -- Poisson statistics; an almost linear gain function (firing frequency as a function of stimulus contrast) of the neurons within the network; and a contrast-invariant tuning width of the neuronal firing. We find that the irregularity in firing depends sensitively on synaptic strengths. If Fano factors are bigger than 1, then they are so for all stim...
A Study of Quasar Selection in the Supernova Fields of the Dark Energy Survey
International Nuclear Information System (INIS)
Tie, S. S.; Martini, P.; Mudd, D.; Ostrovski, F.; Reed, S. L.
2017-01-01
In this paper, we present a study of quasar selection using the supernova fields of the Dark Energy Survey (DES). We used a quasar catalog from an overlapping portion of the SDSS Stripe 82 region to quantify the completeness and efficiency of selection methods involving color, probabilistic modeling, variability, and combinations of color/probabilistic modeling with variability. In all cases, we considered only objects that appear as point sources in the DES images. We examine color selection methods based on the Wide-field Infrared Survey Explorer (WISE) mid-IR W1-W2 color, a mixture of WISE and DES colors (g - i and i-W1), and a mixture of Vista Hemisphere Survey and DES colors (g - i and i - K). For probabilistic quasar selection, we used XDQSO, an algorithm that employs an empirical multi-wavelength flux model of quasars to assign quasar probabilities. Our variability selection uses the multi-band χ"2-probability that sources are constant in the DES Year 1 griz-band light curves. The completeness and efficiency are calculated relative to an underlying sample of point sources that are detected in the required selection bands and pass our data quality and photometric error cuts. We conduct our analyses at two magnitude limits, i 85% for both i-band magnitude limits and efficiencies of >80% to the bright limit and >60% to the faint limit; however, the giW1 and giW1+variability methods give the highest quasar surface densities. The XDQSOz method and combinations of W1W2/giW1/XDQSOz with variability are among the better selection methods when both high completeness and high efficiency are desired. We also present the OzDES Quasar Catalog of 1263 spectroscopically confirmed quasars from three years of OzDES observation in the 30 deg"2 of the DES supernova fields. Finally, the catalog includes quasars with redshifts up to z ~ 4 and brighter than i = 22 mag, although the catalog is not complete up to this magnitude limit.
r2VIM: A new variable selection method for random forests in genome-wide association studies.
Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E
2016-01-01
Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.
Phase diagrams of a spin-1/2 transverse Ising model with three-peak random field distribution
International Nuclear Information System (INIS)
Bassir, A.; Bassir, C.E.; Benyoussef, A.; Ez-Zahraouy, H.
1996-07-01
The effect of the transverse magnetic field on the phase diagrams structures of the Ising model in a random longitudinal magnetic field with a trimodal symmetric distribution is investigated within a finite cluster approximation. We find that a small magnetizations ordered phase (small ordered phase) disappears completely for a sufficiently large value of the transverse field or/and large value of the concentration of the disorder of the magnetic field. Multicritical behaviour and reentrant phenomena are discussed. The regions where the tricritical, reentrant phenomena and the small ordered phase persist are delimited as a function of the transverse field and the concentration p. Longitudinal magnetizations are also presented. (author). 33 refs, 6 figs
Patel, Raj Kumar; Giri, V.K.
2016-01-01
Fault detection and diagnosis is the most important technology in condition-based maintenance (CBM) system for rotating machinery. This paper experimentally explores the development of a random forest (RF) classifier, a recently emerged machine learning technique, for multi-class mechanical fault diagnosis in bearing of an induction motor. Firstly, the vibration signals are collected from the bearing using accelerometer sensor. Parameters from the vibration signal are extracted in the form of...
Energy Technology Data Exchange (ETDEWEB)
Scott Reeves; Buckley Walsh
2003-08-01
In 1996, Advanced Resources International (ARI) began performing R&D targeted at enhancing production and reserves from natural gas fields. The impetus for the effort was a series of field R&D projects in the early-to-mid 1990's, in eastern coalbed methane and gas shales plays, where well remediation and production enhancement had been successfully demonstrated. As a first step in the R&D effort, an assessment was made of the potential for restimulation to provide meaningful reserve additions to the U.S. gas resource base, and what technologies were needed to do so. That work concluded that: (1) A significant resource base did exist via restimulation (multiples of Tcf). (2) The greatest opportunities existed in non-conventional plays where completion practices were (relatively) complex and technology advancement was rapid. (3) Accurate candidate selection is the greatest single factor that contributes to a successful restimulation program. With these findings, a field-oriented program targeted at tight sand formations was initiated to develop and demonstrate successful candidate recognition technology. In that program, which concluded in 2001, nine wells were restimulated in the Green River, Piceance and East Texas basins, which in total added 2.9 Bcf of reserves at an average cost of $0.26/Mcf. In addition, it was found that in complex and heterogeneous reservoirs (such as tight sand formations), candidate selection procedures should involve a combination of fundamental engineering and advanced pattern recognition approaches, and that simple statistical methods for identifying candidate wells are not effective. In mid-2000, the U.S. Department of Energy (DOE) awarded ARI an R&D contract to determine if the methods employed in that project could also be applied to stripper gas wells. In addition, the ability of those approaches to identify more general production enhancement opportunities (beyond only restimulation), such as via artificial lift and compression
Khrennikov, Andrei
2017-02-01
The scientific methodology based on two descriptive levels, ontic (reality as it is) and epistemic (observational), is briefly presented. Following Schrödinger, we point to the possible gap between these two descriptions. Our main aim is to show that, although ontic entities may be unaccessible for observations, they can be useful for clarification of the physical nature of operational epistemic entities. We illustrate this thesis by the concrete example: starting with the concrete ontic model preceding quantum mechanics (the latter is treated as an epistemic model), namely, prequantum classical statistical field theory (PCSFT), we propose the natural physical interpretation for the basic quantum mechanical entity-the quantum state ("wave function"). The correspondence PCSFT ↦ QM is not straightforward, it couples the covariance operators of classical (prequantum) random fields with the quantum density operators. We use this correspondence to clarify the physical meaning of the pure quantum state and the superposition principle-by using the formalism of classical field correlations. In classical mechanics the phase space description can be considered as the ontic description, here states are given by points λ =(x , p) of phase space. The dynamics of the ontic state is given by the system of Hamiltonian equations.We can also consider probability distributions on the phase space (or equivalently random variables valued in it). We call them probabilistic ontic states. Dynamics of probabilistic ontic states is given by the Liouville equation.In classical physics we can (at least in principle) measure both the coordinate and momentum and hence ontic states can be treated as epistemic states as well (or it is better to say that here epistemic states can be treated as ontic states). Probabilistic ontic states represent probabilities for outcomes of joint measurement of position and momentum.However, this was a very special, although very important, example of
Heikamp, Kathrin; Bajorath, Jürgen
2013-07-22
The choice of negative training data for machine learning is a little explored issue in chemoinformatics. In this study, the influence of alternative sets of negative training data and different background databases on support vector machine (SVM) modeling and virtual screening has been investigated. Target-directed SVM models have been derived on the basis of differently composed training sets containing confirmed inactive molecules or randomly selected database compounds as negative training instances. These models were then applied to search background databases consisting of biological screening data or randomly assembled compounds for available hits. Negative training data were found to systematically influence compound recall in virtual screening. In addition, different background databases had a strong influence on the search results. Our findings also indicated that typical benchmark settings lead to an overestimation of SVM-based virtual screening performance compared to search conditions that are more relevant for practical applications.
International Nuclear Information System (INIS)
Smith, B.R.
1995-01-01
This document identifies the candidate materials and manufacturing processes selected for development of the TPX Toroidal Field (TF) Magnet. Supporting rationale and selection criteria are provided for justification and the materials properties database report is included for completeness. Specific properties for each material selection are included in this document
A method simulating random magnetic field in interplanetary space by an autoregressive method
International Nuclear Information System (INIS)
Kato, Masahito; Sakai, Takasuke
1985-01-01
With an autoregressive method, we tried to generate the random noise fitting in with the power spectrum which can be analytically Fouriertransformed into an autocorrelation function. Although we can not directly compare our method with FFT by Owens (1978), we can only point out the following; FFT method should determine at first the number of data points N, or the total length to be generated and we cannot generate random data more than N. Because, beyond the NΔy, the generated data repeats the same pattern as below NΔy, where Δy = minimum interval for random noise. So if you want to change or increase N after generating the random noise, you should start the generation from the first step. The characteristic of the generated random number may depend upon the number of N, judging from the generating method. Once the prediction error filters are determined, our method can produce successively the random numbers, that is, we can possibly extend N to infinite without any effort. (author)
Zi, Bin; Zhou, Bin
2016-07-01
For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .
Crossfostering in mice selectively bred for high and low levels of open-field thigmotaxis.
Leppänen, Pia K; Ewalds-Kvist, S Béatrice M
2005-02-01
The main purpose of this research was to investigate whether the difference in open-field (OF) thigmotaxis between mice selectively bred for high and low levels of wall-seeking behavior originated from genetic or acquired sources. Unfostered, infostered, and crossfostered mice were compared in two experiments in which the effects of strain, sex, and fostering on ambulation, defecation, exploration, grooming, latency to move, radial latency, rearing, thigmotaxis, and urination were studied. These experiments revealed that OF thigmotaxis was unaffected by the foster condition and thus genetically determined. The selected strains of mice also diverged repeatedly with regard to exploration and rearing. The findings are in line with the previously described existence of an inverse relationship between emotionality and exploration.
Directory of Open Access Journals (Sweden)
Morley O. Stone
2011-06-01
Full Text Available Zinc oxide field effect transistors (ZnO-FET, covalently functionalized with single stranded DNA aptamers, provide a highly selective platform for label-free small molecule sensing. The nanostructured surface morphology of ZnO provides high sensitivity and room temperature deposition allows for a wide array of substrate types. Herein we demonstrate the selective detection of riboflavin down to the pM level in aqueous solution using the negative electrical current response of the ZnO-FET by covalently attaching a riboflavin binding aptamer to the surface. The response of the biofunctionalized ZnO-FET was tuned by attaching a redox tag (ferrocene to the 3’ terminus of the aptamer, resulting in positive current modulation upon exposure to riboflavin down to pM levels.
Novel Zn2+-chelating peptides selected from a fimbria-displayed random peptide library
DEFF Research Database (Denmark)
Kjærgaard, Kristian; Schembri, Mark; Klemm, Per
2001-01-01
The display of peptide sequences on the surface of bacteria is a technology that offers exciting applications in biotechnology and medical research. Type 1 fimbriae are surface organelles of Escherichia coli which mediate D-mannose-sensitive binding to different host surfaces by virtue of the Fim......H adhesin. FimH is a component of the fimbrial organelle that can accommodate and display a diverse range of peptide sequences on the E. coli cell surface. In this study we have constructed a random peptide library in FimH. The library, consisting of similar to 40 million individual clones, was screened...
CSIR Research Space (South Africa)
Salmon, BP
2015-07-01
Full Text Available In this paper the authors present a 2-tier higher order Conditional Random Field which is used for land cover classification. The Conditional Random Field is based on probabilistic messages being passed along a graph to compute efficiently...
International Nuclear Information System (INIS)
Kamieniarz, G.
1984-12-01
A zero temperature real space renormalization group block method is applied to the random quantum Ising model with a transverse field on the planar honeycomb and square lattices. For the bond diluted system the magnetisation and the separation of the ground state energy level (in the paramagnetic phase) are presented for several bond concentrations p. The critical exponents extracted both from the fixed-points and from direct numerical computations preserve some scaling relations, and the critical curve displays a characteristic discontinuity at the percolation concentration. For the McCoy and Wu distribution the random fields and bonds are found to introduce a strong relevant disorder. The order parameter still falls off continuously to zero for well-defined values of the parameters, but a new fixed point yields a slight change in the critical exponents. (author)
International Nuclear Information System (INIS)
Kim, Un Jeong; Park, Wanjun
2009-01-01
The transport properties of randomly networked single walled carbon nanotube (SWNT) transistors with different channel lengths of L c = 2-10 μm were investigated. Randomly networked SWNTs were directly grown for the two different densities of ρ ∼ 25 μm -2 and ρ ∼ 50 μm -2 by water plasma enhanced chemical vapour deposition. The field effect transport is governed mainly by formation of the current paths that is related to the nanotube density. On the other hand, the off-state conductivity deviates from linear dependence for both nanotube density and channel length. The field effect mobility of holes is estimated as 4-13 cm 2 V -1 s -1 for the nanotube transistors based on the simple MOS theory. The mobility is increased for the higher density without meaningful dependence on the channel lengths.
Dahlberg, Peter D; Boughter, Christopher T; Faruk, Nabil F; Hong, Lu; Koh, Young Hoon; Reyer, Matthew A; Shaiber, Alon; Sherani, Aiman; Zhang, Jiacheng; Jureller, Justin E; Hammond, Adam T
2016-11-01
A standard wide field inverted microscope was converted to a spatially selective spectrally resolved microscope through the addition of a polarizing beam splitter, a pair of polarizers, an amplitude-mode liquid crystal-spatial light modulator, and a USB spectrometer. The instrument is capable of simultaneously imaging and acquiring spectra over user defined regions of interest. The microscope can also be operated in a bright-field mode to acquire absorption spectra of micron scale objects. The utility of the instrument is demonstrated on three different samples. First, the instrument is used to resolve three differently labeled fluorescent beads in vitro. Second, the instrument is used to recover time dependent bleaching dynamics that have distinct spectral changes in the cyanobacteria, Synechococcus leopoliensis UTEX 625. Lastly, the technique is used to acquire the absorption spectra of CH 3 NH 3 PbBr 3 perovskites and measure differences between nanocrystal films and micron scale crystals.
Dahlberg, Peter D.; Boughter, Christopher T.; Faruk, Nabil F.; Hong, Lu; Koh, Young Hoon; Reyer, Matthew A.; Shaiber, Alon; Sherani, Aiman; Zhang, Jiacheng; Jureller, Justin E.; Hammond, Adam T.
2016-11-01
A standard wide field inverted microscope was converted to a spatially selective spectrally resolved microscope through the addition of a polarizing beam splitter, a pair of polarizers, an amplitude-mode liquid crystal-spatial light modulator, and a USB spectrometer. The instrument is capable of simultaneously imaging and acquiring spectra over user defined regions of interest. The microscope can also be operated in a bright-field mode to acquire absorption spectra of micron scale objects. The utility of the instrument is demonstrated on three different samples. First, the instrument is used to resolve three differently labeled fluorescent beads in vitro. Second, the instrument is used to recover time dependent bleaching dynamics that have distinct spectral changes in the cyanobacteria, Synechococcus leopoliensis UTEX 625. Lastly, the technique is used to acquire the absorption spectra of CH3NH3PbBr3 perovskites and measure differences between nanocrystal films and micron scale crystals.
Biological effects of static magnetic fields: a selective review with emphasis on risk assessment
International Nuclear Information System (INIS)
Easterly, C.E.
1982-04-01
Rather than focusing on literature per se, the current study determines the status of magnetic field information that is applicable to risk assessment. Hence, an attempt is made to identify both the literature that is useful to the goal of risk assessment and a framework within which risk assessment methodologies can be derived. From this selected review, it is concluded that three areas exist for which adequate information can be found to begin modelling: disease induction, reproduction and development, and cardiovascular response. The first two are supported by a combination of positive and negative findings and the last by a calculational technique which utilizes the physically well-known principle of flow retardation for a conducting fluid moving through a magnetic field
Biological effects of static magnetic fields: a selective review with emphasis on risk assessment
Energy Technology Data Exchange (ETDEWEB)
Easterly, C. E.
1982-04-01
Rather than focusing on literature per se, the current study determines the status of magnetic field information that is applicable to risk assessment. Hence, an attempt is made to identify both the literature that is useful to the goal of risk assessment and a framework within which risk assessment methodologies can be derived. From this selected review, it is concluded that three areas exist for which adequate information can be found to begin modelling: disease induction, reproduction and development, and cardiovascular response. The first two are supported by a combination of positive and negative findings and the last by a calculational technique which utilizes the physically well-known principle of flow retardation for a conducting fluid moving through a magnetic field.
An Approach to Near Field Data Selection in Radio Frequency Identification
Winkworth, Robert D.
Personal identification is needed in many civil activities, and the common identification cards, such as a driver's license, have become the standard document de facto. Radio frequency identification has complicated this matter. Unlike their printed predecessors, contemporary RFID cards lack a practical way for users to control access to their individual fields of data. This leaves them more available to unauthorized parties, and more prone to abuse. Here, then was undertaken a means to test a novel RFID card technology that allows overlays to be used for reliable, reversible data access settings. Similar to other proposed switching mechanisms, it offers advantages that may greatly improve outcomes. RFID use is increasing in identity documents such as drivers' licenses and passports, and with it concern over the theft of personal information, which can enable unauthorized tracking or fraud. Effort put into designing a strong foundation technology now may allow for widespread development on them later. In this dissertation, such a technology was designed and constructed, to drive the central thesis that selective detuning could serve as a feasible, reliable mechanism. The concept had been illustrated effective in limiting access to all fields simultaneously before, and was here effective in limiting access to specific fields selectively. A novel card was produced in familiar dimensions, with an intuitive interface by which users may conceal the visible print of the card to conceal the wireless emissions it allows. A discussion was included of similar technologies, involving capacitive switching, that could further improve the outcomes if such a product were put to large-scale commercial fabrication. The card prototype was put to a battery of laboratory tests to measure the degree of independence between data fields and the reliability of the switching mechanism when used under realistically variable coverage, demonstrating statistically consistent performance in
Directory of Open Access Journals (Sweden)
Phil Diamond
2003-01-01
Full Text Available Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.
On the usage of geomagnetic indices for data selection in internal field modelling
DEFF Research Database (Denmark)
Kauristie, K.; Morschhauser, A.; Olsen, Nils
2017-01-01
are primarily used in data selection criteria for weak magnetic activity.The publicly available extensive data bases of index values are used to derive joint conditional Probability Distribution Functions (PDFs) for different pairs of indices in order to investigate their mutual consistency in describing quiet......) as derived from solar wind observations. We use in our PDF analysis the PC-index as a proxy for MEF and estimate the magnetic activity level at auroral latitudes with the AL-index. With these boundary conditions we conclude that the quiet time conditions that are typically used in main field modelling (PC...
International Nuclear Information System (INIS)
Fu Chuanji; Zhu Qinsheng; Wu Shaoyi
2010-01-01
Based on algebraic dynamics and the concept of the concurrence of the entanglement, we investigate the evolutive properties of the two-qubit entanglement that formed by Heisenberg XXX models under a time-depending external held. For this system, the property of the concurrence that is only dependent on the coupling constant J and total values of the external field is proved. Furthermore, we found that the thermal concurrence of the system under a static random external field is a function of the coupling constant J, temperature T, and the magnitude of external held. (general)
Directory of Open Access Journals (Sweden)
Victor NORDIN
2014-01-01
Full Text Available Expert systems can be defined as computer programs, whose main task is to simulate a human expert, usually in a narrow field of expertise. Possible applications of modern information technology are very extensive, ranging from medicine, geology and technology to applications in the field of economic and financial decision support. The purpose of this paper is to present the practical application of an expert system that supports the process of managing the production of yachts and has a high suitability for use in this application. Using the expert system described in the paper reduces the time during the design and production preparation process.
WANG, P. T.
2015-12-01
Groundwater modeling requires to assign hydrogeological properties to every numerical grid. Due to the lack of detailed information and the inherent spatial heterogeneity, geological properties can be treated as random variables. Hydrogeological property is assumed to be a multivariate distribution with spatial correlations. By sampling random numbers from a given statistical distribution and assigning a value to each grid, a random field for modeling can be completed. Therefore, statistics sampling plays an important role in the efficiency of modeling procedure. Latin Hypercube Sampling (LHS) is a stratified random sampling procedure that provides an efficient way to sample variables from their multivariate distributions. This study combines the the stratified random procedure from LHS and the simulation by using LU decomposition to form LULHS. Both conditional and unconditional simulations of LULHS were develpoed. The simulation efficiency and spatial correlation of LULHS are compared to the other three different simulation methods. The results show that for the conditional simulation and unconditional simulation, LULHS method is more efficient in terms of computational effort. Less realizations are required to achieve the required statistical accuracy and spatial correlation.
van Nierop, Lotte E; Slottje, Pauline; Kingma, Herman; Kromhout, Hans
2013-07-01
We assessed postural body sway performance after exposure to movement induced time-varying magnetic fields in the static magnetic stray field in front of a 7 Tesla (T) magnetic resonance imaging scanner. Using a double blind randomized crossover design, 30 healthy volunteers performed two balance tasks (i.e., standing with eyes closed and feet in parallel and then in tandem position) after standardized head movements in a sham, low exposure (on average 0.24 T static magnetic stray field and 0.49 T·s(-1) time-varying magnetic field) and high exposure condition (0.37 T and 0.70 T·s(-1)). Personal exposure to static magnetic stray fields and time-varying magnetic fields was measured with a personal dosimeter. Postural body sway was expressed in sway path, area, and velocity. Mixed-effects model regression analysis showed that postural body sway in the parallel task was negatively affected (P < 0.05) by exposure on all three measures. The tandem task revealed the same trend, but did not reach statistical significance. Further studies are needed to investigate the possibility of independent or synergetic effects of static magnetic stray field and time-varying magnetic field exposure. In addition, practical safety implications of these findings, e.g., for surgeons and others working near magnetic resonance imaging scanners need to be investigated. Copyright © 2012 Wiley Periodicals, Inc.
Lee, Stella Juhyun; Brennan, Emily; Gibson, Laura Anne; Tan, Andy S. L.; Kybert-Momjian, Ani; Liu, Jiaying; Hornik, Robert
2016-01-01
Several message topic selection approaches propose that messages based on beliefs pretested and found to be more strongly associated with intentions will be more effective in changing population intentions and behaviors when used in a campaign. This study aimed to validate the underlying causal assumption of these approaches which rely on cross-sectional belief–intention associations. We experimentally tested whether messages addressing promising themes as identified by the above criterion were more persuasive than messages addressing less promising themes. Contrary to expectations, all messages increased intentions. Interestingly, mediation analyses showed that while messages deemed promising affected intentions through changes in targeted promising beliefs, messages deemed less promising also achieved persuasion by influencing nontargeted promising beliefs. Implications for message topic selection are discussed. PMID:27867218
Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models
DEFF Research Database (Denmark)
Kock, Anders Bredahl
This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...
Presence of psychoactive substances in oral fluid from randomly selected drivers in Denmark
DEFF Research Database (Denmark)
Simonsen, K. Wiese; Steentoft, A.; Hels, Tove
2012-01-01
. The percentage of drivers positive for medicinal drugs above the Danish legal concentration limit was 0.4%; while, 0.3% of the drivers tested positive for one or more illicit drug at concentrations exceeding the Danish legal limit. Tetrahydrocannabinol, cocaine, and amphetamine were the most frequent illicit......This roadside study is the Danish part of the EU-project DRUID (Driving under the Influence of Drugs, Alcohol, and Medicines) and included three representative regions in Denmark. Oral fluid samples (n = 3002) were collected randomly from drivers using a sampling scheme stratified by time, season......, and road type. The oral fluid samples were screened for 29 illegal and legal psychoactive substances and metabolites as well as ethanol. Fourteen (0.5%) drivers were positive for ethanol alone or in combination with drugs) at concentrations above 0.53 g/l (0.5 mg/g), which is the Danish legal limit...
International Nuclear Information System (INIS)
Janaszczyk, A.; Bogusz-Czerniewicz, M.
2011-01-01
Background: Radiation technology is a discipline of medical science which deals with diagnostics, imaging and radiotherapy, that is treatment by ionizing radiation. Aim: To present and compare the existing curricula of radiation technology in selected EU countries. Materials and methods: The research work done for the purpose of the comparative analysis was based on the methods of diagnostic test and document analysis. Results: The comparison of curricula in selected countries, namely Austria, France, the Netherlands and Poland, showed that admission criteria to radiation technology courses are varied and depend on regulations of respective Ministries of Health. The most restrictive conditions, including written tests in biology, chemistry and physics, and psychometric test, are those in France. Contents of basic and specialist subject groups are very similar in all the countries. The difference is in the number of ECT points assigned to particular subjects and the number of course hours offered. The longest practical training is provided in the Netherlands and the shortest one in Poland. The duration of studies in the Netherlands is 4 years, while in Poland it is 3 years. Austria is the only country to offer extra practical training in quality management. Conclusion: Graduates in the compared EU countries have similar level of qualifications in the fields of operation of radiological equipment, radiotherapy, nuclear medicine, foreign language and specialist terminology in the field of medical and physical sciences, general knowledge of medical and physical sciences, and detailed knowledge of radiation technology. (authors)
Woitas-Slubowska, Donata; Hurnik, Elzbieta; Skarpańska-Stejnborn, Anna
2010-12-01
To determine the association between smoking status and leisure time physical activity (LTPA), alcohol consumption, and socioeconomic status (SES) among Polish adults. 466 randomly selected men and women (aged 18-66 years) responded to an anonymous questionnaire regarding smoking, alcohol consumption, LTPA, and SES. Multiple logistic regression was used to examine the association of smoking status with six socioeconomic measures, level of LTPA, and frequency and type of alcohol consumed. Smokers were defined as individuals smoking occasionally or daily. The odds of being smoker were 9 times (men) and 27 times (women) higher among respondents who drink alcohol several times/ week or everyday in comparison to non-drinkers (p times higher compared to those with the high educational attainment (p = 0.007). Among women we observed that students were the most frequent smokers. Female students were almost three times more likely to smoke than non-professional women, and two times more likely than physical workers (p = 0.018). The findings of this study indicated that among randomly selected Polish man and women aged 18-66 smoking and alcohol consumption tended to cluster. These results imply that intervention strategies need to target multiple risk factors simultaneously. The highest risk of smoking was observed among low educated men, female students, and both men and women drinking alcohol several times a week or every day. Information on subgroups with the high risk of smoking will help in planning future preventive strategies.
Afshari, Daryoush; Moradian, Nasrin; Khalili, Majid; Razazian, Nazanin; Bostani, Arash; Hoseini, Jamal; Moradian, Mohamad; Ghiasian, Masoud
2016-10-01
Evidence is mounting that magnet therapy could alleviate the symptoms of multiple sclerosis (MS). This study was performed to test the effects of the pulsing magnetic fields on the paresthesia in MS patients. This study has been conducted as a randomized, double-blind, parallel-group clinical trial during the April 2012 to October 2013. The subjects were selected among patients referred to MS clinic of Imam Reza Hospital; affiliated to Kermanshah University of Medical Sciences, Iran. Sixty three patients with MS were included in the study and randomly were divided into two groups, 35 patients were exposed to a magnetic pulsing field of 4mT intensity and 15-Hz frequency sinusoidal wave for 20min per session 2 times per week over a period of 2 months involving 16 sessions and 28 patients was exposed to a magnetically inactive field (placebo) for 20min per session 2 times per week over a period of 2 months involving 16 sessions. The severity of paresthesia was measured by the numerical rating scale (NRS) at 30, 60days. The study primary end point was NRS change between baseline and 60days. The secondary outcome was NRS change between baseline and 30days. Patients exposing to magnetic field showed significant paresthesia improvement compared with the group of patients exposing to placebo. According to our results pulsed magnetic therapy could alleviate paresthesia in MS patients .But trials with more patients and longer duration are mandatory to describe long-term effects. Copyright © 2016 Elsevier B.V. All rights reserved.
Séry, D. Jean-Marc; Kouadjo, Z. G. Claude; Voko, B. R. Rodrigue; Zézé, Adolphe
2016-01-01
The use of arbuscular mycorrhizal fungal (AMF) inoculation in sustainable agriculture is now widespread worldwide. Although the use of inoculants consisting of native AMF is highly recommended as an alternative to commercial ones, there is no strategy to allow the selection of efficient fungal species from natural communities. The objective of this study was (i) to select efficient native AMF species (ii) evaluate their impact on nematode and water stresses, and (iii) evaluate their impact on cassava yield, an important food security crop in tropical and subtropical regions. Firstly, native AMF communities associated with cassava rhizospheres in fields were collected from different areas and 7 AMF species were selected, based upon their ubiquity and abundance. Using these criteria, two morphotypes (LBVM01 and LBVM02) out of the seven AMF species selected were persistently dominant when cassava was used as a trap plant. LBVM01 and LBVM02 were identified as Acaulospora colombiana (most abundant) and Ambispora appendicula, respectively, after phylogenetic analyses of LSU-ITS-SSU PCR amplified products. Secondly, the potential of these two native AMF species to promote growth and enhance tolerance to root-knot nematode and water stresses of cassava (Yavo variety) was evaluated using single and dual inoculation in greenhouse conditions. Of the two AMF species, it was shown that A. colombiana significantly improved the growth of the cassava and enhanced tolerance to water stress. However, both A. colombiana and A. appendicula conferred bioprotective effects to cassava plants against the nematode Meloidogyne spp., ranging from resistance (suppression or reduction of the nematode reproduction) or tolerance (low or no suppression in cassava growth). Thirdly, the potential of these selected native AMF to improve cassava growth and yield was evaluated under field conditions, compared to a commercial inoculant. In these conditions, the A. colombiana single inoculation and the
Hardwick, Kayla M.; Harmon, Luke J.; Hardwick, Scott D.; Rosenblum, Erica Bree
2015-01-01
Determining the adaptive significance of phenotypic traits is key for understanding evolution and diversification in natural populations. However, evolutionary biologists have an incomplete understanding of how specific traits affect fitness in most populations. The White Sands system provides an opportunity to study the adaptive significance of traits in an experimental context. Blanched color evolved recently in three species of lizards inhabiting the gypsum dunes of White Sands and is likely an adaptation to avoid predation. To determine whether there is a relationship between color and susceptibility to predation in White Sands lizards, we conducted enclosure experiments, quantifying survivorship of Holbrookia maculate exhibiting substrate-matched and substrate-mismatched phenotypes. Lizards in our study experienced strong predation. Color did not have a significant effect on survival, but we found several unexpected relationships including variation in predation over small spatial and temporal scales. In addition, we detected a marginally significant interaction between sex and color, suggesting selection for substrate matching may be stronger for males than females. We use our results as a case study to examine six major challenges frequently encountered in field-based studies of natural selection, and suggest that insight into the complexities of selection often results when experiments turn out differently than expected. PMID:25714838
Abdel Nabi, Amr A
2017-09-21
This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.
Abdel Nabi, Amr A; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammed
2017-01-01
This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.
A portable high-quality random number generator for lattice field theory simulations
International Nuclear Information System (INIS)
Luescher, M.
1993-09-01
The theory underlying a proposed random number generator for numerical simulations in elementary particle physics and statistical mechanics is discussed. The generator is based on an algorithm introduced by Marsaglia and Zaman, with an important added feature leading to demonstrably good statistical properties. It can be implemented exactly on any computer complying with the IEEE-754 standard for single precision floating point arithmetic. (orig.)
van Klaveren, Chris; Vonk, Sebastiaan; Cornelisz, Ilja
2017-01-01
Schools and governments are increasingly investing in adaptive practice software. To date, the evidence whether adaptivity improves learning outcomes is limited and mixed. A large-scale randomized control trial is conducted in Dutch secondary schools to evaluate the effectiveness of an adaptive
Explaining Feast or Famine in Randomized Field Trials: Medical Science and Criminology Compared.
Shepherd, Jonathan P.
2003-01-01
Discusses the contrast between the frequency of randomized clinical trials in the health sciences and the relative famine of such studies in criminology. Attributes this difference to the contexts in which research is done and the difference in the status of situational research in the two disciplines. (SLD)
Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark
2015-01-01
Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed
Selective Cooperation in the Supermarket : Field Experimental Evidence for Indirect Reciprocity.
Lange, Florian; Eggert, Frank
2015-12-01
Numerous laboratory experiments suggest that mechanisms of indirect reciprocity might account for human cooperation. However, conclusive field data supporting the predictions of indirect reciprocity in everyday life situations is still scarce. Here, we attempt to compensate for this lack by examining the determinants of cooperative behavior in a German supermarket. Our methods were as follows: Confederates of the experimenter lined up at the checkout, apparently to buy a single item. As an act of cooperation, the waiting person in front (the potential helper) could allow the confederate to go ahead. By this means, the potential helper could take a cost (additional waiting time) by providing the confederate with a benefit (saved waiting time). We recorded the potential helpers' behavior and the number of items they purchased as a quantitative measure proportional to the confederate's benefit. Moreover, in a field experimental design, we varied the confederates' image by manipulating the item they purchased (beer vs. water). As predicted, the more waiting time they could save, the more likely the confederates were to receive cooperation. This relationship was moderated by the confederates' image. Cost-to-benefit ratios were required to be more favorable for beer-purchasing individuals to receive cooperation. Our results demonstrate that everyday human cooperation can be studied unobtrusively in the field and that cooperation among strangers is selective in a way that is consistent with current models of indirect reciprocity.
Extremes of random fields over arbitrary domains with application to concrete rupture stresses
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2004-01-01
function class is studied for Gaussian processes in earlier works by the author and it has been obtained explicitly for Gaussian fields on rectangular domains in the plane. Simulation studies show that rather good predictions are obtained for sufficiently smooth wide band Gaussian processes and fields...
Capturing the Flatness of a peer-to-peer lending network through random and selected perturbations
Karampourniotis, Panagiotis D.; Singh, Pramesh; Uparna, Jayaram; Horvat, Emoke-Agnes; Szymanski, Boleslaw K.; Korniss, Gyorgy; Bakdash, Jonathan Z.; Uzzi, Brian
Null models are established tools that have been used in network analysis to uncover various structural patterns. They quantify the deviance of an observed network measure to that given by the null model. We construct a null model for weighted, directed networks to identify biased links (carrying significantly different weights than expected according to the null model) and thus quantify the flatness of the system. Using this model, we study the flatness of Kiva, a large international crownfinancing network of borrowers and lenders, aggregated to the country level. The dataset spans the years from 2006 to 2013. Our longitudinal analysis shows that flatness of the system is reducing over time, meaning the proportion of biased inter-country links is growing. We extend our analysis by testing the robustness of the flatness of the network in perturbations on the links' weights or the nodes themselves. Examples of such perturbations are event shocks (e.g. erecting walls) or regulatory shocks (e.g. Brexit). We find that flatness is unaffected by random shocks, but changes after shocks target links with a large weight or bias. The methods we use to capture the flatness are based on analytics, simulations, and numerical computations using Shannon's maximum entropy. Supported by ARL NS-CTA.
Clark, Imogen N; Baker, Felicity A; Peiris, Casey L; Shoebridge, Georgie; Taylor, Nicholas F
2017-03-01
To evaluate effects of participant-selected music on older adults' achievement of activity levels recommended in the physical activity guidelines following cardiac rehabilitation. A parallel group randomized controlled trial with measurements at Weeks 0, 6 and 26. A multisite outpatient rehabilitation programme of a publicly funded metropolitan health service. Adults aged 60 years and older who had completed a cardiac rehabilitation programme. Experimental participants selected music to support walking with guidance from a music therapist. Control participants received usual care only. The primary outcome was the proportion of participants achieving activity levels recommended in physical activity guidelines. Secondary outcomes compared amounts of physical activity, exercise capacity, cardiac risk factors, and exercise self-efficacy. A total of 56 participants, mean age 68.2 years (SD = 6.5), were randomized to the experimental ( n = 28) and control groups ( n = 28). There were no differences between groups in proportions of participants achieving activity recommended in physical activity guidelines at Week 6 or 26. Secondary outcomes demonstrated between-group differences in male waist circumference at both measurements (Week 6 difference -2.0 cm, 95% CI -4.0 to 0; Week 26 difference -2.8 cm, 95% CI -5.4 to -0.1), and observed effect sizes favoured the experimental group for amounts of physical activity (d = 0.30), exercise capacity (d = 0.48), and blood pressure (d = -0.32). Participant-selected music did not increase the proportion of participants achieving recommended amounts of physical activity, but may have contributed to exercise-related benefits.
Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro
2016-12-15
MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.
LENUS (Irish Health Repository)
Cronin, C C
2012-02-03
Abnormalities of the renin-angiotensin system have been reported in patients with diabetes mellitus and with diabetic complications. In this study, plasma concentrations of prorenin, renin, and aldosterone were measured in a stratified random sample of 110 insulin-dependent (Type 1) diabetic patients attending our outpatient clinic. Fifty-four age- and sex-matched control subjects were also examined. Plasma prorenin concentration was higher in patients without complications than in control subjects when upright (geometric mean (95% confidence intervals (CI): 75.9 (55.0-105.6) vs 45.1 (31.6-64.3) mU I-1, p < 0.05). There was no difference in plasma prorenin concentration between patients without and with microalbuminuria and between patients without and with background retinopathy. Plasma renin concentration, both when supine and upright, was similar in control subjects, in patients without complications, and in patients with varying degrees of diabetic microangiopathy. Plasma aldosterone was suppressed in patients without complications in comparison to control subjects (74 (58-95) vs 167 (140-199) ng I-1, p < 0.001) and was also suppressed in patients with microvascular disease. Plasma potassium was significantly higher in patients than in control subjects (mean +\\/- standard deviation: 4.10 +\\/- 0.36 vs 3.89 +\\/- 0.26 mmol I-1; p < 0.001) and plasma sodium was significantly lower (138 +\\/- 4 vs 140 +\\/- 2 mmol I-1; p < 0.001). We conclude that plasma prorenin is not a useful early marker for diabetic microvascular disease. Despite apparently normal plasma renin concentrations, plasma aldosterone is suppressed in insulin-dependent diabetic patients.
International Nuclear Information System (INIS)
Velez Juarez, Esteban; Rodriguez Garciapinna, Jorge L.; Ostrovsky, Andrey S.
2016-01-01
A technique for experimental determining the coherent-mode structure of electromagnetic field is proposed. This technique is based on the coherence measurements of the field in some reference basis and represents a nontrivial vector generalization of the dual-mode field correlation method recently reported by F. Ferreira and M. Belsley. The justifiability and efficiency of the proposed technique is illustrated by an example of determining the coherent-mode structure of some specially generated and experimentally characterized secondary electromagnetic source using a spatial modulator of light of liquid crystal (SLM-LC). (Author)
Directory of Open Access Journals (Sweden)
Nantian Huang
2016-09-01
Full Text Available The prediction accuracy of short-term load forecast (STLF depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.
Mixed spin Ising model with four-spin interaction and random crystal field
International Nuclear Information System (INIS)
Benayad, N.; Ghliyem, M.
2012-01-01
The effects of fluctuations of the crystal field on the phase diagram of the mixed spin-1/2 and spin-1 Ising model with four-spin interactions are investigated within the finite cluster approximation based on a single-site cluster theory. The state equations are derived for the two-dimensional square lattice. It has been found that the system exhibits a variety of interesting features resulting from the fluctuation of the crystal field interactions. In particular, for low mean value D of the crystal field, the critical temperature is not very sensitive to fluctuations and all transitions are of second order for any value of the four-spin interactions. But for relatively high D, the transition temperature depends on the fluctuation of the crystal field, and the system undergoes tricritical behaviour for any strength of the four-spin interactions. We have also found that the model may exhibit reentrance for appropriate values of the system parameters.
Brémaud, Pierre
2017-01-01
The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book. .
DEFF Research Database (Denmark)
Bakmar, Christian LeBlanc
.D. thesis was to enable low-cost and low-risk support structures to be designed in order to improve the economic feasibility of future offshore wind farms. The research work was divided in the following four selected research topics in the field of geotechnical engineering, relating to the monopile......Breaking the dependence on fossil fuels offers many opportunities for strengthened competitiveness, technological development and progress. Offshore wind power is a domestic, sustainable and largely untapped energy resource that provides an alternative to fossil fuels, reduces carbon emissions......, and decreases the economic and supply risks associated with reliance on imported fuels. Today, the modern offshore wind turbine offers competitive production prices for renewable energy and is therefore a key technology in achieving the energy and climate goals of the future. The overall aim of this Ph...
MicroCHP: Overview of selected technologies, products and field test results
Energy Technology Data Exchange (ETDEWEB)
Kuhn, Vollrad [Berliner Energieagentur GmbH, Franzoesische Strasse 23, 10117 Berlin (Germany); Klemes, Jiri; Bulatov, Igor [Centre for Process Integration, CEAS, The University of Manchester, P.O. Box 88, M60 1QD Manchester (United Kingdom)
2008-11-15
This paper gives an overview on selected microCHP technologies and products with the focus on Stirling and steam machines. Field tests in Germany, the UK and some other EC countries are presented, assessed and evaluated. Test results show the overall positive performance with differences in sectors (domestic vs. small business). Some negative experiences have been received, especially from tests with the Stirling engines and the free-piston steam machine. There are still obstacles for market implementation. Further projects and tests of microCHP are starting in various countries. When positive results will prevail and deficiencies are eliminated, a way to large-scale production and market implementation could be opened. (author)
Bucur, Roxana C; Reid, Lauren S; Hamilton, Celeste J; Cummings, Steven R; Jamal, Sophie A
2013-09-08
comparisons with the best' approach for data analyses, as this strategy allows practical considerations of ease of use and tolerability to guide selection of the preparation for future studies. Data from this protocol will be used to develop a randomized, controlled trial of nitrates to prevent osteoporotic fractures. ClinicalTrials.gov Identifier: NCT01387672. Controlled-Trials.com: ISRCTN08860742.
Further constraints on the evolution of K-s-selected galaxies in the GOODS/CDFS field
Caputi, KI; McLure, RJ; Dunlop, JS; Cirasuolo, M; Schael, AM
2006-01-01
We have selected and analysed the properties of a sample of 2905 K-s <21.5 galaxies in similar to 131 arcmin(2) of the Great Observatories Origins Deep Survey (GOODS) Chandra Deep Field South (CDFS), to obtain further constraints on the evolution of K-s-selected galaxies with respect to the results
Cid, C.C.; Jimenez-Cadena, G.; Riu, J.; Maroto, A.; Rius, F.X.; Batema, G.D.; van Koten, G.
2009-01-01
We report a field effect transistor (FET) based on a network of single-walled carbon nanotubes (SWCNTs) that for the first time can selectively detect a single gaseous molecule in air by chemically functionalizing the SWCNTs with a selective molecular receptor. As a target model we used SO2. The
Repar, Jelena; Warnecke, Tobias
2017-08-01
Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin-terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus-Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Rodríguez-Feliciano, B.; García-Varela, A.; Pérez-Ortiz, M. F.; Sabogal, B. E.; Minniti, D.
2017-07-01
We characterize properties of time series of variable stars in the B278 field of the VVV survey, using robust statistics. Using random forest and support vector machines classifiers we propose 47 candidates to RR Lyraae, and 12 candidates to WU Ursae Majoris eclipsing binaries.
Li, Ningzhi; Li, Shizhe; Shen, Jun
2017-06-01
In vivo 13C magnetic resonance spectroscopy (MRS) is a unique and effective tool for studying dynamic human brain metabolism and the cycling of neurotransmitters. One of the major technical challenges for in vivo 13C-MRS is the high radio frequency (RF) power necessary for heteronuclear decoupling. In the common practice of in vivo 13C-MRS, alkanyl carbons are detected in the spectra range of 10-65ppm. The amplitude of decoupling pulses has to be significantly greater than the large one-bond 1H-13C scalar coupling (1JCH=125-145 Hz). Two main proton decoupling methods have been developed: broadband stochastic decoupling and coherent composite or adiabatic pulse decoupling (e.g., WALTZ); the latter is widely used because of its efficiency and superb performance under inhomogeneous B1 field. Because the RF power required for proton decoupling increases quadratically with field strength, in vivo 13C-MRS using coherent decoupling is often limited to low magnetic fields (protons via weak long-range 1H-13C scalar couplings, which can be decoupled using low RF power broadband stochastic decoupling. Recently, the carboxylic/amide 13C-MRS technique using low power random RF heteronuclear decoupling was safely applied to human brain studies at 7T. Here, we review the two major decoupling methods and the carboxylic/amide 13C-MRS with low power decoupling strategy. Further decreases in RF power deposition by frequency-domain windowing and time-domain random under-sampling are also discussed. Low RF power decoupling opens the possibility of performing in vivo 13C experiments of human brain at very high magnetic fields (such as 11.7T), where signal-to-noise ratio as well as spatial and temporal spectral resolution are more favorable than lower fields.
Gregory P. Asner; Michael Keller; Rodrigo Pereira; Johan C. Zweede
2002-01-01
We combined a detailed field study of forest canopy damage with calibrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) reflectance data and texture analysis to assess the sensitivity of basic broadband optical remote sensing to selective logging in Amazonia. Our field study encompassed measurements of ground damage and canopy gap fractions along a chronosequence of...
The selection of field component reliability data for use in nuclear safety studies
International Nuclear Information System (INIS)
Coxson, B.A.; Tabaie, Mansour
1990-01-01
The paper reviews the user requirements for field component failure data in nuclear safety studies, and the capability of various data sources to satisfy these requirements. Aspects such as estimating the population of items exposed to failure, incompleteness, and under-reporting problems are discussed. The paper takes as an example the selection of component reliability data for use in the Pre-Operational Safety Report (POSR) for Sizewell 'B' Power Station, where field data has in many cases been derived from equipment other than that to be procured and operated on site. The paper concludes that the main quality sought in the available data sources for such studies is the ability to examine failure narratives in component reliability data systems for equipment performing comparable duties to the intended plant application. The main benefit brought about in the last decade is the interactive access to data systems which are adequately structured with regard to the equipment covered, and also provide a text-searching capability of quality-controlled event narratives. (author)
Messer, Dolores; Wolter, Stefan C.
2009-01-01
This paper presents the results of a randomized experiment analyzing the use of vouchers for adult training. In 2006, 2,400 people were issued with a training voucher which they were entitled to use in payment for a training course of their choice. User behavior was compared with a control group of 14,000 people. People in the treatment and in the control group were not aware at any time that they were part of an experiment. The experiment shows that the voucher had a significant causal impac...
Warris, Sven; Boymans, Sander; Muiser, Iwe; Noback, Michiel; Krijnen, Wim; Nap, Jan-Peter
2014-01-13
Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.
Huh, In; Cheon, Woo Young; Choi, Woo Young
2016-04-01
A subthreshold-swing-adjustable tunneling-field-effect-transistor-based random-access memory (SAT RAM) has been proposed and fabricated for low-power nonvolatile memory applications. The proposed SAT RAM cell demonstrates adjustable subthreshold swing (SS) depending on stored information: small SS in the erase state ("1" state) and large SS in the program state ("0" state). Thus, SAT RAM cells can achieve low read voltage (Vread) with a large memory window in addition to the effective suppression of ambipolar behavior. These unique features of the SAT RAM are originated from the locally stored charge, which modulates the tunneling barrier width (Wtun) of the source-to-channel tunneling junction.
International Nuclear Information System (INIS)
Yao Zhibin; He Baoping; Zhang Fengqi; Guo Hongxia; Luo Yinhong; Wang Yuanming; Zhang Keying
2009-01-01
Based on the detailed investigation in field programmable gate array(FPGA) radiation effects theory, a measurement system for radiation effects on static random access memory(SRAM)-based FPGA was developed. The testing principle of internal memory, function and power current was introduced. The hardware and software implement means of system were presented. Some important parameters for radiation effects on SRAM-based FPGA, such as configuration RAM upset section, block RAM upset section, function fault section and single event latchup section can be gained with this system. The transmission distance of the system can be over 50 m and the maximum number of tested gates can reach one million. (authors)
Li, Jin; Tran, Maggie; Siwabessy, Justy
2016-01-01
Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and
Near field heat transfer between random composite materials. Applications and limitations
Energy Technology Data Exchange (ETDEWEB)
Santiago, Eva Yazmin; Esquivel-Sirvent, Raul [Univ. Nacional Autonoma de Mexico (Mexico). Inst. de Fisica
2017-05-01
We present a theoretical study of the limits and bounds of using effective medium approximations in the calculation of the near field radiative heat transfer between a composite system made of Au nanoparticles in a SiC host and an homogeneous SiC slab. The effective dielectric function of the composite slab is calculated using three different approximations: Maxwell-Garnett, Bruggeman, and Looyenga's. In addition, we considered an empirical fit to the effective dielectric function by Grundquist and Hunderi. We show that the calculated value of the heat flux in the near field is dependent on the model, and the difference in the effective dielectric function is larger around the plasmonic response of the Au nanoparticles. This, in turn, accounts for the difference in the near field radiative heat flux. For all values of filling fractions, the Looyenga approximation gives a lower bound for the heat flux.
The influence of mitigation on sage-grouse habitat selection within an energy development field.
Directory of Open Access Journals (Sweden)
Bradley C Fedy
Full Text Available Growing global energy demands ensure the continued growth of energy development. Energy development in wildlife areas can significantly impact wildlife populations. Efforts to mitigate development impacts to wildlife are on-going, but the effectiveness of such efforts is seldom monitored or assessed. Greater sage-grouse (Centrocercus urophasianus are sensitive to energy development and likely serve as an effective umbrella species for other sagebrush-steppe obligate wildlife. We assessed the response of birds within an energy development area before and after the implementation of mitigation action. Additionally, we quantified changes in habitat distribution and abundance in pre- and post-mitigation landscapes. Sage-grouse avoidance of energy development at large spatial scales is well documented. We limited our research to directly within an energy development field in order to assess the influence of mitigation in close proximity to energy infrastructure. We used nest-location data (n = 488 within an energy development field to develop habitat selection models using logistic regression on data from 4 years of research prior to mitigation and for 4 years following the implementation of extensive mitigation efforts (e.g., decreased activity, buried powerlines. The post-mitigation habitat selection models indicated less avoidance of wells (well density β = 0.18 ± 0.08 than the pre-mitigation models (well density β = -0.09 ± 0.11. However, birds still avoided areas of high well density and nests were not found in areas with greater than 4 wells per km2 and the majority of nests (63% were located in areas with ≤ 1 well per km2. Several other model coefficients differed between the two time periods and indicated stronger selection for sagebrush (pre-mitigation β = 0.30 ± 0.09; post-mitigation β = 0.82 ± 0.08 and less avoidance of rugged terrain (pre-mitigation β = -0.35 ± 0.12; post-mitigation β = -0.05 ± 0.09. Mitigation efforts
Markov Random Field Restoration of Point Correspondences for Active Shape Modelling
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen; Paulsen, Rasmus Reinhold; Larsen, Rasmus
2004-01-01
In this paper it is described how to build a statistical shape model using a training set with a sparse of landmarks. A well defined model mesh is selected and fitted to all shapes in the training set using thin plate spline warping. This is followed by a projection of the points of the warped...
Estimating adhesive seed-dispersal distances : field experiments and correlated random walks
Mouissie, AM; Lengkeek, W; van Diggelen, R
1. In this study we aimed to estimate distance distributions of adhesively dispersed seeds and the factors that determine them. 2. Seed attachment and detachment were studied using field experiments with a real sheep, a sheep dummy and a cattle dummy. Seed-retention data were used in correlated
Sahlsten, Hanna; Virtanen, Juuso; Joutsa, Juho; Niinivirta-Joutsa, Katri; Löyttyniemi, Eliisa; Johansson, Reijo; Paavola, Janika; Taiminen, Tero; Sjösten, Noora; Salonen, Jaakko; Holm, Anu; Rauhala, Esa; Jääskeläinen, Satu K
2017-09-01
Repetitive transcranial magnetic stimulation (rTMS) may alleviate tinnitus. We evaluated effects of electric field (E-field) navigated rTMS targeted according to tinnitus pitch. No controlled studies have investigated anatomically accurate E-field-rTMS for tinnitus. Effects of E-field-rTMS were evaluated in a prospective randomised placebo-controlled 6-month follow-up study on parallel groups. Patients received 10 sessions of 1 Hz rTMS or placebo targeted to the left auditory cortex corresponding to tonotopic representation of tinnitus pitch. Effects were evaluated immediately after treatment and at 1, 3 and 6 months. Primary outcome measures were visual analogue scores (VAS 0-100) for tinnitus intensity, annoyance and distress, and the Tinnitus Handicap Inventory (THI). Thirty-nine patients (mean age 50.3 years). The mean tinnitus intensity (F 3 = 15.7, p tinnitus, differences between active and placebo groups remained non-significant, due to large placebo-effect and wide inter-individual variation.
Fleskes, Joseph P.; Jarvis, Robert L.; Gilmer, David S.
2003-01-01
Habitat selection and use are measures of relative importance of habitats to wildlife and necessary information for effective wildlife conservation. To measure the relative importance of flooded agricultural fields and other landscapes to northern pintails (Anas acuta) wintering in Tulare Basin (TB), California, we radiotagged female pintails during late August-early October, 1991-1993 in TB and other San Joaquin Valley areas and determined use and selection of these TB landscapes through March each year. Availability of landscape and field types in TB changed within and among years. Pintail use and selection (based upon use-to-availability log ratios) of landscape and field types differed among seasons, years, and diel periods. Fields flooded after harvest and before planting (i.e., pre-irrigated) were the most available, used, and selected landscape type before the hunting season (Prehunt). Safflower was the most available, used, and-except in 1993, when pre-irrigated fallow was available-selected pre-irrigated field type during Prehunt. Pre-irrigated barley-wheat received 19-22% of use before hunting season, but selection varied greatly among years and diel periods. During and after hunting season, managed marsh was the most available, used, and, along with floodwater areas, selected landscape type; pre-irrigated cotton and alfalfa were the least selected field types and accounted for <13% of pintail use. Agricultural drainwater evaporation ponds, sewage treatment ponds, and reservoirs accounted for 42-48% of flooded landscape available but were little used and least selected. Exodus of pintails from TB coincided with drying of pre-irrigated fallow, safflower, and barley-wheat fields early in winter, indicating that preferred habitats were lacking in TB during late winter. Agriculture conservation programs could improve TB for pintails by increasing flooding of fallow and harvested safflower and grain fields. Conservation of remaining wetlands should concentrate
Apanasovich, Tatiyana V.; Genton, Marc G.; Sun, Ying
2012-01-01
We introduce a valid parametric family of cross-covariance functions for multivariate spatial random fields where each component has a covariance function from a well-celebrated Matérn class. Unlike previous attempts, our model indeed allows
Energy Technology Data Exchange (ETDEWEB)
Wang, Yonggang, E-mail: wangyg@ustc.edu.cn; Hui, Cong; Liu, Chong; Xu, Chao [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China)
2016-04-15
The contribution of this paper is proposing a new entropy extraction mechanism based on sampling phase jitter in ring oscillators to make a high throughput true random number generator in a field programmable gate array (FPGA) practical. Starting from experimental observation and analysis of the entropy source in FPGA, a multi-phase sampling method is exploited to harvest the clock jitter with a maximum entropy and fast sampling speed. This parametrized design is implemented in a Xilinx Artix-7 FPGA, where the carry chains in the FPGA are explored to realize the precise phase shifting. The generator circuit is simple and resource-saving, so that multiple generation channels can run in parallel to scale the output throughput for specific applications. The prototype integrates 64 circuit units in the FPGA to provide a total output throughput of 7.68 Gbps, which meets the requirement of current high-speed quantum key distribution systems. The randomness evaluation, as well as its robustness to ambient temperature, confirms that the new method in a purely digital fashion can provide high-speed high-quality random bit sequences for a variety of embedded applications.
DEFF Research Database (Denmark)
Jensen, J.L.
1993-01-01
Previous results on Edgeworth expansions for sums over a random field are extended to the case where the strong mixing coefficient depends not only on the distance between two sets of random variables, but also on the size of the two sets. The results are applied to the Poisson and the Strauss...
Lenzi, Tathiane Larissa; Pires, Carine Weber; Soares, Fabio Zovico Maxnuck; Raggio, Daniela Prócida; Ardenghi, Thiago Machado; de Oliveira Rocha, Rachel
2017-09-15
To evaluate the 18-month clinical performance of a universal adhesive, applied under different adhesion strategies, after selective carious tissue removal in primary molars. Forty-four subjects (five to 10 years old) contributed with 90 primary molars presenting moderately deep dentin carious lesions on occlusal or occluso-proximal surfaces, which were randomly assigned following either self-etch or etch-and-rinse protocol of Scotchbond Universal Adhesive (3M ESPE). Resin composite was incrementally inserted for all restorations. Restorations were evaluated at one, six, 12, and 18 months using the modified United States Public Health Service criteria. Survival estimates for restorations' longevity were evaluated using the Kaplan-Meier method. Multivariate Cox regression analysis with shared frailty to assess the factors associated with failures (Padhesion strategy did not influence the restorations' longevity (P=0.06; 72.2 percent and 89.7 percent with etch-and-rinse and self-etch mode, respectively). Self-etch and etch-and-rinse strategies did not influence the clinical behavior of universal adhesive used in primary molars after selective carious tissue removal; although there was a tendency for better outcome of the self-etch strategy.
Ma, Xin; Guo, Jing; Sun, Xiao
2016-01-01
DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.
Matsumoto, Mari; Ohba, Ryuji; Yasuda, Shin-ichi; Uchida, Ken; Tanamoto, Tetsufumi; Fujita, Shinobu
2008-08-01
The demand for random numbers for security applications is increasing. A conventional random number generator using thermal noise can generate unpredictable high-quality random numbers, but the circuit is extremely large because of large amplifier circuit for a small thermal signal. On the other hand, a pseudo-random number generator is small but the quality of randomness is bad. For a small circuit and a high quality of randomness, we purpose a non-stoichiometric SixN metal-oxide-semiconductor field-effect transistor (MOSFET) noise source device. This device generates a very large noise signal without an amplifier circuit. As a result, it is shown that, utilizing a SiN MOSFET, we can attain a compact random number generator with a high generation rate near 1 Mbit/s, which is suitable for almost all security applications.
Mota, Bernardo; Pereira, Jose; Campagnolo, Manuel; Killick, Rebeca
2013-04-01
Area burned in tropical savannas of Brazil was mapped using MODIS-AQUA daily 250m resolution imagery by adapting one of the European Space Agency fire_CCI project burned area algorithms, based on change point detection and Markov random fields. The study area covers 1,44 Mkm2 and was performed with data from 2005. The daily 1000 m image quality layer was used for cloud and cloud shadow screening. The algorithm addresses each pixel as a time series and detects changes in the statistical properties of NIR reflectance values, to identify potential burning dates. The first step of the algorithm is robust filtering, to exclude outlier observations, followed by application of the Pruned Exact Linear Time (PELT) change point detection technique. Near-infrared (NIR) spectral reflectance changes between time segments, and post change NIR reflectance values are combined into a fire likelihood score. Change points corresponding to an increase in reflectance are dismissed as potential burn events, as are those occurring outside of a pre-defined fire season. In the last step of the algorithm, monthly burned area probability maps and detection date maps are converted to dichotomous (burned-unburned maps) using Markov random fields, which take into account both spatial and temporal relations in the potential burned area maps. A preliminary assessment of our results is performed by comparison with data from the MODIS 1km active fires and the 500m burned area products, taking into account differences in spatial resolution between the two sensors.
Ni Luh Arpiwi; I Made Sutha Negara; I Nengah Simpen
2017-01-01
Millettia pinnata (L.) Panigrahi is a potential legume tree that produces seed oil for biodiesel feedstock. The initial step for raising a large-scale plantation of the species is selection of high oil yielding trees from the natural habitat. This is followed by vegetative propagation of the selected trees and then testing the growth of the clone in the field. The aim of the present study was to select high-oil yielding trees of M. pinnata, to propagate the selected trees by budding and to e...
Yüksel, Yusuf
2018-05-01
We propose an atomistic model and present Monte Carlo simulation results regarding the influence of FM/AF interface structure on the hysteresis mechanism and exchange bias behavior for a spin valve type FM/FM/AF magnetic junction. We simulate perfectly flat and roughened interface structures both with uncompensated interfacial AF moments. In order to simulate rough interface effect, we introduce the concept of random exchange anisotropy field induced at the interface, and acting on the interface AF spins. Our results yield that different types of the random field distributions of anisotropy field may lead to different behavior of exchange bias.
International Nuclear Information System (INIS)
Zimbardo, Gaetano
2005-01-01
Plasma transport in the presence of turbulence depends on a variety of parameters such as the fluctuation level, δB/B 0 , the ratio between the particle Larmor radius and the turbulence correlation length, and the turbulence anisotropy. In this paper, we present the results of numerical simulations of plasma and magnetic field line transport in the case of anisotropic magnetic turbulence, for parameter values close to those of the solar wind. We assume a uniform background magnetic field B 0 = B 0 e z and a Fourier representation for magnetic fluctuations, which includes wavectors oblique with respect to B 0 . The energy density spectrum is a power law, and in k space it is described by the correlation lengths l x , l y , l z , which quantify the anisotropy of turbulence. For magnetic field lines, transport perpendicular to the background field depends on the Kubo number R (δB/B 0 ) (l z /l x ). For small Kubo numbers, R 0 , or the ratio l z /l x , we find first a quasilinear regime and then a percolative regime, both corresponding to Gaussian diffusion. For particles, we find that transport parallel and perpendicular to the background magnetic field depends heavily on the turbulence anisotropy and on the particle Larmor radius. For turbulence levels typical of the solar wind, δB/B 0 ≅ 0.5-1, when the ratio between the particle Larmor radius and the turbulence correlation lengths is small, anomalous regimes are found in the case l z /l x ≤ 1, with a Levy random walk (superdiffusion) along the magnetic field and subdiffusion in the perpendicular directions. Conversely, for l z /l x > 1 normal Gaussian diffusion is found. A possible expression for generalized double diffusion is discussed
International Nuclear Information System (INIS)
Ueshima, N.; Yasuda, H.; Yoshiya, M.; Fukuda, T.; Kakeshita, T.
2014-01-01
Variant selection of L1 0 -type ferromagnetic alloys has been numerically investigated using the phase-field modeling, to clarify the phenomena at greater temporal and spatial resolution and to reveal the underlying mechanism. The duration for which the external magnetic field is effective is found to be very short, and variant selection is significantly affected by not only direct response to the external magnetic field but also their interplay between the field, intrinsic transformation strain, and various thermodynamic energy components involved in the course of microstructure evolution. The detailed mechanism of the interplay was quantitatively analyzed in terms of the driving force for the variant selection, by partitioning it into the various energy components. Careful examination of the variant selection at the very early stage revealed that the slight difference in size and configuration of variants during disorder-to-order transition realized by the interplay between transformation strain and external field is essentially needed before proceeding to the latter stage of the variant selection driven by interface energy
International Nuclear Information System (INIS)
Zimbardo, G.
2005-01-01
Plasma transport in the presence of turbulence depends on a variety of parameters like the fluctuation level ? B/B0, the ratio between the particle Larmor radius and the turbulence correlation lengths, and the turbulence anisotropy. In this presentation, we review the results of numerical simulations of plasma and magnetic field line transport in the case of anisotropic magnetic turbulence, for parameter values close to those of the solar wind. We assume a uniform background magnetic field B0 = B0ez and a Fourier representation for magnetic fluctuations, with wavectors forming any angle with respect to B0. The energy density spectrum is a power law, and in k space the constant amplitude surfaces are ellipsoids, described by the correlation lengths lx, ly, lz, which quantify the anisotropy of turbulence. For magnetic field lines, we find that transport perpendicular to the background field depends on the Kubo number R = ? B B0 lz lx . For small Kubo numbers, R ? 1, we find anomalous, non Gaussian transport regimes (both sub and superdiffusive) which can be described as a Levy random walk. Increasing the Kubo number, i.e., the fluctuation level ? B/B0 and/or the ratio lz/lx, we find first a quasilinear and then a percolative regime, both corresponding to Gaussian diffusion. For particles, we find that transport parallel and perpendicular to the background magnetic field heavily depends on the turbulence anisotropy and on the particle Larmor radius. For turbulence levels typical of the solar wind, ? B/B0 ? 0.5 ?1, when the ratio between the particle Larmor radius and the turbulence correlation lengths is small, anomalous regimes are found in the case lz/lx ? 1, with Levy random walk (superdiffusion) along the magnetic field and subdiffusion in the perpendicular directions. Conversely, for lz/lx > 1 normal, Gaussian diffusion is found. Increasing the ratio between the particle Larmor radius and the turbulence correlation lengths, the parallel superdiffusion is
International Nuclear Information System (INIS)
Stern, Daniel; Assef, Roberto J.; Eisenhardt, Peter; Benford, Dominic J.; Blain, Andrew; Cutri, Roc; Griffith, Roger L.; Jarrett, T. H.; Masci, Frank; Tsai, Chao-Wei; Yan, Lin; Dey, Arjun; Lake, Sean; Petty, Sara; Wright, E. L.; Stanford, S. A.; Harrison, Fiona; Madsen, Kristin
2012-01-01
The Wide-field Infrared Survey Explorer (WISE) is an extremely capable and efficient black hole finder. We present a simple mid-infrared color criterion, W1 – W2 ≥ 0.8 (i.e., [3.4]–[4.6] ≥0.8, Vega), which identifies 61.9 ± 5.4 active galactic nucleus (AGN) candidates per deg 2 to a depth of W2 ∼ 15.0. This implies a much larger census of luminous AGNs than found by typical wide-area surveys, attributable to the fact that mid-infrared selection identifies both unobscured (type 1) and obscured (type 2) AGNs. Optical and soft X-ray surveys alone are highly biased toward only unobscured AGNs, while this simple WISE selection likely identifies even heavily obscured, Compton-thick AGNs. Using deep, public data in the COSMOS field, we explore the properties of WISE-selected AGN candidates. At the mid-infrared depth considered, 160 μJy at 4.6 μm, this simple criterion identifies 78% of Spitzer mid-infrared AGN candidates according to the criteria of Stern et al. and the reliability is 95%. We explore the demographics, multiwavelength properties and redshift distribution of WISE-selected AGN candidates in the COSMOS field.
Exploring and reducing stress in young restaurant workers: results of a randomized field trial.
Petree, Robyn D; Broome, Kirk M; Bennett, Joel B
2012-01-01
Young adult restaurant workers face the dual stressors of work adjustment and managing personal responsibilities. We assessed a new psychosocial/health promotion training designed to reduce these stressors in the context of restaurant work. DESIGN . A cluster-randomized trial of a training program, with surveys administered approximately 2 weeks before training and both 6 and 12 months after training. A national restaurant chain. A total of 947 restaurant workers in 28 restaurants. Personal stress, exposure to problem coworkers, and personal and job characteristics. Team Resilience (TR) is an interactive program for stress management, teamwork, and work-life balance. TR focuses on "five Cs" of resilience: compassion, commitment, centering, community, and confidence. ANALYSIS . Mixed-model (multilevel) analysis of covariances. Compared with workers in control stores, workers in TR-trained stores showed significant reductions over time in exposure to problem coworkers (F[2, 80.60] = 4.48; p = .01) and in personal stress (F[2, 75.28] = 6.12; p = .003). The TR program may help young workers who face the challenges of emerging adulthood and work-life balance.
Explaining feast or famine in randomized field trials. Medical science and criminology compared.
Shepherd, Jonathan P
2003-06-01
A feast of randomized controlled trials (RCTs) in medical science and comparative famine in criminology can be explained in terms of cultural and structural factors. Of central importance is the context in which the evaluation of interventions is done and the difference in status of situational research in the two disciplines. Evaluation of medical interventions has traditionally been led by practitioner (clinical) academics. This is not the case in criminal justice, where theory has had higher status than intervention research. Medical science has advanced in, or closely associated with, university teaching hospitals, but links between criminology and criminal justice services are far more tenuous. The late development of situational crime prevention seems extraordinary from a medical perspective, as does the absence of university police schools in the United Kingdom and elsewhere. These structural and cultural factors explain concentration of expectation, resource, and RCT productivity in medical science. The Campbell Collaboration and the Academy of Experimental Criminology are forces which are reducing this polarization of feast and famine in RCTs. But unless scientific criminology is embedded in university schools which are responsible for the education and training of law, probation, and police practitioners, convergence in terms of RCTs and implementation of findings in practice seems unlikely.
Plazier, Mark; Ost, Jan; Stassijns, Gaëtane; De Ridder, Dirk; Vanneste, Sven
2015-01-01
Fibromyalgia is a condition characterized by widespread chronic pain. Due to the high prevalence and high costs, it has a substantial burden on society. Treatment results are diverse and only help a small subset of patients. C2 nerve field stimulation, aka occipital nerve stimulation, is helpful and a minimally invasive treatment for primary headache syndromes. Small C2 pilot studies seem to be beneficial in fibromyalgia. Forty patients were implanted with a subcutaneous electrode in the C2 dermatoma as part of a prospective, double-blind, randomized, controlled cross-over study followed by an open label follow up period of 6 months. The patients underwent 2 week periods of different doses of stimulation consisting of minimal (.1 mA), subthreshold, and suprathreshold (for paresthesias) in a randomized order. Twenty seven patients received a permanent implant and 25 completed the 6 month open label follow up period. During the 6 week trial phase of the study, patients had an overall decrease of 36% on the fibromyalgia impact questionnaire (FIQ), a decrease of 33% fibromyalgia pain and improvement of 42% on the impact on daily life activities and quality. These results imply an overall improvement in the disease burden, maintained at 6 months follow up, as well as an improvement in life quality of 50%. Seventy six percent of patients were satisfied or very satisfied with their treatment. There seems to be a dose-response curve, with increasing amplitudes leading to better clinical outcomes. Subcutaneous C2 nerve field stimulation seems to offer a safe and effective treatment option for selected medically intractable patients with fibromyalgia. Copyright © 2015 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Niederle, J; Bednar, M; Bicak, J
1987-01-01
The conference, the fourth in the series of conferences on this subject, was held at the Bechyne castle (Czechoslovakia) on June 23-27, 1986, and was attended by about 100 theoreticians from 15 countries. The conference was organized by the Institute of Physics of the Czechoslovak Academy of Sciences in Prague together with the Faculties of Mathematics and Physics of the Charles University, Prague, and of the Comenius University, Bratislava, the Faculty of Nuclear Science and Physical Engineering of the Czech Techical University, Prague, with the Institute of Physics of the Electro-Physical Research Centre of the Slovak Academy of Sciences, Bratislava, and the Institute of Nuclear Physics of the Czechoslovak Academy of Sciences in Rez. It was sponsored by the International Union for Pure and Applied Physics, the International Association of Mathematical Physics and the Physical Scientific Section of the Union of Czechoslovak Mathematicians and Physicists. The main subjects discussed at the conference were: supersymmetries, supergravity and superstring theories; quantum field theory and in particular gauge theories, theories on lattices, renormalization; selected topics in non-linear equations, scattering theory and quantization. Details are given in the attached program. The proceedings include invited talks and contributions presented respectively at the morning and afternoon sessions of the conference. The main part of the proceedings will be published in the Czechoslovak Journal of Physics v. 37(1987), nos. 3,4 and 9.
Infrared Selection of Obscured Active Galactic Nuclei in the COSMOS Field
Chang, Yu-Yen; Le Floc'h, Emeric; Juneau, Stéphanie; da Cunha, Elisabete; Salvato, Mara; Civano, Francesca; Marchesi, Stefano; Ilbert, Olivier; Toba, Yoshiki; Lim, Chen-Fatt; Tang, Ji-Jia; Wang, Wei-Hao; Ferraro, Nicholas; Urry, Megan C.; Griffiths, Richard E.; Kartaltepe, Jeyhan S.
2017-12-01
We present a study of the connection among black hole accretion, star formation, and galaxy morphology at z≤slant 2.5. We focus on active galactic nuclei (AGNs) selected by their mid-IR power-law emission. By fitting optical to far-IR photometry with state-of-the-art spectral energy distribution (SED) techniques, we derive stellar masses, star formation rates, dust properties, and AGN contributions in galaxies over the whole COSMOS field. We find that obscured AGNs lie within or slightly above the star-forming sequence. We confirm our previous finding about compact host galaxies of obscured AGNs at z˜ 1, and find that galaxies with 20%-50% AGN contributions tend to have smaller sizes, by ˜25%-50%, compared to galaxies without AGNs. Furthermore, we find that a high merger fraction of up to 0.5 is appropriate for the most luminous ({log}({L}{IR}/{L}⊙ )˜ 12.5) AGN hosts and non-AGN galaxies, but not for the whole obscured AGN sample. Moreover, the merger fraction depends on the total and star-forming IR luminosity, rather than on the decomposed AGN infrared luminosity. Our results suggest that major mergers are not the main driver of AGN activity, and therefore obscured AGNs might be triggered by internal mechanisms, such as secular processes, disk instabilities, and compaction in a particular evolutionary stage. We make the SED modeling results publicly available.
Gianulis, Elena C; Labib, Chantelle; Saulis, Gintautas; Novickij, Vitalij; Pakhomova, Olga N; Pakhomov, Andrei G
2017-05-01
Tumor ablation by nanosecond pulsed electric fields (nsPEF) is an emerging therapeutic modality. We compared nsPEF cytotoxicity for human cell lines of cancerous (IMR-32, Hep G2, HT-1080, and HPAF-II) and non-cancerous origin (BJ and MRC-5) under strictly controlled and identical conditions. Adherent cells were uniformly treated by 300-ns PEF (0-2000 pulses, 1.8 kV/cm, 50 Hz) on indium tin oxide-covered glass coverslips, using the same media and serum. Cell survival plotted against the number of pulses displayed three distinct regions (initial resistivity, logarithmic survival decline, and residual resistivity) for all tested cell types, but with differences in LD 50 spanning as much as nearly 80-fold. The non-cancerous cells were less sensitive than IMR-32 neuroblastoma cells but more vulnerable than the other cancers tested. The cytotoxic efficiency showed no apparent correlation with cell or nuclear size, cell morphology, metabolism level, or the extent of membrane disruption by nsPEF. Increasing pulse duration to 9 µs (0.75 kV/cm, 5 Hz) produced a different selectivity pattern, suggesting that manipulation of PEF parameters can, at least for certain cancers, overcome their resistance to nsPEF ablation. Identifying mechanisms and cell markers of differential nsPEF susceptibility will critically contribute to the proper choice and outcome of nsPEF ablation therapies.
International Nuclear Information System (INIS)
Niederle, J.; Bednar, M.; Bicak, J.
1987-01-01
The conference, the fourth in the series of conferences on this subject, was held at the Bechyne castle (Czechoslovakia) on June 23-27, 1986, and was attended by about 100 theoreticians from 15 countries. The conference was organized by the Institute of Physics of the Czechoslovak Academy of Sciences in Prague together with the Faculties of Mathematics and Physics of the Charles University, Prague, and of the Comenius University, Bratislava, the Faculty of Nuclear Science and Physical Engineering of the Czech Techical University, Prague, with the Institute of Physics of the Electro-Physical Research Centre of the Slovak Academy of Sciences, Bratislava, and the Institute of Nuclear Physics of the Czechoslovak Academy of Sciences in Rez. It was sponsored by the International Union for Pure and Applied Physics, the International Association of Mathematical Physics and the Physical Scientific Section of the Union of Czechoslovak Mathematicians and Physicists. The main subjects discussed at the conference were: supersymmetries, supergravity and superstring theories; quantum field theory and in particular gauge theories, theories on lattices, renormalization; selected topics in non-linear equations, scattering theory and quantization. Details are given in the attached program. The proceedings include invited talks and contributions presented respectively at the morning and afternoon sessions of the conference. The main part of the proceedings will be published in the Czechoslovak Journal of Physics v. 37(1987), nos. 3,4 and 9. (author)
Careau, Vincent; Bininda-Emonds, Olaf R P; Ordonez, Genesis; Garland, Theodore
2012-09-01
Voluntary wheel running and open-field behavior are probably the two most widely used measures of locomotion in laboratory rodents. We tested whether these two behaviors are correlated in mice using two approaches: the phylogenetic comparative method using inbred strains of mice and an ongoing artificial selection experiment on voluntary wheel running. After taking into account the measurement error and phylogenetic relationships among inbred strains, we obtained a significant positive correlation between distance run on wheels and distance moved in the open-field for both sexes. Thigmotaxis was negatively correlated with distance run on wheels in females but not in males. By contrast, mice from four replicate lines bred for high wheel running did not differ in either distance covered or thigmotaxis in the open field as compared with mice from four non-selected control lines. Overall, results obtained in the selection experiment were generally opposite to those observed among inbred strains. Possible reasons for this discrepancy are discussed.
High-field magnetization behavior in random anisotropy amorphous Co-Er alloys
Lassri, H.; Driouch, L.; Krishnan, R.
1994-05-01
Amorphous Co1-xErx ribbons with x=55 and 65 were prepared by the melt-spinning technique. Magnetization measurements were carried out in the temperature range 4-100 K under high magnetic fields up to 20 T. Even at 20 T the saturation is not fully attained. Assuming that Co has no moment in the alloy with x=65 the Er moment is found to be 7.0μB which indicates a speromagnetic spin structure. The Co moment in the alloy with x=55 is then found to be 0.1μB, which is negligibly small. By analyzing the approach to saturation using Chudnovsky's theory we have extracted some fundamental parameters.
A story about estimation of a random field of boulders from incomplete seismic measurements
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2005-01-01
deposits along the tunnel line. By use of this important distribution information and of the observed homogeneity of the seismic point source field together with the physical properties of diffraction it became possible to make the wanted prediction. During the excavation the found boulders were counted......This paper reports on the statistical interpretation of seismic diffraction measurements of boulder locations. The measurements are made in a corridor along the planned tunnel line for the later realized bored tunnel through the till deposits under the East Channel of the Great Belt in Denmark...... graphical registrations on seismograms do not make a proper interpretation possible without detailed knowledge about the joint distribution of the primary dimensions of the boulders. Therefore separate measurements were made of the dimensions of boulders deposited visibly on the cliff beaches of the Great...
Critical behavior of mean-field spin glasses on a dilute random graph
Energy Technology Data Exchange (ETDEWEB)
De Sanctis, Luca [Dipartimento di Matematica e di Psicologia, Universita di Bologna, P.zza di Porta San Donato 5, 40126 Bologna (Italy); Barra, Adriano; Folli, Viola [Dipartimento di Fisica, Universita La Sapienza, P.le Aldo Moro 5, 00185 Roma (Italy)], E-mail: desanctis@dm.unibo.it, E-mail: adriano.barra@roma1.infn.it, E-mail: viola.folli@roma1.infn.it
2008-05-30
We provide a rigorous strategy to find the critical exponents of the overlaps for dilute spin glasses, in the absence of an external field. Such a strategy is based on the expansion of a suitably perturbed average of the overlaps, which is used in the formulation of the free energy as the difference between a cavity part and the derivative of the free energy itself, considered as a function of the connectivity of the model. We assume the validity of certain reasonable approximations, equivalent to assuming a second-order transition, e.g. that higher powers of overlap monomials are of smaller magnitude near the critical point, of which we do not provide a rigorous proof.
Critical behavior of mean-field spin glasses on a dilute random graph
International Nuclear Information System (INIS)
De Sanctis, Luca; Barra, Adriano; Folli, Viola
2008-01-01
We provide a rigorous strategy to find the critical exponents of the overlaps for dilute spin glasses, in the absence of an external field. Such a strategy is based on the expansion of a suitably perturbed average of the overlaps, which is used in the formulation of the free energy as the difference between a cavity part and the derivative of the free energy itself, considered as a function of the connectivity of the model. We assume the validity of certain reasonable approximations, equivalent to assuming a second-order transition, e.g. that higher powers of overlap monomials are of smaller magnitude near the critical point, of which we do not provide a rigorous proof
International Nuclear Information System (INIS)
Tang Sai; Wang Zhijun; Guo Yaolin; Wang Jincheng; Yu Yanmei; Zhou Yaohe
2012-01-01
Using the phase-field crystal model, we investigate the orientation selection of the cubic dendrite growth at the atomic scale. Our simulation results reproduce how a face-centered cubic (fcc) octahedral nucleus and a body-centered cubic (bcc) truncated-rhombic dodecahedral nucleus choose the preferred growth direction and then evolve into the dendrite pattern. The interface energy anisotropy inherent in the fcc crystal structure leads to the fastest growth velocity in the 〈1 0 0〉 directions. New { 1 1 1} atomic layers prefer to nucleate at positions near the tips of the fcc octahedron, which leads to the directed growth of the fcc dendrite tips in the 〈1 0 0〉 directions. A similar orientation selection process is also found during the early stage of bcc dendrite growth. The orientation selection regime obtained by phase-field crystal simulation is helpful for understanding the orientation selection processes of real dendrite growth.
Shamey, Renzo; Zubair, Muhammad; Cheema, Hammad
2015-08-01
The aim of this study was twofold, first to determine the effect of field view size and second of illumination conditions on the selection of unique hue samples (UHs: R, Y, G and B) from two rotatable trays, each containing forty highly chromatic Natural Color System (NCS) samples, on one tray corresponding to 1.4° and on the other to 5.7° field of view size. UH selections were made by 25 color-normal observers who repeated assessments three times with a gap of at least 24h between trials. Observers separately assessed UHs under four illumination conditions simulating illuminants D65, A, F2 and F11. An apparent hue shift (statistically significant for UR) was noted for UH selections at 5.7° field of view compared to those at 1.4°. Observers' overall variability was found to be higher for UH stimuli selections at the larger field of view. Intra-observer variability was found to be approximately 18.7% of inter-observer variability in selection of samples for both sample sizes. The highest intra-observer variability was under simulated illuminant D65, followed by A, F11, and F2. Copyright © 2015 Elsevier Ltd. All rights reserved.
Random-field induced memory effects in inhomogeneously diluted antiferromagnets K2NixZn1−xF4
DEFF Research Database (Denmark)
Dikken, B. J.; Arts, A. F. M.; de Wijn, H. W.
1986-01-01
Using neutron diffraction a random-field generated memory is observed in K2NixZn1−xF4 with x = 0.96, 0.85, and 0.75. The intensities and profiles of magnetic Bragg reflections are found to follow unique trajectories determined by switching the external magnetic field on and off while cooling...