Statistical inference of selection and divergence from a time-dependent Poisson random field model.
Directory of Open Access Journals (Sweden)
Amei Amei
Full Text Available We apply a recently developed time-dependent Poisson random field model to aligned DNA sequences from two related biological species to estimate selection coefficients and divergence time. We use Markov chain Monte Carlo methods to estimate species divergence time and selection coefficients for each locus. The model assumes that the selective effects of non-synonymous mutations are normally distributed across genetic loci but constant within loci, and synonymous mutations are selectively neutral. In contrast with previous models, we do not assume that the individual species are at population equilibrium after divergence. Using a data set of 91 genes in two Drosophila species, D. melanogaster and D. simulans, we estimate the species divergence time t(div = 2.16 N(e (or 1.68 million years, assuming the haploid effective population size N(e = 6.45 x 10(5 years and a mean selection coefficient per generation μ(γ = 1.98/N(e. Although the average selection coefficient is positive, the magnitude of the selection is quite small. Results from numerical simulations are also presented as an accuracy check for the time-dependent model.
PReFerSim: fast simulation of demography and selection under the Poisson Random Field model.
Ortega-Del Vecchyo, Diego; Marsden, Clare D; Lohmueller, Kirk E
2016-11-15
The Poisson Random Field (PRF) model has become an important tool in population genetics to study weakly deleterious genetic variation under complicated demographic scenarios. Currently, there are no freely available software applications that allow simulation of genetic variation data under this model. Here we present PReFerSim, an ANSI C program that performs forward simulations under the PRF model. PReFerSim models changes in population size, arbitrary amounts of inbreeding, dominance and distributions of selective effects. Users can track summaries of genetic variation over time and output trajectories of selected alleles. PReFerSim is freely available at: https://github.com/LohmuellerLab/PReFerSim CONTACT: klohmueller@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Durner, Maximilian; Márton, Zoltán.; Hillenbrand, Ulrich; Ali, Haider; Kleinsteuber, Martin
2017-03-01
In this work, a new ensemble method for the task of category recognition in different environments is presented. The focus is on service robotic perception in an open environment, where the robot's task is to recognize previously unseen objects of predefined categories, based on training on a public dataset. We propose an ensemble learning approach to be able to flexibly combine complementary sources of information (different state-of-the-art descriptors computed on color and depth images), based on a Markov Random Field (MRF). By exploiting its specific characteristics, the MRF ensemble method can also be executed as a Dynamic Classifier Selection (DCS) system. In the experiments, the committee- and topology-dependent performance boost of our ensemble is shown. Despite reduced computational costs and using less information, our strategy performs on the same level as common ensemble approaches. Finally, the impact of large differences between datasets is analyzed.
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.
Blocked randomization with randomly selected block sizes.
Efird, Jimmy
2011-01-01
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.
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...
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.
Randomized selection on the GPU
Energy Technology Data Exchange (ETDEWEB)
Monroe, Laura Marie [Los Alamos National Laboratory; Wendelberger, Joanne R [Los Alamos National Laboratory; Michalak, Sarah E [Los Alamos National Laboratory
2011-01-13
We implement here a fast and memory-sparing probabilistic top N selection algorithm on the GPU. To our knowledge, this is the first direct selection in the literature for the GPU. The algorithm proceeds via a probabilistic-guess-and-chcck process searching for the Nth element. It always gives a correct result and always terminates. The use of randomization reduces the amount of data that needs heavy processing, and so reduces the average time required for the algorithm. Probabilistic Las Vegas algorithms of this kind are a form of stochastic optimization and can be well suited to more general parallel processors with limited amounts of fast memory.
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
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.
Random selection of Borel sets
Directory of Open Access Journals (Sweden)
Bernd Günther
2010-10-01
Full Text Available A theory of random Borel sets is presented, based on dyadic resolutions of compact metric spaces. The conditional expectation of the intersection of two independent random Borel sets is investigated. An example based on an embedding of Sierpinski’s universal curve into the space of Borel sets is given.
Field Induced Memory Effects in Random Nematics
Directory of Open Access Journals (Sweden)
Amid Ranjkesh
2014-01-01
Full Text Available We studied numerically external field induced memory effects in randomly perturbed nematic liquid crystals. Random anisotropy nematic-type lattice model was used. The impurities imposing orientational disorder were randomly spatially distributed with the concentration p below the percolation threshold. Simulations were carried for finite temperatures, where we varied p, interaction strength between LC molecules, and impurities and external field B. In the {B,T} plane we determined lines separating short range—quasi long range and quasi long range—long range order. Furthermore, crossover regime separating external field and random field dominated regime was estimated. We calculated remanent nematic ordering in samples at B=0 as a function of the previously experienced external field strength B.
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...
Concentration inequalities for random fields via coupling
Chazottes, J. R.; Collet, P.; Kuelske, C.; Redig, F.
We present a new and simple approach to concentration inequalities in the context of dependent random processes and random fields. Our method is based on coupling and does not use information inequalities. In case one has a uniform control on the coupling, one obtains exponential concentration
Species selection and random drift in macroevolution.
Chevin, Luis-Miguel
2016-03-01
Species selection resulting from trait-dependent speciation and extinction is increasingly recognized as an important mechanism of phenotypic macroevolution. However, the recent bloom in statistical methods quantifying this process faces a scarcity of dynamical theory for their interpretation, notably regarding the relative contributions of deterministic versus stochastic evolutionary forces. I use simple diffusion approximations of birth-death processes to investigate how the expected and random components of macroevolutionary change depend on phenotype-dependent speciation and extinction rates, as can be estimated empirically. I show that the species selection coefficient for a binary trait, and selection differential for a quantitative trait, depend not only on differences in net diversification rates (speciation minus extinction), but also on differences in species turnover rates (speciation plus extinction), especially in small clades. The randomness in speciation and extinction events also produces a species-level equivalent to random genetic drift, which is stronger for higher turnover rates. I then show how microevolutionary processes including mutation, organismic selection, and random genetic drift cause state transitions at the species level, allowing comparison of evolutionary forces across levels. A key parameter that would be needed to apply this theory is the distribution and rate of origination of new optimum phenotypes along a phylogeny. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.
Selection of 3013 Containers for Field Surveillance
Energy Technology Data Exchange (ETDEWEB)
Larry Peppers, Elizabeth Kelly, James McClard, Gary Friday, Theodore Venetz, and 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
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...
Random field estimation approach to robot dynamics
Rodriguez, Guillermo
1990-01-01
The difference equations of Kalman filtering and smoothing recursively factor and invert the covariance of the output of a linear state-space system driven by a white-noise process. Here it is shown that similar recursive techniques factor and invert the inertia matrix of a multibody robot system. The random field models are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. They are easier to describe than the models based on classical mechanics, which typically require extensive derivation and manipulation of equations of motion for complex mechanical systems. With the spatially random models, more primitive locally specified computations result in a global collective system behavior equivalent to that obtained with deterministic models. The primary goal of applying random field estimation is to provide a concise analytical foundation for solving robot control and motion planning problems.
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...
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...
Gaussian Markov random fields theory and applications
Rue, Havard
2005-01-01
Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studies and, online, a c-library for fast and exact simulation. With chapters contributed by leading researchers in the field, this volume is essential reading for statisticians working in spatial theory and its applications, as well as quantitative researchers in a wide range of science fields where spatial data analysis is important.
Improving randomness characterization through Bayesian model selection.
Díaz Hernández Rojas, Rafael; Solís, Aldo; Angulo Martínez, Alí M; U'Ren, Alfred B; Hirsch, Jorge G; Marsili, Matteo; Pérez Castillo, Isaac
2017-06-08
Random number generation plays an essential role in technology with important applications in areas ranging from cryptography to Monte Carlo methods, and other probabilistic algorithms. All such applications require high-quality sources of random numbers, yet effective methods for assessing whether a source produce truly random sequences are still missing. Current methods either do not rely on a formal description of randomness (NIST test suite) on the one hand, or are inapplicable in principle (the characterization derived from the Algorithmic Theory of Information), on the other, for they require testing all the possible computer programs that could produce the sequence to be analysed. Here we present a rigorous method that overcomes these problems based on Bayesian model selection. We derive analytic expressions for a model's likelihood which is then used to compute its posterior distribution. Our method proves to be more rigorous than NIST's suite and Borel-Normality criterion and its implementation is straightforward. We applied our method to an experimental device based on the process of spontaneous parametric downconversion to confirm it behaves as a genuine quantum random number generator. As our approach relies on Bayesian inference our scheme transcends individual sequence analysis, leading to a characterization of the source itself.
Random Circles and Fields on Circles.
1986-05-01
p is on the true circle C ; X is the corresponding radius of the random circle -5- Examples and comments Let W be a Wiener process on 3+, let a > 0 be...properties on C when M = W, it is expected that X be the analog of the Ornstein-Uhlenbeck process on the circle C . Indeed, the representation (2.12) shows this...evolution in time of a random field on the circle C . -35- The message of the following theorem is that the sections of X are all stationary and Markov
32 CFR 1624.1 - Random selection procedures for induction.
2010-07-01
... 32 National Defense 6 2010-07-01 2010-07-01 false Random selection procedures for induction. 1624... SYSTEM INDUCTIONS § 1624.1 Random selection procedures for induction. (a) The Director of Selective Service shall from time to time establish a random selection sequence for induction by a drawing to be...
Random wave fields and scintillated beams
CSIR Research Space (South Africa)
Roux, FS
2009-01-01
Full Text Available fields . Artificial vortex fields CSIR National Laser Centre – p.2/29 Scintillated optical beams When an optical beam propagates through a turbulent atmosphere, the index variations cause random phase modulations that lead to distortions of the optical... 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...
Gradient Boosting for Conditional Random Fields
2014-09-23
evidence boosting. In Proceedings of the 20th International Joint Conference on Artifical Intelligence , IJCAI’07, 2007. [13] O. Meshi, D. Sontag, T...Conference on Artificial Intelligence and Statistics (AISTATS’10), 2010. [3] J. Domke. Structured learning via logistic regression. In Advances in Neural...Artificial Intelligence (UAI’10), pages 302–311, 2010. [12] L. Liao, T. Choudhury, D. Fox, and H. Kautz. Training conditional random fields using virtual
Variational Infinite Hidden Conditional Random Fields.
Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin
2015-09-01
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 hidden states, which rids us not only of the necessity to specify a priori a fixed number of hidden states available but also of the problem of overfitting. Markov chain Monte Carlo (MCMC) sampling algorithms are often employed for inference in such models. However, convergence of such algorithms is rather difficult to verify, and as the complexity of the task at hand increases the computational cost of such algorithms often becomes prohibitive. These limitations can be overcome by variational techniques. In this paper, we present a generalized framework for infinite HCRF models, and a novel variational inference approach on a model based on coupled Dirichlet Process Mixtures, the HCRF-DPM. We show that the variational HCRF-DPM is able to converge to a correct number of represented hidden states, and performs as well as the best parametric HCRFs-chosen via cross-validation-for the difficult tasks of recognizing instances of agreement, disagreement, and pain in audiovisual sequences.
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
with material properties modeled in terms of the considered random fields.The paper addsthe gamma field, the Fisher field, the beta field, and their reciprocal fields to the catalogue. These fields are all defined on the basis of sums of squares of independent standard Gaussian random variables.All the existing......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 supplement the catalogue of positive fields beyond the class of those obtained by simple marginal transformation of a Gaussian field, this class containing the lognormal field.As a minimum for a random field to be included in the catalogue itis required that an algorithm for simulation of realizations can...
Conrad: gene prediction using conditional random fields.
DeCaprio, David; Vinson, Jade P; Pearson, Matthew D; Montgomery, Philip; Doherty, Matthew; Galagan, James E
2007-09-01
We present Conrad, the first comparative gene predictor based on semi-Markov conditional random fields (SMCRFs). Unlike the best standalone gene predictors, which are based on generalized hidden Markov models (GHMMs) and trained by maximum likelihood, Conrad is discriminatively trained to maximize annotation accuracy. In addition, unlike the best annotation pipelines, which rely on heuristic and ad hoc decision rules to combine standalone gene predictors with additional information such as ESTs and protein homology, Conrad encodes all sources of information as features and treats all features equally in the training and inference algorithms. Conrad outperforms the best standalone gene predictors in cross-validation and whole chromosome testing on two fungi with vastly different gene structures. The performance improvement arises from the SMCRF's discriminative training methods and their ability to easily incorporate diverse types of information by encoding them as feature functions. On Cryptococcus neoformans, configuring Conrad to reproduce the predictions of a two-species phylo-GHMM closely matches the performance of Twinscan. Enabling discriminative training increases performance, and adding new feature functions further increases performance, achieving a level of accuracy that is unprecedented for this organism. Similar results are obtained on Aspergillus nidulans comparing Conrad versus Fgenesh. SMCRFs are a promising framework for gene prediction because of their highly modular nature, simplifying the process of designing and testing potential indicators of gene structure. Conrad's implementation of SMCRFs advances the state of the art in gene prediction in fungi and provides a robust platform for both current application and future research.
Random Network Coding over Composite Fields
DEFF Research Database (Denmark)
Geil, Olav; Lucani Rötter, Daniel Enrique
2017-01-01
Random network coding is a method that achieves multicast capacity asymptotically for general networks [1, 7]. In this approach, vertices in the network randomly and linearly combine incoming information in a distributed manner before forwarding it through their outgoing edges. To ensure success...
In-Place Randomized Slope Selection
DEFF Research Database (Denmark)
Blunck, Henrik; Vahrenhold, Jan
2006-01-01
Slope selection is a well-known algorithmic tool used in the context of computing robust estimators for fitting a line to a collection P of n points in the plane. We demonstrate that it is possible to perform slope selection in expected O(nlogn) time using only constant extra space in addition to...
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 ...
Fuzzy conditional random fields for temporal data mining
Nurma Yulita, Intan; Setiawan Abdullah, Atje
2017-10-01
Temporal data mining is one of the interesting problems in computer science and its application has been performed in a wide variety of fields. The difference between the temporal data mining and data mining is the use of variable time. Therefore, the method used must be capable of processing variables of time. Compared with other methods, conditional random field has advantages in the processing variables of time. The method is a directed graph models that has been widely applied for segmenting and labelling sequence data that appears in various domains. In this study, we proposed use of Fuzzy Logic to be applied in Conditional Random Fields to overcome the problems of uncertainty. The experiment is compared Fuzzy Conditional Random Fields, Conditional Random Fields, and Hidden Markov Models. The result showed that accuracy of Fuzzy Conditional Random Fields is the best.
Ordering and phase transitions in random-field Ising systems
Maritan, Amos; Swift, Michael R.; Cieplak, Marek; Chan, Moses H. W.; Cole, Milton W.; Banavar, Jayanth R.
1991-01-01
An exact analysis of the Ising model with infinite-range interactions in a random field and a local mean-field theory in three dimensions is carried out leading to a phase diagram with several coexistence surfaces and lines of critical points. The results show that the phase diagram depends crucially on whether the distribution of random fields is symmetric or not. Thus, Ising-like phase transitions in a porous medium (the asymmetric case) are in a different universality class from the conventional random-field model (symmetric case).
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.
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...
Effects of random fields in an antiferromagnetic Ising bilayer film
Kaneyoshi, T.
2017-10-01
The magnetic properties (phase diagrams and magnetizations) of an antiferromagnetic Ising bilayer film with random fields are investigated by the use of the effective field theory with correlations. It is examined how an uncompensated magnetization can be realized in the system, due to the effects of random fields in the two layers. They show the tricritical, compensation point and reentrant phenomena, depending on these parameters.
Sequential selection of random vectors under a sum constraint
Stanke, Mario
2004-01-01
We observe a sequence X1,X2,...,Xn of independent and identically distributed coordinatewise nonnegative d-dimensional random vectors. When a vector is observed it can either be selected or rejected but once made this decision is final. In each coordinate the sum of the selected vectors must not exceed a given constant. The problem is to find a selection policy that maximizes the expected number of selected vectors. For a general absolutely continuous distribution of t...
Randomly evolving idiotypic networks: modular mean field theory.
Schmidtchen, Holger; Behn, Ulrich
2012-07-01
We develop a modular mean field theory for a minimalistic model of the idiotypic network. The model comprises the random influx of new idiotypes and a deterministic selection. It describes the evolution of the idiotypic network towards complex modular architectures, the building principles of which are known. The nodes of the network can be classified into groups of nodes, the modules, which share statistical properties. Each node experiences only the mean influence of the groups to which it is linked. Given the size of the groups and linking between them the statistical properties such as mean occupation, mean lifetime, and mean number of occupied neighbors are calculated for a variety of patterns and compared with simulations. For a pattern which consists of pairs of occupied nodes correlations are taken into account.
Classification of hyperspectral images based on conditional random fields
Hu, Yang; Saber, Eli; Monteiro, Sildomar T.; Cahill, Nathan D.; Messinger, David W.
2015-02-01
A significant increase in the availability of high resolution hyperspectral images has led to the need for developing pertinent techniques in image analysis, such as classification. Hyperspectral images that are correlated spatially and spectrally provide ample information across the bands to benefit this purpose. Conditional Random Fields (CRFs) are discriminative models that carry several advantages over conventional techniques: no requirement of the independence assumption for observations, flexibility in defining local and pairwise potentials, and an independence between the modules of feature selection and parameter leaning. In this paper we present a framework for classifying remotely sensed imagery based on CRFs. We apply a Support Vector Machine (SVM) classifier to raw remotely sensed imagery data in order to generate more meaningful feature potentials to the CRFs model. This approach produces promising results when tested with publicly available AVIRIS Indian Pine imagery.
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.
Stochastic analysis for gaussian random processes and fields with applications
Mandrekar, Vidyadhar S
2015-01-01
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).The book begins with preliminary results on covariance and associated RKHS before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the Itô integral. They show how the Skorokhod integral is a dual operator of Skorokhod differenti
The space transformation in the simulation of multidimensional random fields
Christakos, G.
1987-01-01
Space transformations are proposed as a mathematically meaningful and practically comprehensive approach to simulate multidimensional random fields. Within this context the turning bands method of simulation is reconsidered and improved in both the space and frequency domains. ?? 1987.
Random-Field Model of a Cooper Pair Insulator
Proctor, Thomas; Chudnovsky, Eugene; Garanin, Dmitry
2013-03-01
The model of a disordered superconducting film with quantum phase fluctuations is mapped on a random-field XY spin model in 2+1 dimensions. Analytical studies within continuum field theory, supported by our recent numerical calculations on discrete lattices, show the onset of the low-temperature Cooper pair insulator phase. The constant external field in the random-field spin model maps on the Josephson coupling between the disordered film and a bulk superconductor. Such a coupling, if sufficiently strong, restores superconductivity in the film. This provides an experimental test for the quantum fluctuation model of a superinsulator.
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 giv......, 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....
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.
Chemically modified field effect transistors with nitrite or fluoride selectivity
Antonisse, M.M.G.; Ruel, Bianca H.M.; Engbersen, Johannes F.J.; Reinhoudt, David
1998-01-01
Polysiloxanes with different types of polar substituents are excellent membrane materials for nitrite and fluoride selective chemically modified field effect transistors (CHEMFETs). Nitrite selectivity has been introduced by incorporation of a cobalt porphyrin into the membrane; fluoride selectivity
Effective diffusion equation in a random velocity field
Vinals, Jorge; Sekerka, Robert F.
1992-01-01
The effects are studied of assumed random velocity fields on diffusion in a binary fluid. Random velocity fields can result, for example, from the high-frequency components of residual accelerations onboard spacecraft (often called g-jitter). An effective diffusion equation is derived for an average concentration which includes spatial and temporal correlations induced by the fluctuating velocity fields assumed to be Gaussianly distributed. The resulting equation becomes nonlocal, and if correlations between different components of the velocity field exist, it is also anisotropic. The simple limiting case of short correlation times is discussed and an effective diffusivity is obtained which reflects the enhanced mixing caused by the velocity fields. The results obtained in the limit of short correlation times are valid even if the probability distribution of the velocity field is not Gaussian.
Fast, Randomized Join-Order Selection - Why Use Transformations?
C.A. Galindo-Legaria; A.J. Pellenkoft (Jan); M.L. Kersten (Martin)
1994-01-01
textabstractWe study the effectiveness of probabilistic selection of join-query evaluation plans, without reliance on tree transformation rules. Instead, each candidate plan is chosen uniformly at random from the space of valid evaluation orders. This leads to a transformation-free strategy where a
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 ...
RANDOM FORESTS-BASED FEATURE SELECTION FOR LAND-USE CLASSIFICATION USING LIDAR DATA AND ORTHOIMAGERY
Directory of Open Access Journals (Sweden)
H. Guan
2012-07-01
Full Text Available The development of lidar system, especially incorporated with high-resolution camera components, has shown great potential for urban classification. However, how to automatically select the best features for land-use classification is challenging. Random Forests, a newly developed machine learning algorithm, is receiving considerable attention in the field of image classification and pattern recognition. Especially, it can provide the measure of variable importance. Thus, in this study the performance of the Random Forests-based feature selection for urban areas was explored. First, we extract features from lidar data, including height-based, intensity-based GLCM measures; other spectral features can be obtained from imagery, such as Red, Blue and Green three bands, and GLCM-based measures. Finally, Random Forests is used to automatically select the optimal and uncorrelated features for landuse classification. 0.5-meter resolution lidar data and aerial imagery are used to assess the feature selection performance of Random Forests in the study area located in Mannheim, Germany. The results clearly demonstrate that the use of Random Forests-based feature selection can improve the classification performance by the selected features.
High Performance Ambipolar Field-Effect Transistor of Random Network Carbon Nanotubes
Bisri, Satria Zulkarnaen; Gao, Jia; Derenskyi, Vladimir; Gomulya, Widianta; Iezhokin, Igor; Gordiichuk, Pavlo; Herrmann, Andreas; Loi, Maria Antonietta
2012-01-01
Ambipolar field-effect transistors of random network carbon nanotubes are fabricated from an enriched dispersion utilizing a conjugated polymer as the selective purifying medium. The devices exhibit high mobility values for both holes and electrons (3 cm(2)/V.s) with a high on/off ratio (10(6)). The
Efficient Incorporation of Markov Random Fields in Change Detection
DEFF Research Database (Denmark)
Aanæs, Henrik; Nielsen, Allan Aasbjerg; Carstensen, Jens Michael
2009-01-01
Many change detection algorithms work by calculating the probability of change on a pixel-wise basis. This is a disadvantage since one is usually looking for regions of change, and such information is not used in pixel-wise classification - per definition. This issue becomes apparent in the face...... 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...... of efficient optimization methods or numerical solvers. We here address the issue of efficient incorporation of local homogeneity constraints into change detection algorithms. We do this by exploiting recent advances in graph based algorithms for Markov Random Fields. This is combined with an IR-MAD change...
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.
Acharyya, Muktish
2013-05-01
The dynamical steady state behaviour of the random field Ising ferromagnet swept by a propagating magnetic field wave is studied at zero temperature by Monte Carlo simulation in two dimensions. The distribution of the random field is bimodal type. For a fixed set of values of the frequency, wavelength and amplitude of propagating magnetic field wave and the strength of the random field, four distinct dynamical steady states or nonequilibrium phases were identified. These four nonequilibrium phases are characterised by different values of structure factors. State or phase of first kind, where all spins are parallel (up). This phase is a frozen or pinned where the propagating field has no effect. The second one is the propagating type, where the sharp strips formed by parallel spins are found to move coherently. The third one is also propagating type, where the boundary of the strips of spins is not very sharp. The fourth kind shows no propagation of strips of magnetic spins, forming a homogeneous distribution of up and down spins. This is disordered phase. The existence of these four dynamical phases or modes depends on the value of the amplitude of propagating magnetic field wave and the strength of random (static) field. A phase diagram has also been drawn, in the plane formed by the amplitude of propagating field and the strength of random field. It is also checked that the existence of these dynamical phases is neither a finite size effect nor a transient phenomenon.
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.
Selecting a phoneme-to-grapheme mapping: Random or weighted selection?
Directory of Open Access Journals (Sweden)
Binna Lee
2015-05-01
Our findings demonstrate that random selection underestimates MOA’s PG correspondences whereas weighted selection predicts higher PG correspondences than he produces. To explain his intermediate spelling performance on PPEs, we will test additional approaches to weighing the relative probability of PG mappings, including using log frequencies, separating consonant and vowel status, and considering the number of grapheme options in each phoneme.
Selection for altruism through random drift in variable size populations.
Houchmandzadeh, Bahram; Vallade, Marcel
2012-05-10
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. 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. 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.
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.
Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures
Bousmalis, K.; Zafeiriou, S.; Morency, L.P.; Pantic, Maja; Ghahramani, Z.
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 HCRF is an HCRF with a countably infinite number of hidden states, which rids us not only of the
Development of a Layered Conditional Random Field Based ...
African Journals Online (AJOL)
PROF. OLIVER OSUAGWA
2014-12-01
Dec 1, 2014 ... Conditional Estimation in NLP Models,” Proc. ACL Conf. Empirical. Methods in Natural Language Processing (EMNLP '02), Association for. Computational Linguistics, 10, (9-16). [39] Sutton, C. and McCallum, A (2006). “An Introduction to Conditional Random Fields for. Relational Learning,” Introduction to ...
Modeling fiber type grouping by a binary Markov random field
Venema, H. W.
1992-01-01
A new approach to the quantification of fiber type grouping is presented, in which the distribution of histochemical type in a muscle cross section is regarded as a realization of a binary Markov random field (BMRF). Methods for the estimation of the parameters of this model are discussed. The first
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
Fuzzy Field Theory as a Random Matrix Model
Tekel, Juraj
This dissertation considers the theory of scalar fields on fuzzy spaces from the point of view of random matrices. First we define random matrix ensembles, which are natural description of such theory. These ensembles are new and the novel feature is a presence of kinetic term in the probability measure, which couples the random matrix to a set of external matrices and thus breaks the original symmetry. Considering the case of a free field ensemble, which is generalization of a Gaussian matrix ensemble, we develop a technique to compute expectation values of the observables of the theory based on explicit Wick contractions and we write down recursion rules for these. We show that the eigenvalue distribution of the random matrix follows the Wigner semicircle distribution with a rescaled radius. We also compute distributions of the matrix Laplacian of the random matrix given by the new term and demonstrate that the eigenvalues of these two matrices are correlated. We demonstrate the robustness of the method by computing expectation values and distributions for more complicated observables. We then consider the ensemble corresponding to an interacting field theory, with a quartic interaction. We use the same method to compute the distribution of the eigenvalues and show that the presence of the kinetic terms rescales the distribution given by the original theory, which is a polynomially deformed Wigner semicircle. We compute the eigenvalue distribution of the matrix Laplacian and the joint distribution up to second order in the correlation and we show that the correlation between the two changes from the free field case. Finally, as an application of these results, we compute the phase diagram of the fuzzy scalar field theory, we find multiscaling which stabilizes this diagram in the limit of large matrices and compare it with the results obtained numerically and by considering the kinetic part as a perturbation.
Random vectorial fields representing the local structure of turbulence
Energy Technology Data Exchange (ETDEWEB)
Chevillard, Laurent [Laboratoire de Physique de l' ENS Lyon, CNRS, Universite de Lyon, 46 allee d' Italie, 69007 Lyon (France); Robert, Raoul [Institut Fourier, CNRS, Universite Grenoble 1, 100 rue des Mathematiques, BP 74, 38402 Saint-Martin d' Heres cedex (France); Vargas, Vincent, E-mail: laurent.chevillard@ens-lyon.fr [Ceremade, CNRS, Universite Paris-Dauphine, F-75016 Paris (France)
2011-12-22
We propose a method to build up a random homogeneous, isotropic and incompressible turbulent velocity field that mimics turbulence in the inertial range. The underlying Gaussian field is given by a modified Biot-Savart law. The long range correlated nature of turbulence is then incorporated heuristically using a non linear transformation inspired by the recent fluid deformation imposed by the Euler equations. The resulting velocity field shows a non vanishing mean energy transfer towards the small scales and realistic alignment properties of vorticity with the eigenframe of the deformation rate.
Driving a Superconductor to Insulator Transition with Random Gauge Fields.
Nguyen, H Q; Hollen, S M; Shainline, J; Xu, J M; Valles, J M
2016-11-30
Typically the disorder that alters the interference of particle waves to produce Anderson localization is potential scattering from randomly placed impurities. Here we show that disorder in the form of random gauge fields that act directly on particle phases can also drive localization. We present evidence of a superfluid bose glass to insulator transition at a critical level of this gauge field disorder in a nano-patterned array of amorphous Bi islands. This transition shows signs of metallic transport near the critical point characterized by a resistance , indicative of a quantum phase transition. The critical disorder depends on interisland coupling in agreement with recent Quantum Monte Carlo simulations. We discuss how this disorder tuned SIT differs from the common frustration tuned SIT that also occurs in magnetic fields. Its discovery enables new high fidelity comparisons between theoretical and experimental studies of disorder effects on quantum critical systems.
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.
Ghayab, Hadi Ratham Al; Li, Yan; Abdulla, Shahab; Diykh, Mohammed; Wan, Xiangkui
2016-01-01
Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on. This paper presents a new method which extracts and selects features from multi-channel EEG signals. This research focuses on three main points. Firstly, simple random sampling (SRS) technique is used to extract features from the time domain of EEG signals. Secondly, the sequential fea...
Shape modelling using Markov random field restoration of point correspondences.
Paulsen, Rasmus R; Hilger, Klaus B
2003-07-01
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 shapes and improves the capability of reconstruction of the training data. Furthermore, the method leads to an overall reduction in the total variance of the point distribution model. Thus, it finds correspondence between semi-landmarks that are highly correlated in the shape tangent space. The method is demonstrated on a set of human ear canals extracted from 3D-laser scans.
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...... shapes and improves the capability of reconstruction of the training data. Furthermore, the method leads to an overall reduction in the total variance of the point distribution model. Thus, it finds correspondence between semilandmarks that are highly correlated in the shape tangent space. The method...
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.
Statistical Downscaling Based on Spartan Spatial Random Fields
Hristopulos, Dionissios
2010-05-01
Stochastic methods of space-time interpolation and conditional simulation have been used in statistical downscaling approaches to increase the resolution of measured fields. One of the popular interpolation methods in geostatistics is kriging, also known as optimal interpolation in data assimilation. Kriging is a stochastic, linear interpolator which incorporates time/space variability by means of the variogram function. However, estimation of the variogram from data involves various assumptions and simplifications. At the same time, the high numerical complexity of kriging makes it difficult to use for very large data sets. We present a different approach based on the so-called Spartan Spatial Random Fields (SSRFs). SSRFs were motivated from classical field theories of statistical physics [1]. The SSRFs provide a different approach of parametrizing spatial dependence based on 'effective interactions,' which can be formulated based on general statistical principles or even incorporate physical constraints. This framework leads to a broad family of covariance functions [2], and it provides new perspectives in covariance parameter estimation and interpolation [3]. A significant advantage offered by SSRFs is reduced numerical complexity, which can lead to much faster codes for spatial interpolation and conditional simulation. In addition, on grids composed of rectangular cells, the SSRF representation leads to an explicit expression for the precision matrix (the inverse covariance). Therefore SSRFs could provide useful models of error covariance for data assimilation methods. We use simulated and real data to demonstrate SSRF properties and downscaled fields. keywords: interpolation, conditional simulation, precision matrix References [1] Hristopulos, D.T., 2003. Spartan Gibbs random field models for geostatistical applications, SIAM Journal in Scientific Computation, 24, 2125-2162. [2] Hristopulos, D.T., Elogne, S. N. 2007. Analytic properties and covariance
Ghayab, Hadi Ratham Al; Li, Yan; Abdulla, Shahab; Diykh, Mohammed; Wan, Xiangkui
2016-06-01
Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on. This paper presents a new method which extracts and selects features from multi-channel EEG signals. This research focuses on three main points. Firstly, simple random sampling (SRS) technique is used to extract features from the time domain of EEG signals. Secondly, the sequential feature selection (SFS) algorithm is applied to select the key features and to reduce the dimensionality of the data. Finally, the selected features are forwarded to a least square support vector machine (LS_SVM) classifier to classify the EEG signals. The LS_SVM classifier classified the features which are extracted and selected from the SRS and the SFS. The experimental results show that the method achieves 99.90, 99.80 and 100 % for classification accuracy, sensitivity and specificity, respectively.
Wright, Marvin N; Dankowski, Theresa; Ziegler, Andreas
2017-04-15
The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption may not always be fulfilled. An alternative approach for survival prediction is random forests for survival outcomes. The standard split criterion for random survival forests is the log-rank test statistic, which favors splitting variables with many possible split points. Conditional inference forests avoid this split variable selection bias. However, linear rank statistics are utilized by default in conditional inference forests to select the optimal splitting variable, which cannot detect non-linear effects in the independent variables. An alternative is to use maximally selected rank statistics for the split point selection. As in conditional inference forests, splitting variables are compared on the p-value scale. However, instead of the conditional Monte-Carlo approach used in conditional inference forests, p-value approximations are employed. We describe several p-value approximations and the implementation of the proposed random forest approach. A simulation study demonstrates that unbiased split variable selection is possible. However, there is a trade-off between unbiased split variable selection and runtime. In benchmark studies of prediction performance on simulated and real datasets, the new method performs better than random survival forests if informative dichotomous variables are combined with uninformative variables with more categories and better than conditional inference forests if non-linear covariate effects are included. In a runtime comparison, the method proves to be computationally faster than both alternatives, if a simple p-value approximation is used. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Visibility graphs of random scalar fields and spatial data
Lacasa, Lucas; Iacovacci, Jacopo
2017-07-01
We extend the family of visibility algorithms to map scalar fields of arbitrary dimension into graphs, enabling the analysis of spatially extended data structures as networks. We introduce several possible extensions and provide analytical results on the topological properties of the graphs associated to different types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension. This result holds independently of the field's marginal distribution and it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatiotemporal chaos. The range of potential applications of this combinatorial framework includes image processing in engineering, the description of surface growth in material science, soft matter or medicine, and the characterization of potential energy surfaces in chemistry, disordered systems, and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed.
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.
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.
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 (Ppsychomotricity a safe and efficacy therapy for pediatric selective mutism.
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
Markov random fields for static foreground classification in surveillance systems
Fitzsimons, Jack K.; Lu, Thomas T.
2014-09-01
We present a novel technique for classifying static foreground in automated airport surveillance systems between abandoned and removed objects by representing the image as a Markov Random Field. The proposed algorithm computes and compares the net probability of the region of interest before and after the event occurs, hence finding which fits more naturally with their respective backgrounds. Having tested on a dataset from the PETS 2006, PETS 2007, AVSS20074, CVSG, VISOR, CANDELA and WCAM datasets, the algorithm has shown capable of matching the results of the state-of-the-art, is highly parallel and has a degree of robustness to noise and illumination changes.
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...
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...
Random field Ising model and community structure in complex networks
Son, S.-W.; Jeong, H.; Noh, J. D.
2006-04-01
We propose a method to determine the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field Bs = +∞, Bt = -∞, and Bi≠s,t=0 for a node pair s and t. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of s and t. Our method provides a criterion for the existence of the community structure, and is applicable equally well to unweighted and weighted networks. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network. (Ising, Potts, etc.)
Parsing citations in biomedical articles using conditional random fields.
Zhang, Qing; Cao, Yong-Gang; Yu, Hong
2011-04-01
Citations are used ubiquitously in biomedical full-text articles and play an important role for representing both the rhetorical structure and the semantic content of the articles. As a result, text mining systems will significantly benefit from a tool that automatically extracts the content of a citation. In this study, we applied the supervised machine-learning algorithms Conditional Random Fields (CRFs) to automatically parse a citation into its fields (e.g., Author, Title, Journal, and Year). With a subset of html format open-access PubMed Central articles, we report an overall 97.95% F1-score. The citation parser can be accessed at: http://www.cs.uwm.edu/∼qing/projects/cithit/index.html. Copyright © 2011 Elsevier Ltd. All rights reserved.
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.
Relations between Lagrangian models and synthetic random velocity fields.
Olla, Piero; Paradisi, Paolo
2004-10-01
The authors propose an alternative interpretation of Markovian transport models based on the well-mixed condition, in terms of the properties of a random velocity field with second order structure functions scaling linearly in the space-time increments. This interpretation allows direct association of the drift and noise terms entering the model, with the geometry of the turbulent fluctuations. In particular, the well-known nonuniqueness problem in the well-mixed approach is solved in terms of the antisymmetric part of the velocity correlations; its relation with the presence of nonzero mean helicity and other geometrical properties of the flow is elucidated. The well-mixed condition appears to be a special case of the relation between conditional velocity increments of the random field and the one-point Eulerian velocity distribution, allowing generalization of the approach to the transport of nontracer quantities. Application to solid particle transport leads to a model satisfying, in the homogeneous isotropic turbulence case, all the conditions on the behavior of the correlation times for the fluid velocity sampled by the particles. In particular, correlation times in the gravity and in the inertia dominated case, respectively, longer and shorter than in the passive tracer case; in the gravity dominated case, correlation times longer for velocity components along gravity, than for the perpendicular ones. The model produces, in channel flow geometry, particle deposition rates in agreement with experiments.
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.
Kumar, Manoj; Banerjee, Varsha; Puri, Sanjay
2017-11-08
In this paper, we study the random field Ising model (RFIM) in an external magnetic field h . A computationally efficient graph-cut method is used to study ground state (GS) morphologies in this system for three different disorder types: Gaussian, uniform and bimodal. We obtain the critical properties of this system and find that they are independent of the disorder type. We also study GS morphologies via pinned-cluster distributions, which are scale-free at criticality. The spin-spin correlation functions (and structure factors) are characterized by a roughness exponent [Formula: see text]. The corresponding scaling function is universal for all disorder types and independent of h.
Random Field Ising Models: Fractal Interfaces and their Implications
Bupathy, A.; Kumar, M.; Banerjee, V.; Puri, S.
2017-10-01
We use a computationally efficient graph-cut (GC) method to obtain exact ground-states of the d = 3 random field Ising model (RFIM) on simple cubic (SC), bodycentered cubic (BCC) and face-centered cubic (FCC) lattices with Gaussian, Uniform and Bimodal distributions for the disorder Δ. At small-r, the correlation function C(r; Δ) shows a cusp singularity characterised by a non-integer roughness exponent α signifying rough fractal interfaces with dimension d f = d – α. In the paramagnetic phase (Δ > Δ c ), α ≃ 0:5 for all lattice and disorder types. In the ferromagnetic phase (Δ Fractal interfaces have important implications on growth and relaxation.
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.
Field resistance of selected potato clones to Early blight
Novisel Veitía; Lourdes R. García; Idalmis Bermúdez-Caraballoso; Mayra Acosta- Suárez; Michel Leiva-Mora; Damaris Torres; Carlos Romero; Pedro Orellana
2014-01-01
Six potato clones, selected in vitro for their resistance to Alternaria solani Sor. culture filtrates, were evaluated for their field response to early blight infection. Field screening were performance under artificial inoculation and natural conditions. Early blight response was evaluated based on lesion size, disease severity, and area under disease progress curve (AUDPC). One clone displayed reduced lesion area (0.35 cm2) and AUDPC values compared to cv. `Desirée' (susceptible control) (0...
A Tutorial of the Poisson Random Field Model in Population Genetics
Directory of Open Access Journals (Sweden)
Praveen Sethupathy
2008-01-01
Full Text Available Population genetics is the study of allele frequency changes driven by various evolutionary forces such as mutation, natural selection, and random genetic drift. Although natural selection is widely recognized as a bona-fide phenomenon, the extent to which it drives evolution continues to remain unclear and controversial. Various qualitative techniques, or so-called “tests of neutrality”, have been introduced to detect signatures of natural selection. A decade and a half ago, Stanley Sawyer and Daniel Hartl provided a mathematical framework, referred to as the Poisson random field (PRF, with which to determine quantitatively the intensity of selection on a particular gene or genomic region. The recent availability of large-scale genetic polymorphism data has sparked widespread interest in genome-wide investigations of natural selection. To that end, the original PRF model is of particular interest for geneticists and evolutionary genomicists. In this article, we will provide a tutorial of the mathematical derivation of the original Sawyer and Hartl PRF model.
A dissipative random velocity field for fully developed fluid turbulence
Chevillard, Laurent; Pereira, Rodrigo; Garban, Christophe
2016-11-01
We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent flow. A key step in the construction of this model is the introduction of some aspects of the vorticity stretching mechanism that governs the dynamics of fluid particles along their trajectory. An additional further phenomenological step aimed at including the long range correlated nature of turbulence makes this model depending on a single free parameter that can be estimated from experimental measurements. We confirm the realism of the model regarding the geometry of the velocity gradient tensor, the power-law behaviour of the moments of velocity increments, including the intermittent corrections, and the existence of energy transfers across scales. We quantify the dependence of these basic properties of turbulent flows on the free parameter and derive analytically the spectrum of exponents of the structure functions in a simplified non dissipative case. A perturbative expansion shows that energy transfers indeed take place, justifying the dissipative nature of this random field.
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...... model mesh to the target shapes. When this is done by a nearest neighbour projection it can result in folds and inhomogeneities in the correspondence vector field. The novelty in this paper is the use and extension of a Markov random field regularisation of the correspondence field. The correspondence...... model that produces highly homogeneous polygonised shapes with improved reconstruction capabilities of the training data. Furthermore, the method leads to an overall reduction in the total variance of the resulting point distribution model. The method is demonstrated on a set of human ear canals...
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.
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.…
Event selection with a Random Forest in IceCube
Energy Technology Data Exchange (ETDEWEB)
Ruhe, Tim [TU, Dortmund (Germany); Collaboration: IceCube-Collaboration
2011-07-01
The Random Forest method is a multivariate algorithm that can be used for classification and regression respectively. The Random Forest implemented in the RapidMiner learning environment has been used for training and validation on data and Monte Carlo simulations of the IceCube neutrino telescope. Latest results are presented.
Elperin, T; Kleeorin, N; Rogachevskii, I; Sokoloff, D
2001-08-01
Mean-field theory for turbulent transport of a passive scalar (e.g., particles and gases) is discussed. Equations for the mean number density of particles advected by a random velocity field, with a finite correlation time, are derived. Mean-field equations for a passive scalar comprise spatial derivatives of high orders due to the nonlocal nature of passive scalar transport in a random velocity field with a finite correlation time. A turbulent velocity field with a random renewal time is considered. This model is more realistic than that with a constant renewal time used by Elperin et al. [Phys. Rev. E 61, 2617 (2000)], and employs two characteristic times: the correlation time of a random velocity field tau(c), and a mean renewal time tau. It is demonstrated that the turbulent diffusion coefficient is determined by the minimum of the times tau(c) and tau. The mean-field equation for a passive scalar was derived for different ratios of tau/tau(c). The important role of the statistics of the field of Lagrangian trajectories in turbulent transport of a passive scalar, in a random velocity field with a finite correlation time, is demonstrated. It is shown that in the case tau(c)
In search of random uncorrelated particle motion (RUM) in a simple random flow field
Reeks, Michael W; Soldati, Alfredo
2012-01-01
DNS studies of dispersed particle motion in isotropic homogeneous turbulence [1] have revealed the existence of a component of random uncorrelated motion (RUM)dependent on the particle inertia {\\tau}p(normalised particle response time or Stoke number). This paper reports the presence of RUM in a simple linear random smoothly varying flow field of counter rotating vortices where the two-particle velocity correlation was measured as a function of spatial separation. Values of the correlation less than one for zero separation indicated the presence of RUM. In terms of Stokes number, the motion of the particles in one direction corresponds to either a heavily damped ({\\tau}p 0.25)harmonic oscillator. In the lightly damped case the particles overshoot the stagnation lines of the flow and are projected from one vortex to another (the so-called sling-shot effect). It is shown that RUM occurs only when {\\tau}p > 0.25, increasing monotonically with increasing Stokes number. Calculations of the particle pair separatio...
Kouritzin, Michael A; Newton, Fraser; Wu, Biao
2013-04-01
Herein, we propose generating CAPTCHAs through random field simulation and give a novel, effective and efficient algorithm to do so. Indeed, we demonstrate that sufficient information about word tests for easy human recognition is contained in the site marginal probabilities and the site-to-nearby-site covariances and that these quantities can be embedded directly into certain conditional probabilities, designed for effective simulation. The CAPTCHAs are then partial random realizations of the random CAPTCHA word. We start with an initial random field (e.g., randomly scattered letter pieces) and use Gibbs resampling to re-simulate portions of the field repeatedly using these conditional probabilities until the word becomes human-readable. The residual randomness from the initial random field together with the random implementation of the CAPTCHA word provide significant resistance to attack. This results in a CAPTCHA, which is unrecognizable to modern optical character recognition but is recognized about 95% of the time in a human readability study.
Conditional random field modelling of interactions between findings in mammography
Kooi, Thijs; Mordang, Jan-Jurre; Karssemeijer, Nico
2017-03-01
Recent breakthroughs in training deep neural network architectures, in particular deep Convolutional Neural Networks (CNNs), made a big impact on vision research and are increasingly responsible for advances in Computer Aided Diagnosis (CAD). Since many natural scenes and medical images vary in size and are too large to feed to the networks as a whole, two stage systems are typically employed, where in the first stage, small regions of interest in the image are located and presented to the network as training and test data. These systems allow us to harness accurate region based annotations, making the problem easier to learn. However, information is processed purely locally and context is not taken into account. In this paper, we present preliminary work on the employment of a Conditional Random Field (CRF) that is trained on top the CNN to model contextual interactions such as the presence of other suspicious regions, for mammography CAD. The model can easily be extended to incorporate other sources of information, such as symmetry, temporal change and various patient covariates and is general in the sense that it can have application in other CAD problems.
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.
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.
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.
Segmentation and labeling of documents using conditional random fields
Shetty, Shravya; Srinivasan, Harish; Beal, Matthew; Srihari, Sargur
2007-01-01
The paper describes the use of Conditional Random Fields(CRF) utilizing contextual information in automatically labeling extracted segments of scanned documents as Machine-print, Handwriting and Noise. The result of such a labeling can serve as an indexing step for a context-based image retrieval system or a bio-metric signature verification system. A simple region growing algorithm is first used to segment the document into a number of patches. A label for each such segmented patch is inferred using a CRF model. The model is flexible enough to include signatures as a type of handwriting and isolate it from machine-print and noise. The robustness of the model is due to the inherent nature of modeling neighboring spatial dependencies in the labels as well as the observed data using CRF. Maximum pseudo-likelihood estimates for the parameters of the CRF model are learnt using conjugate gradient descent. Inference of labels is done by computing the probability of the labels under the model with Gibbs sampling. Experimental results show that this approach provides for 95.75% of the data being assigned correct labels. The CRF based model is shown to be superior to Neural Networks and Naive Bayes.
Challenges in estimating insecticide selection pressures from mosquito field data.
Directory of Open Access Journals (Sweden)
Susana Barbosa
2011-11-01
Full Text Available Insecticide resistance has the potential to compromise the enormous effort put into the control of dengue and malaria vector populations. It is therefore important to quantify the amount of selection acting on resistance alleles, their contributions to fitness in heterozygotes (dominance and their initial frequencies, as a means to predict the rate of spread of resistance in natural populations. We investigate practical problems of obtaining such estimates, with particular emphasis on Mexican populations of the dengue vector Aedes aegypti. Selection and dominance coefficients can be estimated by fitting genetic models to field data using maximum likelihood (ML methodology. This methodology, although widely used, makes many assumptions so we investigated how well such models perform when data are sparse or when spatial and temporal heterogeneity occur. As expected, ML methodologies reliably estimated selection and dominance coefficients under idealised conditions but it was difficult to recover the true values when datasets were sparse during the time that resistance alleles increased in frequency, or when spatial and temporal heterogeneity occurred. We analysed published data on pyrethroid resistance in Mexico that consists of the frequency of a Ile1,016 mutation. The estimates for selection coefficient and initial allele frequency on the field dataset were in the expected range, dominance coefficient points to incomplete dominance as observed in the laboratory, although these estimates are accompanied by strong caveats about possible impact of spatial and temporal heterogeneity in selection.
Heterogeneous Web Data Extraction Algorithm Based On Modified Hidden Conditional Random Fields
Cui Cheng
2014-01-01
As it is of great importance to extract useful information from heterogeneous Web data, in this paper, we propose a novel heterogeneous Web data extraction algorithm using a modified hidden conditional random fields model. Considering the traditional linear chain based conditional random fields can not effectively solve the problem of complex and heterogeneous Web data extraction, we modify the standard hidden conditional random fields in three aspects, which are 1) Using the hidden Markov mo...
Error Bounds Due to Random Noise in Cylindrical Near-Field Measurements
Romeu Robert, Jordi; Jofre Roca, Lluís
1991-01-01
The far field errors due to near field random noise are statistically bounded when performing cylindrical near to far field transform. In this communication, the far field noise variance it is expressed as a function of the measurement parameters and the near field noise variance. Peer Reviewed
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.
Study on MAX-MIN Ant System with Random Selection in Quadratic Assignment Problem
Iimura, Ichiro; Yoshida, Kenji; Ishibashi, Ken; Nakayama, Shigeru
Ant Colony Optimization (ACO), which is a type of swarm intelligence inspired by ants' foraging behavior, has been studied extensively and its effectiveness has been shown by many researchers. The previous studies have reported that MAX-MIN Ant System (MMAS) is one of effective ACO algorithms. The MMAS maintains the balance of intensification and diversification concerning pheromone by limiting the quantity of pheromone to the range of minimum and maximum values. In this paper, we propose MAX-MIN Ant System with Random Selection (MMASRS) for improving the search performance even further. The MMASRS is a new ACO algorithm that is MMAS into which random selection was newly introduced. The random selection is one of the edgechoosing methods by agents (ants). In our experimental evaluation using ten quadratic assignment problems, we have proved that the proposed MMASRS with the random selection is superior to the conventional MMAS without the random selection in the viewpoint of the search performance.
Larrasa, J; Garcia, A; Ambrose, N C; Alonso, J M; Parra, A; de Mendoza, M Hermoso; Salazar, J; Rey, J; de Mendoza, J Hermoso
2002-04-01
Dermatophilus congolensis is the pathogenic actinomycete that causes dermatophilosis in cattle, lumpy wool in sheep and rain scald in horses. Phenotypic variation between isolates has previously been described, but its genetic basis, extent and importance have not been investigated. Standard DNA extraction methods are not always successful for D. congolensis due to its complex life cycle, one stage of which is encapsulated. Here we describe the development of rapid and reliable DNA extraction and random amplified polymorphic DNA (RAPD) methods that can be used for genotyping D. congolensis field isolates. Our results suggest that genotypic variation between isolates correlates with host species. Several DNA extraction methods and RAPD protocols were compared. An extraction method based on incubation of the bacterium in lysozyme, sodium dodecyl sulphate (SDS) and proteinase K treatments and phenolic extraction yielded high-quality DNA, which was used to optimize RAPD-polymerase chain reaction (PCR) protocols for two random primers. An alternative rapid, non-phenolic extraction method based on proteinase K treatment and thermal shock was selected for routine RAPD typing of isolates. DNA extracted from reference strains from cattle, sheep and horse using either method gave reproducible banding patterns with different DNA batches and different thermal cyclers. The rapid DNA extraction method and RAPD-PCR were applied to 38 D. congolensis field isolates. The band patterns of the field and type isolates correlated with host species but not with geographical location.
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....
Gesture Recognition using Latent-Dynamic based Conditional Random Fields and Scalar Features
Yulita, I. N.; Fanany, M. I.; Arymurthy, A. M.
2017-02-01
The need for segmentation and labeling of sequence data appears in several fields. The use of the conditional models such as Conditional Random Fields is widely used to solve this problem. In the pattern recognition, Conditional Random Fields specify the possibilities of a sequence label. This method constructs its full label sequence to be a probabilistic graphical model based on its observation. However, Conditional Random Fields can not capture the internal structure so that Latent-based Dynamic Conditional Random Fields is developed without leaving external dynamics of inter-label. This study proposes the use of Latent-Dynamic Conditional Random Fields for Gesture Recognition and comparison between both methods. Besides, this study also proposes the use of a scalar features to gesture recognition. The results show that performance of Latent-dynamic based Conditional Random Fields is not better than the Conditional Random Fields, and scalar features are effective for both methods are in gesture recognition. Therefore, it recommends implementing Conditional Random Fields and scalar features in gesture recognition for better performance
Reduction of the Random Variables of the Turbulent Wind Field
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.
2012-01-01
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.......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...... 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...
Optimal Exact Simulation of Max-Stable and Related Random Fields
Liu, Zhipeng; Blanchet, Jose H.; Dieker, A. B.; Mikosch, Thomas
2016-01-01
We consider the random field M(t)=\\sup_{n\\geq 1}\\big\\{-\\log A_{n}+X_{n}(t)\\big\\}\\,,\\qquad t\\in T\\, for a set $T\\subset \\mathbb{R}^{m}$, where $(X_{n})$ is an iid sequence of centered Gaussian random fields on $T$ and $0
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.
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
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
Risk Attitudes, Sample Selection and Attrition in a Longitudinal Field Experiment
DEFF Research Database (Denmark)
Harrison, Glenn W.; Lau, Morten; Yoo, Hong Il
incentives can affect sample response rates and help one identify the effects of selection. Correcting for endogenous sample selection and panel attrition changes inferences about risk preferences in an economically and statistically significant manner. We draw mixed conclusions on temporal stability of risk......Longitudinal experiments allow one to evaluate the temporal stability of latent preferences, but raise concerns about sample selection and attrition that may confound inferences about temporal stability. We evaluate the hypothesis of temporal stability in risk preferences using a remarkable data...... set that combines socio-demographic information from the Danish Civil Registry with information on risk attitudes from a longitudinal field experiment. Our experimental design builds in explicit randomization on the incentives for participation. The results show that the use of different participation...
Seeking mathematics success for college students: a randomized field trial of an adapted approach
Gula, Taras; Hoessler, Carolyn; Maciejewski, Wes
2015-11-01
Many students enter the Canadian college system with insufficient mathematical ability and leave the system with little improvement. Those students who enter with poor mathematics ability typically take a developmental mathematics course as their first and possibly only mathematics course. The educational experiences that comprise a developmental mathematics course vary widely and are, too often, ineffective at improving students' ability. This trend is concerning, since low mathematics ability is known to be related to lower rates of success in subsequent courses. To date, little attention has been paid to the selection of an instructional approach to consistently apply across developmental mathematics courses. Prior research suggests that an appropriate instructional method would involve explicit instruction and practising mathematical procedures linked to a mathematical concept. This study reports on a randomized field trial of a developmental mathematics approach at a college in Ontario, Canada. The new approach is an adaptation of the JUMP Math program, an explicit instruction method designed for primary and secondary school curriculae, to the college learning environment. In this study, a subset of courses was assigned to JUMP Math and the remainder was taught in the same style as in the previous years. We found consistent, modest improvement in the JUMP Math sections compared to the non-JUMP sections, after accounting for potential covariates. The findings from this randomized field trial, along with prior research on effective education for developmental mathematics students, suggest that JUMP Math is a promising way to improve college student outcomes.
In vivo selection of randomly mutated retroviral genomes
Berkhout, B.; Klaver, B.
1993-01-01
Darwinian evolution, that is the outgrowth of the fittest variants in a population, usually applies to living organisms over long periods of time. Recently, in vitro selection/amplification techniques have been developed that allow for the rapid evolution of functionally active nucleic acids from a
Philipp-Dormston, Wolfgang G
2015-01-01
The incidence of non-melanoma skin cancer (NMSC), including actinic keratosis (AK), squamous cell carcinoma (SCC), Bowen's Disease (BD) and basal cell carcinoma (BCC), is increasing. UVA and UVB radiation lead to genetic alterations in keratinocytes, which eventually result in skin cancer. In the concept of field cancerization of the skin, genetically altered keratinocytes accumulate over an area exposed to UV radiation. Field treatment not only clears clinically visible NMSC lesions but also potentially targets subclinical 'sleeping' cell patches and fields. Topical treatments are available for the field-directed management of NMSC. They are either self-administered by the patient (ingenol mebutate, diclofenac, imiquimod or 5-FU) or administered by the dermatologist (photodynamic therapy (PDT)). This article discusses the treatment options with respect to their efficacy, tolerability and selectivity. Selective treatment options for atypic keratinocytes include imiquimod, ingenol mebutate, diclofenac and PDT. PDT yields 100% treatment compliance because it is always administered by the treating dermatologist. The efficacy rates achieved with PDT significantly exceed those of the patient-administered topicals. The first clinical trials assessing the effects of PDT on field cancerization clinically, histologically and immunochemically have been conducted and have yielded promising results. Preventive effects and a delay in the re-occurrence of NMSC have been observed in animal experiments of ingenol mebutate and PDT, whereas for the latter, clinical data are already available. © 2015 S. Karger AG, Basel.
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.
A multiscale Markov random field model in wavelet domain for image segmentation
Dai, Peng; Cheng, Yu; Wang, Shengchun; Du, Xinyu; Wu, Dan
2017-07-01
The human vision system has abilities for feature detection, learning and selective attention with some properties of hierarchy and bidirectional connection in the form of neural population. In this paper, a multiscale Markov random field model in the wavelet domain is proposed by mimicking some image processing functions of vision system. For an input scene, our model provides its sparse representations using wavelet transforms and extracts its topological organization using MRF. In addition, the hierarchy property of vision system is simulated using a pyramid framework in our model. There are two information flows in our model, i.e., a bottom-up procedure to extract input features and a top-down procedure to provide feedback controls. The two procedures are controlled simply by two pyramidal parameters, and some Gestalt laws are also integrated implicitly. Equipped with such biological inspired properties, our model can be used to accomplish different image segmentation tasks, such as edge detection and region segmentation.
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...
The frequency of drugs in randomly selected drivers in Denmark
DEFF Research Database (Denmark)
Simonsen, Kirsten Wiese; Steentoft, Anni; Hels, Tove
Introduction Driving under the influence of alcohol and drugs is a global problem. In Denmark as well as in other countries there is an increasing focus on impaired driving. Little is known about the occurrence of psychoactive drugs in the general traffic. Therefore the European commission...... initiated the DRUID project. 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. Methods 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. Results Fourteen (0.5%) drivers were positive for ethanol (alone or in combination with drugs) at concentrations above 0.53 g/l, which...
Sample Selection in Randomized Experiments: A New Method Using Propensity Score Stratified Sampling
Tipton, Elizabeth; Hedges, Larry; Vaden-Kiernan, Michael; Borman, Geoffrey; Sullivan, Kate; Caverly, Sarah
2014-01-01
Randomized experiments are often seen as the "gold standard" for causal research. Despite the fact that experiments use random assignment to treatment conditions, units are seldom selected into the experiment using probability sampling. Very little research on experimental design has focused on how to make generalizations to well-defined…
Pseudo cluster randomization dealt with selection bias and contamination in clinical trials
Teerenstra, S.; Melis, R.J.F.; Peer, P.G.M.; Borm, G.F.
2006-01-01
BACKGROUND AND OBJECTIVES: When contamination is present, randomization on a patient level leads to dilution of the treatment effect. The usual solution is to randomize on a cluster level, but at the cost of efficiency and more importantly, this may introduce selection bias. Furthermore, it may slow
Transport properties of a two-dimensional electron gas due to a spatially random magnetic field
Rushforth, A. W.; Gallagher, B. L.; Main, P. C.; Neumann, A. C.; Marrows, C. H.; Zoller, I.; Howson, M. A.; Hickey, B. J.; Henini, M.
2000-02-01
We have studied the magnetoresistance of a near-surface two-dimensional electron gas (2DEG) in the presence of a random magnetic field produced by CoPd multilayers deposited onto the surface of the heterostructure. This novel method allows us to switch the random field on and off by applying an external magnetic field and also to control the amplitude and correlation length of the random field by varying the growth parameters of the multilayers. The presence of the random field is confirmed by quenching of the Shubnikov-de Haas oscillations and we see an enhanced magnetoresistance which can be interpreted semi-classically. We also observe other unusual features which may be quantum in origin.
Wong, A. Y.; Deng, B.; Quon, B.; Wang, R.; Hartzell, J.; Rosenthal, G.; Hazelton, L. R.
2007-12-01
Laboratory and Field Experiments on Expulsion of Selected Ions along Divergent Polar Geomagnetic Fields. Laboratory experiments have shown significant gyro-resonance acceleration of minority ion species in a magnetized plasma. Field aligned elctron drifts can provide free energy needed to make this process efficient. The linear magnetized device has a uniform magnetic field linked to two adjustable mirrors at the ends. Outdoor experiments at HIPAS Facility Ak(1) ( 84 MW ERP ) are used to test this process in the earth's "chimneys" at the two poles. The divergent polar geomagnetic field converts the perpendicular ion velocity into an upward motion. Satellites and ground-based ELF receivers,supplemented by UHF radars, LIDARs and infrared diagnostics , will monitor low-frequency EM waves and upflows of ions. The upward transport of ions in the lower atmosphere by field-induced diffusion and convection and the coupling to the free energy in the auroral region will be discussed. Computer modeling and theoeries complement our experiments. 1. Wong, A.Y. et al. AIP CIP 96-27719, Chap 3, pp 41-75, 1997
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.
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
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......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...
Selection of speech messages in free-field listening.
Teder, W; Kujala, T; Näätänen, R
1993-12-13
Event-related brain potentials (ERPs) elicited by initial consonants of words in a spoken message were recorded from 10 human subjects. In an ecologically valid free-field situation, brain responses to speech were recorded for the first time without using artificial probe stimuli as ERP trigger signals. In an analogy to a 'Cocktail-Party' situation in its most elementary form, two concurrent stories were delivered via separate left and right loudspeakers. The subject's task was to selectively attend to a designated message while ignoring the other. Results show a very early attention effect for a speech message commencing at about 40 ms from stimulus onset. This early effect appears to be based on tonic facilitation of the attended message and contextual cues.
Field resistance of selected potato clones to Early blight
Directory of Open Access Journals (Sweden)
Novisel Veitía
2014-10-01
Full Text Available Six potato clones, selected in vitro for their resistance to Alternaria solani Sor. culture filtrates, were evaluated for their field response to early blight infection. Field screening were performance under artificial inoculation and natural conditions. Early blight response was evaluated based on lesion size, disease severity, and area under disease progress curve (AUDPC. One clone displayed reduced lesion area (0.35 cm2 and AUDPC values compared to cv. `Desirée' (susceptible control (0.58 cm2 but those values were higher than that of the resistant control Solanum chacoense `PI 275136' (0.14 cm2. On the other hand, no differences in lesion number were detected between the susceptible control and the selected clones. This variable showed values between 21.82 and 23.87 lesions in two leaves per plant. Although early blight resistance in potato is generally associated to late maturity, the mutant IBP-27 displayed increased resistance to early blight with medium-late maturity. The six clones presented medium-early to medium-late maturity, similar to parental cv. `Desirée' (vegetative cycle ranging from 90 to 110 days. One clone was found to have higher levels of resistant to early blight than cv. `Desirée' but lower than the levels of the resistant control S. chacoense. The resistance in this clone was characterized by the reduction in lesion area, disease severity, and AUDPC values in both artificial inoculation and natural infection screening. Keywords: Alternaria solani,components of resistance, Solanum tuberosum
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.
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...
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...
The Continuous Spin Random Field Model : Ferromagnetic Ordering in d ≥ 3
Külske, Christof
1999-01-01
We investigate the Gibbs-measures of ferromagnetically coupled continuous spins in double-well potentials subjected to a random field (our specific example being the φ4 theory), showing ferromagnetic ordering in d ≥ 3 dimensions for weak disorder and large energy barriers. We map the random
Random fields of initial out of straightness leading to column buckling
DEFF Research Database (Denmark)
Kala, Zdeněk; Valeš, Jan; Jönsson, Jeppe
2017-01-01
to compression, bending and torsion from the onset of loading. Numerical simulations are performed using the geometrically non-linear model created using the ANSYS software package. Each simulation run has input random realizations of yield strength and the random field generated using the Latin Hypercube...
On the Inference of Spatial Continuity using Spartan Random Field Models
Elogne, Samuel; Hristopulos, Dionisis
2006-01-01
This paper addresses the inference of spatial dependence in the context of a recently proposed framework. More specifically, the paper focuses on the estimation of model parameters for a class of generalized Gibbs random fields, i.e., Spartan Spatial Random Fields (SSRFs). The problem of parameter inference is based on the minimization of a distance metric. The latter involves a specifically designed distance between sample constraints (variance, generalized ``gradient'' and ``curvature'') an...
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...... momentum rule for its phase. Some statistics associated with vortices, such as density, anisotropy ellipse eccentricity, and its relation to zero crossings of real and imaginary parts of the random field, are also investigated by experiments....
Selected aspects of wide-field stellar interferometry
D'Arcio, Luigi Arsenio
1999-11-01
In Michelson stellar interferometry, the high-resolution information about the source structure is detected by performing observations with widely separated telescopes, interconnected to form an interferometer. At optical wavelengths, this method provides a technically viable approach for achieving angular resolutions in the milliarcsecond range, comparable to those of a 100 m diameter telescope, whose realization is beyond the immediate engineering capabilities. Considerable efforts are currently devoted to the definition of dedicated interferometric instruments, which will allow to address ambitious astronomical tasks such as high-resolution imaging, astrometry at microarcsecond level, and the direct detection of exoplanets. Astrometry and related techniques employ the so-called wide field-of-view interferometric mode, where phase measurements are performed simultaneously at two (or more) sources; often, the actual observable is the instantaneous phase difference of the two object signals. The future success of wide-field interferometry critically depends on the development of techniques for the accurate control of field-dependent (anisoplanatic) phase errors. In this thesis, we address two aspects of this problem in detail. The first one is theoretical in nature. For ground-based measurements, atmospheric turbulence is the largest source of random phase fluctuations between the on- and the off-axis fringes. We developed a model of the temporal power spectrum of this disturbance, whose validity is not limited to low frequencies only, as it is the case with earlier models. This extension opens the possibility of the analysis of dynamic issues, such as the determination of the allowable coherent integration time T for the off-axis fringes. The spectrum turns out to be well approximated by a sequences of four power-law branches. In first instance, its overall form is determined by the values of the baseline length, telescope diameter, and average beam separation in
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≤DIsing model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.
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.
Random walk study of electron motion in helium in crossed electromagnetic fields
Englert, G. W.
1972-01-01
Random walk theory, previously adapted to electron motion in the presence of an electric field, is extended to include a transverse magnetic field. In principle, the random walk approach avoids mathematical complexity and concomitant simplifying assumptions and permits determination of energy distributions and transport coefficients within the accuracy of available collisional cross section data. Application is made to a weakly ionized helium gas. Time of relaxation of electron energy distribution, determined by the random walk, is described by simple expressions based on energy exchange between the electron and an effective electric field. The restrictive effect of the magnetic field on electron motion, which increases the required number of collisions per walk to reach a terminal steady state condition, as well as the effect of the magnetic field on electron transport coefficients and mean energy can be quite adequately described by expressions involving only the Hall parameter.
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...
Extremes of random fields over arbitrary domains with application to concrete rupture stresses
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2004-01-01
To find the exact probability distribution of the global maximum or minimum of a random field within a bounded domain is a pending problem even for Gaussian fields. Except for very special examples of fields, recourse must be taken to approximate reasoning or asymptotic considerations to be judged...... functions of a smooth approximately Gaussian field, herein called a broken line Hino field. For completeness this particular field type is defined in Appendices A and B. The paper concludes with a statistical application on data for plain concrete tensile strength. (C) 2004 Elsevier Ltd. All rights reserved....
Field trip guide to selected outcrops, Arbuckle Mountains, Oklahoma
Energy Technology Data Exchange (ETDEWEB)
NONE
1991-11-17
The Arbuckle Mountains, named for Brigadier General Matthew Arbuckle, are located in south-central Oklahoma. The formations that comprise the Arbuckle Mountains have been extensively studied for hydrocarbon source rock and reservoir rock characteristics that can be applied to the subsurface in the adjacent Anadarko and Ardmore basins. Numerous reports and guidebooks have been written concerning the Arbuckle Mountains. A few important general publications are provided in the list of selected references. The purpose of this handout is to provide general information on the geology of the Arbuckle Mountains and specific information on the four field trip stops, adapted from the literature. The four stops were at: (1) Sooner Rock and Sand Quarry; (2) Woodford Shale; (3) Hunton Anticline and Hunton Quarry; and (4) Tar Sands of Sulfur Area. As part of this report, two papers are included for more detail: Paleomagnetic dating of basinal fluid migration, base-metal mineralization, and hydrocarbon maturation in the Arbuckle Mountains, Oklahoma and Laminated black shale-bedded chert cyclicity in the Woodford Formation, southern Oklahoma.
Exploring Bayesian model selection methods for effective field theory expansions
Schaffner, Taylor; Yamauchi, Yukari; Furnstahl, Richard
2017-09-01
A fundamental understanding of the microscopic properties and interactions of nuclei has long evaded physicists due to the complex nature of quantum chromodynamics (QCD). One approach to modeling nuclear interactions is known as chiral effective field theory (EFT). Today, the method's greatest limitation lies in the approximation of interaction potentials and their corresponding uncertainties. Computing EFT expansion coefficients, known as Low-Energy Constants (LECs), from experimental data reduces to a problem of statistics and fitting. In the conventional approach, the fitting is done using frequentist methods that fail to evaluate the quality of the model itself (e.g., how many orders to use) in addition to its fit to the data. By utilizing Bayesian statistical methods for model selection, the model's quality can be taken into account, providing a more controlled and robust EFT expansion. My research involves probing different Bayesian model checking techniques to determine the most effective means for use with estimating the values of LECs. In particular, we are using model problems to explore the Bayesian calculation of an EFT expansion's evidence and an approximation to this value known as the WAIC (Widely Applicable Information Criterion). This work was supported in part by the National Science Foundation under Grant No. PHY-1306250.
A dissipative random velocity field for fully developed fluid turbulence
Pereira, Rodrigo M; Chevillard, Laurent
2015-01-01
We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent flow. A key step in the construction of this model is the introduction of some aspects of the vorticity stretching mechanism that governs the dynamics of fluid particles along their trajectory. An additional further phenomenological step aimed at including the long range correlated nature of turbulence makes this model depending on a single free parameter $\\gamma$ that can be estimated from experimental measurements. We confirm the realism of the model regarding the geometry of the velocity gradient tensor, the power-law behaviour of the moments of velocity increments (i.e. the structure functions), including the intermittent corrections, and the existence of energy transfers across scales. We quantify the dependence of these basic properties of turbulent flows on the free...
Effect of a dilute random field on a continuous-symmetry order parameter
Proctor, T. C.; Chudnovsky, E. M.
2015-04-01
X Y and Heisenberg spins, subjected to strong random fields acting at a few points in space with a concentration cr≪1 , are studied numerically on three-dimensional lattices containing over 4 ×106 sites. Glassy behavior with a strong dependence on initial conditions is found. Beginning with a random initial orientation of spins, the system evolves into ferromagnetic domains inversely proportional to cr in size. The area of the hysteresis loop m (H ) scales as cr2. These findings are explained by mapping the effect of a strong dilute random field onto the effect of a weak continuous random field. Our theory applies directly to ferromagnets with magnetic impurities, and is conceptually relevant to strongly pinned vortex lattices in superconductors and pinned charge-density waves.
Gartin, Patrick R.
1995-01-01
Asserts that several analytical issues in randomized field experiments conducted by criminal justice scholars must be addressed more systematically. Notes that issues related to statistical power and desired sample size remain unresolved. Reviews related literature from the field of medicine to provide insights regarding the dilemmas created by…
SNP selection and classification of genome-wide SNP data using stratified sampling random forests.
Wu, Qingyao; Ye, Yunming; Liu, Yang; Ng, Michael K
2012-09-01
For high dimensional genome-wide association (GWA) case-control data of complex disease, there are usually a large portion of single-nucleotide polymorphisms (SNPs) that are irrelevant with the disease. A simple random sampling method in random forest using default mtry parameter to choose feature subspace, will select too many subspaces without informative SNPs. Exhaustive searching an optimal mtry is often required in order to include useful and relevant SNPs and get rid of vast of non-informative SNPs. However, it is too time-consuming and not favorable in GWA for high-dimensional data. The main aim of this paper is to propose a stratified sampling method for feature subspace selection to generate decision trees in a random forest for GWA high-dimensional data. Our idea is to design an equal-width discretization scheme for informativeness to divide SNPs into multiple groups. In feature subspace selection, we randomly select the same number of SNPs from each group and combine them to form a subspace to generate a decision tree. The advantage of this stratified sampling procedure can make sure each subspace contains enough useful SNPs, but can avoid a very high computational cost of exhaustive search of an optimal mtry, and maintain the randomness of a random forest. We employ 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) to demonstrate that the proposed stratified sampling method is effective, and it can generate better random forest with higher accuracy and lower error bound than those by Breiman's random forest generation method. For Parkinson data, we also show some interesting genes identified by the method, which may be associated with neurological disorders for further biological investigations.
Yun, Yong-Huan; Li, Hong-Dong; Wood, Leslie R. E.; Fan, Wei; Wang, Jia-Jun; Cao, Dong-Sheng; Xu, Qing-Song; Liang, Yi-Zeng
2013-07-01
Wavelength selection is a critical step for producing better prediction performance when applied to spectral data. Considering the fact that the vibrational and rotational spectra have continuous features of spectral bands, we propose a novel method of wavelength interval selection based on random frog, called interval random frog (iRF). To obtain all the possible continuous intervals, spectra are first divided into intervals by moving window of a fix width over the whole spectra. These overlapping intervals are ranked applying random frog coupled with PLS and the optimal ones are chosen. This method has been applied to two near-infrared spectral datasets displaying higher efficiency in wavelength interval selection than others. The source code of iRF can be freely downloaded for academy research at the website: http://code.google.com/p/multivariate-calibration/downloads/list.
Delay line length selection in generating fast random numbers with a chaotic laser.
Zhang, Jianzhong; Wang, Yuncai; Xue, Lugang; Hou, Jiayin; Zhang, Beibei; Wang, Anbang; Zhang, Mingjiang
2012-04-10
The chaotic light signals generated by an external cavity semiconductor laser have been experimentally demonstrated to extract fast random numbers. However, the photon round-trip time in the external cavity can cause the occurrence of the periodicity in random sequences. To overcome it, the exclusive-or operation on corresponding random bits in samples of the chaotic signal and its time-delay signal from a chaotic laser is required. In this scheme, the proper selection of delay length is a key issue. By doing a large number of experiments and theoretically analyzing the interplay between the Runs test and the threshold value of the autocorrelation function, we find when the corresponding delay time of autocorrelation trace with the correlation coefficient of less than 0.007 is considered as the delay time between the chaotic signal and its time-delay signal, streams of random numbers can be generated with verified randomness.
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
on stacked classifiers; the benefits are two fold: on one hand, the system scales well to consider different types of complex features and, on the other hand, the use of stacked classifiers makes the performance of the proposed technique more accurate. The proposed method consists of a random forest using...... better performance than state of the art methods on the same dataset. The results show an improvement of 2.3% over the base model by using MMSSL and displays that the method is effective in this problem domain....
Metal-insulator transition of 2d electron gas in a random magnetic field
Wang, X R; Liu, D Z
1999-01-01
We study the metal-insulator transition of a two-dimensional electron gas in the presence of a random magnetic field from the localization property. The localization length is directly calculated using a transfer matrix technique and finite size scaling analysis. We argue that there is a metal-insulator transition in such a system and show strong numerical evidence that the system undergoes a disorder driven Kosterlitz-Thouless type metal-insulator transition. We will also discuss a mean field theory which maps the random field system into a two-dimensional XY-model. The vortex and antivortex excitations in the XY-model correspond to two different kinds of magnetic domains in the random field system.
Selection of 3013 containers for field surveillance: LA-14310, Revision 1
Energy Technology Data Exchange (ETDEWEB)
Peppers, Larry; Kelly, Elizabeth; McClard, James; Friday, Gary; Venetz, Theodore; Stakebake, Jerry
2009-04-01
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.
Two-year Randomized Clinical Trial Of Self-etching Adhesives And Selective Enamel Etching
Pena, MR; Rodrigues CE; JA; Ely; Giannini, C.; Reis, M; AF
2016-01-01
Objective: 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. Methods: 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...
rft1d: Smooth One-Dimensional Random Field Upcrossing Probabilities in Python
Directory of Open Access Journals (Sweden)
Todd C. Pataky
2016-07-01
Full Text Available Through topological expectations regarding smooth, thresholded n-dimensional Gaussian continua, random field theory (RFT describes probabilities associated with both the field-wide maximum and threshold-surviving upcrossing geometry. A key application of RFT is a correction for multiple comparisons which affords field-level hypothesis testing for both univariate and multivariate fields. For unbroken isotropic fields just one parameter in addition to the mean and variance is required: the ratio of a field's size to its smoothness. Ironically the simplest manifestation of RFT (1D unbroken fields has rarely surfaced in the literature, even during its foundational development in the late 1970s. This Python package implements 1D RFT primarily for exploring and validating RFT expectations, but also describes how it can be applied to yield statistical inferences regarding sets of experimental 1D fields.
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...
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...
Submicron structure random field on granular soil material with retinex algorithm optimization
Liang Yu; Tao Chenyuan; Zhou Bingcheng; Huang Shuai; Huang Linchong
2017-01-01
In this paper, a Retinex scale optimized image enhancement algorithm is proposed, which can enhance the micro vision image and eliminate the influence of the uneven illumination. Based on that, a random geometric model of the microstructure of granular materials is established with Monte-Carlo method, the numerical simulation including consolidation process of granular materials is compared with the experimental data. The results have proved that the random field method with Retinex image enh...
Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.
Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R; Miller, Earl K; Fusi, Stefano
2017-11-08
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 ("mixed
Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks
DEFF Research Database (Denmark)
Heide, Janus; Zhang, Qi; Fitzek, Frank
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...
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.
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…
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.
Phase-space representation and polarization domains of random electromagnetic fields.
Castaneda, Roman; Betancur, Rafael; Herrera, Jorge; Carrasquilla, Juan
2008-08-01
The phase-space representation of stationary random electromagnetic fields is developed by using electromagnetic spatial coherence wavelets. The propagation of the field's power and states of spatial coherence and polarization results from correlations between the components of the field vectors at pairs of points in space. Polarization domains are theoretically predicted as the structure of the field polarization at the observation plane. In addition, the phase-space representation provides a generalization of the Poynting theorem. Theoretical predictions are examined by numerically simulating the Young experiment with electromagnetic waves. The experimental implementation of these results is a current subject of research.
Excursion sets of infinitely divisible random fields with convolution equivalent Lévy measure
DEFF Research Database (Denmark)
Rønn-Nielsen, Anders; Jensen, Eva B. Vedel
2017-01-01
We consider a continuous, infinitely divisible random field in ℝ d , d = 1, 2, 3, given as an integral of a kernel function with respect to a Lévy basis with convolution equivalent Lévy measure. For a large class of such random fields, we compute the asymptotic probability that the excursion set ...... at level x contains some rotation of an object with fixed radius as x → ∞. Our main result is that the asymptotic probability is equivalent to the right tail of the underlying Lévy measure....
Excursion sets of infinitely divisible random fields with convolution equivalent Lévy measure
DEFF Research Database (Denmark)
Rønn-Nielsen, Anders; Jensen, Eva B. Vedel
We consider a continuous, infinitely divisible random field in R d , d = 1, 2, 3, given as an integral of a kernel function with respect to a Lévy basis with convolution equivalent Lévy measure. For a large class of such random fields we compute the asymptotic probability that the excursion set a...... at level x contains some rotation of an object with fixed radius as x → ∞. Our main result is that the asymptotic probability is equivalent to the right tail of the underlying Lévy measure...
Random magnetic field and quasiparticle transport in the mixed state of high- Tc cuprates.
Ye, J
2001-01-08
By a singular gauge transformation, the quasiparticle transport in the mixed state of high- Tc cuprates is mapped into a charge-neutral Dirac moving in short-range correlated random scalar and long-range correlated vector potential. A fully quantum mechanical approach to longitudinal and transverse thermal conductivities is presented. The semiclassical Volovik effect is presented in a quantum mechanical way. The quasiparticle scattering from the random magnetic field which was completely missed in all the previous semiclassical approaches is the dominant scattering mechanism at sufficient high magnetic field. The implications for experiments are discussed.
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......, as a consequence the random field model specification introduces non-stationarity and non-ergodicity in the misspecified model and it becomes non-trivial, relative to the existing literature, to establish the limiting behavior of the estimated parameters. The asymptotic results are obtained by applying some...
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.
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.
Carbon nanotube field emitters on KOVAR substrate modified by random pattern
Energy Technology Data Exchange (ETDEWEB)
Park, Seol Ah; Song, Eun-Ho; Kang, Byung Hyun; Ju, Byeong-Kwon, E-mail: bkju@korea.ac.kr [Korea University, Display and Nanosystem Laboratory, College of Engineering (Korea, Republic of)
2015-07-15
We investigated the field emission characteristics of patterned carbon nanotubes (CNTs) on KOVAR substrates with different surface morphologies. The substrate with a micro-sized random pattern was fabricated through chemical wet etching, whereas the substrate with a nano-sized random pattern was formed by surface roughening process of polymer and chemical wet etching. The field emission characteristics of these substrates were the compared with those of non-treated substrates. It was clearly revealed that the field emission characteristics of CNTs were influenced by the surface morphology of the cathode substrate. When the surface of cathode was modified by random pattern, the modified substrate provided a large surface area and a wider print area. Also, the modified surface morphology of the cathode provided strong adhesion between the CNT paste and the cathode. Particularly, the substrate with the nano-sized random pattern showed that the turn-on field value decreases and the field enhancement factor value improves as compared with non-treated substrate.
BRZOZKA, Z; COBBEN, PLHM; REINHOUDT, DN; EDEMA, JJH; KELLOGG, RM
1993-01-01
A chemically modified field-effect transistor (CHEMFET) with satisfactory Ag+ selectivity is described. The potentiometric Ag+ selectivities of CHEMFETs with plasticized PVC membranes based on macrocyclic thioethers have been determined. All the macrocyclic thioethers tested showed silver response
Falagas, Matthew E; Grigori, Tatiana; Ioannidou, Eleni
2009-03-01
We sought to evaluate the trends in the methodological quality of randomized controlled trials in various medical fields. Relevant studies were retrieved by the PubMed and the ISI Web of science databases. Thirty-five out of 457 retrieved studies met the inclusion criteria. Twenty-one out of 35 selected studies reported significant improvement in at least one methodological quality factor. Overall quality scores were increased in 13 out of 26 studies providing relevant data. The most commonly separately examined key quality factors were allocation concealment and blinding in 13 out of 21 studies that reported relevant data. Allocation concealment was the quality characteristic most commonly reported as significantly improving during the reviewed period (in five out of eight studies reporting relevant comparative data). Certain aspects of methodological quality have improved significantly over time, but others remain stagnant. Further efforts to improve study design, conduct, and reporting of randomized controlled trials are warranted.
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 ...
Okagbue, Hilary I; Opanuga, Abiodun A; Adamu, Muminu O; Ugwoke, Paulinus O; Obasi, Emmanuela C M; Eze, Grace A
2017-12-01
This data article contains the statistical analysis of Igbo personal names and a sample of randomly selected of such names. This was presented as the following: 1). A simple random sampling of some Igbo personal names and their respective gender associated with each name. 2). The distribution of the vowels, consonants and letters of alphabets of the personal names. 3). The distribution of name length. 4). The distribution of initial and terminal letters of Igbo personal names. The significance of the data was discussed.
Kraft, Matthew A.; Dougherty, Shaun M.
2013-01-01
In this study, we evaluate the efficacy of teacher communication with parents and students as a means of increasing student engagement. We estimate the causal effect of teacher communication by conducting a randomized field experiment in which sixth- and ninth-grade students were assigned to receive a daily phone call home and a text/written…
The Role of Treatment Fidelity on Outcomes during a Randomized Field Trial of an Autism Intervention
Mandell, David S; Stahmer, Aubyn C; Shin, Sujie; Xie, Ming; Reisinger, Erica; Marcus, Steven C
2013-01-01
This randomized field trial comparing Strategies for Teaching based on Autism Research and Structured Teaching enrolled educators in 33 kindergarten-through-second-grade autism support classrooms and 119 students, aged 5-8 years in the School District of Philadelphia. Students were assessed at the beginning and end of the academic year using the…
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...
The effect of early entrepreneurship education: evidence from a randomized field experiment
Rosendahl Huber, L.; Sloof, R.; van Praag, M.
2012-01-01
The aim of this study is to analyze the effectiveness of early entrepreneurship education. To this end, we conduct a randomized field experiment to evaluate a leading entrepreneurship education program that is taught worldwide in the final grade of primary school. We focus on pupils' development of
Is Bonferroni correction more sensitive than Random Field Theory for most fMRI studies?
Tierney, Tim M; Carmichael, David W
2016-01-01
Random Field Theory has been used in the fMRI literature to address the multiple comparisons problem. The method provides an analytical solution for the computation of precise p-values when its assumptions are met. When its assumptions are not met the thresholds generated by Random Field Theory can be more conservative than Bonferroni corrections, which are arguably too stringent for use in fMRI. As this has been well documented theoretically it is surprising that a majority of current studies (~80%) would not meet the assumptions of Random Field Theory and therefore would have reduced sensitivity. Specifically most data is not smooth enough to meet the good lattice assumption. Current studies smooth data on average by twice the voxel size which is rarely sufficient to meet the good lattice assumption. The amount of smoothing required for Random Field Theory to produce accurate p-values increases with image resolution and decreases with degrees of freedom. There is no rule of thumb that is valid for all study...
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
Application of operator-scaling anisotropic random fields to binary mixtures
Anders, Denis; Hoffmann, Alexander; Scheffler, Hans-Peter; Weinberg, Kerstin
2011-10-01
In modern technical applications various multiphase mixtures are used to meet demanding mechanical, chemical and electrical requirements. To understand their structural properties as continuous macroscopic materials, it is important to capture the microstructure of these mixtures. Due to their vast range of applications multicomponent systems are subjected to microstructural changes such as phase separation and coarsening. Therefore the ultimate microstructural arrangement depends on the system's configuration and on exterior driving forces. In addition to this, random physical imperfections within the material and random noise in the exterior thermodynamic fields influence in essence the microstructural evolution. Since all physical processes are subjected to a certain degree of random inhomogeneity under realistic conditions, the influence of random phenomena cannot be neglected in modern physical models. An advanced mathematical description and an implementation of these stochastic processes are required to adapt simulation results based on deterministic mathematical models to experimental observations. In our contribution we will present an operator-scaling anisotropic random field embedded in the Cahn-Hilliard phase-field model to describe the phase evolution in a binary mixture. The arising nonlinear diffusion equation will be solved numerically in the innovative framework of the isogeometric finite element method. To illustrate the flexibility and versatility of our approach, numerical and experimental results for a eutectic Sn-Pb alloy are contraposed. This is the first time that the microstructural evolution in a multicomponent system has been associated with operator-scaling anisotropic random fields. Due to its enormous potential as an essential ingredient in stochastic mathematical and physical modeling it is only a matter of time until these processes will become prevalent in engineering applications.
Magnetic Field Design for Selecting and Aligning Immunomagnetic Labeled Cells
Tibbe, Arjan G.J.; de Grooth, B.G.; Greve, Jan; Dolan, Gerald J.; Rao, Chandra; Terstappen, Leonardus Wendelinus Mathias Marie
2002-01-01
Background: Recently we introduced the CellTracks cell analysis system, in which samples are prepared based on a combination of immunomagnetic selection, separation, and alignment of cells along ferromagnetic lines. Here we describe the underlying magnetic principles and considerations made in the
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 ...
Field evaluation of selected formulations of Trichoderma species as ...
African Journals Online (AJOL)
The experiment was carried out between 1997 and 1998 at the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria to test the efficacy of biological seed treatment of cowpea against Macrophomina phaseolina infection in the field. Trichoderma sp., T. koningii Oudem (IMI 361600) and T. harzianum Rifai (IMI ...
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)
Field tolerance of selected varieties to and fungicide efficacy against ...
African Journals Online (AJOL)
The materials were planted in fields having a history of AB disease and rated for tolerance based on a General Disease Index (GDI), with the lowest scores representing tolerance, and the higher scores representing susceptibility. Variety 199062-1 had the lowest GDI value, and was the most tolerant to AB; while W119 had ...
Exact Partition Function for the Random Walk of an Electrostatic Field
Directory of Open Access Journals (Sweden)
Gabriel González
2017-01-01
Full Text Available The partition function for the random walk of an electrostatic field produced by several static parallel infinite charged planes in which the charge distribution could be either ±σ is obtained. We find the electrostatic energy of the system and show that it can be analyzed through generalized Dyck paths. The relation between the electrostatic field and generalized Dyck paths allows us to sum overall possible electrostatic field configurations and is used for obtaining the partition function of the system. We illustrate our results with one example.
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....
The van Hemmen model and effect of random crystalline anisotropy field
Energy Technology Data Exchange (ETDEWEB)
Morais, Denes M. de [Instituto de Física, Universidade Federal de Mato Grosso, 78060-900 Cuiabá, Mato Grosso (Brazil); Godoy, Mauricio, E-mail: mgodoy@fisica.ufmt.br [Instituto de Física, Universidade Federal de Mato Grosso, 78060-900 Cuiabá, Mato Grosso (Brazil); Arruda, Alberto S. de, E-mail: aarruda@fisica.ufmt.br [Instituto de Física, Universidade Federal de Mato Grosso, 78060-900 Cuiabá, Mato Grosso (Brazil); Silva, Jonathas N. da [Universidade Estadual Paulista, 14800-901, Araraquara, São Paulo (Brazil); Ricardo de Sousa, J. [Instituto Nacional de Sistemas Complexos, Departamento de Fisica, Universidade Federal do Amazona, 69077-000, Manaus, Amazonas (Brazil)
2016-01-15
In this work, we have presented the generalized phase diagrams of the van Hemmen model for spin S=1 in the presence of an anisotropic term of random crystalline field. In order to study the critical behavior of the phase transitions, we employed a mean-field Curie–Weiss approach, which allows calculation of the free energy and the equations of state of the model. The phase diagrams obtained here displayed tricritical behavior, with second-order phase transition lines separated from the first-order phase transition lines by a tricritical point. - Highlights: • Several phase diagrams are obtained for the model. • The influence of the random crystalline anisotropy field on the model is investigated. • Three ordered (spin-glass, ferromagnetic and mixed) phases are found. • The tricritical behavior is examined.
One-dimensional classical diffusion in a random force field with weakly concentrated absorbers
Texier, C.; Hagendorf, C.
2009-05-01
A one-dimensional model of classical diffusion in a random force field with a weak concentration ρ of absorbers is studied. The force field is taken as a Gaussian white noise with langphi(x)rang=0 and langphi(x)phi(x')rang=g δ(x- x'). Our analysis relies on the relation between the Fokker-Planck operator and a quantum Hamiltonian in which absorption leads to breaking of supersymmetry. Using a Lifshits argument, it is shown that the average return probability is a power law \\langle {P(x,t\\vert x,0)} \\rangle \\sim t^{-\\sqrt{2\\rho/g}} (to be compared with the usual Lifshits exponential decay exp-(ρ2t)1/3 in the absence of the random force field). The localisation properties of the underlying quantum Hamiltonian are discussed as well.
Simulated Performance Evaluation of a Selective Tracker Through Random Scenario Generation
DEFF Research Database (Denmark)
Hussain, Dil Muhammad Akbar
2006-01-01
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...
Selective data analysis for diamond detectors in neutron fields
Weiss, Christina; Frais-Kölbl, Helmut; Griesmayer, Erich; Kavrigin, Pavel
2017-09-01
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.
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.
Yang, Yongchao; Sun, Peng; Nagarajaiah, Satish; Bachilo, Sergei M.; Weisman, R. Bruce
2017-07-01
Structural damage is typically a local phenomenon that initiates and propagates within a limited area. As such high spatial resolution measurement and monitoring is often needed for accurate damage detection. This requires either significantly increased costs from denser sensor deployment in the case of global simultaneous/parallel measurements, or increased measurement time and labor in the case of global sequential measurements. This study explores the feasibility of an alternative approach to this problem: a computational solution in which a limited set of randomly positioned, low-resolution global strain measurements are used to reconstruct the full-field, high-spatial-resolution, two-dimensional (2D) strain field and rapidly detect local damage. The proposed approach exploits the implicit low-rank and sparse data structure of the 2D strain field: it is highly correlated without many edges and hence has a low-rank structure, unless damage-manifesting itself as sparse local irregularity-is present and alters such a low-rank structure slightly. Therefore, reconstruction of the full-field, high-spatial-resolution strain field from a limited set of randomly positioned low-resolution global measurements is modeled as a low-rank matrix completion framework and damage detection as a sparse decomposition formulation, enabled by emerging convex optimization techniques. Numerical simulations on a plate structure are conducted for validation. The results are discussed and a practical iterative global/local procedure is recommended. This new computational approach should enable the efficient detection of local damage using limited sets of strain measurements.
Endo, Tomoyuki; Fujise, Hikaru; Kawachi, Yuuna; Ishihara, Ayaka; Matsuda, Akitaka; Fushitani, Mizuho; Kono, Hirohiko; Hishikawa, Akiyoshi
2017-02-01
Selective bond breaking of CO2 in phase-locked ω-2ω two-color intense laser fields (λ = 800 nm and 400 nm, total field intensity I ∼ 10(14) W cm(-2)) has been investigated by coincidence momentum imaging. The CO(+) and O(+) fragment ions produced by two-body Coulomb explosion, CO2(2+) → CO(+) + O(+), exhibit asymmetric distributions along the laser polarization direction, showing that one of the two equivalent C-O bonds is selectively broken by the laser fields. At a field intensity higher than 2 × 10(14) W cm(-2), the largest fragment asymmetry is observed when the relative phase ϕ between the ω and 2ω laser fields is ∼0 and π. On the other hand, an increase of the asymmetry and a shift of the phase providing the largest asymmetry are observed at lower field intensities. The selective bond breaking and its dependence on the laser field intensity are discussed in terms of a mechanism involving deformation of the potential energy surfaces and electron recollision in intense laser fields.
Randomized Soil Survey of the Distribution of Burkholderia pseudomallei in Rice Fields in Laos ▿ †
Rattanavong, Sayaphet; Wuthiekanun, Vanaporn; Langla, Sayan; Amornchai, Premjit; Sirisouk, Joy; Phetsouvanh, Rattanaphone; Moore, Catrin E.; Peacock, Sharon J.; Buisson, Yves; Newton, Paul N.
2011-01-01
Melioidosis is a major cause of morbidity and mortality in Southeast Asia, where the causative organism (Burkholderia pseudomallei) is present in the soil. In the Lao People's Democratic Republic (Laos), B. pseudomallei is a significant cause of sepsis around the capital, Vientiane, and has been isolated in soil near the city, adjacent to the Mekong River. We explored whether B. pseudomallei occurs in Lao soil distant from the Mekong River, drawing three axes across northwest, northeast, and southern Laos to create nine sampling areas in six provinces. Within each sampling area, a random rice field site containing a grid of 100 sampling points each 5 m apart was selected. Soil was obtained from a depth of 30 cm and cultured for B. pseudomallei. Four of nine sites (44%) were positive for B. pseudomallei, including all three sites in Saravane Province, southern Laos. The highest isolation frequency was in east Saravane, where 94% of soil samples were B. pseudomallei positive with a geometric mean concentration of 464 CFU/g soil (95% confidence interval, 372 to 579 CFU/g soil; range, 25 to 10,850 CFU/g soil). At one site in northwest Laos (Luangnamtha), only one sample (1%) was positive for B. pseudomallei, at a concentration of 80 CFU/g soil. Therefore, B. pseudomallei occurs in Lao soils beyond the immediate vicinity of the Mekong River, alerting physicians to the likelihood of melioidosis in these areas. Further studies are needed to investigate potential climatic, soil, and biological determinants of this heterogeneity. PMID:21075883
Ruffolo, D. J.; Snodin, A. P.; Oughton, S.; Servidio, S.; Matthaeus, W. H.
2013-12-01
The random walk of magnetic field lines is examined analytically and numerically in the context of reduced magnetohydrodynamic (RMHD) turbulence, which provides a useful description of plasmas dominated by a strong mean field, such as in the solar corona. A nonperturbative theory of magnetic field line diffusion [1] is compared with the diffusion coefficients obtained by accurate numerical tracing of magnetic field lines for both synthetic models and direct numerical simulations of RMHD. Statistical analysis of an ensemble of trajectories confirms the applicability of the theory, which very closely matches the numerical field line diffusion coefficient as a function of distance z along the mean magnetic field for a wide range of the Kubo number R. The theory employs Corrsin's independence hypothesis, sometimes thought to be valid only at low R. However, the results demonstrate that it works well up to R=10, both for a synthetic RMHD model and an RMHD simulation. The numerical results from RMHD simulation are compared with and without phase randomization, demonstrating an effect of coherent structures on the field line random walk for low Kubo number. Partially supported by a postdoctoral fellowship from Mahidol University, the Thailand Research Fund, POR Calabria FSE-2007/2013, the US NSF (AGS-1063439 and SHINE AGS-1156094), NASA (Heliophysics Theory NNX08AI47G & NNX11AJ44G), by the Solar Probe Plus Project through the ISIS Theory team, by the MMS Theory and Modeling team, and by EU Marie Curie Project FP7 PIRSES-2010-269297 'Turboplasmas' at Università della Calabria. [1] D. Ruffolo and W. H. Matthaeus, Phys. Plasmas, 20, 012308 (2013).
Random fields generation on the GPU with the spectral turning bands method
Hunger, L.; Cosenza, B.; Kimeswenger, S.; Fahringer, T.
2014-08-01
Random field (RF) generation algorithms are of paramount importance for many scientific domains, such as astrophysics, geostatistics, computer graphics and many others. Some examples are the generation of initial conditions for cosmological simulations or hydrodynamical turbulence driving. In the latter a new random field is needed every time-step. Current approaches commonly make use of 3D FFT (Fast Fourier Transform) and require the whole generated field to be stored in memory. Moreover, they are limited to regular rectilinear meshes and need an extra processing step to support non-regular meshes. In this paper, we introduce TBARF (Turning BAnd Random Fields), a RF generation algorithm based on the turning band method that is optimized for massively parallel hardware such as GPUs. Our algorithm replaces the 3D FFT with a lower order, one-dimensional FFT followed by a projection step, and is further optimized with loop unrolling and blocking. We show that TBARF can easily generate RF on non-regular (non uniform) meshes and can afford mesh sizes bigger than the available GPU memory by using a streaming, out-of-core approach. TBARF is 2 to 5 times faster than the traditional methods when generating RFs with more than 16M cells. It can also generate RF on non-regular meshes, and has been successfully applied to two real case scenarios: planetary nebulae and cosmological simulations.
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
DEFF Research Database (Denmark)
Barrera Figueroa, Salvador; Henriquez, Vicente Cutanda; Jacobsen, Finn
2006-01-01
to the definition of the latter, a number of plane waves coming from random directions and having random phases impinge simultaneously upon the microphone. The random-incidence sensitivity can be estimated using measurements made in an anechoic chamber, while the diffuse-field sensitivity requires a reverberation...
Joint random field model for all-weather moving vehicle detection.
Wang, Yang
2010-09-01
This paper proposes a joint random field (JRF) model for moving vehicle detection in video sequences. The JRF model extends the conditional random field (CRF) by introducing auxiliary latent variables to characterize the structure and evolution of visual scene. Hence, detection labels (e.g., vehicle/roadway) and hidden variables (e.g., pixel intensity under shadow) are jointly estimated to enhance vehicle segmentation in video sequences. Data-dependent contextual constraints among both detection labels and latent variables are integrated during the detection process. The proposed method handles both moving cast shadows/lights and various weather conditions. Computationally efficient algorithm has been developed for real-time vehicle detection in video streams. Experimental results show that the approach effectively deals with various illumination conditions and robustly detects moving vehicles even in grayscale video.
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.
Statistics of highly heterogeneous flow fields confined to three-dimensional random porous media
Jin, C.; Langston, P. A.; Pavlovskaya, G. E.; Hall, M. R.; Rigby, S. P.
2016-01-01
We present a strong relationship between the microstructural characteristics of, and the fluid velocity fields confined to, three-dimensional random porous materials. The relationship is revealed through simultaneously extracting correlation functions Ru u(r ) of the spatial (Eulerian) velocity fields and microstructural two-point correlation functions S2(r ) of the random porous heterogeneous materials. This demonstrates that the effective physical transport properties depend on the characteristics of complex pore structure owing to the relationship between Ru u(r ) and S2(r ) revealed in this study. Further, the mean excess plot was used to investigate the right tail of the streamwise velocity component that was found to obey light-tail distributions. Based on the mean excess plot, a generalized Pareto distribution can be used to approximate the positive streamwise velocity distribution.
A Modified FCM Classifier Constrained by Conditional Random Field Model for Remote Sensing Imagery
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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.
Effect of non-random mating on genomic and BLUP selection schemes
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Nirea Kahsay G
2012-04-01
Full Text Available Abstract Background The risk of long-term unequal contribution of mating pairs to the gene pool is that deleterious recessive genes can be expressed. Such consequences could be alleviated by appropriately designing and optimizing breeding schemes i.e. by improving selection and mating procedures. Methods We studied the effect of mating designs, random, minimum coancestry and minimum covariance of ancestral contributions on rate of inbreeding and genetic gain for schemes with different information sources, i.e. sib test or own performance records, different genetic evaluation methods, i.e. BLUP or genomic selection, and different family structures, i.e. factorial or pair-wise. Results Results showed that substantial differences in rates of inbreeding due to mating design were present under schemes with a pair-wise family structure, for which minimum coancestry turned out to be more effective to generate lower rates of inbreeding. Specifically, substantial reductions in rates of inbreeding were observed in schemes using sib test records and BLUP evaluation. However, with a factorial family structure, differences in rates of inbreeding due mating designs were minor. Moreover, non-random mating had only a small effect in breeding schemes that used genomic evaluation, regardless of the information source. Conclusions It was concluded that minimum coancestry remains an efficient mating design when BLUP is used for genetic evaluation or when the size of the population is small, whereas the effect of non-random mating is smaller in schemes using genomic evaluation.
Simulation of the pressure field near a jet by randomly distributed vortex rings
Fung, Y. T.; Liu, C. H.; Gunzburger, M. D.
1979-01-01
Fluctuations of the pressure field in the vicinity of a jet are simulated numerically by a flow model consisting of axially symmetric vortex rings with viscous cores submerged in a uniform stream. The time interval between the shedding of successive vortices is taken to be a random variable with a probability distribution chosen to match that from experiments. It is found that up to 5 diameters downstream of the jet exit, statistics of the computed pressure field are in good agreement with experimental results. Statistical comparisons are provided for the overall sound pressure level, the peak amplitude, and the Strouhal number based on the peak frequency of the pressure signals.
Phase transitions of Ising mixed spin 1 and 3/2 with random crystal field distribution
Sabri, S.; EL Falaki, M.; EL Yadari, M.; Benyoussef, A.; EL Kenz, A.
2016-10-01
The thermal and magnetic properties of the mixed spin-1 and spin-3/2 in the presence of the random crystal field are studied within the mean field approach based on the Bogoliubov inequality for the Gibbs free energy. The model exhibits first, second order transitions, a tricritical point, triple point and an isolated critical end point. It is found that the system displays simple and double compensation temperatures, five topologies of the phase diagrams. A re-entrant phenomenon is also discussed and the thermal dependences of total magnetization according to extended Neel classification have been also given.
Spatial Random Field Models Inspired from Statistical Physics with Applications in the Geosciences
Hristopulos, D. T.
2005-01-01
The spatial structure of fluctuations in spatially inhomogeneous processes can be modeled in terms of Gibbs random fields. A local low energy estimator (LLEE) is proposed for the interpolation (prediction) of such processes at points where observations are not available. The LLEE approximates the spatial dependence of the data and the unknown values at the estimation points by low-lying excitations of a suitable energy functional. It is shown that the LLEE is a linear, unbiased, non-exact est...
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.
Spectral turning bands for efficient Gaussian random fields generation on GPUs and accelerators
Hunger, L.; Cosenza, B.; Kimeswenger, S.; Fahringer, T.
2015-11-01
A random field (RF) is a set of correlated random variables associated with different spatial locations. RF generation algorithms are of crucial importance for many scientific areas, such as astrophysics, geostatistics, computer graphics, and many others. Current approaches commonly make use of 3D fast Fourier transform (FFT), which does not scale well for RF bigger than the available memory; they are also limited to regular rectilinear meshes. We introduce random field generation with the turning band method (RAFT), an RF generation algorithm based on the turning band method that is optimized for massively parallel hardware such as GPUs and accelerators. Our algorithm replaces the 3D FFT with a lower-order, one-dimensional FFT followed by a projection step and is further optimized with loop unrolling and blocking. RAFT can easily generate RF on non-regular (non-uniform) meshes and efficiently produce fields with mesh sizes bigger than the available device memory by using a streaming, out-of-core approach. Our algorithm generates RF with the correct statistical behavior and is tested on a variety of modern hardware, such as NVIDIA Tesla, AMD FirePro and Intel Phi. RAFT is faster than the traditional methods on regular meshes and has been successfully applied to two real case scenarios: planetary nebulae and cosmological simulations.
Fluorescence microscopy image noise reduction using a stochastically-connected random field model.
Haider, S A; Cameron, A; Siva, P; Lui, D; Shafiee, M J; Boroomand, A; Haider, N; Wong, A
2016-02-17
Fluorescence microscopy is an essential part of a biologist's toolkit, allowing assaying of many parameters like subcellular localization of proteins, changes in cytoskeletal dynamics, protein-protein interactions, and the concentration of specific cellular ions. A fundamental challenge with using fluorescence microscopy is the presence of noise. This study introduces a novel approach to reducing noise in fluorescence microscopy images. The noise reduction problem is posed as a Maximum A Posteriori estimation problem, and solved using a novel random field model called stochastically-connected random field (SRF), which combines random graph and field theory. Experimental results using synthetic and real fluorescence microscopy data show the proposed approach achieving strong noise reduction performance when compared to several other noise reduction algorithms, using quantitative metrics. The proposed SRF approach was able to achieve strong performance in terms of signal-to-noise ratio in the synthetic results, high signal to noise ratio and contrast to noise ratio in the real fluorescence microscopy data results, and was able to maintain cell structure and subtle details while reducing background and intra-cellular noise.
Validity of the mean-field approximation for diffusion on a random comb
Revathi, S.; Balakrishnan, V.; Lakshmibala, S.; Murthy, K. P. N.
1996-09-01
We consider unbiased diffusion on a random comb structure (an infinitely long backbone with loopless branches of arbitrary length emanating from it). If w=T0 is the mean time (averaged over all random walks) for first passage from an arbitrary origin 0 on the backbone to either of the sites +j or -j on it in a given realization of the structure, the exact diffusion constant for the problem is defined as K=limj-->∞j2c, where c stands for the configuration average over the realizations of the random comb. The diffusion constant in the mean-field approximation is given by KMF=limj-->∞j2/c. We compute T0 exactly for an arbitrary realization of the comb and then show rigorously that, owing to the suppression of the relative fluctuations in T0 in the ``thermodynamic limit'' j-->∞, we have KMF=K whenever the moments of certain random variables Γ(L,α,β) are finite; here the site-dependent random variables L, α, and β are, respectively, the branch length, stay probability at the tip of a branch, and the backbone-to-branch jump probability. Finally, we discuss different situations in which K will not be equal to KMF, although the transport remains diffusive, as opposed to those in which anomalous diffusion occurs.
Directory of Open Access Journals (Sweden)
Keke Shao
Full Text Available Aptamers are short RNA or DNA oligonucleotides which can bind with different targets. Typically, they are selected from a large number of random DNA sequence libraries. The main strategy to obtain aptamers is systematic evolution of ligands by exponential enrichment (SELEX. Low efficiency is one of the limitations for conventional PCR amplification of random DNA sequence library in aptamer selection because of relative low products and high by-products formation efficiency. Here, we developed emulsion PCR for aptamer selection. With this method, the by-products formation decreased tremendously to an undetectable level, while the products formation increased significantly. Our results indicated that by-products in conventional PCR amplification were from primer-product and product-product hybridization. In emulsion PCR, we can completely avoid the product-product hybridization and avoid the most of primer-product hybridization if the conditions were optimized. In addition, it also showed that the molecule ratio of template to compartment was crucial to by-product formation efficiency in emulsion PCR amplification. Furthermore, the concentration of the Taq DNA polymerase in the emulsion PCR mixture had a significant impact on product formation efficiency. So, the results of our study indicated that emulsion PCR could improve the efficiency of SELEX.
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
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...... for peptide sequences that conferred on recombinant cells the ability to bind Zn2+. By serial selection, sequences that exhibited various degrees of binding affinity and specificity toward Zn2+ were enriched. None of the isolated sequences showed similarity to known Zn2+-binding proteins, indicating...
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
Analytical description of field-line random walk in Goldreich-Sridhar turbulence
Shalchi, A.; Kolly, A.
2013-05-01
We describe analytically the random walk of magnetic field lines for two correlation tensors based on the Goldreich-Sridhar model. We show that for this type of tensor, field-line wandering is normal diffusive in contrast to subdiffusive and superdiffusive transport obtained for other turbulence models. Furthermore, we demonstrate that there are two transport regimes. The first one corresponds to quasi-linear theory, whereas the second one is non-linear. We show that for one of the tensors the quasi-linear regime is obtained in the limit of strong turbulence, whereas the non-linear regime is found for weak turbulence. For the other tensor, we obtain a field-line diffusion coefficient which behaves more like diffusion parameters derived previously.
Directory of Open Access Journals (Sweden)
Z. Zhang
2013-05-01
Full Text Available Feature fusion of remote sensing images and LiDAR points cloud data, which have strong complementarity, can effectively play the advantages of multi-class features to provide more reliable information support for the remote sensing applications, such as object classification and recognition. In this paper, we introduce a novel multi-source hierarchical conditional random field (MSHCRF model to fuse features extracted from remote sensing images and LiDAR data for image classification. Firstly, typical features are selected to obtain the interest regions from multi-source data, then MSHCRF model is constructed to exploit up the features, category compatibility of images and the category consistency of multi-source data based on the regions, and the outputs of the model represents the optimal results of the image classification. Competitive results demonstrate the precision and robustness of the proposed method.
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
DEFF Research Database (Denmark)
Filsinger, Frank; Küpper, Jochen; Meijer, Gerard
2009-01-01
Supersonic beams of polar molecules are deflected using inhomogeneous electric fields. The quantum-state selectivity of the deflection is used to spatially separate molecules according to their quantum state. A detailed analysis of the deflection and the obtained quantum-state selection...
Directory of Open Access Journals (Sweden)
Danilo R. Oliveira
2011-05-01
Full Text Available The municipality of Oriximiná, Brazil, has 33 quilombola communities in remote areas, endowed with wide experience in the use of medicinal plants. An ethnobotanical survey was carried out in five of these communities. A free-listing method directed for the survey of species locally indicated against Tuberculosis and lung problems was also applied. Data were analyzed by quantitative techniques: saliency index and major use agreement. Thirty four informants related 254 ethnospecies. Among these, 43 were surveyed for possible antimycobacterial activity. As a result of those informations, ten species obtained from the ethnodirected approach (ETHNO and eighteen species obtained from the random approach (RANDOM were assayed against Mycobacterium tuberculosis by the microdilution method, using resazurin as an indicator of cell viability. The best results for antimycobacterial activity were obtained of some plants selected by the ethnopharmacological approach (50% ETHNO x 16,7% RANDOM. These results can be even more significant if we consider that the therapeutic success obtained among the quilombola practice is complex, being the use of some plants acting as fortifying agents, depurative, vomitory, purgative and bitter remedy, especially to infectious diseases, of great importance to the communities in the curing or recovering of health as a whole.
Kapwata, Thandi; Gebreslasie, Michael T
2016-11-16
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.
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.
Albertsen, A E; Nielsen, J C
2003-12-01
Several observational studies have indicated that selection of pacing mode may be important for the clinical outcome in patients with symptomatic bradycardia, affecting the development of atrial fibrillation (AF), thromboembolism, congestive heart failure, mortality and quality of life. In this paper we present and discuss the most recent data from six randomized trials on mode selection in patients with sick sinus syndrome (SSS). In pacing mode selection, VVI(R) pacing is the least attractive solution, increasing the incidence of AF and-as compared with AAI(R) pacing, also the incidence of heart failure, thromboembolism and death. VVI(R) pacing should not be used as the primary pacing mode in patients with SSS, who haven't chronic AF. AAIR pacing is superior to DDDR pacing, reducing AF and preserving left ventricular function. Single site right ventricular pacing-VVI(R) or DDD(R) mode-causes an abnormal ventricular activation and contraction (called ventricular desynchronization), which results in a reduced left ventricular function. Despite the risk of AV block, we consider AAIR pacing to be the optimal pacing mode for isolated SSS today and an algorithm to select patients for AAIR pacing is suggested. Trials on new pacemaker algorithms minimizing right ventricular pacing as well as trials testing alternative pacing sites and multisite pacing to reduce ventricular desynchronization can be expected within the next years.
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
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.
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.
Paul, Desbordes; Su, Ruan; Romain, Modzelewski; Sébastien, Vauclin; Pierre, Vera; Isabelle, Gardin
2017-09-01
The outcome prediction of patients can greatly help to personalize cancer treatment. A large amount of quantitative features (clinical exams, imaging, …) are potentially useful to assess the patient outcome. The challenge is to choose the most predictive subset of features. In this paper, we propose a new feature selection strategy called GARF (genetic algorithm based on random forest) extracted from positron emission tomography (PET) images and clinical data. The most relevant features, predictive of the therapeutic response or which are prognoses of the patient survival 3 years after the end of treatment, were selected using GARF on a cohort of 65 patients with a local advanced oesophageal cancer eligible for chemo-radiation therapy. The most relevant predictive results were obtained with a subset of 9 features leading to a random forest misclassification rate of 18±4% and an areas under the of receiver operating characteristic (ROC) curves (AUC) of 0.823±0.032. The most relevant prognostic results were obtained with 8 features leading to an error rate of 20±7% and an AUC of 0.750±0.108. Both predictive and prognostic results show better performances using GARF than using 4 other studied methods. Copyright © 2016 Elsevier Ltd. All rights reserved.
Submicron structure random field on granular soil material with retinex algorithm optimization
Liang, Yu; Tao, Chenyuan; Zhou, Bingcheng; Huang, Shuai; Huang, Linchong
2017-06-01
In this paper, a Retinex scale optimized image enhancement algorithm is proposed, which can enhance the micro vision image and eliminate the influence of the uneven illumination. Based on that, a random geometric model of the microstructure of granular materials is established with Monte-Carlo method, the numerical simulation including consolidation process of granular materials is compared with the experimental data. The results have proved that the random field method with Retinex image enhancement algorithm is effective, the image of microstructure of granular materials becomes clear and the contrast ratio is improved, after using Retinex image enhancement algorithm to enhance the CT image. The fidelity of enhanced image is higher than that dealing with other method, which have explained that the algorithm can preserve the microstructure information of the image well. The result of numerical simulation is similar with the one obtained from conventional three axis consolidation test, which proves that the simulation result is reliable.
Submicron structure random field on granular soil material with retinex algorithm optimization
Directory of Open Access Journals (Sweden)
Liang Yu
2017-01-01
Full Text Available In this paper, a Retinex scale optimized image enhancement algorithm is proposed, which can enhance the micro vision image and eliminate the influence of the uneven illumination. Based on that, a random geometric model of the microstructure of granular materials is established with Monte-Carlo method, the numerical simulation including consolidation process of granular materials is compared with the experimental data. The results have proved that the random field method with Retinex image enhancement algorithm is effective, the image of microstructure of granular materials becomes clear and the contrast ratio is improved, after using Retinex image enhancement algorithm to enhance the CT image. The fidelity of enhanced image is higher than that dealing with other method, which have explained that the algorithm can preserve the microstructure information of the image well. The result of numerical simulation is similar with the one obtained from conventional three axis consolidation test, which proves that the simulation result is reliable.
Directory of Open Access Journals (Sweden)
Géraud Thierry
2004-01-01
Full Text Available We present a fast method for road network extraction in satellite images. It can be seen as a transposition of the segmentation scheme "watershed transform region adjacency graph Markov random fields" to the extraction of curvilinear objects. Many road extractors which are composed of two stages can be found in the literature. The first one acts like a filter that can decide from a local analysis, at every image point, if there is a road or not. The second stage aims at obtaining the road network structure. In the method we propose to rely on a "potential" image, that is, unstructured image data that can be derived from any road extractor filter. In such a potential image, the value assigned to a point is a measure of its likelihood to be located in the middle of a road. A filtering step applied on the potential image relies on the area closing operator followed by the watershed transform to obtain a connected line which encloses the road network. Then a graph describing adjacency relationships between watershed lines is built. Defining Markov random fields upon this graph, associated with an energetic model of road networks, leads to the expression of road network extraction as a global energy minimization problem. This method can easily be adapted to other image processing fields, where the recognition of curvilinear structures is involved.
Random-field Ising model: Insight from zero-temperature simulations
Directory of Open Access Journals (Sweden)
P.E. Theodorakis
2014-12-01
Full Text Available We enlighten some critical aspects of the three-dimensional (d=3 random-field Ising model (RFIM from simulations performed at zero temperature. We consider two different, in terms of the field distribution, versions of model, namely a Gaussian RFIM and an equal-weight trimodal RFIM. By implementing a computational approach that maps the ground-state of the system to the maximum-flow optimization problem of a network, we employ the most up-to-date version of the push-relabel algorithm and simulate large ensembles of disorder realizations of both models for a broad range of random-field values and systems sizes V=LxLxL, where L denotes linear lattice size and Lmax=156. Using as finite-size measures the sample-to-sample fluctuations of various quantities of physical and technical origin, and the primitive operations of the push-relabel algorithm, we propose, for both types of distributions, estimates of the critical field hmax and the critical exponent ν of the correlation length, the latter clearly suggesting that both models share the same universality class. Additional simulations of the Gaussian RFIM at the best-known value of the critical field provide the magnetic exponent ratio β/ν with high accuracy and clear out the controversial issue of the critical exponent α of the specific heat. Finally, we discuss the infinite-limit size extrapolation of energy- and order-parameter-based noise to signal ratios related to the self-averaging properties of the model, as well as the critical slowing down aspects of the algorithm.
Espinosa, Pedro J; Bielza, Pablo; Contreras, Josefina; Lacasa, Alfredo
2002-09-01
Response of western flower thrips, Frankliniella occidentalis (Pergande), to selection for resistance to insecticides commonly used to control this pest in Murcia (south-east Spain) was studied under field and laboratory conditions. In the field, plots within sweet pepper crops in commercial and experimental greenhouses were treated under different selection strategies: insecticide rotation versus formetanate reiteration, formetanate reiteration versus acrinathrin reiteration, and formetanate reiteration versus methiocarb reiteration. Thrips populations were sampled monthly and bioassayed against methiocarb, methamidophos, acrinathrin, endosulfan, deltamethrin and formetanate. In the laboratory, F occidentalis strains were selected against each insecticide for several generations. To evaluate cross-resistance, each selected strain was bioassayed with the other insecticides. Frankliniella occidentalis populations showed a rapid development of acrinathrin resistance, reaching high levels in field and laboratory conditions. Formetanate and methiocarb resistance were also observed, although development was slower and at moderate levels. Cross-resistances between acrinathrin/deltamethrin and acrinathrin/formetanate were detected under field and laboratory conditions. Formetanate/methiocarb cross-resistance was suspected in laboratory selections, but not in field assays. Simultaneous moderate resistance levels to the three specific insecticides against thrips (formetanate, methiocarb and acrinathrin) were shown in laboratory selection strains, indicating a general mechanism of resistance, probably metabolic.
Chen, Mingsheng; Yan, Qingguang; Qin, Mingxin
2017-12-01
Image segmentation is a preliminary and fundamental step in computer aided magnetic resonance imaging (MRI) images analysis. But the performance of most current image segmentation methods is easily depreciated by noise in MRI images. A precise and anti-noise segmentation of MRI images is desired in modern medical image diagnosis. This paper presents a segmentation of MRI images which combines fuzzy clustering and Markov random field (MRF). In order to utilize gray level information sufficiently and alleviate noise disturbance, fuzzy clustering is carried out on the original image and the coarse scale image of multi-scale decomposition. The spatial constraints between neighboring pixels are modeled by a defined potential function in the MRF to reduce the effect of noise and increase the integrity of segmented regions. Spatial constraints and the gray level information refined by Fuzzy C-Means (FCM) algorithm are integrated by maximum a posteriori Markov random field (MAP-MRF). In the proposed method, the fuzzy clustering membership obtained from the original image and the coarse scale image is integrated into the single-site clique potential functions by MAP-MRF. The defined potential functions and the distance weight are introduced to model the neighborhood constraint with MRF. The experiments are carried out on noised synthetic images, simulated brain MR images and real MR images. The experimental results show that the proposed method has strong robustness and satisfying performance. Meanwhile the method is compared with FCM, FGFCM and FLICM algorithms visually and statistically in the experiments. In the comparison, the proposed method has achieved the best results. In the statistical comparison, the proposed method has an average similarity index of 36.8%, 33.7%, 2.75% increase against FCM, FGFCM and FLICM. This paper proposes a MRI segmentation method combining fuzzy clustering and Markov random field. The method is tested in the noised image databases and
Traffic Video Image Segmentation Model Based on Bayesian and Spatio-Temporal Markov Random Field
Zhou, Jun; Bao, Xu; Li, Dawei; Yin, Yongwen
2017-10-01
Traffic video image is a kind of dynamic image and its background and foreground is changed at any time, which results in the occlusion. In this case, using the general method is more difficult to get accurate image segmentation. A segmentation algorithm based on Bayesian and Spatio-Temporal Markov Random Field is put forward, which respectively build the energy function model of observation field and label field to motion sequence image with Markov property, then according to Bayesian' rule, use the interaction of label field and observation field, that is the relationship of label field’s prior probability and observation field’s likelihood probability, get the maximum posterior probability of label field’s estimation parameter, use the ICM model to extract the motion object, consequently the process of segmentation is finished. Finally, the segmentation methods of ST - MRF and the Bayesian combined with ST - MRF were analyzed. Experimental results: the segmentation time in Bayesian combined with ST-MRF algorithm is shorter than in ST-MRF, and the computing workload is small, especially in the heavy traffic dynamic scenes the method also can achieve better segmentation effect.
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.
Spatial random field models inspired from statistical physics with applications in the geosciences
Hristopulos, Dionissios T.
2006-06-01
The spatial structure of fluctuations in spatially inhomogeneous processes can be modeled in terms of Gibbs random fields. A local low energy estimator (LLEE) is proposed for the interpolation (prediction) of such processes at points where observations are not available. The LLEE approximates the spatial dependence of the data and the unknown values at the estimation points by low-lying excitations of a suitable energy functional. It is shown that the LLEE is a linear, unbiased, non-exact estimator. In addition, an expression for the uncertainty (standard deviation) of the estimate is derived.
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...... temporal stability. We evaluate the hypothesis that risk preferences are stable over time using a remarkable data set combining administrative information from the Danish registry with longitudinal experimental data we designed to allow better identification of joint selection and attrition effects...... 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...
Markov random field and Gaussian mixture for segmented MRI-based partial volume correction in PET
Bousse, Alexandre; Pedemonte, Stefano; Thomas, Benjamin A.; Erlandsson, Kjell; Ourselin, Sébastien; Arridge, Simon; Hutton, Brian F.
2012-10-01
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.
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...... themselves a generic holistic tool in various segmentation and simulation studies. Finding a basis of homologous points is a fundamental issue in PDMs which effects both alignment and decomposition of the training data, and may be aided by Markov Random Field Restoration (MRF) of the correspondence...... 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...
Korteland, Nelleke M.; Ahmed, Yunus; Koolbergen, David R.; Brouwer, Marjan; de Heer, Frederiek; Kluin, Jolanda; Bruggemans, Eline F.; Klautz, Robert J. M.; Stiggelbout, Anne M.; Bucx, Jeroen J. J.; Roos-Hesselink, Jolien W.; Polak, Peter; Markou, Thanasie; van den Broek, Inge; Ligthart, Rene; Bogers, Ad J. J. C.; Takkenberg, Johanna J. M.
2017-01-01
A Dutch online patient decision aid to support prosthetic heart valve selection was recently developed. A multicenter randomized controlled trial was conducted to assess whether use of the patient decision aid results in optimization of shared decision making in prosthetic heart valve selection. In
Selective outcome reporting and sponsorship in randomized controlled trials in IVF and ICSI.
Braakhekke, M; Scholten, I; Mol, F; Limpens, J; Mol, B W; van der Veen, F
2017-10-01
Are randomized controlled trials (RCTs) on IVF and ICSI subject to selective outcome reporting and is this related to sponsorship? There are inconsistencies, independent from sponsorship, in the reporting of primary outcome measures in the majority of IVF and ICSI trials, indicating selective outcome reporting. RCTs are subject to bias at various levels. Of these biases, selective outcome reporting is particularly relevant to IVF and ICSI trials since there is a wide variety of outcome measures to choose from. An established cause of reporting bias is sponsorship. It is, at present, unknown whether RCTs in IVF/ICSI are subject to selective outcome reporting and whether this is related with sponsorship. We systematically searched RCTs on IVF and ICSI published between January 2009 and March 2016 in MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials and the publisher subset of PubMed. We analysed 415 RCTs. Per included RCT, we extracted data on impact factor of the journal, sample size, power calculation, and trial registry and thereafter data on primary outcome measure, the direction of trial results and sponsorship. Of the 415 identified RCTs, 235 were excluded for our primary analysis, because the sponsorship was not reported. Of the 180 RCTs included in our analysis, 7 trials did not report on any primary outcome measure and 107 of the remaining 173 trials (62%) reported on surrogate primary outcome measures. Of the 114 registered trials, 21 trials (18%) provided primary outcomes in their manuscript that were different from those in the trial registry. This indicates selective outcome reporting. We found no association between selective outcome reporting and sponsorship. We ran additional analyses to include the trials that had not reported sponsorship and found no outcomes that differed from our primary analysis. Since the majority of the trials did not report on sponsorship, there is a risk on sampling bias. IVF and ICSI trials are subject, to
Lamb's problem on random mass density fields with fractal and Hurst effects.
Nishawala, V V; Ostoja-Starzewski, M; Leamy, M J; Porcu, E
2016-12-01
This paper reports on a generalization of Lamb's problem to a linear elastic, infinite half-space with random fields (RFs) of mass density, subject to a normal line load. Both, uncorrelated and correlated (with fractal and Hurst characteristics) RFs without any weak noise restrictions, are proposed. Cellular automata (CA) is used to simulate the wave propagation. CA is a local computational method which, for rectangular discretization of spatial domain, is equivalent to applying the finite difference method to the governing equations of classical elasticity. We first evaluate the response of CA to an uncorrelated mass density field, more commonly known as white-noise, of varying coarseness as compared to CA's node density. We then evaluate the response of CA to multiscale mass density RFs of Cauchy and Dagum type; these fields are unique in that they are able to model and decouple the field's fractal dimension and Hurst parameter. We focus on stochastic imperfection sensitivity; we determine to what extent the fractal or the Hurst parameter is a significant factor in altering the solution to the planar stochastic Lamb's problem by evaluating the coefficient of variation of the response when compared with the coefficient of variation of the RF.
Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model
Navarro, C A; Deng, Youjin
2015-01-01
The study of disordered spin systems through Monte Carlo simulations has proven to be a hard task due to the adverse energy landscape present at the low temperature regime, making it difficult for the simulation to escape from a local minimum. Replica based algorithms such as the Exchange Monte Carlo (also known as parallel tempering) are effective at overcoming this problem, reaching equilibrium on disordered spin systems such as the Spin Glass or Random Field models, by exchanging information between replicas of neighbor temperatures. In this work we present a multi-GPU Exchange Monte Carlo method designed for the simulation of the 3D Random Field Model. The implementation is based on a two-level parallelization scheme that allows the method to scale its performance in the presence of faster and GPUs as well as multiple GPUs. In addition, we modified the original algorithm by adapting the set of temperatures according to the exchange rate observed from short trial runs, leading to an increased exchange rate...
Karimaghaloo, Zahra; Shah, Mohak; Francis, Simon J; Arnold, Douglas L; Collins, D Louis; Arbel, Tal
2012-06-01
Gadolinium-enhancing lesions in brain magnetic resonance imaging of multiple sclerosis (MS) patients are of great interest since they are markers of disease activity. Identification of gadolinium-enhancing lesions is particularly challenging because the vast majority of enhancing voxels are associated with normal structures, particularly blood vessels. Furthermore, these lesions are typically small and in close proximity to vessels. In this paper, we present an automatic, probabilistic framework for segmentation of gadolinium-enhancing lesions in MS using conditional random fields. Our approach, through the integration of different components, encodes different information such as correspondence between the intensities and tissue labels, patterns in the labels, or patterns in the intensities. The proposed algorithm is evaluated on 80 multimodal clinical datasets acquired from relapsing-remitting MS patients in the context of multicenter clinical trials. The experimental results exhibit a sensitivity of 98% with a low false positive lesion count. The performance of the proposed algorithm is also compared to a logistic regression classifier, a support vector machine and a Markov random field approach. The results demonstrate superior performance of the proposed algorithm at successfully detecting all of the gadolinium-enhancing lesions while maintaining a low false positive lesion count.
Extreme of random field over rectangle with application to concrete rupture stresses
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2000-01-01
Probabilities of excursions of random processes and fields into critical domains are of fundamental interestin many civil engineering decision problems. Examples are reliability evaluations of structures subject torandom load processes, the influence of the size of a structural element on the car......Probabilities of excursions of random processes and fields into critical domains are of fundamental interestin many civil engineering decision problems. Examples are reliability evaluations of structures subject torandom load processes, the influence of the size of a structural element...... results for such probabilities. However, dueto the engineering importance of the problem, several approximate assessment methods have been suggestedin the past. The suitability and accuracy of each of these methods depends on the type of process or fieldunder consideration. Often recourse must be taken...... 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....
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
Balaban, Basak; Yakin, Kayhan; Alatas, Cengiz; Oktem, Ozgur; Isiklar, Aycan; Urman, Bulent
2011-05-01
Recent evidence shows that the selection of spermatozoa based on the analysis of morphology under high magnification (×6000) may have a positive impact on embryo development in cases with severe male factor infertility and/or previous implantation failures. The objective of this prospective randomized study was to compare the clinical outcome of 87 intracytoplasmic morphologically selected sperm injection (IMSI) cycles with 81 conventional intracytoplasmic sperm injection (ICSI) cycles in an unselected infertile population. IMSI did not provide a significant improvement in the clinical outcome compared with ICSI although there were trends for higher implantation (28.9% versus 19.5%), clinical pregnancy (54.0% versus 44.4%) and live birth rates (43.7% versus 38.3%) in the IMSI group. However, severe male factor patients benefited from the IMSI procedure as shown by significantly higher implantation rates compared with their counterparts in the ICSI group (29.6% versus 15.2%, P=0.01). These results suggest that IMSI may improve IVF success rates in a selected group of patients with male factor infertility. New technological developments enable the real time examination of motile spermatozoa with an inverted light microscope equipped with high-power differential interference contrast optics, enhanced by digital imaging. High magnification (over ×6000) provides the identification of spermatozoa with a normal nucleus and nuclear content. Intracytoplasmic injection of spermatozoa selected according to fine nuclear morphology under high magnification may improve the clinical outcome in cases with severe male factor infertility. Copyright © 2010 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
Škof, Branko; Rotovnik Kozjek, Nada
2015-09-01
The aim of the study was to compare the dietary habits of recreational runners with those of a random sample of the general population. We also wanted to determine the influence of gender, age and sports performance of recreational runners on their basic diet and compliance with recommendations in sports nutrition. The study population consisted of 1,212 adult Slovenian recreational runners and 774 randomly selected residents of Slovenia between the ages of 18 and 65 years. The data on the dietary habits of our subjects was gathered by means of two questionnaires. The following parameters were evaluated: the type of diet, a food pattern, and the frequency of consumption of individual food groups, the use of dietary supplements, fluid intake, and alcohol consumption. Recreational runners had better compliance with recommendations for healthy nutrition than the general population. This pattern increased with the runner's age and performance level. Compared to male runners, female runners ate more regularly and had a more frequent consumption of food groups associated with a healthy diet (fruit, vegetables, whole grain foods, and low-fat dairy products). The consumption of simple sugars and use of nutritional supplements by well-trained runners was inadequate with values recommended for physically active individuals. Recreational runners are an exemplary population group that actively seeks to adopt a healthier lifestyle.
Matzen, Louise H; Petersen, Lars B; Wenzel, Ann
2016-01-01
To assess radiographic methods and diagnostically sufficient images used before removal of mandibular third molars among randomly selected general dental clinics. Furthermore, to assess factors predisposing for an additional radiographic examination. 2 observers visited 18 randomly selected clinics in Denmark and studied patient files, including radiographs of patients who had their mandibular third molar(s) removed. The radiographic unit and type of receptor were registered. A diagnostically sufficient image was defined as the whole tooth and mandibular canal were displayed in the radiograph (yes/no). Overprojection between the tooth and mandibular canal (yes/no) and patient-reported inferior alveolar nerve sensory disturbances (yes/no) were recorded. Regression analyses tested if overprojection between the third molar and the mandibular canal and an insufficient intraoral image predisposed for additional radiographic examination(s). 1500 mandibular third molars had been removed; 1090 had intraoral, 468 had panoramic and 67 had CBCT examination. 1000 teeth were removed after an intraoral examination alone, 433 after panoramic examination and 67 after CBCT examination. 90 teeth had an additional examination after intraoral. Overprojection between the tooth and mandibular canal was a significant factor (p < 0.001, odds ratio = 3.56) for an additional examination. 63.7% of the intraoral images were sufficient and 36.3% were insufficient, with no significant difference between images performed with phosphor plates and solid-state sensors (p = 0.6). An insufficient image predisposed for an additional examination (p = 0.008, odds ratio = 1.8) but was only performed in 11% of the cases. Most mandibular third molars were removed based on an intraoral examination although 36.3% were insufficient.
Selection of 3013 Containers for Field Surveillance. Fiscal Year 2016 Update
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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.
Turbulence generation by a shock wave interacting with a random density inhomogeneity field
Huete Ruiz de Lira, C.
2010-12-01
When a planar shock wave interacts with a random pattern of pre-shock density non-uniformities, it generates an anisotropic turbulent velocity/vorticity field. This turbulence plays an important role in the early stages of the mixing process in a compressed fluid. This situation emerges naturally in a shock interaction with weakly inhomogeneous deuterium-wicked foam targets in inertial confinement fusion and with density clumps/clouds in astrophysics. We present an exact small-amplitude linear theory describing such an interaction. It is based on the exact theory of time and space evolution of the perturbed quantities behind a corrugated shock front for a single-mode pre-shock non-uniformity. Appropriate mode averaging in two dimensions results in closed analytical expressions for the turbulent kinetic energy, degree of anisotropy of velocity and vorticity fields in the shocked fluid, shock amplification of the density non-uniformity and sonic energy flux radiated downstream. These explicit formulae are further simplified in the important asymptotic limits of weak/strong shocks and highly compressible fluids. A comparison with the related problem of a shock interacting with a pre-shock isotropic vorticity field is also presented.
Silverman, Henry J; Miller, Franklin G
2004-03-01
Ethical concern has been raised with critical care randomized controlled trials in which the standard of care reflects a broad range of clinical practices. Commentators have argued that trials without an unrestricted control group, in which standard practices are implemented at the discretion of the attending physician, lack the ability to redefine the standard of care and might expose subjects to excessive harms due to an inability to stop early. To develop a framework for analyzing control group selection for critical care trials. Ethical analysis. A key ethical variable in trial design is the extent with which the control group adequately reflects standard care practices. Such a control group might incorporate either the "unrestricted" practices of physicians or a protocol that specifies and restricts the parameters of standard practices. Control group selection should be determined with respect to the following ethical objectives of trial design: 1) clinical value, 2) scientific validity, 3) efficiency and feasibility, and 4) protection of human subjects. Because these objectives may conflict, control group selection will involve trade-offs and compromises. Trials using a protocolized rather than an unrestricted standard care control group will likely have enhanced validity. However, if the protocolized control group lacks representativeness to standard care practices, then trials that use such groups will offer less clinical value and could provide less assurance of protecting subjects compared with trials that use unrestricted control groups. For trials evaluating contrasting strategies that do not adequately represent standard practices, use of a third group that is more representative of standard practices will enhance clinical value and increase the ability to stop early if needed to protect subjects. These advantages might come at the expense of efficiency and feasibility. Weighing and balancing the competing ethical objectives of trial design should be
Gushchin, A. A.
1982-12-01
CONTENTSIntroduction § 1. Basic notation and definitions § 2. The Doléans measure and increasing fields § 3. Theorems on predictable projections. Decomposition of weak submartingales § 4. Weakly predictable random fields § 5. Theorems on weakly predictable projections § 6. Decomposition of strong martingales References
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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.
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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.
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Guan, Jianguo; Yan, Gongqin; Wang, Wei; Liu, Jun
2012-03-07
This work describes an easy and flexible approach for the synthesis of 2D nanostructures by external composite field-induced self-assembly. Amorphous iron nanoplatelets with a large aspect ratio were prepared by reducing a concentrated FeSO4 solution with NaBH4 without any templates or surfactants under a magnetic field and a shear field, and characterized by field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD). Based on the morphological dependence of the resultant iron nanostructures on the kinetic parameters such as reactant concentration, reaction temperature, external fields as well as reaction time, etc., a novel conceivable formation mechanism of the iron nanoplatelets was substantiated to be a self-assembly of concentrated iron nuclei induced by the synergistic effect of both a magnetic field and a shear field. Due to the amorphous nature and shape anisotropy, the as-synthesized iron nanoplatelets exhibit quite different magnetic properties with an enhanced coercivity of >220 Oe from isotropic iron nanoparticles. In the oxidation of cyclohexane with hydrogen peroxide as a 'green' oxidant, the as-obtained amorphous iron nanoplatelets show a conversion more than 84% and a complete selectivity for cyclohexanol and cyclohexanone due to the unique structure. Moreover, their catalytic performances are strongly influenced by their morphology, and the iron atoms located on the faces tend to catalyze the formation of cyclohexanol while those on the sides tend to catalyze the formation of cyclohexanone. The external composite field-induced solution synthesis reported here can be readily explored for fabricating other 2D magnetic nanoplatelets, and the resulting iron nanoplatelets are promising for a number of applications such as high efficient selective catalysis, energy, environment fields and so forth.
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.
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.
Sign language recognition with the Kinect sensor based on conditional random fields.
Yang, Hee-Deok
2014-12-24
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%.
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.
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%.
Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population Genetics
François, Olivier; Ancelet, Sophie; Guillot, Gilles
2006-01-01
We introduce a new Bayesian clustering algorithm for studying population structure using individually geo-referenced multilocus data sets. The algorithm is based on the concept of hidden Markov random field, which models the spatial dependencies at the cluster membership level. We argue that (i) a Markov chain Monte Carlo procedure can implement the algorithm efficiently, (ii) it can detect significant geographical discontinuities in allele frequencies and regulate the number of clusters, (iii) it can check whether the clusters obtained without the use of spatial priors are robust to the hypothesis of discontinuous geographical variation in allele frequencies, and (iv) it can reduce the number of loci required to obtain accurate assignments. We illustrate and discuss the implementation issues with the Scandinavian brown bear and the human CEPH diversity panel data set. PMID:16888334
Broadcast News Story Segmentation Using Conditional Random Fields and Multimodal Features
Wang, Xiaoxuan; Xie, Lei; Lu, Mimi; Ma, Bin; Chng, Eng Siong; Li, Haizhou
In this paper, we propose integration of multimodal features using conditional random fields (CRFs) for the segmentation of broadcast news stories. We study story boundary cues from lexical, audio and video modalities, where lexical features consist of lexical similarity, chain strength and overall cohesiveness; acoustic features involve pause duration, pitch, speaker change and audio event type; and visual features contain shot boundaries, anchor faces and news title captions. These features are extracted in a sequence of boundary candidate positions in the broadcast news. A linear-chain CRF is used to detect each candidate as boundary/non-boundary tags based on the multimodal features. Important interlabel relations and contextual feature information are effectively captured by the sequential learning framework of CRFs. Story segmentation experiments show that the CRF approach outperforms other popular classifiers, including decision trees (DTs), Bayesian networks (BNs), naive Bayesian classifiers (NBs), multilayer perception (MLP), support vector machines (SVMs) and maximum entropy (ME) classifiers.
Superresolution with compound Markov random fields via the variational EM algorithm.
Kanemura, Atsunori; Maeda, Shin-ichi; Ishii, Shin
2009-09-01
This study deals with a reconstruction-type superresolution problem and the accompanying image registration problem simultaneously. We propose a Bayesian approach in which the prior is modeled as a compound Gaussian Markov random field (MRF) and marginalization is performed over unknown variables to avoid overfitting. Our algorithm not only avoids overfitting, but also preserves discontinuity in the estimated image, unlike existing single-layer Gaussian MRF models for Bayesian superresolution. Maximum-marginal-likelihood estimation of the registration parameters is carried out using a variational EM algorithm where hidden variables are marginalized out, and the posterior distribution is variationally approximated by a factorized trial distribution. High-resolution image estimates are obtained through the process of posterior computation in the EM algorithm. Experiments show that our Bayesian approach with the two-layer compound model exhibits better performance both in quantitative measures and visual quality than the single-layer model.
Hidden State Conditional Random Field for Abnormal Activity Recognition in Smart Homes
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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.
Nakagami Markov random field as texture model for ultrasound RF envelope image.
Bouhlel, N; Sevestre-Ghalila, S
2009-06-01
The aim of this paper is to propose a new Markov random field (MRF) model for the backscattered ultrasonic echo in order to get information about backscatter characteristics, such as the scatterer density, amplitude and spacing. The model combines the Nakagami distribution that describes the envelope of backscattered echo with spatial interaction using MRF. In this paper, the parameters of the model and the estimation parameter method are introduced. Computer simulation using ultrasound radio-frequency (RF) simulator and experiments on choroidal malignant melanoma have been undertaken to test the validity of the model. The relationship between the parameters of MRF model and the backscatter characteristics has been established. Furthermore, the ability of the model to distinguish between normal and abnormal tissue has been proved. All the results can show the success of the model.
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.
Incorporating conditional random fields and active learning to improve sentiment identification.
Zhang, Kunpeng; Xie, Yusheng; Yang, Yi; Sun, Aaron; Liu, Hengchang; Choudhary, Alok
2014-10-01
Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
Laifa, Oumeima; Le Guillou-Buffello, Delphine; Racoceanu, Daniel
2017-11-01
The fundamental role of vascular supply in tumor growth makes the evaluation of the angiogenesis crucial in assessing effect of anti-angiogenic therapies. Since many years, such therapies are designed to inhibit the vascular endothelial growth factor (VEGF). To contribute to the assessment of anti-angiogenic agent (Pazopanib) effect on vascular and cellular structures, we acquired data from tumors extracted from a murine tumor model using Multi- Fluorescence Scanning. In this paper, we implemented an unsupervised algorithm combining the Watershed segmentation and Markov Random Field model (MRF). This algorithm allowed us to quantify the proportion of apoptotic endothelial cells and to generate maps according to cell density. Stronger association between apoptosis and endothelial cells was revealed in the tumors receiving anti-angiogenic therapy (n = 4) as compared to those receiving placebo (n = 4). A high percentage of apoptotic cells in the tumor area are endothelial. Lower density cells were detected in tumor slices presenting higher apoptotic endothelial areas.
A novel approach to assess the treatment response using Gaussian random field in PET
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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
Adaptation of the projection-slice theorem for stock valuation estimation using random Markov fields
Riasati, Vahid R.
2009-04-01
The Projection-Slice Synthetic Discriminant function filter is utilized with Random Markov Fields, RMF to estimate trends that may be used as prediction for stock valuation through the representation of the market behavior as a hidden Markov Model, HMM. In this work, we utilize a set of progressive and contiguous time segments of a given stock, and treat the set as a two dimensional object that has been represented by its one-d projections. The abstract two-D object is thus an incarnation of N-temporal projections. The HMM is then utilized to generate N+1 projections that maximizes the two-dimensional correlation peak between the data and the HMM-generated stochastic processes. This application of the PSDF provides a method of stock valuation prediction via the market stochastic behavior utilized in the filter.
Roy, Pallab Kanti; Bhuiyan, Alauddin; Janke, Andrew; Desmond, Patricia M; Wong, Tien Yin; Abhayaratna, Walter P; Storey, Elsdon; Ramamohanarao, Kotagiri
2015-10-01
White matter lesions (WMLs) are small groups of dead cells that clump together in the white matter of brain. In this paper, we propose a reliable method to automatically segment WMLs. Our method uses a novel filter to enhance the intensity of WMLs. Then a feature set containing enhanced intensity, anatomical and spatial information is used to train a random forest classifier for the initial segmentation of WMLs. Following that a reliable and robust edge potential function based Markov Random Field (MRF) is proposed to obtain the final segmentation by removing false positive WMLs. Quantitative evaluation of the proposed method is performed on 24 subjects of ENVISion study. The segmentation results are validated against the manual segmentation, performed under the supervision of an expert neuroradiologist. The results show a dice similarity index of 0.76 for severe lesion load, 0.73 for moderate lesion load and 0.61 for mild lesion load. In addition to that we have compared our method with three state of the art methods on 20 subjects of Medical Image Computing and Computer Aided Intervention Society's (MICCAI's) MS lesion challenge dataset, where our method shows better segmentation accuracy compare to the state of the art methods. These results indicate that the proposed method can assist the neuroradiologists in assessing the WMLs in clinical practice. Copyright © 2015 Elsevier Ltd. All rights reserved.
Distribution of the Height of Local Maxima of Gaussian Random Fields*
Cheng, Dan; Schwartzman, Armin
2015-01-01
Let {f(t) : t ∈ T} be a smooth Gaussian random field over a parameter space T, where T may be a subset of Euclidean space or, more generally, a Riemannian manifold. We provide a general formula for the distribution of the height of a local maximum P{f(t0)>u∣t0 is a local maximum of f(t)} when f is non-stationary. Moreover, we establish asymptotic approximations for the overshoot distribution of a local maximum P{f(t0)>u+v∣t0 is a local maximum of f(t) and f(t0) > v} as v → ∞. Assuming further that f is isotropic, we apply techniques from random matrix theory related to the Gaussian orthogonal ensemble to compute such conditional probabilities explicitly when T is Euclidean or a sphere of arbitrary dimension. Such calculations are motivated by the statistical problem of detecting peaks in the presence of smooth Gaussian noise. PMID:26478714
The adverse effect of selective cyclooxygenase-2 inhibitor on random skin flap survival in rats.
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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.
Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces
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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.
Boulware, David R
2006-01-01
Jellyfish stings are a common occurrence among ocean goers worldwide with an estimated 150 million envenomations annually. Fatalities and hospitalizations occur annually, particularly in the Indo-Pacific regions. A new topical jellyfish sting inhibitor based on the mucous coating of the clown fish prevents 85% of jellyfish stings in laboratory settings. The field effectiveness is unknown. The objective is to evaluate the field efficacy of the jellyfish sting inhibitor, Safe Sea. A double-blind, randomized, placebo-controlled trial occurred at the Dry Tortugas National Park, FL, USA and Sapodilla Cayes, Belize. Participants were healthy volunteers planning to snorkel for 30 to 45 minutes. Ten minutes prior to swimming, each participant was directly observed applying a blinded sample of Safe Sea (Nidaria Technology Ltd, Jordan Valley, Israel) to one side of their body and a blinded sample of Coppertone (Schering-Plough, Kenilworth, NJ, USA) to the contralateral side as placebo control. Masked 26 g samples of both Safe Sea SPF15 and Coppertone SPF15 were provided in identical containers to achieve 2 mg/cm(2) coverage. Sides were randomly chosen by participants. The incidence of jellyfish stings was the main outcome measure. This was assessed by participant interview and examination as subjects exited the water. A total of 82 observed water exposures occurred. Thirteen jellyfish stings occurred during the study period for a 16% incidence. Eleven jellyfish stings occurred with placebo, two with the sting inhibitor, resulting in a relative risk reduction of 82% (95% confidence interval: 21%-96%; p= 0.02). No seabather's eruption or side effects occurred. Safe Sea is a topical barrier cream effective at preventing >80% jellyfish stings under real-world conditions.
Bayesian Markov Random Field analysis for protein function prediction based on network data.
Kourmpetis, Yiannis A I; van Dijk, Aalt D J; Bink, Marco C A M; van Ham, Roeland C H J; ter Braak, Cajo J F
2010-02-24
Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S. cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.
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…
Lundblad, Eirik W.; Xiao, Gaoping; Ko, Jae-hyeong; Altman, Sidney
2008-01-01
A method of inhibiting the expression of particular genes by using external guide sequences (EGSs) has been improved in its rapidity and specificity. Random EGSs that have 14-nt random sequences are used in the selection procedure for an EGS that attacks the mRNA for a gene in a particular location. A mixture of the random EGSs, the particular target RNA, and RNase P is used in the diagnostic procedure, which, after completion, is analyzed in a gel with suitable control lanes. Within a few ho...
The biocytin wide-field bipolar cell in the rabbit retina selectively contacts blue cones
MacNeil, Margaret A.; Gaul, Paulette A.
2010-01-01
The biocytin wide-field bipolar cell in rabbit retina is a sparsely populated ON cone bipolar cell with a broad dendritic arbor that does not contact all cones in its dendritic field. The purpose of our study was to identify the cone types that this cell contacts. We identified the bipolar cells by selective uptake of biocytin, labeled the cones with peanut agglutinin and then used antibodies against blue cone opsin and red-green cone opsin to identify the individual cone types. The biocytin-labeled cells selectively contacted cones whose outer segments stained for blue cone opsin and avoided cones that did not. We conclude that the biocytin wide-field bipolar cell is an ON blue cone bipolar cell in the rabbit retina and is homologous to the blue cone bipolar cells that have been previously described in primate, mouse, and ground squirrel retinas. PMID:17990268
Biocytin wide-field bipolar cells in rabbit retina selectively contact blue cones.
MacNeil, Margaret A; Gaul, Paulette A
2008-01-01
The biocytin wide-field bipolar cell in rabbit retina has a broad axonal arbor in layer 5 of the inner plexiform layer and a wide dendritic arbor that does not contact all cones in its dendritic field. The purpose of our study was to identify the types of cones that this cell contacts. We identified the bipolar cells by selective uptake of biocytin, labeled the cones with peanut agglutinin, and then used antibodies against blue cone opsin and red-green cone opsin to identify the individual cone types. The biocytin-labeled cells selectively contacted cones whose outer segments stained for blue cone opsin and avoided cones that did not. We conclude that the biocytin wide-field bipolar cell is an ON blue cone bipolar cell in the rabbit retina and is homologous to the blue cone bipolar cells that have been previously described in primate, mouse, and ground squirrel retinas. Copyright 2007 Wiley-Liss, Inc.
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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)
2014-09-15
Purpose: MR-Linac devices under development worldwide will require standard calibration, commissioning, and quality assurance. Solid state radiation detectors are often used for dose profiles and percent depth dose measurements. The dose response of selected solid state detectors is therefore evaluated in varying transverse and longitudinal magnetic fields for this purpose. Methods: The Monte Carlo code PENELOPE was used to model irradiation of a PTW 60003 diamond detector and IBA PFD diode detector in the presence of a magnetic field. The field itself was varied in strength, and oriented both transversely and longitudinally with respect to the incident photon beam. The long axis of the detectors was oriented either parallel or perpendicular to the photon beam. The dose to the active volume of each detector in air was scored, and its ratio to dose with zero magnetic field strength was determined as the “dose response” in magnetic field. Measurements at low fields for both detectors in transverse magnetic fields were taken to evaluate the accuracy of the simulations. Additional simulations were performed in a water phantom to obtain few representative points for beam profile and percent depth dose measurements. Results: Simulations show significant dose response as a function of magnetic field in transverse field geometries. This response can be near 20% at 1.5 T, and it is highly dependent on the detectors’ relative orientation to the magnetic field, the energy of the photon beam, and detector composition. Measurements at low transverse magnetic fields verify the simulations for both detectors in their relative orientations to radiation beam. Longitudinal magnetic fields, in contrast, show little dose response, rising slowly with magnetic field, and reaching 0.5%–1% at 1.5 T regardless of detector orientation. Water tank and in air simulation results were the same within simulation uncertainty where lateral electronic equilibrium is present and expectedly
Tydén, Eva; Skarin, Moa; Höglund, Johan
2014-12-01
The most widespread helminth parasites of grazing cattle in northern Europe are the gastrointestinal nematodes Ostertagia ostertagi and Cooperia oncophora. Heavy reliance on the use of macrocyclic lactone (ML) in cattle has led to world-wide emergence of resistance to this drug class in C. oncophora. There is evidence that members of the ATP-binding cassette (ABC) transporter family, such as P-glycoproteins (P-gp) and multidrug-resistant proteins (MRP), play a role in resistance to ML. In this study gene expression of Con-pgp9, Con-pgp11, Con-pgp12, Con-pgp16 and Con-mrp1 was examined in two isolates of C. oncophora sharing the same genetic background but exposed to ML differently. For isolate one (Laboratory-selected), adult worms were recovered before and after treatment with ML in vivo. For isolate two (Field-selected), adult worms were collected from tracer animals that had never received anthelmintics themselves. One group grazed together with untreated animals and one group grazed with animals that received suppressive prophylactic treatment with ML at monthly intervals for up to two consecutive grazing seasons. Real-time PCR data demonstrated differences in gene expression after ML selection, with the highest constitutive expression levels for Con-pgp16 and Con-mrp1. Remarkably, the same pattern of increasing expression levels of the ABC transport genes was observed in both Laboratory- and Field-selected isolates, despite the Field-selected isolate not being directly exposed to ML. The higher expression levels of ABC transporters observed in the Field-selected isolate was thus not a response to direct exposure to ML, but rather appeared to reflect a genetic characteristic inherited from worms in the previous generation which had survived exposure to ML in the co-grazing treated animals. Copyright © 2015 Elsevier B.V. All rights reserved.
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.
IMPLEMENTATION OF THE MARKOV RANDOM FIELD FOR URBAN LAND COVER CLASSIFICATION OF UAV VHIR DATA
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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.
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Ibrahim Ben Daya
Full Text Available 3-D ultrasound imaging offers unique opportunities in the field of non destructive testing that cannot be easily found in A-mode and B-mode images. To acquire a 3-D ultrasound image without a mechanically moving transducer, a 2-D array can be used. The row column technique is preferred over a fully addressed 2-D array as it requires a significantly lower number of interconnections. Recent advances in 3-D row-column ultrasound imaging systems were largely focused on sensor design. However, these imaging systems face three intrinsic challenges that cannot be addressed by improving sensor design alone: speckle noise, sparsity of data in the imaged volume, and the spatially dependent point spread function of the imaging system. In this paper, we propose a compensated row-column ultrasound image reconstruction system using Fisher-Tippett multilayered conditional random field model. Tests carried out on both simulated and real row-column ultrasound images show the effectiveness of our proposed system as opposed to other published systems. Visual assessment of the results show our proposed system's potential at preserving detail 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.
Multi-fidelity Gaussian process regression for prediction of random fields
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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.
A Poisson random field model of pathogen transport in surface water
Yeghiazarian, L.; Samorodnitsky, G.; Montemagno, C. D.
2009-11-01
To address the uncertainty associated with microbial transport and surface water contamination events, we developed a new comprehensive stochastic framework that combines processes on the microscopic (single microorganism) and macroscopic (ensembles of microorganisms) scales. The spatial and temporal population behavior is modeled as a nonhomogeneous Poisson random field with Markovian field dynamics. The model parameters are based on the actual physical and biological characteristics of the Cryptosporidium parvum transport process and can be extended to cover a variety of other pathogens. Since soil particles have been shown to be a major vehicle in microbial transport, a U.S. Department of Agriculture approved erosion model (Water Erosion Prediction Project) is incorporated into the model. Risk assessment is an integral part of the stochastic model and is conducted using a set of simple calculations. Poisson intensity functions and correlations are computed. The results consistently indicate that surface water contamination events are transient, with traveling high peaks of microorganism concentrations. Correlations between microorganism populations at different points in time and space reach relatively significant levels even at large distances from one another. This information is aimed to assist water resources management teams in the decision-making process to identify the likely timing and locations of high-risk areas and thus to avoid collection of contaminated water.
Ma, Li; Fan, Suohai
2017-03-14
The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.
Noise-induced hearing loss in randomly selected New York dairy farmers.
May, J J; Marvel, M; Regan, M; Marvel, L H; Pratt, D S
1990-01-01
To understand better the effects of noise levels associated with dairy farming, we randomly selected 49 full-time dairy farmers from an established cohort. Medical and occupational histories were taken and standard audiometric testing was done. Forty-six males (94%) and three females (6%) with a mean age of 43.5 (+/- 13) years and an average of 29.4 (+/- 14) years in farming were tested. Pure Tone Average thresholds (PTA4) at 0.5, 1.0, 2.0, and 3.0 kHz plus High Frequency Average thresholds (HFA3) at 3.0, 4.0, and 6.0 kHz were calculated. Subjects with a loss of greater than or equal to 20 db in either ear were considered abnormal. Eighteen subjects (37%) had abnormal PTA4S and 32 (65%) abnormal HFA3S. The left ear was more severely affected in both groups (p less than or equal to .05, t-test). Significant associations were found between hearing loss and years worked (odds ratio 4.1, r = .53) and age (odds ratio 4.1, r = .59). No association could be found between hearing loss and measles; mumps; previous ear infections; or use of power tools, guns, motorcycles, snowmobiles, or stereo headphones. Our data suggest that among farmers, substantial hearing loss occurs especially in the high-frequency ranges. Presbycusis is an important confounding variable.
Modeling Slotted Aloha as a Stochastic Game with Random Discrete Power Selection Algorithms
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Rachid El-Azouzi
2009-01-01
Full Text Available We consider the uplink case of a cellular system where bufferless mobiles transmit over a common channel to a base station, using the slotted aloha medium access protocol. We study the performance of this system under several power differentiation schemes. Indeed, we consider a random set of selectable transmission powers and further study the impact of priorities given either to new arrival packets or to the backlogged ones. Later, we address a general capture model where a mobile transmits successfully a packet if its instantaneous SINR (signal to interferences plus noise ratio is lager than some fixed threshold. Under this capture model, we analyze both the cooperative team in which a common goal is jointly optimized as well as the noncooperative game problem where mobiles reach to optimize their own objectives. Furthermore, we derive the throughput and the expected delay and use them as the objectives to optimize and provide a stability analysis as alternative study. Exhaustive performance evaluations were carried out, we show that schemes with power differentiation improve significantly the individual as well as global performances, and could eliminate in some cases the bi-stable nature of slotted aloha.
Nanopore extended field-effect transistor for selective single-molecule biosensing.
Ren, Ren; Zhang, Yanjun; Nadappuram, Binoy Paulose; Akpinar, Bernice; Klenerman, David; Ivanov, Aleksandar P; Edel, Joshua B; Korchev, Yuri
2017-09-19
There has been a significant drive to deliver nanotechnological solutions to biosensing, yet there remains an unmet need in the development of biosensors that are affordable, integrated, fast, capable of multiplexed detection, and offer high selectivity for trace analyte detection in biological fluids. Herein, some of these challenges are addressed by designing a new class of nanoscale sensors dubbed nanopore extended field-effect transistor (nexFET) that combine the advantages of nanopore single-molecule sensing, field-effect transistors, and recognition chemistry. We report on a polypyrrole functionalized nexFET, with controllable gate voltage that can be used to switch on/off, and slow down single-molecule DNA transport through a nanopore. This strategy enables higher molecular throughput, enhanced signal-to-noise, and even heightened selectivity via functionalization with an embedded receptor. This is shown for selective sensing of an anti-insulin antibody in the presence of its IgG isotype.Efficient detection of single molecules is vital to many biosensing technologies, which require analytical platforms with high selectivity and sensitivity. Ren et al. combine a nanopore sensor and a field-effect transistor, whereby gate voltage mediates DNA and protein transport through the nanopore.
Random-field Potts model for the polar domains of lead magnesium niobate and lead scandium tantalate
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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.
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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).
Marais, B.; Obihara, C; Gie, R.; Schaaf, H; Hesseling, A.; Lombard, C.; Enarson, D; Bateman, E; Beyers, N
2005-01-01
Background: Diagnosis of childhood tuberculosis is problematic and symptom based diagnostic approaches are often promoted in high burden settings. This study aimed (i) to document the prevalence of symptoms associated with tuberculosis among randomly selected children living in a high burden community, and (ii) to compare the prevalence of these symptoms in children without tuberculosis to those in children with newly diagnosed tuberculosis.
Role of the electric field in selective ion filtration in nanostructures.
Park, Yong; Kim, Sueon; Jang, In Hyuk; Nam, Young Suk; Hong, Hiki; Choi, Dukhyun; Lee, Won Gu
2016-02-21
Nafion has received great attention as a proton conductor that can block negative ions. Here, we report the effect of a Nafion coating on an anodic aluminium oxide (AAO) nanoporous membrane on its function of ion rejection and filtering depending on the electric field. In our experiments, Nafion, once coated, was used to repel the negative ions (anions) from the coated surface, and then selectively allowed positive ions (cations) to pass through the nanopores in the presence of an electric field. To demonstrate the proof-of-concept validation, we coated Nafion solution onto the surface of AAO membranes with 20 nm nanopores average diameter at different solution concentration levels. Vacuum filtration methods for Nafion coating were vertically applied to the plane of an AAO membrane. An electric field was then applied to the upper surface of the Nafion-coated AAO membrane to investigate if ion rejection and filtering was affected by the presence of the electric field. Both anions and cations could pass through the AAO nanopores without an electric field applied. However, only cations could well pass through the AAO nanopores under an electric field, thus effectively blocking anions from passing through the nanopores. This result shows that ion filtration of electrons has been selectively performed while the system also works as a vital catalyst in reactivating Nafion via electrolysis. A saturated viscosity ratio of Nafion solution for the coating was also determined. We believe that this approach is potentially beneficial for better understanding the fundamentals of selective ion filtration in nanostructures and for promoting the use of nanostructures in potential applications such as ion-based water purification and desalination system at the nanoscale in a massively electrically integrated format.
ANALYSIS AND VALIDATION OF GRID DEM GENERATION BASED ON GAUSSIAN MARKOV RANDOM FIELD
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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.
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.
Transverse eV ion heating by random electric field fluctuations in the plasmasphere
Artemyev, A. V.; Mourenas, D.; Agapitov, O. V.; Blum, L.
2017-02-01
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˜0.3 eV could potentially explain the observations.
Mahdian, M.; Motagh, M.; Akbari, V.
2013-09-01
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.
Heinemann, Colleen
Research in material science is increasingly reliant on image-based data from experiments, demanding construction of new analysis tools that help scientists discover information from digital images. Because there is such a wide variety of materials and image modalities, detecting different compounds from imaged materials continues to be a challenging task. A vast collection of algorithms for filtering, image segmentation, and texture description have facilitated and improved accuracy for sample measurements (see Chapter 1 Introduction and Literature Review). Despite this, the community still lacks scalable, general purpose, easily configurable image analysis frameworks that allow pattern detection on different imaging modalities across multiple scales. The need for such a framework was the motivation behind the development of a distributed-memory parallel Markov Random Field based framework. Markov Random Field (MRF) algorithms provide the ability to explore contextual information about a given dataset. Given the complexity of such algorithms, however, they are limited by performance when running serial. Thus, running in some sort of parallel fashion is necessary. The effects are twofold. Not only does running the MRF algorithm in parallel provide the ability to run current datasets faster and more efficiently, it also provides the ability for datasets to continue to grow in size and still be able to be run with such frameworks. The variation of the Markov Random Field algorithm utilized in this study first oversegments the given input image and constructs a graph model based on photometric and geometric distances. Next, the resulting graph model is refactored specifically into the MRF model to target image segmentation. Finally, a distributed approach is used for the optimization process to obtain the best labeling for the graph, which is essentially the goal of using a MRF algorithm. Given the concept of using a distributed memory parallel framework, specifically
The biocytin wide-field bipolar cell in the rabbit retina selectively contacts blue cones
MacNeil, Margaret A.; Gaul, Paulette A.
2008-01-01
The biocytin wide-field bipolar cell in rabbit retina is a sparsely populated ON cone bipolar cell with a broad dendritic arbor that does not contact all cones in its dendritic field. The purpose of our study was to identify the cone types that this cell contacts. We identified the bipolar cells by selective uptake of biocytin, labeled the cones with peanut agglutinin and then used antibodies against blue cone opsin and red-green cone opsin to identify the individual cone types. The biocytin-...
Lundblad, Eirik W; Xiao, Gaoping; Ko, Jae-Hyeong; Altman, Sidney
2008-02-19
A method of inhibiting the expression of particular genes by using external guide sequences (EGSs) has been improved in its rapidity and specificity. Random EGSs that have 14-nt random sequences are used in the selection procedure for an EGS that attacks the mRNA for a gene in a particular location. A mixture of the random EGSs, the particular target RNA, and RNase P is used in the diagnostic procedure, which, after completion, is analyzed in a gel with suitable control lanes. Within a few hours, the procedure is complete. The action of EGSs designed by an older method is compared with EGSs designed by the random EGS method on mRNAs from two bacterial pathogens.
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
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
The spatial clustering of X-ray selected AGN in the XMM-COSMOS field
Gilli, R.; Zamorani, G.; Miyaji, T.; Silverman, J.; Brusa, M.; Mainieri, V.; Cappelluti, N.; Daddi, E.; Porciani, C.; Pozzetti, L.; Civano, F.; Comastri, A.; Finoguenov, A.; Fiore, F.; Salvato, M.; Vignali, C.; Hasinger, G.; Lilly, S.; Impey, C.; Trump, J.; Capak, P.; McCracken, H.; Scoville, N.; Taniguchi, Y.; Carollo, C. M.; Contini, T.; Kneib, J. -P.; Le Fevre, O.; Renzini, A.; Scodeggio, M.; Bardelli, S.; Bolzonella, M.; Bongiorno, A.; Caputi, K.; Cimatti, A.; Coppa, G.; Cucciati, O.; de la Torre, S.; de Ravel, L.; Franzetti, P.; Garilli, B.; Iovino, A.; Kampczyk, P.; Knobel, C.; Kovac, K.; Lamareille, F.; Le Borgne, J. -F.; Le Brun, V.; Maier, C.; Mignoli, M.; Pello, R.; Peng, Y.; Montero, E. Perez; Ricciardelli, E.; Tanaka, M.; Tasca, L.; Tresse, L.; Vergani, D.; Zucca, E.; Abbas, U.; Bottini, D.; Cappi, A.; Cassata, P.; Fumana, M.; Guzzo, L.; Leauthaud, A.; Maccagni, D.; Marinoni, C.; Memeo, P.; Meneux, B.; Oesch, P.; Scaramella, R.; Walcher, J.
We study the spatial clustering of 538 X-ray selected AGN in the 2 deg(2) XMM-COSMOS field that are spectroscopically identified with I(AB) <23 and span the redshift range z = 0.2-3.0. The median redshift and X-ray luminosity of the sample are z = 0.98 and L(0.5-10) = 6.3 x 10(43) erg s(-1),
Mode selection of modal expansion method estimating vibration field of washing machine
Jung, B. K.; Jeong, W. B.
2015-03-01
This paper is about a study estimating the vibration and radiated noise of a washing machine by using a mode selection-applied modal expansion method (MEM). MEM is a technique that identifies the vibration field from a portion of eigenvectors (or mode shapes) of a structure, and thus, the selection of the eigenvectors has a big impact on the vibration results identified. However, there have been few studies about selecting the eigenvectors with respect to the structural vibration and radiated noise estimation. Accordingly, this paper proposes the use of a new mode selection method to identify the vibration based on the MEM and then calculate radiated noise of a washing machine. The results gained from the experiment were also compared. The vibration and noise results of numerical analysis using the proposed selection method are in line with the measured results. The selection method proposed in this paper corresponds well with the MEM and this process seems to be applicable to the estimation of various structure vibrations and radiated noise.
Segmentation of cone-beam CT using a hidden Markov random field with informative priors
Moores, M.; Hargrave, C.; Harden, F.; Mengersen, K.
2014-03-01
Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.
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Min Chen
2011-04-01
Full Text Available Genome-wide association studies (GWAS examine a large number of markers across the genome to identify associations between genetic variants and disease. Most published studies examine only single markers, which may be less informative than considering multiple markers and multiple genes jointly because genes may interact with each other to affect disease risk. Much knowledge has been accumulated in the literature on biological pathways and interactions. It is conceivable that appropriate incorporation of such prior knowledge may improve the likelihood of making genuine discoveries. Although a number of methods have been developed recently to prioritize genes using prior biological knowledge, such as pathways, most methods treat genes in a specific pathway as an exchangeable set without considering the topological structure of a pathway. However, how genes are related with each other in a pathway may be very informative to identify association signals. To make use of the connectivity information among genes in a pathway in GWAS analysis, we propose a Markov Random Field (MRF model to incorporate pathway topology for association analysis. We show that the conditional distribution of our MRF model takes on a simple logistic regression form, and we propose an iterated conditional modes algorithm as well as a decision theoretic approach for statistical inference of each gene's association with disease. Simulation studies show that our proposed framework is more effective to identify genes associated with disease than a single gene-based method. We also illustrate the usefulness of our approach through its applications to a real data example.
Language Recognition Using Latent Dynamic Conditional Random Field Model with Phonological Features
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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.
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M. Bassier
2017-11-01
Full Text Available 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.
Scene Segmentation with Low-Dimensional Semantic Representations and Conditional Random Fields
Yang, Wen; Triggs, Bill; Dai, Dengxin; Xia, Gui-Song
2010-12-01
This paper presents a fast, precise, and highly scalable semantic segmentation algorithm that incorporates several kinds of local appearance features, example-based spatial layout priors, and neighborhood-level and global contextual information. The method works at the level of image patches. In the first stage, codebook-based local appearance features are regularized and reduced in dimension using latent topic models, combined with spatial pyramid matching based spatial layout features, and fed into logistic regression classifiers to produce an initial patch level labeling. In the second stage, these labels are combined with patch-neighborhood and global aggregate features using either a second layer of Logistic Regression or a Conditional Random Field. Finally, the patch-level results are refined to pixel level using MRF or over-segmentation based methods. The CRF is trained using a fast Maximum Margin approach. Comparative experiments on four multi-class segmentation datasets show that each of the above elements improves the results, leading to a scalable algorithm that is both faster and more accurate than existing patch-level approaches.
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.
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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.
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.
Financial versus health motivation to quit smoking: a randomized field study.
Sindelar, Jody L; O'Malley, Stephanie S
2014-02-01
Smoking is the most preventable cause of death, thus justifying efforts to effectively motivate quitting. We compared the effectiveness of financial versus health messages to motivate smoking cessation. Low-income individuals disproportionately smoke and, given their greater income constraints, we hypothesized that making financial costs of smoking more salient would encourage more smokers to try quitting. Further, we predicted that financial messages would be stronger in financial settings where pecuniary constraints are most salient. We conducted a field study in low-income areas of New Haven, Connecticut using brochures with separate health vs. financial messages to motivate smoking cessation. Displays were rotated among community settings-check-cashing, health clinics, and grocery stores. We randomized brochure displays with gain-framed cessation messages across locations. Our predictions were confirmed. Financial messages attracted significantly more attention than health messages, especially in financial settings. These findings suggest that greater emphasis on the financial gains to quitting and use of financial settings to provide cessation messages may be more effective in motivating quitting. Importantly, use of financial settings could open new, non-medical venues for encouraging cessation. Encouraging quitting could improve health, enhance spending power of low-income smokers, and reduce health disparities in both health and purchasing power. © 2013.
Detection of microcalcification with top-hat transform and the Gibbs random fields.
Bharadwaj, Akshay S; Celenk, Mehmet
2015-01-01
Breast cancer is one of the most common causes of death in women aged 40 and above. Early detection of breast cancer has been one of the prime topics of research in biomedical engineering area. Micro-calcifications (MCs) are the indicators of early stages of breast cancer, and the detection of these MCs will, in turn, lead to diagnosis and treatment of breast cancer at its earliest stages. This paper proposes a new method to detect MCs in a digital mammogram. The approach starts with the segmentation of the digital mammogram to isolate the breast region, using fuzzy C means clustering algorithm. The segmented image is then further segmented using top-hat transform to localize the region of interest. A watershed transform is used to isolate the region of interest from rest of the image. The Gibbs random fields are employed to analyze the pixels in conjunction with the devised clique patterns and detect MCs in the image. A thresholding is performed on the processed image where the MCs are detected. The proposed algorithm is highly effective in reducing the region of interest to the region which has a high probability of finding a calcification or MC. It has an overall detection rate of 94.4% and accuracy of 88.2% with a false negative detection rate of 5.6%, respectively.
Zeng, Jia; Liu, Zhi-Qiang
2008-05-01
This paper proposes a statistical-structural character modeling method based on Markov random fields (MRFs) for handwritten Chinese character recognition (HCCR). The stroke relationships of a Chinese character reflect its structure, which can be statistically represented by the neighborhood system and clique potentials within the MRF framework. Based on the prior knowledge of character structures, we design the neighborhood system that accounts for the most important stroke relationships. We penalize the structurally mismatched stroke relationships with MRFs using the prior clique potentials, and derive the likelihood clique potentials from Gaussian mixture models, which encode the large variations of stroke relationships statistically. In the proposed HCCR system, we use the single-site likelihood clique potentials to extract many candidate strokes from character images, and use the pairsite clique potentials to determine the best structural match between the input candidate strokes and the MRF-based character models by relaxation labeling. The experiments on the KAIST character database demonstrate that MRFs can statistically model character structures, and work well in the HCCR system.
Kazemzadeh, Farnoud; Shafiee, Mohammad J.; Wong, Alexander; Clausi, David A.
2014-09-01
The prevalence of compressive sensing is continually growing in all facets of imaging science. Com- pressive sensing allows for the capture and reconstruction of an entire signal from a sparse (under- sampled), yet sufficient, set of measurements that is representative of the target being observed. This compressive sensing strategy reduces the duration of the data capture, the size of the acquired data, and the cost of the imaging hardware as well as complexity while preserving the necessary underlying information. Compressive sensing systems require the accompaniment of advanced re- construction algorithms to reconstruct complete signals from the sparse measurements made. Here, a new reconstruction algorithm is introduced specifically for the reconstruction of compressive multispectral (MS) sensing data that allows for high-quality reconstruction from acquisitions at sub-Nyquist rates. We propose a multilayered conditional random field (MCRF) model, which extends upon the CRF model by incorporating two joint layers of certainty and estimated states. The proposed algorithm treats the reconstruction of each spectral channel as a MCRF given the sparse MS measurements. Since the observations are incomplete, the MCRF incorporates an extra layer determining the certainty of the measurements. The proposed MCRF approach was evaluated using simulated compressive MS data acquisitions, and is shown to enable fast acquisition of MS sensing data with reduced imaging hardware cost and complexity.
Automatic Lung Tumor Segmentation on PET/CT Images Using Fuzzy Markov Random Field Model
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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.
spam: A Sparse Matrix R Package with Emphasis on MCMC Methods for Gaussian Markov Random Fields
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Reinhard Furrer
2010-10-01
Full Text Available spam is an R package for sparse matrix algebra with emphasis on a Cholesky factorization of sparse positive definite matrices. The implemantation of spam is based on the competing philosophical maxims to be competitively fast compared to existing tools and to be easy to use, modify and extend. The first is addressed by using fast Fortran routines and the second by assuring S3 and S4 compatibility. One of the features of spam is to exploit the algorithmic steps of the Cholesky factorization and hence to perform only a fraction of the workload when factorizing matrices with the same sparsity structure. Simulations show that exploiting this break-down of the factorization results in a speed-up of about a factor 5 and memory savings of about a factor 10 for large matrices and slightly smaller factors for huge matrices. The article is motivated with Markov chain Monte Carlo methods for Gaussian Markov random fields, but many other statistical applications are mentioned that profit from an efficient Cholesky factorization as well.
Wei, Qikang; Chen, Tao; Xu, Ruifeng; He, Yulan; Gui, Lin
2016-01-01
The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Due to the diversity and complexity of disease names, the recognition of named entities of diseases is rather tougher than those of chemical names. Although there are some remarkable chemical named entity recognition systems available online such as ChemSpot and tmChem, the publicly available recognition systems of disease named entities are rare. This article presents a system for disease named entity recognition (DNER) and normalization. First, two separate DNER models are developed. One is based on conditional random fields model with a rule-based post-processing module. The other one is based on the bidirectional recurrent neural networks. Then the named entities recognized by each of the DNER model are fed into a support vector machine classifier for combining results. Finally, each recognized disease named entity is normalized to a medical subject heading disease name by using a vector space model based method. Experimental results show that using 1000 PubMed abstracts for training, our proposed system achieves an F1-measure of 0.8428 at the mention level and 0.7804 at the concept level, respectively, on the testing data of the chemical-disease relation task in BioCreative V. Database URL: http://219.223.252.210:8080/SS/cdr.html PMID:27777244
The effects of random field at surface on the magnetic properties in the Ising nanotube and nanowire
Kaneyoshi, T.
2016-12-01
The phase diagrams and temperature dependences of total magnetization mT in two nanosystems (nanotube and nanowire) with a random magnetic field at the surface shell are studied by the uses of the effective-field theory with correlations. Some characteristic phenomena (reentrant phenomena and unconventional thermal variation of total magnetization) are found in the two systems. They are rather different between the two systems, which mainly come from the structural differences of the cores
VizieR Online Data Catalog: Selection function of Milky Way field stars (Stonkute+, 2016)
Stonkute, E.; Koposov, S. E.; Howes, L. M.; Feltzing, S.; Worley, C. C.; Gilmore, G.; Ruchti, G. R.; Kordopatis, G.; Randich, S.; Zwitter, T.; Bensby, T.; Bragaglia, A.; Smiljanic, R.; Costado, M. T.; Tautvaisiene, G.; Casey, A. R.; Korn, A. J.; Lanzafame, A. C.; Pancino, E.; Franciosini, E.; Hourihane, A.; Jofre, P.; Lardo, C.; Lewis, J.; Magrini, L.; Monaco, L.; Morbidelli, L.; Sacco, G. G.; Sbordone, L.
2017-10-01
The observations are conducted with the FLAMES (Pasquini et al., 2002Msngr.110....1P) at the Very Large Telescope (VLT) array operated by the European Southern Observatory on Cerro Paranal, Chile. FLAMES is a fibre facility of the VLT and is mounted at the Nasmyth A platform of the second Unit Telescope of VLT. In this paper, we present the Gaia-ESO Survey selection function only for the Milky Way field stars observed with the GIRAFFE and UVES spectrographs at VLT, not including the bulge. All targets were selected according to their colours and magnitudes, using photometry from the VISTA Hemisphere Survey (VHS; McMahon et al. 2013Msngr.154...35M) and the Two Micron All-Sky Survey (2MASS; Skrutskie et al., 2006, Cat. VII/233). Selected potential target lists were generated at the Cambridge Astronomy Survey Unit (CASU) centre. (3 data files).
Tsao, Shih-Ming; Lai, Ji-Ching; Horng, Horng-Er; Liu, Tu-Chen; Hong, Chin-Yih
2017-04-01
Aptamers are oligonucleotides that can bind to specific target molecules. Most aptamers are generated using random libraries in the standard systematic evolution of ligands by exponential enrichment (SELEX). Each random library contains oligonucleotides with a randomized central region and two fixed primer regions at both ends. The fixed primer regions are necessary for amplifying target-bound sequences by PCR. However, these extra-sequences may cause non-specific bindings, which potentially interfere with good binding for random sequences. The Magnetic-Assisted Rapid Aptamer Selection (MARAS) is a newly developed protocol for generating single-strand DNA aptamers. No repeat selection cycle is required in the protocol. This study proposes and demonstrates a method to isolate aptamers for C-reactive proteins (CRP) from a randomized ssDNA library containing no fixed sequences at 5‧ and 3‧ termini using the MARAS platform. Furthermore, the isolated primer-free aptamer was sequenced and binding affinity for CRP was analyzed. The specificity of the obtained aptamer was validated using blind serum samples. The result was consistent with monoclonal antibody-based nephelometry analysis, which indicated that a primer-free aptamer has high specificity toward targets. MARAS is a feasible platform for efficiently generating primer-free aptamers for clinical diagnoses.
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...
Selective particle trapping and optical binding in the evanescent field of an optical nanofiber
Frawley, Mary C; Truong, Viet Giang; Sergides, Marios; Chormaic, Síle Nic
2014-01-01
The evanescent field of an optical nanofiber presents a versatile interface for the manipulation of micron-scale particles in dispersion. Here, we present a detailed study of the optical binding interactions of a pair of 3.13 $\\mu$m SiO$_2$ particles in the nanofiber evanescent field. Preferred equilibrium positions for the spheres as a function of nanofiber diameter and sphere size are discussed. We demonstrated optical propulsion and self-arrangement of chains of one to seven 3.13 $\\mu$m SiO$_2$ particles; this effect is associated with optical binding via simulated trends of multiple scattering effects. Incorporating an optical nanofiber into an optical tweezers setup facilitated the individual and collective introduction of selected particles to the nanofiber evanescent field for experiments. Computational simulations provide insight into the dynamics behind the observed behavior.
A time-selective technique for free-field reciprocity calibration of condenser microphones
DEFF Research Database (Denmark)
Barrera Figueroa, Salvador; Rasmussen, Knud; Jacobsen, Finn
2003-01-01
In normal practice, microphones are calibrated in a closed coupler where the sound pressure is uniformly distributed over the diaphragm. Alternatively, microphones can be placed in a free field, although in that case the distribution of sound pressure over the diaphragm will change as a result...... are considered that improve the accuracy of the free-field calibration method. In particular, a fast Fourier transform (FFT)-based time-selective technique for removing undesired reflections from the walls of the measurement chamber has been developed and applied to the electric transfer impedance function...... of the diffraction of the body of the microphone, and thus, its sensitivity will change. In the two cases, a technique based on the reciprocity theorem can be applied for obtaining the absolute sensitivity either under uniform pressure or free-field conditions. In this paper, signal-processing techniques...
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.
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…
A Lagrangian description of nearshore hydrodynamics and rip currents forced by a random wave field
Leandro, S.; Cienfuegos, R.; Escauriaza, C. R.
2011-12-01
Nonlinear processes become important for waves propagating in the shoaling and surf zones. Wave shape changes when approaching the coast under the influence of bathymetry, becoming increasingly asymmetric until reaching the breaking limit. In the shoaling zone, non-linearities induce a net velocity in the direction of wave propagation, a phenomenon called Stokes drift, while in the surf zone, currents are mainly driven by spatio-temporal variations in energy dissipation gradients. In this work we aim at investigating and characterizing the nearshore circulation forced by a random wave field propagating over a variable bathymetry. We carry out numerical simulations over a laboratory experiment conducted in a wave basin over a realistic bathymetry [Michallet et al. 2010]. For the hydrodynamics, we use a 2D shock-capturing finite-volume model that solves the non-linear shallow water equations, taking into account energy dissipation by breaking, friction, bed-slope variations, and an accurate description for the moving shoreline in the swash zone [Marche et al. 2007;Guerra et al. 2010]. Model predictions are compared and validated against experimental data giving confidence for its use in the description of wave propagation in the surf/swash zone, together with mean eulerian velocities. The resulting wave propagation and circulation provided by the 2D model will then be used to describe drifter's patterns in the surf zone and construct Lagrangian particle tracking. The chosen experimental configuration is of great interest due to the random wave forcing (slowly modulated), the beach non-uniformities, and the existence of several bar-rip channels that enhance quasi-periodic rip instabilities. During the experiment, balloons filled with water, with a diameter between 5 and 10 cm, were placed in the surf zone in order to characterize circulation in a Lagrangian framework [Castelle et al. 2010]. The time-location of the balloons was continuously tracked by a shore
The upper bound of Pier 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 several field investigations of pier scour in South Carolina (Benedict and Caldwell, 2006; Benedict and Caldwell, 2009) and used that data to develop envelope curves defining the upper bound of pier scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with pier-scour data from other sources and evaluate the upper bound of pier scour with this larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published pier-scour data, and selected data were compiled into a digital spreadsheet consisting of approximately 570 laboratory and 1,880 field measurements. These data encompass a wide range of laboratory and field conditions and represent field data from 24 states within the United States and six other countries. This extensive database was used to define the upper bound of pier-scour depth with respect to pier width encompassing the laboratory and field data. Pier width is a primary variable that influences pier-scour depth (Laursen and Toch, 1956; Melville and Coleman, 2000; Mueller and Wagner, 2005, Ettema et al. 2011, Arneson et al. 2012) and therefore, was used as the primary explanatory variable in developing the upper-bound envelope curve. The envelope curve provides a simple but useful tool for assessing the potential maximum pier-scour depth for pier widths of about 30 feet or less.
Irrational use of antimalarial drugs in rural areas of eastern Pakistan: a random field study
Directory of Open Access Journals (Sweden)
Khan Shafaat Yar
2012-11-01
Full Text Available Abstract Background Prescription of antimalarial drugs in the absence of malarial disease is a common practice in countries where malaria is endemic. However, unwarranted use of such drugs can cause side effects in some people and is a financial drain on local economies. In this study, we surveyed the prevalence of malaria parasites in humans, and the prevalence of the malaria transmitting mosquito vectors in the study area. We also investigated the use of antimalarial drugs in the local people. We focused on randomly selected rural areas of eastern Pakistan where no malaria cases had been reported since May 2004. Methods Mass blood surveys, active case detection, passive case detection, and vector density surveys were carried out in selected areas of Sargodha district from September 2008 to August 2009. Data pertaining to the quantities and types of antimalarial drugs used in these areas were collected from health centers, pharmacies, and the district CDC program of the Health Department of the Government of the Punjab. Results Seven hundred and forty four blood samples were examined, resulting in a Blood Examination Rate (BER of 3.18; microscopic analysis of blood smears showed that none of the samples were positive for malaria parasites. Investigation of the mosquito vector density in 43 living rooms (bedrooms or rooms used for sleeping, 23 stores, and 32 animal sheds, revealed no vectors capable of transmitting malaria in these locations. In contrast, the density of Culex mosquitoes was high. Substantial consumption of a variety of antimalarial tablets, syrups, capsules and injections costing around 1000 US$, was documented for the region. Conclusion Use of antimalarial drugs in the absence of malarial infection or the vectors that transmit the disease was common in the study area. Continuous use of such drugs, not only in Pakistan, but in other parts of the world, may lead to drug-induced side effects amongst users. Better training of
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.
Jin, Ick Hoon; Yuan, Ying; Bandyopadhyay, Dipankar
2016-01-01
Research in dental caries generates data with two levels of hierarchy: that of a tooth overall and that of the different surfaces of the tooth. The outcomes often exhibit spatial referencing among neighboring teeth and surfaces, i.e., the disease status of a tooth or surface might be influenced by the status of a set of proximal teeth/surfaces. Assessments of dental caries (tooth decay) at the tooth level yield binary outcomes indicating the presence/absence of teeth, and trinary outcomes at the surface level indicating healthy, decayed, or filled surfaces. The presence of these mixed discrete responses complicates the data analysis under a unified framework. To mitigate complications, we develop a Bayesian two-level hierarchical model under suitable (spatial) Markov random field assumptions that accommodates the natural hierarchy within the mixed responses. At the first level, we utilize an autologistic model to accommodate the spatial dependence for the tooth-level binary outcomes. For the second level and conditioned on a tooth being non-missing, we utilize a Potts model to accommodate the spatial referencing for the surface-level trinary outcomes. The regression models at both levels were controlled for plausible covariates (risk factors) of caries, and remain connected through shared parameters. To tackle the computational challenges in our Bayesian estimation scheme caused due to the doubly-intractable normalizing constant, we employ a double Metropolis-Hastings sampler. We compare and contrast our model performances to the standard non-spatial (naive) model using a small simulation study, and illustrate via an application to a clinical dataset on dental caries.
Energy Technology Data Exchange (ETDEWEB)
Smith, B.R. [Babcock and Wilcox Co., Lynchburg, VA (United States)
1995-08-15
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.
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.
Pradhan, M.; Suryadarma, D.; Beatty, A.; Wong, M.; Alishjabana, A.; Gaduh, A.
2011-01-01
This study evaluates the effect of four randomized interventions aimed at strengthening school committees, and subsequently improving learning outcomes, in public primary schools in Indonesia. All study schools were randomly allocated to either a control group receiving no intervention, or to
DEFF Research Database (Denmark)
Rasmussen, Knud; Barrera Figueroa, Salvador
2006-01-01
Although the basic principle of reciprocity calibration of microphones in a free field is simple, the practical problems are complicated due to the low signal-to-noise ratio and the influence of cross talk and reflections from the surroundings. The influence of uncorrelated noise can be reduced...... by conventional narrow-band filtering and time averaging, while correlated signals like cross talk and reflections can be eliminated by using time-selective postprocessing techniques. The technique used at DPLA overcomes both these problems using a B&K Pulse analyzer in the SSR mode (steady state response......) and an FFT-based time-selective technique. The complex electrical transfer impedance is measured in linear frequency steps from a few kHz to about three times the resonance frequency of the microphones. The missing values at low frequencies are estimated from a detailed knowledge of the pressure...
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.
Hagen, Joshua A; Kim, Sang N; Bayraktaroglu, Burhan; Leedy, Kevin; Chávez, Jorge L; Kelley-Loughnane, Nancy; Naik, Rajesh R; Stone, Morley O
2011-01-01
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.
Laboratory selection for increased longevity in Drosophila melanogaster reduces field performance
DEFF Research Database (Denmark)
Wit, Janneke; Kristensen, Torsten Nygaard; Sarup, Pernille
2013-01-01
Drosophilamelanogaster is frequently used in ageing studies to elucidate whichmechanisms determine the onset and progress of senescence. Lines selected for increased longevity have often been shown to performaswell as or superior to control lines in life history, stress resistance and behavioural...... in performance. Control lines were better able to locate a resource compared to longevity selected lines of the same age, suggesting that longevity comes at a cost in early life field fitness, supporting the antagonistic pleiotropy theory of ageing.......Drosophilamelanogaster is frequently used in ageing studies to elucidate whichmechanisms determine the onset and progress of senescence. Lines selected for increased longevity have often been shown to performaswell as or superior to control lines in life history, stress resistance and behavioural...... traits when tested in the laboratory. Functional senescence in longevity selected lines has also been shown to occur at a slower rate. However, it is known that performance in a controlled laboratory setting is not necessarily representative of performance in nature. In this study the effect of ageing...
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
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.
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...
On the Usage of Geomagnetic Indices for Data Selection in Internal Field Modelling
Kauristie, K.; Morschhauser, A.; Olsen, N.; Finlay, C. C.; McPherron, R. L.; Gjerloev, J. W.; Opgenoorth, H. J.
2017-03-01
We present a review on geomagnetic indices describing global geomagnetic storm activity ( Kp, am, Dst and dDst/dt) and on indices designed to characterize high latitude currents and substorms ( PC and AE-indices and their variants). The focus in our discussion is in main field modelling, where indices 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 conditions. This exercise reveals that Dst and its time derivative yield a similar picture as Kp on quiet conditions as determined with the conditions typically used in internal field modelling. Magnetic quiescence at high latitudes is typically searched with the help of Merging Electric Field ( MEF) 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-300 nT) can take place, when these criteria prevail. Although AE-indices have been designed to probe electrojet activity only in average conditions and thus their performance is not optimal during weak activity, we note that careful data selection with advanced AE-variants may appear to be the most practical way to lower the elevated RMS-values which still exist in the residuals between modeled and observed values at high latitudes. Recent initiatives to upgrade the AE-indices, either with a better coverage of observing stations and improved baseline corrections (the SuperMAG concept) or with higher accuracy in pinpointing substorm activity (the Midlatitude Positive Bay-index) will most likely be helpful in these efforts.
Varadi, K; Michelfelder, S; Korff, T; Hecker, M; Trepel, M; Katus, H A; Kleinschmidt, J A; Müller, O J
2012-08-01
We have demonstrated the potential of random peptide libraries displayed on adeno-associated virus (AAV)2 to select for AAV2 vectors with improved efficiency for cell type-directed gene transfer. AAV9, however, may have advantages over AAV2 because of a lower prevalence of neutralizing antibodies in humans and more efficient gene transfer in vivo. Here we provide evidence that random peptide libraries can be displayed on AAV9 and can be utilized to select for AAV9 capsids redirected to the cell type of interest. We generated an AAV9 peptide display library, which ensures that the displayed peptides correspond to the packaged genomes and performed four consecutive selection rounds on human coronary artery endothelial cells in vitro. This screening yielded AAV9 library capsids with distinct peptide motifs enabling up to 40-fold improved transduction efficiencies compared with wild-type (wt) AAV9 vectors. Incorporating sequences selected from AAV9 libraries into AAV2 capsids could not increase transduction as efficiently as in the AAV9 context. To analyze the potential on endothelial cells in the intact natural vascular context, human umbilical veins were incubated with the selected AAV in situ and endothelial cells were isolated. Fluorescence-activated cell sorting analysis revealed a 200-fold improved transduction efficiency compared with wt AAV9 vectors. Furthermore, AAV9 vectors with targeting sequences selected from AAV9 libraries revealed an increased transduction efficiency in the presence of human intravenous immunoglobulins, suggesting a reduced immunogenicity. We conclude that our novel AAV9 peptide library is functional and can be used to select for vectors for future preclinical and clinical gene transfer applications.
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
Albert, Lena; Rottensteiner, Franz; Heipke, Christian
2017-08-01
We propose a new approach for the simultaneous classification of land cover and land use considering spatial as well as semantic context. We apply a Conditional Random Fields (CRF) consisting of a land cover and a land use layer. In the land cover layer of the CRF, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Intra-layer edges of the CRF model spatial dependencies between neighbouring image sites. All spatially overlapping sites in both layers are connected by inter-layer edges, which leads to higher order cliques modelling the semantic relation between all land cover and land use sites in the clique. A generic formulation of the higher order potential is proposed. In order to enable efficient inference in the two-layer higher order CRF, we propose an iterative inference procedure in which the two classification tasks mutually influence each other. We integrate contextual relations between land cover and land use in the classification process by using contextual features describing the complex dependencies of all nodes in a higher order clique. These features are incorporated in a discriminative classifier, which approximates the higher order potentials during the inference procedure. The approach is designed for input data based on aerial images. Experiments are carried out on two test sites to evaluate the performance of the proposed method. The experiments show that the classification results are improved compared to the results of a non-contextual classifier. For land cover classification, the result is much more homogeneous and the delineation of land cover segments is improved. For the land use classification, an improvement is mainly achieved for land use objects showing non-typical characteristics or similarities to other land use classes. Furthermore, we have shown that the size of the super-pixels has an influence on the level of detail of the classification result, but also on the
Luo, Sizuo; Hu, Wenhui; Yu, Jiaqi; Zhu, Ruihan; He, Lanhai; Li, Xiaokai; Ma, Pan; Wang, Chuncheng; Liu, Fuchun; Roeterdink, Wim G; Stolte, Steven; Ding, Dajun
2017-02-02
Rotational dynamics of quantum state selected and unselected CH3I molecules in intense femtosecond laser fields has been studied. The orientation and alignment evolutions are derived from a pump-probe measurement and in good agreement with the numerical results from the time-dependent Schrödinger equation (TDSE) calculation. The different rotational transitions through nonresonant Raman process have been assigned from the Fourier analysis of the orientation and alignment revivals. These revivals are derived from a pump-probe measurement and in good agreement with the numerical results from the TDSE calculation. For the molecules in rotational state |1, ±1, ∓1⟩, the transitions can be assigned to ΔJ = ±1, ±2, while for thermally populated molecules, the transitions are ΔJ = ±2. Our results illustrate that the orientation and alignment revivals of the rotational quantum-state-selected molecules give a deep insight into the rotational excitation pathways for the transition of different rotational states of molecules in ultrafast laser fields.
Espinosa, Avelina; Bai, Chunyan Y.
2016-01-01
Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke “design creationism” to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane's hydrophobic/philic nature; a selective “pore” for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the “jackprot,” which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the “jackprot,” or highest-fitness complete-peptide sequence, required cumulative smaller “wins” (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons (“jackdons” that led to “jackacids” that led to the “jackprot”). The “jackprot” is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide
Paz-Y-Miño C, Guillermo; Espinosa, Avelina; Bai, Chunyan Y
2011-09-01
Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke "design creationism" to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane's hydrophobic/philic nature; a selective "pore" for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the "jackprot," which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the "jackprot," or highest-fitness complete-peptide sequence, required cumulative smaller "wins" (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons ("jackdons" that led to "jackacids" that led to the "jackprot"). The "jackprot" is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide "edition" and gene duplications to generate the 6
Borm, G.F.; Melis, R.J.F.; Teerenstra, S.; Peer, P.G.M.
2005-01-01
In some clinical trials, treatment allocation on a patient level is not feasible, and whole groups or clusters of patients are allocated to the same treatment. If, for example, a clinical trial is investigating the efficacy of various patient coaching methods and randomization is done on a patient
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...
Arnaut, Luk R
2010-04-01
We derive an integral expression for the plane-wave expansion of the time-varying (nonstationary) random field inside a mode-stirred reverberation chamber. It is shown that this expansion is a so-called oscillatory process, whose kernel can be expressed explicitly in closed form. The effect of nonstationarity is a modulation of the spectral density of the field on a time scale that is a function of the cavity relaxation time. It is also shown how the contribution by a nonzero initial value of the field can be incorporated into the expansion. The results are extended to a special class of second-order processes, relevant to the reception of a mode-stirred reverberation field by a device under test with a first-order (relaxation-type) frequency response.
Directory of Open Access Journals (Sweden)
XU Miaozhong
2015-02-01
Full Text Available In consideration of the visual system's tremendous ability to perceive and identify the information, a new image segmentation method is presented which simulates the mechanism of visual system for the high resolution remote sensing image segmentation with Markov random field model. Firstly, the characteristics of the visual system have been summarized as: hierarchy, learning ability, feature detection capability and sparse coding property. Secondly, the working mechanism of visual system is simulated by wavelet transform, unsupervised clustering algorithm, feature analysis and Laplace distribution. Then, the segmentation is achieved by the visual mechanism and the Markov random field. Different satellites remote sensing images are adopted as the experimental data, and the segmentation results demonstrate the proposed method have good performance in high resolution remote sensing images.
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.
Selective detection of heavy metal ions by self assembled chemical field effect transistors
Energy Technology Data Exchange (ETDEWEB)
Ruan, Hang, E-mail: hruan@nanosonic.com; Kang, Yuhong; Gladwin, Elizabeth; Claus, Richard O. [NanoSonic, Inc., 158 Wheatland Drive, Pembroke, Virginia 24136 (United States)
2015-04-20
Multiple layer-by-layer sensor material modifications were designed and implemented to achieve selectivity of semiconductor based chemical field effect transistors (ChemFETs) to particular heavy metal ions. The ChemFET sensors were fabricated and modified in three ways, with the intent to initially target first mercury and lead ions and then chromium ions, respectively. Sensor characterization was performed with the gate regions of the sensor elements exposed to different concentrations of target heavy metal ion solutions. A minimum detection level in the range of 0.1 ppm and a 10%–90% response time of less than 10 s were demonstrated. By combining layer-by-layer gold nanoparticles and lead ionophores, a sensor is produced that is sensitive and selective not only to chromium but also to Cr{sup 3+} and Cr{sup 6+}. This result supports the claim that high selectivity can be achieved by designing self-assembled bonding for lead, arsenic, chromium, cesium, mercury, and cadmium.
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.
Optimum selection of artificial lift system for one of the Iranian heavy oil fields
Energy Technology Data Exchange (ETDEWEB)
Taheri, A. [Petroleum Univ. of Technology, Tehran, (Iran, Islamic Republic of); Hooshmand, A. [Hamrah Poushesh Oil and Gas Co., Tehran (Iran, Islamic Republic of)
2006-07-01
The Kuh-E-Mond field in southwest Iran is the country's first priority heavy oil prospect. The occurrence of heavy oil in the Asmari-Jahrum formation was confirmed when well MD-6 was drilled in Kuh-E-Mond on September 19, 1984. The samples throughout most of the Sarvak limestone revealed a black tarry oil with an API gravity of 13. Since there were no development programs in this field, the well was secured and the rig was released on May 5, 1985. However in early 1999, the field became part of the development program. When well MD-6 was opened, the static oil level in the well was 400 m below surface. An artificial lift was required to flow the well, to restore the production rate to normal levels and to optimize ultimate recovery. The technical consideration behind each method of artificial lift for this well were examined, including the beam pump, the electro submersible pump (ESP), the progressive cavity pump (PCP), gas lift and hydraulic lift. This paper discussed the technical issues which led to the selection of the PCP as the most suitable artificial lift method for recovering oil from well MD-6.
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.
Study of self-compensation of random field errors in low-/β insertion triplets of hadron colliders
Shi, Jicong
1999-06-01
The presence of unavoidable field errors in superconducting low-β insertion triplets is one of the major causes for limiting the dynamic aperture of colliders during collisions. Sorting of quadrupoles of the triplets, in which the quadrupoles are installed in the ring according to a certain sequence based on the measured multipole errors, is a way to reduce the adverse effects of random field errors without an increase in the cost. Because of a very small phase advance within each triplet, significant self-compensation of random field errors of the triplet can be achieved even with sorting of a small number of quadrupoles. A study on low-β insertion triplets of the LHC interaction regions show that sorting of the quadrupoles with the vector sorting scheme is quite effective in enlargement of the dynamic aperture and improvement of the linearity of the phase-space region occupied by beams. Since the sorting scheme is based entirely on the local compensation of random errors, the effectiveness of the sorting is independent of the operational condition of the collider.
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
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...... of narcotic drugs. It can be concluded that driving under the influence of drugs is as serious a road safety problem as drunk driving.......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...
Presence of psychoactive substances in oral fluid from randomly selected drivers in Denmark
DEFF Research Database (Denmark)
Simonsen, Kirsten Wiese; Steentoft, Anni; Hels, Tove
2012-01-01
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....... It can be concluded that driving under the influence of drugs is as serious a road safety problem as drunk driving.......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...
Directory of Open Access Journals (Sweden)
Raj Kumar Patel
2016-09-01
Full Text Available 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 statistical features and used as input feature for the classification problem. These features are classified through RF classifiers for four class problems. The prime objective of this paper is to evaluate effectiveness of random forest classifier on bearing fault diagnosis. The obtained results compared with the existing artificial intelligence techniques, neural network. The analysis of results shows the better performance and higher accuracy than the well existing techniques.
The rate of separation of magnetic lines of force in a random magnetic field.
Jokipii, J. R.
1973-01-01
The mixing of magnetic lines of force, as represented by their rate of separation, as a function of distance along the magnetic field, is considered with emphasis on neighboring lines of force. This effect is particularly important in understanding the transport of charged particles perpendicular to the average magnetic field. The calculation is carried out in the approximation that the separation changes by an amount small compared with the correlation scale normal to the field, in a distance along the field of a few correlation scales. It is found that the rate of separation is very sensitive to the precise form of the power spectrum. Application to the interplanetary and interstellar magnetic fields is discussed, and it is shown that in some cases field lines, much closer together than the correlation scale, separate at a rate which is effectively as rapid as if they were many correlation lengths apart.
Singh, Sudhir; Kumar, Sanjiv; Chahal, Gaurav; Verma, Reetu
2017-01-01
Chronic lumbar radiculopathy has a lifetime prevalence of 5.3% in men and 3.7% in women. It usually resolves spontaneously, but up to 30% cases will have pronounced symptoms even after one year. A prospective randomized single-blind study was conducted to compare the efficacy of caudal epidural steroid injection and selective nerve root block in management of pain and disability in cases of lumbar disc herniation. Eighty patients with confirmed single-level lumbar disc herniation were equally divided in two groups: (a) caudal epidural and (b) selective nerve root block group, by a computer-generated random allocation method. The caudal group received three injections of steroid mixed with local anesthetics while selective nerve root block group received single injection of steroid mixed with local anesthetic agent. Patients were assessed for pain relief and reduction in disability. In SNRB group, pain reduced by more than 50% up till 6 months, while in caudal group more than 50% reduction of pain was maintained till 1 year. The reduction in ODI in SNRB group was 52.8% till 3 months, 48.6% till 6 months, and 46.7% at 1 year, while in caudal group the improvement was 59.6%, 64.6%, 65.1%, and 65.4% at corresponding follow-up periods, respectively. Caudal epidural block is an easy and safe method with better pain relief and improvement in functional disability than selective nerve root block. Selective nerve root block injection is technically more demanding and has to be given by a skilled anesthetist.
Adiabatic hydrodynamic modes in dielectric environment in a random electric field
Stupka, Anton
2016-01-01
Dielectric is considered in the electric field that has equal to zero the first moment and different from zero the second moment of strength in an equilibrium. The equations of ideal hydrodynamics are obtained in such a field for the case of the neglect of dissipative effects. A new variable - the second moment of electric field strength is included in the Euler equation. A temporal equation for this variable is obtained on the basis of Maxwell equations in the hydrodynamic approximation. Adi...
Schießl, Stefan P.; Rother, Marcel; Lüttgens, Jan; Zaumseil, Jana
2017-11-01
The field-effect mobility is an important figure of merit for semiconductors such as random networks of single-walled carbon nanotubes (SWNTs). However, owing to their network properties and quantum capacitance, the standard models for field-effect transistors cannot be applied without modifications. Several different methods are used to determine the mobility with often very different results. We fabricated and characterized field-effect transistors with different polymer-sorted, semiconducting SWNT network densities ranging from low (≈6 μm-1) to densely packed quasi-monolayers (≈26 μm-1) with a maximum on-conductance of 0.24 μS μm-1 and compared four different techniques to evaluate the field-effect mobility. We demonstrate the limits and requirements for each method with regard to device layout and carrier accumulation. We find that techniques that take into account the measured capacitance on the active device give the most reliable mobility values. Finally, we compare our experimental results to a random-resistor-network model.
Directory of Open Access Journals (Sweden)
Malihe Asadollahi
2016-09-01
Full Text Available Introduction: Hospitalization in neonatal intensive care unit may leads to many stresses for premature infants. Since premature infants cannot properly process stressors, identifying interventions that reduce the stress level for them is seems necessary. The aim of present study was to compare the effects of Field massage and Gentle Human Touch (GHT techniques on the urine level of cortisol, as an indicator of stress in preterm infants. Methods: This randomized, controlled clinical trial was carried out in Al-Zahra hospital, Tabriz. A total of 84 premature infants were randomly assigned into three groups. First groups were touched by their mothers three times a day (15 minutes in each session for 5 days by GHT technique. The second group was received 15 minutes Field massage with sunflower oil three times a day by their mothers for 5 days. The third group received routine care. In all groups, 24-hours urine samples were collected in the first and sixth day after the intervention and analyzed for cortisol level. Data were analyzed by SPSS software. Results: There were significant differences between mean of changes in cortisol level between GHT and control groups and Field massage and control groups (0.026. Conclusion: Although the massage with Field technique resulted in a significant reduction in blood cortisol level, but the GHT technique have also a similar effect. So, both methods are recommended for decreasing of stress in preterm infants.
Waldorp, Lourens J
2016-01-01
It was recently shown how graphs can be used to provide descriptions of psychopathologies, where symptoms of, say, depression, affect each other and certain configurations determine whether someone could fall into a sudden depression. To analyse changes over time and characterise possible future behaviour is rather difficult for large graphs. We describe the dynamics of networks using one-dimensional discrete time dynamical systems theory obtained from a mean field approach to (elementary) probabilistic cellular automata (PCA). Often the mean field approach is used on a regular graph (a grid or torus) where each node has the same number of edges and the same probability of becoming active. We show that we can use variations of the mean field of the grid to describe the dynamics of the PCA on a random and small-world graph. Bifurcation diagrams for the mean field of the grid, random, and small-world graphs indicate possible phase transitions for certain parameter settings. Extensive simulations indicate for di...
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......-cost and low-risk support structures to be put into use. Overall, these outcomes are an important contribution to increase the economic feasibility of future offshore wind farms.......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...
Kwon, Soonshin; Chen, Zack C. Y.; Noh, Hyunwoo; Lee, Ju Hun; Liu, Hang; Cha, Jennifer N.; Xiang, Jie
2014-06-01
Crystalline silicon nanotubes (Si NTs) provide distinctive advantages as electrical and biochemical analysis scaffolds through their unique morphology and electrical tunability compared to solid nanowires or amorphous/non-conductive nanotubes. Such potential is investigated in this report. Gate-dependent four-probe current-voltage analysis reveals electrical properties such as resistivity to differ by nearly 3 orders of magnitude between crystalline and amorphous Si NTs. Analysis of transistor transfer characteristics yields a field effect mobility of 40.0 cm2 V-1 s-1 in crystalline Si NTs. The hollow morphology also allows selective inner/outer surface functionalization and loading capability either as a carrier for molecular targets or as a nanofluidic channel for biomolecular assays. We present for the first time a demonstration of internalization of fluorescent dyes (rhodamine) and biomolecules (BSA) in Si NTs as long as 22 μm in length.Crystalline silicon nanotubes (Si NTs) provide distinctive advantages as electrical and biochemical analysis scaffolds through their unique morphology and electrical tunability compared to solid nanowires or amorphous/non-conductive nanotubes. Such potential is investigated in this report. Gate-dependent four-probe current-voltage analysis reveals electrical properties such as resistivity to differ by nearly 3 orders of magnitude between crystalline and amorphous Si NTs. Analysis of transistor transfer characteristics yields a field effect mobility of 40.0 cm2 V-1 s-1 in crystalline Si NTs. The hollow morphology also allows selective inner/outer surface functionalization and loading capability either as a carrier for molecular targets or as a nanofluidic channel for biomolecular assays. We present for the first time a demonstration of internalization of fluorescent dyes (rhodamine) and biomolecules (BSA) in Si NTs as long as 22 μm in length. Electronic supplementary information (ESI) available: Modelling (Fig. S1) and
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
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
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)
Gregory P. Asnera; Michael Keller; Rodrigo Pereira; Johan C. Zweeded
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...
Energy Technology Data Exchange (ETDEWEB)
Apte, Michael G.; Delp, Woody W.; Diamond, Richard C.; Hodgson, Alfred T.; Kumar, Satish; Rainer, Leo I.; Shendell, Derek G.; Sullivan, Doug P.; Fisk, William J.
2001-10-11
It is commonly assumed that efforts to simultaneously develop energy efficient building technologies and to improve indoor environmental quality (IEQ) are unfeasible. The primary reason for this is that IEQ improvements often require additional ventilation that is costly from an energy standpoint. It is currently thought that health and productivity in work and learning environments requires adequate, if not superior, IEQ. Despite common assumptions, opportunities do exist to design building systems that provide improvements in both energy efficiency and IEQ. This report outlines the selection of a heating, ventilation, and air conditioning (HVAC) system to be used in demonstrating such an opportunity in a field study using relocatable school classrooms. Standard classrooms use a common wall mounted heat pump HVAC system. After reviewing alternative systems, a wall-mounting indirect/direct evaporative cooling system with an integral hydronic gas heating is selected. The anticipated advantages of this system include continuous ventilation of 100 percent outside air at or above minimum standards, projected cooling energy reductions of about 70 percent, inexpensive gas heating, improved airborne particle filtration, and reduced peak load electricity use. Potential disadvantages include restricted climate regions and possible increases in indoor relative humidity levels under some conditions.
Hybrid Predictor and Field-Biased Context Pixel Selection Based on PPVO
Directory of Open Access Journals (Sweden)
Hongyin Xiang
2016-01-01
Full Text Available Most pixel-value-ordering (PVO predictors generated prediction-errors including −1 and 1 in a block-by-block manner. Pixel-based PVO (PPVO method provided a novel pixel scan strategy in a pixel-by-pixel way. Prediction-error bin 0 is expanded for embedding with the help of equalizing context pixels for prediction. In this paper, a PPVO-based hybrid predictor (HPPVO is proposed as an extension. HPPVO predicts pixel in both positive and negative orientations. Assisted by expansion bins selection technique, this hybrid predictor presents an optimized prediction-error expansion strategy including bin 0. Furthermore, a novel field-biased context pixel selection is already developed, with which detailed correlations of around pixels are better exploited more than equalizing scheme merely. Experiment results show that the proposed HPPVO improves embedding capacity and enhances marked image fidelity. It also outperforms some other state-of-the-art methods of reversible data hiding, especially for moderate and large payloads.
Traveling pulses in a stochastic neural field model of direction selectivity.
Bressloff, Paul C; Wilkerson, Jeremy
2012-01-01
We analyze the effects of extrinsic noise on traveling pulses in a neural field model of direction selectivity. The model consists of a one-dimensional scalar neural field with an asymmetric weight distribution consisting of an offset Mexican hat function. We first show how, in the absence of any noise, the system supports spontaneously propagating traveling pulses that can lock to externally moving stimuli. Using a separation of time-scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how extrinsic noise in the activity variables leads to a diffusive-like displacement (wandering) of the wave from its uniformly translating position at long time-scales, and fluctuations in the wave profile around its instantaneous position at short time-scales. In the case of freely propagating pulses, the wandering is characterized by pure Brownian motion, whereas in the case of stimulus-locked pulses, it is given by an Ornstein-Uhlenbeck process. This establishes that stimulus-locked pulses are more robust to noise.
Traveling pulses in a stochastic neural field model of direction selectivity
Directory of Open Access Journals (Sweden)
Paul C Bressloff
2012-10-01
Full Text Available We analyze the effects of extrinsic noise on traveling pulses in a neural field model of direction selectivity. The model consists of a one-dimensional scalar neural field with an asymmetric weight distribution consisting of an offset Mexican hat function. We first show how, in the absence of any noise, the system supports spontaneously propagating traveling pulses that can lock to externally moving stimuli. Using a separation of time scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how extrinsic noise in the activity variables leads to a diffusive-like displacement (wandering of the wave from its uniformly translating position at long time scales, and fluctuations in the wave profile around its instantaneous position at short time scales. In the case of freely propagating pulses, the wandering is characterized by pure Brownian motion, whereas in the case of stimulus-locked pulses, it is given by an Ornstein-Uhlenbeck process. This establishes that stimulus-locked pulses are more robust to noise.
Directory of Open Access Journals (Sweden)
Adeney de Freitas Bueno
Full Text Available ABSTRACT: Pesticides are considered the first line of defense for the control of pests and diseases. At least in the short and medium term, the use of pesticides will remain an important strategy for pest management, allowing growers to produce crops of sufficient quality at low costs. A broad approach known as Integrated Pest Management (IPM combines several different pest-control strategies, among which the combination of chemical and biological control stands out. It requires pesticides that achieve optimal control of target pests with minimal impact on the activity of biological control agents. Because of the dynamics of pest infestations, IPM routines are continuously adjusted by growers, requiring comprehensive information about pesticide effects on natural enemies. However, this information is not always available and often contradictory, which constrains the design of field recommendations. In this review, we focused on the importance of selective pesticides in IPM programs, and the effects of chemical pesticides on parasitoids, predators, and entomopathogenic fungi. We provided a detailed discussion of the challenges and constraints for research on pesticide effects on natural enemies, as well as for the resulting field recommendations.
The decision: Relations to oneself, authority and vulnerability in the field of selective abortion.
Risøy, Sølvi Marie; Sirnes, Thorvald
2015-09-01
This article is about selective abortion. It concentrates on the existential, moral and social conditions that arise when pregnant women, using prenatal diagnosis (PND), are told that there is something seriously wrong with the foetuses that they are carrying. This is characterised as a micro state of emergency, where both normal cognitive categories and normative orders are dissolved. The analyses are anchored in the womens' own presentations and understandings of the processes and dilemmas related to the abortion decisions, and our most important empirical materials are interviews with women who have experienced them. Our main ambition is to show the relation between some important dimensions of the situation in which the abortion decision has to be made, and the special kind of authority on behalf of the women that presents itself. Of equal importance is the vulnerability of the pregnant women, resulting in a co-production of the women as both Sovereigns and Homo Sacer in the decision situation. We also analyse some of the experienced relations between the women and the foetuses, and how the women constitute themselves as moral subjects, with a particular emphasis on the motifs of sacrifice and self-sacrifice. It is a central argument in the article that we have to understand the specificity of the decision situation, without reducing it either to other phases (before or after) of the total processes of PND and selective abortion, or to general discourses of disability or normality. The specificity of the situation in which the abortion decision is made is a pivotal point in society's regulation (in a broad sense) of the field and in the constitution of the regime of selective abortion.
De Plano, Laura M; Carnazza, Santina; Messina, Grazia M L; Rizzo, Maria Giovanna; Marletta, Giovanni; Guglielmino, Salvatore P P
2017-09-01
Staphylococcus aureus is a major human pathogen causing health care-associated and community-associated infections. Early diagnosis is essential to prevent disease progression and to reduce complications that can be serious. In this study, we selected, from a 9-mer phage peptide library, a phage clone displaying peptide capable of specific binding to S. aureus cell surface, namely St.au9IVS5 (sequence peptide RVRSAPSSS).The ability of the isolated phage clone to interact specifically with S. aureus and the efficacy of its bacteria-binding properties were established by using enzyme linked immune-sorbent assay (ELISA). We also demonstrated by Western blot analysis that the most reactive and selective phage peptide binds a 78KDa protein on the bacterial cell surface. Furthermore, we observed selectivity of phage-bacteria-binding allowing to identify clinical isolates of S. aureus in comparison with a panel of other bacterial species. In order to explore the possibility of realizing a selective bacteria biosensor device, based on immobilization of affinity-selected phage, we have studied the physisorbed phage deposition onto a mica surface. Atomic Force Microscopy (AFM) was used to determine the organization of phage on mica surface and then the binding performance of mica-physisorbed phage to bacterial target was evaluated during the time by fluorescent microscopy. The system is able to bind specifically about 50% of S. aureus cells after 15' and 90% after one hour. Due to specificity and rapidness, this biosensing strategy paves the way to the further development of new cheap biosensors to be used in developing countries, as lab-on-chip (LOC) to detect bacterial agents in clinical diagnostics applications. Copyright © 2017 Elsevier B.V. All rights reserved.
Selection of locations of knots for linear splines in random regression test-day models.
Jamrozik, J; Bohmanova, J; Schaeffer, L R
2010-04-01
Using spline functions (segmented polynomials) in regression models requires the knowledge of the location of the knots. Knots are the points at which independent linear segments are connected. Optimal positions of knots for linear splines of different orders were determined in this study for different scenarios, using existing estimates of covariance functions and an optimization algorithm. The traits considered were test-day milk, fat and protein yields, and somatic cell score (SCS) in the first three lactations of Canadian Holsteins. Two ranges of days in milk (from 5 to 305 and from 5 to 365) were taken into account. In addition, four different populations of Holstein cows, from Australia, Canada, Italy and New Zealand, were examined with respect to first lactation (305 days) milk only. The estimates of genetic and permanent environmental covariance functions were based on single- and multiple-trait test-day models, with Legendre polynomials of order 4 as random regressions. A differential evolution algorithm was applied to find the best location of knots for splines of orders 4 to 7 and the criterion for optimization was the goodness-of-fit of the spline covariance function. Results indicated that the optimal position of knots for linear splines differed between genetic and permanent environmental effects, as well as between traits and lactations. Different populations also exhibited different patterns of optimal knot locations. With linear splines, different positions of knots should therefore be used for different effects and traits in random regression test-day models when analysing milk production traits.
Beardslee, Joseph A; Sadtler, Bryce; Lewis, Nathan S
2012-11-27
External magnetic fields have been used to vertically align ensembles of silicon microwires coated with ferromagnetic nickel films. X-ray diffraction and image analysis techniques were used to quantify the degree of vertical orientation of the microwires. The degree of vertical alignment and the minimum field strength required for alignment were evaluated as a function of the wire length, coating thickness, magnetic history, and substrate surface properties. Nearly 100% of 100 μm long, 2 μm diameter, Si microwires that had been coated with 300 nm of Ni could be vertically aligned by a 300 G magnetic field. For wires ranging from 40 to 60 μm in length, as the length of the wire increased, a higher degree of alignment was observed at lower field strengths, consistent with an increase in the available magnetic torque. Microwires that had been exposed to a magnetic sweep up to 300 G remained magnetized and, therefore, aligned more readily during subsequent magnetic field alignment sweeps. Alignment of the Ni-coated Si microwires occurred at lower field strengths on hydrophilic Si substrates than on hydrophobic Si substrates. The magnetic field alignment approach provides a pathway for the directed assembly of solution-grown semiconductor wires into vertical arrays, with potential applications in solar cells as well as in other electronic devices that utilize nano- and microscale components as active elements.
van Laarhoven, J J E M; Lansink, K W W; van Heijl, M; Lichtveld, R A; Leenen, L P H
2014-05-01
For optimal treatment of trauma patients it is of great importance to identify patients who are at risk for severe injuries. The Dutch field triage protocol for trauma patients, the LPA (National Protocol of Ambulance Services), is designed to get the right patient, in the right time, to the right hospital. Purpose of this study was to determine diagnostic accuracy and compliance of this triage protocol. Triage criteria were categorised into physiological condition (P), mechanism of trauma (M) and injury type (I). A retrospective analysis of prospectively collected data of all high-energy trauma patients from 2008 to 2011 in the region Central Netherlands is performed. Diagnostic parameters (sensitivity, specificity, negative predictive value, positive predictive value) of the field triage protocol for selecting severely injured patients were calculated including rates of under- and overtriage. Undertriage was defined as the proportion of severely injured patients (Injury Severity Score (ISS)≥16) who were transported to a level two or three trauma care centre. Overtriage was defined as the proportion of non-severely injured patients (ISS<16) who were transported to a level one trauma care centre. Overall sensitivity and specificity of the field triage protocol was 89.1% (95% confidence interval (CI) 84.4-92.6) and 60.5% (95% CI 57.9-63.1), respectively. The overall rate of undertriage was 10.9% (95%CI 7.4-15.7) and the overall rate of overtriage was 39.5% (95%CI 36.9-42.1). These rates were 16.5% and 37.7%, respectively for patients with M+I-P-. Compliance to the triage protocol for patients with M+I-P- was 78.7%. Furthermore, compliance in patients with either a positive I+ or positive P+ was 91.2%. The overall rate of undertriage (10.8%) was mainly influenced by a high rate of undertriage in the group of patients with only a positive mechanism criterion, therefore showing low diagnostic accuracy in selecting severely injured patients. As a consequence these
Mixed spin Ising model with four-spin interaction and random crystal field
Energy Technology Data Exchange (ETDEWEB)
Benayad, N., E-mail: n.benayad@fsac.ac.ma [Groupe de Mecanique Statistique, Laboratoire de physique theorique et appliquee, Faculte des sciences-Aien Chock, Universite Hassan II-Casablanca, B.P 5366 Maarif, Casablanca 20100 (Morocco); Laboratoire de physique des hautes energies et de la matiere condensee, Faculte des sciences-Aien Chock, Universite Hassan II-Casablanca, B.P 5366 Maarif, Casablanca 20100 (Morocco); Ghliyem, M. [Groupe de Mecanique Statistique, Laboratoire de physique theorique et appliquee, Faculte des sciences-Aien Chock, Universite Hassan II-Casablanca, B.P 5366 Maarif, Casablanca 20100 (Morocco); Laboratoire de physique des hautes energies et de la matiere condensee, Faculte des sciences-Aien Chock, Universite Hassan II-Casablanca, B.P 5366 Maarif, Casablanca 20100 (Morocco)
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.
Adiabatic hydrodynamic modes in dielectric environment in a random electric field
Stupka, Anton
2016-01-01
Dielectric is considered in the electric field that has equal to zero the first moment and different from zero the second moment of strength in an equilibrium. The equations of ideal hydrodynamics are obtained in such a field for the case of the neglect of dissipative effects. A new variable - the second moment of electric field strength is included in the Euler equation. A temporal equation for this variable is obtained on the basis of Maxwell equations in the hydrodynamic approximation. Adiabatic one-dimensional waves of small amplitude are studied in this system. Proceeding from the theoretical estimation of the intracrystalline field in an ionic crystal the good consent of the obtained numerical values of transversal velocity of this wave with transversal velocity of sound for isotropic crystals of alkali halides is found.
Support Vector Driven Markov Random Fields towards DTI Segmentation of the Human Skeletal Muscle
Neji, Radhouène; Fleury, Gilles; Deux, J.-F.; Rahmouni, A.; Bassez, G.; Vignaud, A.; Paragios, Nikolaos
2008-01-01
International audience; In this paper we propose a classification-based method towards the segmentation of diffusion tensor images. We use Support Vector Machines to classify diffusion tensors and we extend linear classification to the non linear case. To this end, we discuss and evaluate three different classes of kernels on the space of symmetric definite positive matrices that are well suited for the classification of tensor data. We impose spatial constraints by means of a Markov random f...
Jenkins, Melissa M.; Youngstrom, Eric A.
2015-01-01
Objective This study examined the efficacy of a new cognitive debiasing intervention in reducing decision-making errors in the assessment of pediatric bipolar disorder (PBD). Method The study was a randomized controlled trial using case vignette methodology. Participants were 137 mental health professionals working in different regions of the US (M=8.6±7.5 years of experience). Participants were randomly assigned to a (1) brief overview of PBD (control condition), or (2) the same brief overview plus a cognitive debiasing intervention (treatment condition) that educated participants about common cognitive pitfalls (e.g., base-rate neglect; search satisficing) and taught corrective strategies (e.g., mnemonics, Bayesian tools). Both groups evaluated four identical case vignettes. Primary outcome measures were clinicians’ diagnoses and treatment decisions. The vignette characters’ race/ethnicity was experimentally manipulated. Results Participants in the treatment group showed better overall judgment accuracy, p < .001, and committed significantly fewer decision-making errors, p < .001. Inaccurate and somewhat accurate diagnostic decisions were significantly associated with different treatment and clinical recommendations, particularly in cases where participants missed comorbid conditions, failed to detect the possibility of hypomania or mania in depressed youths, and misdiagnosed classic manic symptoms. In contrast, effects of patient race were negligible. Conclusions The cognitive debiasing intervention outperformed the control condition. Examining specific heuristics in cases of PBD may identify especially problematic mismatches between typical habits of thought and characteristics of the disorder. The debiasing intervention was brief and delivered via the Web; it has the potential to generalize and extend to other diagnoses as well as to various practice and training settings. PMID:26727411
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. .
Segovia, Fermín.; Salas-Gonzalez, Diego; Górriz, Juan M.; Ramírez, Javier; Martínez-Murcia, Francisco J.
2017-03-01
18F-DMFP-PET is a neuroimaging modality that allows us to analyze the striatal dopamine. Thus, it is recently emerging as an effective tool to assist the diagnosis of Parkinsonism and differentiate among parkinsonian syndromes. However the analysis of these data, which require specific preprocessing methods, is still poorly covered. In this work we demonstrate a novel methodology based on Hidden Markov Random Fields (HMRF) and the Gaussian distribution to preprocess 18F-DMFP-PET data. First, we performed a selection of voxels based on the analysis of the histogram in order to remove low-signal regions and regions outside the brain. Specifically, we modeled the histogram of intensities of a neuroimage with a mixture of two Gaussians and then, using a HMRF algorithm the voxels corresponding to the low-intensity Gaussian were discarded. This procedure is similar to the tissue segmentation usually applied to Magnetic Resonance Imaging data. Secondly, the intensity of the selected voxels was scaled so that the Gaussian that models the histogram for each neuroimage has same mean and standard deviation. This step made comparable the data from different patients, without removing the characteristic patterns of each patient's disorder. The proposed approach was evaluated using a computer system based on statistical classification that separated the neuroimages according to the parkinsonian variant they represented. The proposed approach achieved higher accuracy rates than standard approaches for voxel selection (based on atlases) and intensity normalization (based on the global mean).
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 (Drug Administration (FDA). Alternately, carboxylic/amide carbons are coupled to 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.
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
Rehberg, Sebastian; Ertmer, Christian; Lange, Matthias; Morelli, Andrea; Whorton, Elbert; Strohhäcker, Anne-Katrin; Dünser, Martin Wolfgang; Lipke, Erik; Kampmeier, Tim G; Aken, Hugo; Traber, Daniel L; Westphal, Martin
2010-01-01
ABSTRACT : INTRODUCTION : V2-receptor (V2R) stimulation potentially aggravates sepsis-induced vasodilation, fluid accumulation and microvascular thrombosis. Therefore, the present study was performed to determine the effects of a first-line therapy with the selective V2R-antagonist (Propionyl1-D-Tyr(Et)2-Val4-Abu6-Arg8,9)-Vasopressin on cardiopulmonary hemodynamics and organ function vs. the mixed V1aR/V2R-agonist arginine vasopressin (AVP) or placebo in an established ovine model of septic s...
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.
Energy Technology Data Exchange (ETDEWEB)
Yigit, Ali, E-mail: ayigit80@karatekin.edu.tr [Cank Latin-Small-Letter-Dotless-I r Latin-Small-Letter-Dotless-I Karatekin University, Department of Physics, 18100 Cank Latin-Small-Letter-Dotless-I r Latin-Small-Letter-Dotless-I (Turkey); Albayrak, Erhan [Erciyes University, Department of Physics, 38039 Kayseri (Turkey)
2013-03-15
The effects of bimodal random crystal field on the phase diagrams and magnetization curves of ferrimagnetic mixed spin-1/2 and spin-3/2 Blume-Capel model are examined by using the effective field theory with correlations for honeycomb lattice. The phase diagrams are obtained on the ({Delta},kT/|J|), ({Delta},T{sub comp}) and (p,kT/|J|) planes for given values of p and {Delta}, respectively. The model exhibits only the second-order phase transitions as in the Blume-Capel model with constant crystal fields. In addition, it was found that the model presents one or two compensation temperatures for appropriate values of random crystal field for given probability in contrast to constant crystal field case. Therefore, it is shown that the random crystal field considerably affects the thermal variations of net and sublattice magnetizations. - Highlights: Black-Right-Pointing-Pointer Mixed spin-1/2 and spin-3/2 BC model with random crystal field was investigated. Black-Right-Pointing-Pointer Effective-field theory with correlations was used in obtaining the critical temperatures. Black-Right-Pointing-Pointer The phase diagrams of the model were shown for various planes. Black-Right-Pointing-Pointer Randomness of the crystal field leads to emergence the compensation temperatures. Black-Right-Pointing-Pointer It was found that the model exhibits only second-order phase transitions.
Energy Technology Data Exchange (ETDEWEB)
Lee, C.G.; Chen, C.H. [Univ. of Massachusetts, North Dartmouth, MA (United States)
1996-12-31
In this paper a novel multiresolution wavelet analysis (MWA) and non-stationary Gaussian Markov random field (GMRF) technique is introduced for the identification of microcalcifications with high accuracy. The hierarchical multiresolution wavelet information in conjunction with the contextual information of the images extracted from GMRF provides a highly efficient technique for microcalcification detection. A Bayesian teaming paradigm realized via the expectation maximization (EM) algorithm was also introduced for edge detection or segmentation of larger lesions recorded on the mammograms. The effectiveness of the approach has been extensively tested with a number of mammographic images provided by a local hospital.
Berger, Vance W
2015-08-01
Recently a great deal of attention has been paid to conflicts of interest in medical research, and the Institute of Medicine has called for more research into this important area. One research question that has not received sufficient attention concerns the mechanisms of action by which conflicts of interest can result in biased and/or flawed research. What discretion do conflicted researchers have to sway the results one way or the other? We address this issue from the perspective of selective inertia, or an unnatural selection of research methods based on which are most likely to establish the preferred conclusions, rather than on which are most valid. In many cases it is abundantly clear that a method that is not being used in practice is superior to the one that is being used in practice, at least from the perspective of validity, and that it is only inertia, as opposed to any serious suggestion that the incumbent method is superior (or even comparable), that keeps the inferior procedure in use, to the exclusion of the superior one. By focusing on these flawed research methods we can go beyond statements of potential harm from real conflicts of interest, and can more directly assess actual (not potential) harm.
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.
Content analysis of a stratified random selection of JVME articles: 1974-2004.
Olson, Lynne E
2011-01-01
A content analysis was performed on a random sample (N = 168) of 25% of the articles published in the Journal of Veterinary Medical Education (JVME) per year from 1974 through 2004. Over time, there were increased numbers of authors per paper, more cross-institutional collaborations, greater prevalence of references or endnotes, and lengthier articles, which could indicate a trend toward publications describing more complex or complete work. The number of first authors that could be identified as female was greatest for the most recent time period studied (2000-2004). Two different categorization schemes were created to assess the content of the publications. The first categorization scheme identified the most frequently published topics as admissions, descriptions of courses, the effect of changing teaching methods, issues facing the profession, and examples of uses of technology. The second categorization scheme identified the subset of articles that described medical education research on the basis of the purpose of the research, which represented only 14% of the sample articles (24 of 168). Of that group, only three of 24, or 12%, represented studies based on a firm conceptual framework that could be confirmed or refuted by the study's results. The results indicate that JVME is meeting its broadly based mission and that publications in the veterinary medical education literature have features common to publications in medicine and medical education.
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.
Benefits of Selected Physical Exercise Programs in Detention: A Randomized Controlled Study
Directory of Open Access Journals (Sweden)
Claudia Battaglia
2013-10-01
Full Text Available The aim of the study was to determine which kind of physical activity could be useful to inmate populations to improve their health status and fitness levels. A repeated measure design was used to evaluate the effects of two different training protocols on subjects in a state of detention, tested pre- and post-experimental protocol.Seventy-five male subjects were enrolled in the studyand randomly allocated to three groups: the cardiovascular plus resistance training protocol group (CRT (n = 25; mean age 30.9 ± 8.9 years,the high-intensity strength training protocol group (HIST (n = 25; mean age 33.9 ± 6.8 years, and a control group (C (n = 25; mean age 32.9 ± 8.9 years receiving no treatment. All subjects underwent a clinical assessmentandfitness tests. MANOVA revealed significant multivariate effects on group (p < 0.01 and group-training interaction (p < 0.05. CRT protocol resulted the most effective protocol to reach the best outcome in fitness tests. Both CRT and HIST protocols produced significant gains in the functional capacity (cardio-respiratory capacity and cardiovascular disease risk decrease of incarcerated males. The significant gains obtained in functional capacity reflect the great potential of supervised exercise interventions for improving the health status of incarcerated people.
Meadows, Cheyney; Guerino, Frank; Sun, Fangshi
2017-01-19
Fleas are a common ectoparasite of domestic cats and there is a need for novel treatments that improve feline flea control. This investigator-blinded, multi-center randomized, positive-controlled study evaluated the flea control in cats provided by a single owner-applied treatment with a fluralaner topical formulation compared with a positive control. Households with up to five healthy cats, all at least 12 weeks of age and weighing at least 1.2 kg (2.6 lb), were randomized in an approximate 3:1 ratio of fluralaner to positive control. All cats in households randomized to the positive control group were dispensed three treatments, at 4-week intervals, of a commercial formulation of fipronil/(S)-methoprene. All cats in households randomized to the fluralaner group were dispensed an initial treatment at enrollment and a second treatment at week 12 for an additional 3-week observation of treatment safety. One primary cat with at least five live fleas at enrollment was randomly selected within each household. Flea counts were performed on all primary cats at 4-week intervals through week 12. Efficacy measurement was based on reduction in flea counts from baseline. Treatment was considered effective at weeks 4, 8 and 12 if mean live flea count reductions were 90% or greater and statistically significantly different (P ≤ 0.05) from counts at enrollment. In 18 investigational veterinary clinics across 11 USA states, 116 households (224 cats) were randomized to receive topical fluralaner and 45 households (87 cats) were randomized to the fipronil-methoprene combination. Fluralaner was demonstrated to be effective at 4 weeks (99.1% flea count reduction), 8 weeks (99.5%), and 12 weeks (99.0%), and all reductions were significantly different from the enrollment count (all P fluralaner topical treatment was safe in cats and was highly effective in killing fleas over the subsequent 12 weeks.
Hunt, John; Jennions, Michael D; Spyrou, Nicolle; Brooks, Robert
2006-09-01
Although the trade-off between reproductive effort and longevity is central to both sexual selection and evolutionary theories of aging, there has been little synthesis between these fields. Here, we selected directly on adult longevity of male field crickets Teleogryllus commodus and measured the correlated responses of age-dependent male reproductive effort, female lifetime fecundity, and several other life-history traits. Male longevity responded significantly to five generations of divergent selection. Males from downward-selected lines commenced calling sooner and reached their peak calling effort at a younger age. They called more per night and, despite living less than half as long, called more overall than males selected for increased longevity. Females from the downward-selected lines lived significantly shorter lives than females from the upward-selected lines but still produced the same number of offspring. Nymph survival, development time, and body size and weight at eclosion did not show significant correlated response to selection on male longevity, despite evidence for substantial genetic variation in each of these traits. Collectively, our findings directly support the antagonistic pleiotropy model of aging and suggest an important role for sexual selection in the aging process.
Pesticides selectivity list to beneficial arthropods in four field vegetable crops.
Hautier, L; Jansen, J P; Mabon, N; Schiffers, B
2007-01-01
Selectivity of pesticides to beneficial arthropods is a key data for the implementation of IPM program. In the context of field vegetables crop, a set of 16 fungicides, 17 herbicides and 14 insecticides commonly used in Belgium were tested on 5 indicator species: the parasitic hymenoptera Aphidius rhopalosiphi (De Stefani-Perez) (Hym., Aphidiidae), the aphid foliage dwelling predators Adalia bipunctata (L.) (Col., Coccinellidae) and Episyrphus balteatus (Dipt., Syrphidae) and the ground-dwelling predators Aleochara bilineata (Col., Staphyllinidae) and Bembidion lampros (Col., Carabidae). Pesticides were tested according a testing scheme including a first assessment on inert substrate (glass plates for adults of A. rhopalosiphi, larvae of A. bipunctata and E. balteatus, sand on adults of A. bilineata and B. lampros) and, for product that were toxic, a second assessment on natural substrate (barley seedlings for A. rhopalosiphi, french bean plants for A. bipunctato and E. balteatus and two type of soil for 8. lampros and A. bilineato). The effects of the product were assessed on basis on mortality, except for A. bilineata (Onion fly pupae parasitism). According to the final results obtained at the end of this testing scheme, the product were listed in toxicity class: green list if effect < or =30%, yellow list 30% < effect < 60% and orange list 60% < effect < or =80%. Products with toxicity higher than 80% on plants or on soils, or that reduce parasitism more than 80% on soil were put in red list and are not recommended for IPM. Results showed that all fungicides and herbicides were included in the green list except tebuconazole and boscalid + pyraclostrobin that were labeled as yellow for A. bipunctata. In opposite, no foliar insecticide was totally selective for all beneficial tested. However some products are in green list for one or several species. Soil insecticides were all are very toxic for ground dwelling arthropods and classed in red list. All results
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
Near-field short correlation in optical waves transmitted through random media
Emiliani, V.; Intonti, F.; caza, M.; Wiersma, D.S.; Colocci, M.; Aliev, F.; Lagendijk, Aart
2003-01-01
Two-dimensional near-field images of light transmitted through a disordered dielectric structure have been measured for two probe wavelengths. From these data, the 2D spatial dependence of the intensity correlation function, C(¿R¿), has been extracted. We observe that the spatial dependence of C is
On the Gibbsian Nature of the Random Field Kac Model under Block-Averaging
Külske, Christof
2001-01-01
We consider the Kac–Ising model in an arbitrary configuration of local magnetic fields η=(ηi)i ∈ Zd, in any dimension d, at any inverse temperature. We investigate the Gibbs properties of the ‘renormalized’ infinite volume measures obtained by block averaging any of the Gibbs-measures corresponding
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.
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.
N. Renders (Nicole); Y. Romling; A.F. van Belkum (Alex); H.A. Verbrugh (Henri)
1996-01-01
textabstractEighty-seven strains of Pseudomonas aeruginosa were typed by random amplification of polymorphic DNA (RAPD) and pulsed-field gel electrophoresis (PFGE) of macrorestriction fragments. Stains were clustered on the basis of interpretative criteria as presented
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.
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}ȯ )∼ 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.
[A new type of electrochemical immunosensor based on ion-selective field effect transistors].
Starodub, V M
1999-01-01
A new type of an electrochemical sensor based on the use of ion-selective field effect transistors (ISFETs) and conjugates of horse radish peroxidase with specific monoclonal antibodies was developed for the express determination of myoglobine in a solution. For this purpose a simple method of covalent immobilization of myoglobine on the surface of ISFET gate was worked out, an appropriate biochemical approach which allowed potentiometrical registration of the peroxidase activity was used, and an immune chemical analysis was accomplished in competitive way. It was shown that the sensitivity of the analysis with the help of the electrochemical immune sensor corresponds to the demands of medical practice to reveal early stages of myocardial infarction. This sensitivity was significantly higher then that which can be obtained by the traditional ELISA-method. Moreover, overall time of the analysis by the immune sensor was almost one order shorter than this by the ELISA-method. It is concluded that the proposed electrochemical immune sensor based on the ISFETs was very perspective for the express analysis of the level of different types of antigens and antibodies.
Conrod, Patricia J; O'Leary-Barrett, Maeve; Newton, Nicola; Topper, Lauren; Castellanos-Ryan, Natalie; Mackie, Clare; Girard, Alain
2013-03-01
Selective school-based alcohol prevention programs targeting youth with personality risk factors for addiction and mental health problems have been found to reduce substance use and misuse in those with elevated personality profiles. To report 24-month outcomes of the Teacher-Delivered Personality-Targeted Interventions for Substance Misuse Trial (Adventure trial) in which school staff were trained to provide interventions to students with 1 of 4 high-risk (HR) profiles: anxiety sensitivity, hopelessness, impulsivity, and sensation seeking and to examine the indirect herd effects of this program on the broader low-risk (LR) population of students who were not selected for intervention. Cluster randomized controlled trial. Secondary schools in London, United Kingdom. A total of 1210 HR and 1433 LR students in the ninth grade (mean [SD] age, 13.7 [0.33] years). Schools were randomized to provide brief personality-targeted interventions to HR youth or treatment as usual (statutory drug education in class). Participants were assessed for drinking, binge drinking, and problem drinking before randomization and at 6-monthly intervals for 2 years. Two-part latent growth models indicated long-term effects of the intervention on drinking rates (β = -0.320, SE = 0.145, P = .03) and binge drinking rates (β = -0.400, SE = 0.179, P = .03) and growth in binge drinking (β = -0.716, SE = 0.274, P = .009) and problem drinking (β = -0.452, SE = 0.193, P = .02) for HR youth. The HR youth were also found to benefit from the interventions during the 24-month follow-up on drinking quantity (β = -0.098, SE = 0.047, P = .04), growth in drinking quantity (β = -0.176, SE = 0.073, P = .02), and growth in binge drinking frequency (β = -0.183, SE = 0.092, P = .047). Some herd effects in LR youth were observed, specifically on drinking rates (β = -0.259, SE = 0.132, P = .049) and growth of binge drinking (β = -0.244, SE = 0.073, P = .001), during the 24-month follow-up. Findings further
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...
López-Caniego, M.; González-Nuevo, J.; Massardi, M.; Bonavera, L.; Herranz, D.; Negrello, M.; De Zotti, G.; Carrera, F. J.; Danese, L.; Fleuren, S.; Hardcastle, M.; Jarvis, M. J.; Klöckner, H.-R.; Mauch, T.; Procopio, P.; Righini, S.; Sutherland, W.; Auld, R.; Baes, M.; Buttiglione, S.; Clark, C. J. R.; Cooray, A.; Dariush, A.; Dunne, L.; Dye, S.; Eales, S.; Hopwood, R.; Hoyos, C.; Ibar, E.; Ivison, R. J.; Maddox, S.; Valiante, E.
2013-04-01
The Herschel-Astrophysical Terahertz Large Area Survey (H-ATLAS) provides an unprecedented opportunity to search for blazars at sub-mm wavelengths. We cross-matched the Faint Images of the Radio Sky at Twenty-cm (FIRST) radio source catalogue with the 11 655 sources brighter than 35 mJy at 500 μm in the ˜135 deg2 of the sky covered by the H-ATLAS equatorial fields at 9h and 15h, plus half of the field at 12h. We found that 379 of the H-ATLAS sources have a FIRST counterpart within 10 arcsec, including eight catalogued blazars (plus one known blazar that was found at the edge of one of the H-ATLAS maps). To search for additional blazar candidates we have devised new diagnostic diagrams and found that known blazars occupy a region of the log (S500 μm/S350 μm) versus log (S500 μm/S1.4 GHz) plane separated from that of sub-mm sources with radio emission powered by star formation, but shared with radio galaxies and steep-spectrum radio quasars. Using this diagnostic we have selected 12 further possible candidates that turn out to be scattered in the (r - z) versus (u - r) plane or in the Wide-Field Infrared Survey Explorer colour-colour diagram, where known blazars are concentrated in well defined strips. This suggests that the majority of them are not blazars. Based on an inspection of all the available photometric data, including unpublished VISTA Kilo-degree Infrared Galaxy survey photometry and new radio observations, we found that the spectral energy distributions (SEDs) of only one out of the 12 newly selected sources are compatible with being synchrotron dominated at least up to 500 μm, i.e. with being a blazar. Another object may consist of a faint blazar nucleus inside a bright star-forming galaxy. The possibility that some blazar hosts are endowed with active star formation is supported by our analysis of the SEDs of Planck Early Release Compact Source Catalogue blazars detected at both 545 and 857 GHz. The estimated rest-frame synchrotron peak
The random field model of the spatial distribution of heavy vehicle loads on long-span bridges
Chen, Zhicheng; Bao, Yuequan; Li, Hui
2016-04-01
A stochastic model based on Markov random field is proposed to model the spatial distribution of vehicle loads on longspan bridges. The bridge deck is divided into a finite set of discrete grid cells, each cell has two states according to whether the cell is occupied by the heavy vehicle load or not, then a four-neighbor lattice-structured undirected graphical model with each node corresponding to a cell state variable is proposed to model the location distribution of heavy vehicle loads on the bridge deck. The node potential is defined to quantitatively describe the randomness of node state, and the edge potential is defined to quantitatively describe the correlation of the connected node pair. The junction tree algorithm is employed to obtain the systematic solutions of inference problems of the graphical model. A marked random variable is assigned to each node to represent the amplitude of the total weight of vehicle applied on the corresponding cell of the bridge deck. The rationality of the model is validated by a Monte Carlo simulation of a learned model based on monitored data of a cable-stayed bridge.
Wang, Yonggang; Hui, Cong; Liu, Chong; Xu, Chao
2016-04-01
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.
Asymmetry of the Hall Conductance Fluctuations in a Random Magnetic Field
1998-06-01
and CNRS-LCMI, F-38042, Grenoble, France § Paul Scherrer Institute, CH-5232 Villigen-PSI, Switzerland ¶ Instituto de Fisica de Sao Carlos, 13560-970...samples (2 × 2 /•m×/zm) with a dimpled 2 DEG. This type of structures provides an experimental alternative for studying a spatially varying magnetic field...height of the dimples 0.1 Itm, which agrees well the experimental observations. The Hall resistance together with B-linear background reveals
Heo, Moonseong; Meissner, Paul; Litwin, Alain H; Arnsten, Julia H; McKee, M Diane; Karasz, Alison; McKinley, Paula; Rehm, Colin D; Chambers, Earle C; Yeh, Ming-Chin; Wylie-Rosett, Judith
2017-01-01
Comparative effectiveness research trials in real-world settings may require participants to choose between preferred intervention options. A randomized clinical trial with parallel experimental and control arms is straightforward and regarded as a gold standard design, but by design it forces and anticipates the participants to comply with a randomly assigned intervention regardless of their preference. Therefore, the randomized clinical trial may impose impractical limitations when planning comparative effectiveness research trials. To accommodate participants' preference if they are expressed, and to maintain randomization, we propose an alternative design that allows participants' preference after randomization, which we call a "preference option randomized design (PORD)". In contrast to other preference designs, which ask whether or not participants consent to the assigned intervention after randomization, the crucial feature of preference option randomized design is its unique informed consent process before randomization. Specifically, the preference option randomized design consent process informs participants that they can opt out and switch to the other intervention only if after randomization they actively express the desire to do so. Participants who do not independently express explicit alternate preference or assent to the randomly assigned intervention are considered to not have an alternate preference. In sum, preference option randomized design intends to maximize retention, minimize possibility of forced assignment for any participants, and to maintain randomization by allowing participants with no or equal preference to represent random assignments. This design scheme enables to define five effects that are interconnected with each other through common design parameters-comparative, preference, selection, intent-to-treat, and overall/as-treated-to collectively guide decision making between interventions. Statistical power functions for testing
Space-time models based on random fields with local interactions
Hristopulos, Dionissios T.; Tsantili, Ivi C.
2016-08-01
The analysis of space-time data from complex, real-life phenomena requires the use of flexible and physically motivated covariance functions. In most cases, it is not possible to explicitly solve the equations of motion for the fields or the respective covariance functions. In the statistical literature, covariance functions are often based on mathematical constructions. In this paper, we propose deriving space-time covariance functions by solving “effective equations of motion”, which can be used as statistical representations of systems with diffusive behavior. In particular, we propose to formulate space-time covariance functions based on an equilibrium effective Hamiltonian using the linear response theory. The effective space-time dynamics is then generated by a stochastic perturbation around the equilibrium point of the classical field Hamiltonian leading to an associated Langevin equation. We employ a Hamiltonian which extends the classical Gaussian field theory by including a curvature term and leads to a diffusive Langevin equation. Finally, we derive new forms of space-time covariance functions.
Dyrba, Martin; Grothe, Michel J; Mohammadi, Abdolreza; Binder, Harald; Kirste, Thomas; Teipel, Stefan J
2017-07-01
Alzheimer's disease (AD) is characterized by a cascade of pathological processes that can be assessed in vivo using different neuroimaging methods. Recent research suggests a systematic sequence of pathogenic events on a global biomarker level, but little is known about the associations and dependencies of distinct lesion patterns on a regional level. Markov random fields are a probabilistic graphical modeling approach that represent the interaction between individual random variables by an undirected graph. We propose the novel application of this approach to study the interregional associations and dependencies between multimodal imaging markers of AD pathology and to compare different hypotheses regarding the spread of the disease. We retrieved multimodal imaging data from 577 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative. Mean amyloid load (AV45-PET), glucose metabolism (FDG-PET), and gray matter volume (MRI) were calculated for the six principle nodes of the default mode network- a functional network of brain regions that appears to be preferentially targeted by AD. Multimodal Markov random field models were developed for three different hypotheses regarding the spread of the disease: the "intraregional evolution model", the "trans-neuronal spread" hypothesis, and the "wear-and-tear" hypothesis. The model likelihood to reflect the given data was evaluated using tenfold cross-validation with 1,000 repetitions. The most likely graph structure contained the posterior cingulate cortex as main hub region with edges to various other regions, in accordance with the "wear-and-tear" hypothesis of disease vulnerability. Probabilistic graphical models facilitate the analysis of interactions between several variables in a network model and therefore afford great potential to complement traditional multiple regression analyses in multimodal neuroimaging research.
Gras-Masse, H
2001-12-01
Effective vaccine development is now taking advantage of the rapidly accumulating information concerning the molecular basis of a protective immune response. Analysts and medicinal chemists have joined forces with immunologists and taken up the clear challenge of identifying immunologically active structural elements and synthesizing them in pure, reproducible forms. Current literature reveals the growing interest for extremely reductionist approaches aiming at producing totally synthetic vaccines that would be fully defined at the molecular level and particularly safe. The sequential information contained in these formulations tends to be minimized to those epitopes which elicit neutralizing antibodies, or cell-mediated responses. In the following review, we describe some of our results in developing fully synthetic, clinically acceptable lipopeptide vaccines for inducing cytotoxic T lymphocytes (CTL) responses in randomly selected populations.
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
Directory of Open Access Journals (Sweden)
Jin Li
Full Text Available 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
Tecza, Matthias; Thatte, Niranjan; Clarke, Fraser; Freeman, David; Kosmalski, Johan
2012-09-01
HARMONI, the High Angular Resolution Monolithic Optical & Near-infrared Integral field spectrograph is one of two first-light instruments for the European Extremely Large Telescope. Over a 256x128 pixel field-of-view HARMONI will simultaneously measure approximately 32,000 spectra. Each spectrum is about 4000 spectral pixels long, and covers a selectable part of the 0.47-2.45 μm wavelength range at resolving powers of either R≍4000, 10000, or 20000. All 32,000 spectra are imaged onto eight HAWAII4RG detectors using a multiplexing scheme that divides the input field into four sub-fields, each imaged onto one image slicer that in turn re-arranges a single sub-field into two long exit slits feeding one spectrograph each. In total we require eight spectrographs, each with one HAWAII4RG detector. A system of articulated and exchangeable fold-mirrors and VPH gratings allows one to select different spectral resolving powers and wavelength ranges of interest while keeping a fixed geometry between the spectrograph collimator and camera avoiding the need for an articulated grating and camera. In this paper we describe both the field splitting and image slicing optics as well as the optics that will be used to select both spectral resolving power and wavelength range.
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.
Directory of Open Access Journals (Sweden)
Ningzhi Li
2017-06-01
Full Text Available In vivo13C 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 vivo13C-MRS is the high radio frequency (RF power necessary for heteronuclear decoupling. In the common practice of in vivo13C-MRS, alkanyl carbons are detected in the spectra range of 10–65 ppm. 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 vivo13C-MRS using coherent decoupling is often limited to low magnetic fields [<=4 Tesla (T] to keep the local and averaged specific absorption rate (SAR under the safety guidelines established by the International Electrotechnical Commission (IEC and the US Food and Drug Administration (FDA. Alternately, carboxylic/amide carbons are coupled to 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 vivo13C experiments of human brain at very high magnetic fields (such as 11.7T, where signal-to-noise ratio as well as spatial and temporal
DEFF Research Database (Denmark)
Macdonald, Thomas M; Hawkey, Chris J; Ford, Ian
2017-01-01
BACKGROUND: Selective cyclooxygenase-2 inhibitors and conventional non-selective non-steroidal anti-inflammatory drugs (nsNSAIDs) have been associated with adverse cardiovascular (CV) effects. We compared the CV safety of switching to celecoxib vs. continuing nsNSAID therapy in a European setting....... METHOD: Patients aged 60 years and over with osteoarthritis or rheumatoid arthritis, free from established CV disease and taking chronic prescribed nsNSAIDs, were randomized to switch to celecoxib or to continue their previous nsNSAID. The primary endpoint was hospitalization for non-fatal myocardial...... expected developed an on-treatment (OT) primary CV event and the rate was similar for celecoxib, 0.95 per 100 patient-years, and nsNSAIDs, 0.86 per 100 patient-years (HR = 1.12, 95% confidence interval, 0.81-1.55; P = 0.50). Comparable intention-to-treat (ITT) rates were 1.14 per 100 patient...
Critical behavior of mean-field spin glasses on a dilute random graph
DeSanctis, Luca; Barra, Adriano; Folli, Viola
2008-05-01
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.
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.
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...
Koeman, T.; Brandt, P.A. van den; Slottje, P.; Schouten, L.J.; Goldbohm, R.A.; Kromhout, H.; Vermeulen, R.
2014-01-01
Purpose: To investigate the association between exposure to occupational extremely low-frequency magnetic fields (ELF-MF) and the risk of a priori selected cancer outcomes within the prospective Netherlands Cohort Study. Methods: 120,852 men and women aged 55-69 years at time of enrollment in 1986
BIERE, A
1991-01-01
Selection on the timing of seedling emergence was investigated in an experimental population of Lychnis flos-cuculi, a perennial hay-meadow species. Seeds obtained from a full diallel cross of 8 genotypes from a field population were sown along an environment gradient that included the parental
K-Ras(G12D)-selective inhibitory peptides generated by random peptide T7 phage display technology.
Sakamoto, Kotaro; Kamada, Yusuke; Sameshima, Tomoya; Yaguchi, Masahiro; Niida, Ayumu; Sasaki, Shigekazu; Miwa, Masanori; Ohkubo, Shoichi; Sakamoto, Jun-Ichi; Kamaura, Masahiro; Cho, Nobuo; Tani, Akiyoshi
2017-03-11
Amino-acid mutations of Gly 12 (e.g. G12D, G12V, G12C) of V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (K-Ras), the most promising drug target in cancer therapy, are major growth drivers in various cancers. Although over 30 years have passed since the discovery of these mutations in most cancer patients, effective mutated K-Ras inhibitors have not been marketed. Here, we report novel and selective inhibitory peptides to K-Ras(G12D). We screened random peptide libraries displayed on T7 phage against purified recombinant K-Ras(G12D), with thorough subtraction of phages bound to wild-type K-Ras, and obtained KRpep-2 (Ac-RRCPLYISYDPVCRR-NH 2 ) as a consensus sequence. KRpep-2 showed more than 10-fold binding- and inhibition-selectivity to K-Ras(G12D), both in SPR analysis and GDP/GTP exchange enzyme assay. K D and IC 50 values were 51 and 8.9 nM, respectively. After subsequent sequence optimization, we successfully generated KRpep-2d (Ac-RRRRCPLYISYDPVCRRRR-NH 2 ) that inhibited enzyme activity of K-Ras(G12D) with IC 50 = 1.6 nM and significantly suppressed ERK-phosphorylation, downstream of K-Ras(G12D), along with A427 cancer cell proliferation at 30 μM peptide concentration. To our knowledge, this is the first report of a K-Ras(G12D)-selective inhibitor, contributing to the development and study of K-Ras(G12D)-targeting drugs. Copyright © 2017 Elsevier Inc. All rights reserved.
Khan, Hafiz Azhar Ali; Akram, Waseem; Iqbal, Naeem
2015-09-01
House flies are major insect pests at dairy farms in Pakistan and are mainly controlled with insecticides of different classes, including organophosphates. To develop a better resistance management strategy, a field strain of house flies was selected in the laboratory to study the potential for the development of resistance, possible mechanisms of resistance and cross-resistance to other insecticides. The selection of the field strain with profenofos for five consecutive generations resulted in the LC50 values to increase from 50.49 to 176.03 µg/ml, and the resistance ratio increased from 29.70 to 103.55 as compared with a laboratory-susceptible strain; however, the resistance was decreased significantly when the selected strain was reared for the next five generations without exposure to any insecticide. The profenofos-selected strain (Profen-SEL) showed cross-resistance to chlorpyrifos and deltamethrin but no cross-resistance observed to spinosad. Synergism studies with piperonyl butoxide and S,S,S-tributylphosphorotrithioate indicated that the resistance to profenofos was probably associated with esterase and, possibly, microsomal oxidase activity. Resistance to profenofos in the selected strain suggests that the resistance, owing to instability, could be overcome by switching off profenofos use for few generations in the field or by rotation with different insecticides having different modes of action. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
One-Step Recurrences for Stationary Random Fields on the Sphere
Beatson, R. K.; zu Castell, W.
2016-04-01
Recurrences for positive definite functions in terms of the space dimension have been used in several fields of applications. Such recurrences typically relate to properties of the system of special functions characterizing the geometry of the underlying space. In the case of the sphere S^{d-1} subset R^d the (strict) positive definiteness of the zonal function f(cos θ) is determined by the signs of the coefficients in the expansion of f in terms of the Gegenbauer polynomials {C^λ_n}, with λ=(d-2)/2. Recent results show that classical differentiation and integration applied to f have positive definiteness preserving properties in this context. However, in these results the space dimension changes in steps of two. This paper develops operators for zonal functions on the sphere which preserve (strict) positive definiteness while moving up and down in the ladder of dimensions by steps of one. These fractional operators are constructed to act appropriately on the Gegenbauer polynomials {C^λ_n}.
Directory of Open Access Journals (Sweden)
Xiaodan Wu
2015-11-01
Full Text Available To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS and then to identify the most representative combination (MRC. On this basis, an upscaling transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c The most representative combination (MRC combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a
Liao, Liang; Lin, Tusheng; Li, Bi; Zhang, Weidong
2008-12-01
A modified algorithm using fuzzy Gibbs random field model and fuzzy c-means (FCM) clustering is proposed for segmentation of Magnetic resonance(MR) brain images. Spatial constraints using the definitions of homogeneity of cliques and fuzzy Gibbs clique potential are introduced in this algorithm. A new modified objective function , which is established by introducing the spatial constraints into the traditional intensity based FCM algorithm, leads to the establishment of new iterative formulas for membership matrix and centroids. This algorithm can improve the performance of corresponding traditional one by modifying the original intensity based segmentation model. Experiments on synthetic images and MR phantoms show the validation of the proposed algorithm, which is usually a better alternative for segmenting medical MR images corrupted by noise.
Complete Many-Body Localization in the t-J Model Caused by a Random Magnetic Field.
Lemut, Gal; Mierzejewski, Marcin; Bonča, Janez
2017-12-15
The many body localization (MBL) of spin-1/2 fermions poses a challenging problem. It is known that the disorder in the charge sector may be insufficient to cause full MBL. Here, we study dynamics of a single hole in one dimensional t-J model subject to a random magnetic field. We show that strong disorder that couples only to the spin sector localizes both spin and charge degrees of freedom. Charge localization is confirmed also for a finite concentration of holes. While we cannot precisely pinpoint the threshold disorder, we conjecture that there are two distinct transitions. Weaker disorder first causes localization in the spin sector. Carriers become localized for somewhat stronger disorder, when the spin localization length is of the order of a single lattice spacing.
Directory of Open Access Journals (Sweden)
H. E. Schulz
2009-09-01
Full Text Available Mass transfer across a gas-liquid interface was studied theoretically and experimentally, using transfer of oxygen into water as the gas-liquid system. The experimental results support the conclusions of a theoretical description of the concentration field that uses random square waves approximations. The effect of diffusion over the concentration records was quantified. It is shown that the peak of the normalized rms concentration fluctuation profiles must be lower than 0.5, and that the position of the peak of the rms value is an adequate measure of the thickness of the diffusive layer. The position of the peak is the boundary between the regions more subject to molecular diffusion or to turbulent transport of dissolved mass.
Dong, Zhen; Wang, Jianjun; Zhou, Xin
2017-05-01
Antifreeze proteins (AFPs) are the key biomolecules that protect many species from suffering the extreme conditions. Their unique properties of antifreezing provide the potential of a wide range of applications. Inspired by the present experimental approaches of creating an antifreeze surface by coating AFPs, here we present a two-dimensional random-field lattice Ising model to study the effect of AFPs on heterogeneous ice nucleation. The model shows that both the size and the free-energy effect of individual AFPs and their surface coverage dominate the antifreeze capacity of an AFP-coated surface. The simulation results are consistent with the recent experiments qualitatively, revealing the origin of the surprisingly low antifreeze capacity of an AFP-coated surface when the coverage is not particularly high as shown in experiment. These results will hopefully deepen our understanding of the antifreeze effects and thus be potentially useful for designing novel antifreeze coating materials based on biomolecules.
Dong, Zhen; Wang, Jianjun; Zhou, Xin
2017-05-01
Antifreeze proteins (AFPs) are the key biomolecules that protect many species from suffering the extreme conditions. Their unique properties of antifreezing provide the potential of a wide range of applications. Inspired by the present experimental approaches of creating an antifreeze surface by coating AFPs, here we present a two-dimensional random-field lattice Ising model to study the effect of AFPs on heterogeneous ice nucleation. The model shows that both the size and the free-energy effect of individual AFPs and their surface coverage dominate the antifreeze capacity of an AFP-coated surface. The simulation results are consistent with the recent experiments qualitatively, revealing the origin of the surprisingly low antifreeze capacity of an AFP-coated surface when the coverage is not particularly high as shown in experiment. These results will hopefully deepen our understanding of the antifreeze effects and thus be potentially useful for designing novel antifreeze coating materials based on biomolecules.
Shenje, Justin; Millard, Peter S
2016-01-01
The World Health Organization has solicited rapid and minimally invasive techniques to facilitate scale-up of voluntary medical male circumcision (VMMC). Non-blinded randomized controlled field trial with 2:1 allocation ratio. 75 adult male volunteers. Outpatient primary care clinic. Open surgical circumcision under local anesthetic with suturing vs. Unicirc disposable instrument under topical anesthetic and wound sealing with cyanoacrylate tissue adhesive. Intraoperative duration. Intraoperative and postoperative pain; adverse events; time to healing; patient satisfaction; cosmetic result. The intraoperative time was less with the Unicirc technique (median 12 vs. 25 min, p Wound healing and cosmetic results were superior in the Unicirc group. Adverse events were similar in both groups. VMMC with Unicirc under topical anesthetic and wound sealing with cyanoacrylate tissue adhesive is rapid, heals by primary intention with superior cosmetic results, and is potentially safer and more cost-effective than open surgical VMMC. Clinicaltrials.gov NCT02443792.
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...... (WOMAC) questionnaire. RESULTS: Within group analysis revealed a significant improvement in ADL, stiffness and pain in the PEMF-treated group at all evaluations. In the control group there was no effect on ADL after 2 weeks and a weak significance was seen after 6 and 12 weeks. Significant effects were...... years using between group analysis revealed a significant improvement for stiffness on treated knee after 2 weeks, but this effect was not observed for ADL and pain. CONCLUSIONS: Applying between group analysis we were unable to demonstrate a beneficial symptomatic effect of PEMF in the treatment...
Directory of Open Access Journals (Sweden)
Elena Tutubalina
2017-01-01
Full Text Available Adverse drug reactions (ADRs are an essential part of the analysis of drug use, measuring drug use benefits, and making policy decisions. Traditional channels for identifying ADRs are reliable but very slow and only produce a small amount of data. Text reviews, either on specialized web sites or in general-purpose social networks, may lead to a data source of unprecedented size, but identifying ADRs in free-form text is a challenging natural language processing problem. In this work, we propose a novel model for this problem, uniting recurrent neural architectures and conditional random fields. We evaluate our model with a comprehensive experimental study, showing improvements over state-of-the-art methods of ADR extraction.
Directory of Open Access Journals (Sweden)
Oksana Synekop
2017-09-01
Full Text Available In conditions of differentiation the learning materials selection will optimize the training English for Specific Purposes of the future professionals in the field of information technology at university level. The purpose of the article is to define the basic unit of learning material, the factors of influence on the learning material selection, principles, criteria and the procedure of learning material selection in this paper. Reviewing the scientific achievements in the learning material selection in teaching English has become a basis for defining the factors of influence, principles and criteria in the research. The basic unit of learning material (learning English text for professional purposes is outlined. The factors of influence and principles (correspondence of learning materials to professional interests and needs of information technology students; necessary ability and accessibility; regarding the linguistic and stylistic necessity and sufficiency; availability of Internet sources information of the learning material selection are defined. Also, the qualitative criteria (authenticity; professional significance, relevance and informativeness; conformity of foreign language level and intellectual development of students; variety of genres and forms of speech, their sufficient filling by linguistic material; coherence, integrity, consistency, semantic completeness; topic conformity; situation conformity; unlimited access, reliability and exemplarity of Internet sources and the quantitative criteria (the amount of material of the learning material selection are highlighted. The process of English for Specific Purposes material selection (defining the disciplines of different cycles; defining spheres and related topics; outlining situations, communicative roles and intentions of professional communication; specifying the sources of selection; evaluating the texts; analysis of the knowledge, skills and sub-skills required for the
Seed treatment with selected plant growth‐promoting rhizobacteria increases maize yield in the field
National Research Council Canada - National Science Library
Breedt, G; Labuschagne, N; Coutinho, T.A
2017-01-01
.... The beneficial effects of plant growth‐promoting rhizobacteria on crop growth and yield have been well documented, but obtaining reproducible results under field conditions is often difficult...
SU-E-T-368: Effect of a Strong Magnetic Field On Select Radiation Dosimeters
Energy Technology Data Exchange (ETDEWEB)
Mathis, M; Wen, Z; Tailor, R; Sawakuchi, G; Flint, D; Beddar, S; Ibbott, G [The University of Texas MD Anderson Cancer Center, Houston, TX (United States)
2014-06-01
Purpose: To determine the effect of a strong magnetic field on TLD-100, OSLD (Al{sub 2}O{sub 2}:C), and PRESAGE dosimetry devices. This study will help to determine which types of dosimeters can be used for quality assurance and in-vivo dosimetry measurements in a magnetic resonance imaginglinear accelerator (MRI-linac) system. Methods: The dosimeters were separated into two categories which were either exposed or not exposed to a strong magnetic field. In each category a set of dosimeters was irradiated with 0, 2, or 6 Gy. To expose the dosimeters to a magnetic field the samples in that category were place in a Bruker small animal magnetic resonance scanner at a field strength slightly greater than 2.5 T for at least 1 hour preirradiation and at least 1 hour post-irradiation. Irradiations were performed with a 6 MV x-ray beam from a Varian TrueBeam linac with 10×10 cm{sup 2} field at a 600 MU/min dose rate. The samples that received no radiation dose were used as control detectors. Results: The readouts of the dosimeters which were not exposed to a strong magnetic field were compared with the measurements of the dosimetry devices which were exposed to a magnetic field. No significant differences (less than 2% difference) in the performance of TLD, OSLD, or PRESAGE dosimeters due to exposure to a strong magnetic field were observed. Conclusion: Exposure to a strong magnetic field before and after irradiation does not appear to change the dosimetric properties of TLD, OSLD, or PRESAGE which indicates that these dosimeters have potential for use in quality assurance and in-vivo dosimetry in a MRI-linac. We plan to further test the effect of magnetic fields on these devices by irradiating them in the presence of a magnetic fields similar to those produced by a MRI-linac system. Elekta-MD Anderson Cancer Center Research Agreement.
Directory of Open Access Journals (Sweden)
Poeze Martijn
2011-05-01
Full Text Available Abstract Background The scaphoid bone is the most commonly fractured of the carpal bones. In the Netherlands 90% of all carpal fractures is a fracture of the scaphoid bone. The scaphoid has an essential role in functionality of the wrist, acting as a pivot. Complications in healing can result in poor functional outcome. The scaphoid fracture is a troublesome fracture and failure of treatment can result in avascular necrosis (up to 40%, non-union (5-21% and early osteo-arthritis (up to 32% which may seriously impair wrist function. Impaired consolidation of scaphoid fractures results in longer immobilization and more days lost at work with significant psychosocial and financial consequences. Initially Pulsed Electromagnetic Fields was used in the treatment of tibial pseudoarthrosis and non-union. More recently there is evidence that physical forces can also be used in the treatment of fresh fractures, showing accelerated healing by 30% and 71% reduction in nonunion within 12 weeks after initiation of therapy. Until now no double blind randomized, placebo controlled trial has been conducted to investigate the effect of this treatment on the healing of fresh fractures of the scaphoid. Methods/Design This is a multi center, prospective, double blind, placebo controlled, randomized trial. Study population consists of all patients with unilateral acute scaphoid fracture. Pregnant women, patients having a life supporting implanted electronic device, patients with additional fractures of wrist, carpal or metacarpal bones and pre-existing impairment in wrist function are excluded. The scaphoid fracture is diagnosed by a combination of physical and radiographic examination (CT-scanning. Proven scaphoid fractures are treated with cast immobilization and a small Pulsed Electromagnetic Fields bone growth stimulating device placed on the cast. Half of the devices will be disabled at random in the factory. Study parameters are clinical consolidation
Klinger, Emmanuel; Sargsyan, Armen; Tonoyan, Ara; Hakhumyan, Grant; Papoyan, Aram; Leroy, Claude; Sarkisyan, David
2017-08-01
Magnetic field-induced giant modification of the probabilities of five transitions of 5S1 / 2,Fg = 2 → 5P3 / 2,Fe = 4 of 85Rb and three transitions of 5S1 / 2,Fg = 1 → 5P3 / 2,Fe = 3 of 87Rb forbidden by selection rules for zero magnetic field has been observed experimentally and described theoretically for the first time. For the case of excitation with circularly-polarized (σ+) laser radiation, the probability of Fg = 2,mF = - 2 → Fe = 4,mF = - 1 transition becomes the largest among the seventeen transitions of 85Rb Fg = 2 → Fe = 1,2,3,4 group, and the probability of Fg = 1, mF = - 1 → Fe = 3,mF = 0 transition becomes the largest among the nine transitions of 87Rb Fg = 1 → Fe = 0,1,2,3 group, in a wide range of magnetic field 200-1000 G. Complete frequency separation of individual Zeeman components was obtained by implementation of derivative selective reflection technique with a 300 nm-thick nanocell filled with Rb, allowing formation of narrow optical resonances. Possible applications are addressed. The theoretical model is well consistent with the experimental results.
DEFF Research Database (Denmark)
Lerchner, Alexander; Sterner, G.; Hertz, J.
2006-01-01
We present a complete mean field theory for a balanced state of a simple model of an orientation hypercolumn, with a numerical procedure for solving the mean-field equations quantitatively. With our treatment, one can determine self-consistently both the firing rates and the firing correlations...
Radiological impact of oil and Gas Activities in selected oil fields in ...
African Journals Online (AJOL)
MICHAEL HORSFALL
Keywords: Radiological impact, Oil and Gas facilities, oil field, ionizing radiation levels. ABSTRACT: A study of the radiological impact ... 0.031±0.01mRh-1 at the Otorogu gas plant. Mean field exposure ... results show that the radiation levels for the Ughelli East, Kokori, Eriemu, Evwreni, Eriemu,. Oweh, Olomoro-Oleh oil and ...
Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field
Directory of Open Access Journals (Sweden)
Hong Sun
2013-05-01
Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.
Le Maitre, Olivier
2015-01-07
We address model dimensionality reduction in the Bayesian inference of Gaussian fields, considering prior covariance function with unknown hyper-parameters. The Karhunen-Loeve (KL) expansion of a prior Gaussian process is traditionally derived assuming fixed covariance function with pre-assigned hyperparameter values. Thus, the modes strengths of the Karhunen-Loeve expansion inferred using available observations, as well as the resulting inferred process, dependent on the pre-assigned values for the covariance hyper-parameters. Here, we seek to infer the process and its the covariance hyper-parameters in a single Bayesian inference. To this end, the uncertainty in the hyper-parameters is treated by means of a coordinate transformation, leading to a KL-type expansion on a fixed reference basis of spatial modes, but with random coordinates conditioned on the hyper-parameters. A Polynomial Chaos (PC) expansion of the model prediction is also introduced to accelerate the Bayesian inference and the sampling of the posterior distribution with MCMC method. The PC expansion of the model prediction also rely on a coordinates transformation, enabling us to avoid expanding the dependence of the prediction with respect to the covariance hyper-parameters. We demonstrate the efficiency of the proposed method on a transient diffusion equation by inferring spatially-varying log-diffusivity fields from noisy data.
Directory of Open Access Journals (Sweden)
Jean-François Feller
2014-01-01
Full Text Available Different grades of chemically functionalized carbon nanotubes (CNT have been processed by spraying layer-by-layer (sLbL to obtain an array of chemoresistive transducers for volatile organic compound (VOC detection. The sLbL process led to random networks of CNT less conductive, but more sensitive to vapors than filtration under vacuum (bucky papers. Shorter CNT were also found to be more sensitive due to the less entangled and more easily disconnectable conducting networks they are making. Chemical functionalization of the CNT’ surface is changing their selectivity towards VOC, which makes it possible to easily discriminate methanol, chloroform and tetrahydrofuran (THF from toluene vapors after the assembly of CNT transducers into an array to make an e-nose. Interestingly, the amplitude of the CNT transducers’ responses can be enhanced by a factor of five (methanol to 100 (chloroform by dispersing them into a polymer matrix, such as poly(styrene (PS, poly(carbonate (PC or poly(methyl methacrylate (PMMA. COOH functionalization of CNT was found to penalize their dispersion in polymers and to decrease the sensors’ sensitivity. The resulting conductive polymer nanocomposites (CPCs not only allow for a more easy tuning of the sensors’ selectivity by changing the chemical nature of the matrix, but they also allow them to adjust their sensitivity by changing the average gap between CNT (acting on quantum tunneling in the CNT network. Quantum resistive sensors (QRSs appear promising for environmental monitoring and anticipated disease diagnostics that are both based on VOC analysis.
Meadows, Cheyney; Guerino, Frank; Sun, Fangshi
2017-01-19
Orally administered fluralaner effectively controls fleas and ticks on dogs for 12 weeks. This study evaluates the flea control efficacy achieved with topically applied fluralaner in dogs. This investigator-blinded, multi-center randomized, positive controlled study evaluated flea control efficacy in dogs following a single owner-applied treatment of topical fluralaner. A positive control group received three treatments, at 4-week intervals, of a commercial formulation of fipronil/(S)-methoprene. All dogs in households randomized to the fluralaner group were dispensed an initial treatment at enrollment and a second treatment at week 12 for an additional 3-week observation of treatment safety. Households with up to five healthy dogs, all at least 12 weeks of age and weighing at least 2 kg (4.4 lb), were randomized in a ratio of 3:1 of fluralaner to positive control. Within households, one primary dog with at least 10 live fleas at enrollment was randomly selected. Flea counts were performed on all primary dogs every 4 weeks through week 12. Efficacy measurement was based on reduction from baseline flea counts. Treatment was considered effective if geometric mean live flea count reductions at weeks 4, 8, and 12 were 90% or greater and significantly different from counts at enrollment. In addition, for each time point the arithmetic mean live flea counts, the efficacy based on arithmetic means, the number and percentage of dogs with at least a 90% reduction in flea count, and the number and percentage of flea free dogs were calculated. Statistical comparisons were also made between treatment groups. At 12 sites, across 10 states, 121 households (221 dogs) were randomized to receive fluralaner and 44 households (100 dogs) were randomized to receive the positive control. Fluralaner was demonstrated to be significantly effective (all P ≤ 0.0001) at 4 weeks (99.8% reduction), 8 weeks (99.9%), and 12 weeks (99.9%). The positive control was significantly
Gregovich, A.; Feinberg, J. M.; Steffen, A.; Sternberg, R. S.
2014-12-01
Stone tools are one of the most enduring forms of ancient human behavior available to anthropologists. The geologic materials that comprise stone tools are a reflection of the rocks that were available locally or through trade, as are the intended use of the tools and the knapping technology needed to produce them. Investigation of the rock magnetic and geochemical characteristics of the artifacts and the geological source materials provides a baseline to explore these past behaviors. This study uses rock magnetic properties to explore the raw material selection criteria involved in the production of obsidian tools in the region around Valles Caldera in northern New Mexico. Obsidian is locally abundant and was traded by tribes across the central United States. Here we compare the rock magnetic properties of a sample of obsidian projectile points (N =25) that have been geochemically sourced to the Cerro Toledo obsidian flow with geological samples collected from four sites within the same flow (N =135). This collection of archaeological artifacts, albeit small, contains representatives of at least 8 different point styles that were used over 6000 years from the Archaic into the Late Prehistoric. Bulk rock hysteresis parameters (Mr, Ms, Bc, and Bcr) and low-field susceptibility (Χ) measurements show that the projectile points generally contain a lower concentration of magnetic minerals than the geologic samples. For example, the artifacts' median Ms value is 2.9 x 10-3 Am2kg-1, while that of the geological samples is 6.5 x 10-3 Am2kg-1. The concentration of magnetic minerals in obsidian is a proxy for the concentration of microlites in general, and this relationship suggests that although obsidian was locally abundant, toolmakers employed non-random selection criteria resulting in generally lower concentrations of microlites in their obsidian tools.
[The effect of low magnetic field on select parameters of blood coagulation].
Ciejka, Elzbieta; Goraca, Anna; Michalska, Marta; Kostka, Barbara
2005-08-01
Low frequency magnetic field causes the biological effects in organisms--in individual systems and organs. The purpose of our study is to analyse the influence of the low magnetic field used in magnetotherapy on prothrombin time, factor Xa activity and level of platelets in experimental animals. The examination was carried out on rats which were subjected to the activity of low magnetic field. The examination of prothrombin time in Quick's method (the international normalized ratio--INR was counted), activity of factor Xa by spectrophotometric method (lambda = 405 nm) were performed. The level of platelets before and after 14, 28 days of the exposition of magnetic field and after 21 days of exposure to magnetic field was assessed. The extension of prothrombin time (a decrease of INR), decrease activity of factor Xa and decrease platelets level was observed in experimental animals after the exposure to low magnetic field (p parameters). Low magnetic field used in magnetotherapy causes the changes in blood coagulation of experimental animals.
Energy Technology Data Exchange (ETDEWEB)
Crosta, Dante; Elitseche, Luis [Repsol YPF (Argentina); Gutierrez, Mauricio; Ansah, Joe; Everett, Don [Halliburton Argentina S.A., Buenos Aires (Argentina)
2004-07-01
Minimizing the amount of unwanted water production is an important goal at the Barrancas field. This paper describes a selection process for candidate injection wells that is part of a pilot conformance project aimed at improving vertical injection profiles, reducing water cut in producing wells, and improving ultimate oil recovery from this field. The well selection process is based on a review of limited reservoir information available for this field to determine inter-well communications. The methodology focuses on the best use of available information, such as production and injection history, well intervention files, open hole logs and injectivity surveys. After the candidate wells were selected and potential water injection channels were identified, conformance treatment design and future performance of wells in the selected pilot area were evaluated using a new 3 -D conformance simulator, developed specifically for optimization of the design and placement of unwanted fluid shut-off treatments. Thus, when acceptable history match ing of the pilot area production was obtained, the 3 -D simulator was used to: evaluate the required volume of selected conformance treatment fluid; review expected pressures and rates during placement;. model temperature behavior; evaluate placement techniques, and forecast water cut reduction and incremental oil recovery from the producers in this simulated section of the pilot area. This paper outlines a methodology for selecting candidate wells for conformance treatments. The method involves application of several engineering tools, an integral component of which is a user-friendly conformance simulator. The use of the simulator has minimized data preparation time and allows the running of sensitivity cases quickly to explore different possible scenarios that best represent the reservoir. The proposed methodology provides an efficient means of identifying conformance problems and designing optimized solutions for these individual
Directory of Open Access Journals (Sweden)
Sung-Chul Yun
2014-09-01
Full Text Available KYC 3262 was selected as a biocontrol agent against anthracnose on hot pepper from 813 extracts of myxobacterial isolates. Dual culture with Colletotrichum acutatum and 813 myxobacterial extracts was conducted, and 19 extracts were selected that inhibited germination and mycelial growth of C. acutatum. All selections were Sorangium cellulosum, which are cellulolytic myxobacteria from soil. With the infection bioassay on detached fruits in airtight containers, KYC 3262, KYC 3512, KYC 3279, and KYC 3584 were selected. The listed four myxobacteria were cultured in CSG/1 liquid media, and harvested filtrates were sprayed on the infected fruits. KYC 3262 was selected from the studies of attached fruit in a greenhouse study. KYC 3262 filtrate was applied for 3 years (from 2011 to 2013 in a field study in Asan, Republic of Korea. Control values of the KYC 3262 in the field were 31%, 89%, and 82% in 2011, 2012, and 2013, whereas values of the fungicide spray treatment were 19%, 97%, and 91%, respectively. Yields (kg/20 plants of the KYC 3262 were 2.66 kg and 18.6 kg in 2011 and 2013, respectively, and those of the fungicide treatment were 2.0 kg and 20.2 kg, in 2011 and 2013, respectively.
Boyer, Stéphane; Rivault, Colette
2006-01-01
Selection of habitat has a profound influence on interactions among species and the assembly of ecological communities. We investigated habitat preferences to understand how different cockroach species coexist in sugar-cane fields on Réunion island. Cockroach populations belonging to a guild of seven species were surveyed during one annual cycle in eight sugar-cane fields that differed by several environmental factors, in order to investigate ecological features of cockroach species and their patterns of coexistence. Structure variations of the cockroach communities were analyzed at the field scale, at the sample unit scale, and according to variations of environmental conditions related to the annual sugar-cane growth cycle. A canonical correspondence analysis (CCA) was used to elucidate relationships between species diversity, population abundance and environmental characteristics. The examination of partitioning at different spatial and temporal scales evidenced that each species occupied a particular type of habitat. The main factors influencing spatial habitat selection were at the sample unit scale: presence of ants, edge effect, soil moisture and granulometry, at the field scale: irrigation, annual rainfall, altitude and age of the field. Although a pair of species shared the same type of habitat, annual population peaks of each species did not coincide in time. This suggests that resource partitioning is based both on ecological factors and interspecific competition. Factors enhancing cockroach coexistence and factors favoring population outbursts are discussed as well as specific invasive capacities of these cockroaches and the role of the cockroach community in the sugar-cane trophic web.
Directory of Open Access Journals (Sweden)
Fuqun Zhou
2016-10-01
Full Text Available Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS. It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2–3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests’ features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.
Rochman, Auliya Noor; Prasetyo, Hari; Nugroho, Munajat Tri
2017-06-01
Vehicle Routing Problem (VRP) often occurs when the manufacturers need to distribute their product to some customers/outlets. The distribution process is typically restricted by the capacity of the vehicle and the working hours at the distributor. This type of VRP is also known as Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A Biased Random Key Genetic Algorithm (BRKGA) was designed and coded in MATLAB to solve the CVRPTW case of soft drink distribution. The standard BRKGA was then modified by applying chromosome insertion into the initial population and defining chromosome gender for parent undergoing crossover operation. The performance of the established algorithms was then compared to a heuristic procedure for solving a soft drink distribution. Some findings are revealed (1) the total distribution cost of BRKGA with insertion (BRKGA-I) results in a cost saving of 39% compared to the total cost of heuristic method, (2) BRKGA with the gender selection (BRKGA-GS) could further improve the performance of the heuristic method. However, the BRKGA-GS tends to yield worse results compared to that obtained from the standard BRKGA.
Directory of Open Access Journals (Sweden)
Xin Ma
2015-01-01
Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.
Biglar, Mahmood; Soltani, Khadijeh; Nabati, Farzaneh; Bazl, Roya; Mojab, Faraz; Amanlou, Massoud
2012-01-01
Helicobacter pylori (H. pylori) infection leads to different clinical and pathological outcomes in humans, including chronic gastritis, peptic ulcer disease and gastric neoplasia and even gastric cancer and its eradiation dependst upon multi-drug therapy. The most effective therapy is still unknown and prompts people to make great efforts to find better and more modern natural or synthetic anti-H. pylori agents. In this report 21 randomly selected herbal methanolic extracts were evaluated for their effect on inhibition of Jack-bean urease using the indophenol method as described by Weatherburn. The inhibition potency was measured by UV spectroscopy technique at 630 nm which attributes to released ammonium. Among these extracts, five showed potent inhibitory activities with IC50 ranges of 18-35 μg/mL. These plants are Matricaria disciforme (IC50:35 μg/mL), Nasturtium officinale (IC50:18 μg/mL), Punica granatum (IC50:30 μg/mL), Camelia sinensis (IC50:35 μg/mL), Citrus aurantifolia (IC50:28 μg/mL).
Lee, Christine M; Neighbors, Clayton; Kilmer, Jason R; Larimer, Mary E
2010-06-01
Despite clear need, brief web-based interventions for marijuana-using college students have not been evaluated in the literature. The current study was designed to evaluate a brief, web-based personalized feedback intervention for at-risk marijuana users transitioning to college. All entering first-year students were invited to complete a brief questionnaire. Participants meeting criteria completed a baseline assessment (N = 341) and were randomly assigned to web-based personalized feedback or assessment-only control conditions. Participants completed 3-month (95.0%) and 6-month (94.4%) follow-up assessments. Results indicated that although there was no overall intervention effect, moderator analyses found promising effects for those with a family history of drug problems and, to a smaller extent, students who were higher in contemplation of changing marijuana use at baseline. Implications of these findings for selective intervention of college marijuana use and web-based interventions in general are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
Zhou, Fuqun; Zhang, Aining
2016-10-25
Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2-3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests' features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.
GATEWAY Demonstrations: Long-Term Evaluation of SSL Field Performance in Select Interior Projects
Energy Technology Data Exchange (ETDEWEB)
Davis, Tess E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Davis, Robert G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wilkerson, Andrea M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2017-02-28
The GATEWAY program evaluated the long-term performance characteristics (chromaticity change, maintained illuminance, and operations and maintenance) of LED lighting systems in four field installations previously documented in separate DOE GATEWAY reports.
Depth-of-field enhancement in integral imaging by selective depth-deconvolution
Navarro Fructuoso, Héctor; Saavedra Tortosa, Genaro; Martínez Corral, Manuel; Sjöström, Marten; Olsson, Roger
2014-01-01
One of the major drawbacks of the integral imaging technique is its limited depth of field. Such limitation is imposed by the numerical aperture of the microlenses. In this paper, we propose a method to extend the depth of field of integral imaging systems in the reconstruction stage. The method is based on the combination of deconvolution tools and depth filtering of each elemental image using disparity map information. We demonstrate our proposal presenting digital reconstructions of a 3-D ...
Aboud, Frances E; Moore, Anna C; Akhter, Sadika
2008-10-01
Responsive complementary feeding, whereby the mother feeds her child in response to child cues of hunger state and psychomotor abilities, is a problem in some countries, and likely contributes to malnutrition. Interventions are needed to evaluate whether promoting responsive feeding would add any benefit. Using a cluster randomized field trial, we evaluated a six-session educational programme that emphasized practice of two key behaviours, namely child self-feeding and maternal responsiveness. One hundred mothers and their 12- to 24-month-olds attended the sessions as part of village clusters randomly assigned to the intervention group. A similar number of controls received sessions on foods to feed and nutritional disorders. Outcomes assessed at pre-test, 2-week post-intervention and again 5-months post-intervention included weight, mouthfuls of food taken, self-feeding and maternal responsiveness. Research assistants, blind to group assignment, observed and coded mother and child behaviours during the midday meal. Secondary measures included foods fed and feeding messages recalled. Analysis was based on intention to treat and accounted for clustering. Only 10% of each group was lost to follow-up. Weight (d = 0.28), weight gain (d = 0.48) and child self-feeding (d = 0.30) were significantly higher in the responsive feeding group. Mouthfuls of food eaten and maternal responsiveness were not significantly increased by the intervention. Mothers in the intervention gave their children more vegetables, and spontaneously recalled more feeding messages at the 5-month follow-up. These results provide evidence that self-feeding and weight gain can improve by targeting specific behaviours, while maternal responsiveness may require more intensive strategies.
Ozansoy Kasap, Berna; Marchenko, Svitlana V.; Soldatkin, Oleksandr O.; Dzyadevych, Sergei V.; Akata Kurc, Burcu
2017-01-01
The combination of advantages of using zeolites and gold nanoparticles were aimed to be used for the first time to improve the characteristic properties of ion selective field-effect transistor (ISFET)-based creatinine biosensors. The biosensors with covalently cross-linked creatinine deiminase using glutaraldehyde (GA) were used as a control group, and the effect of different types of zeolites on biosensor responses was investigated in detail by using silicalite, zeolite beta (BEA), nano-siz...
The purpose of this study was to evaluate whether the measurement of Escherichia coli levels at two points during the chicken slaughter process has utility as a measure of quality control. A one year long survey was conducted during 2004 and 2005 in 20 randomly selected United States chicken slaught...
Malhotra-Kumar, Surbhi; Van Heirstraeten, Liesbet; Coenen, Samuel; Lammens, Christine; Adriaenssens, Niels; Kowalczyk, Anna; Godycki-Cwirko, Maciek; Bielicka, Zuzana; Hupkova, Helena; Lannering, Christina; Mölstad, Sigvard; Fernandez-Vandellos, Patricia; Torres, Antoni; Parizel, Maxim; Ieven, Margareta; Butler, Chris C.; Verheij, Theo; Little, Paul; Goossens, Hermanon; Frimodt-Møller, Niels; Bruno, Pascale; Hering, Iris; Lemiengre, Marieke; Loens, Katherine; Malmvall, Bo Eric; Muras, Magdalena; Romano, Nuria Sanchez; Prat, Matteu Serra; Svab, Igor; Swain, Jackie; Tarsia, Paolo; Leus, Frank; Veen, Robert; Worby, Tricia
2016-01-01
Objectives: To determine the effect of amoxicillin treatment on resistance selection in patients with community-acquired lower respiratory tract infections in a randomized, placebo-controlled trial. Methods: Patients were prescribed amoxicillin 1 g, three times daily (n = 52) or placebo (n = 50) for
Newton, Nicola C.; Conrod, Patricia J.; Slade, Tim; Carragher, Natacha; Champion, Katrina E.; Barrett, Emma L.; Kelly, Erin V.; Nair, Natasha K.; Stapinski, Lexine; Teesson, Maree
2016-01-01
Background: This study investigated the long-term effectiveness of Preventure, a selective personality-targeted prevention program, in reducing the uptake of alcohol, harmful use of alcohol, and alcohol-related harms over a 3-year period. Methods: A cluster randomized controlled trial was conducted to assess the effectiveness of Preventure.…
Directory of Open Access Journals (Sweden)
Bamidele J. Akinyele
2012-10-01
Full Text Available The influence of electromagnetic field wave on the survival of spoilage fungi associated with some edible fruits consumed in southwestern, Nigeria was studied using cashew (Anacardium occidentale L., pineapple (Ananas comosus, carrot (Daucus carota, cucumber (Cucumis sativus, apple (Malus domestica and African star apple (Chrysophyllum africanum. The spoilage fungi used include the genera of Aspergillus, Penicillium, Articulospora, Mucor, Staphylotrichum, Bisbyopeltis, Fusarium, Rhizopus and a yeast, Saccharomyces cerevisiae. There was a general decrease in fungal growth as shown in the number of spores produced with increase in exposure time of isolates to electromagnetic field except in Articulospora inflata, Penicillium italicum and Mucor mucedo where there was stimulatory effect as there was increase in the fungal spores compared to the control. A decrease was also observed in growth of the fungal isolates with increase in the intensity of the electromagnetic field at voltage of 7 V to 10 V and from 10 V to 13 V. The highest percentage reduction was recorded by Bisbyopeltis phoebesii at intensity of voltage 13V after 60 minutes of exposure. Exposure of the fruits to electromagnetic field wave did not alter the nutrient components of the fruits as observed in the proximate and mineral contents of the treated and untreated fruits. The result of the study revealed that electromagnetic field wave has great potential for use in the control of fruits spoilage and food preservation.
Jin, Y. Q.; Kong, J. A.
1984-01-01
The strong fluctuation theory is applied to the study of electromagnetic wave scattering from a layer of random discrete scatterers. The singularity of the dyadic Green's function is taken into account in the calculation of the effective permittivity functions. The correlation functions for the random medium with different scatterer constituents and size distributions are derived. Applying the dyadic Green's function for a two-layer medium and using the bilocal and distorted Born approximations, the first and the second moments of the fields are then calculated. Both the backscattering and bistatic scattering coefficients are obtained, and the former is shown to match favorably with experimental data obtained from snow fields.
Directory of Open Access Journals (Sweden)
Arshad Raza
2017-03-01
Full Text Available Carbon capture and sequestration technology is recognized as a successful approach taken to mitigate the amount of greenhouse gases released into the atmosphere. However, having a successful storage practice requires wise selection of suitable wells in depleted oil or gas fields to reduce the risk of leakage and contamination of subsurface resources. The aim of this paper is to present a guideline which can be followed to provide a better understanding of sophisticated wells chosen for injection and storage practices. Reviewing recent studies carried out on different aspects of geosequestration indicated that the fracture pressure of seals and borehole conditions such as cement-sheath integrity, distance from faults and fractures together with the depth of wells are important parameters, which should be part of the analysis for well selection in depleted reservoirs. A workflow was then designed covering these aspects and it was applied to a depleted gas field in Malaysia. The results obtained indicated that Well B in the field may have the potential of being a suitable conduit for injection. Although more studies are required to consider other aspects of well selections, it is recommended to employ the formation integrity analysis as part of the caprock assessment before making any decisions.
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
electrojet activity only in average conditions and thus their performance is not optimal during weak activity, we note that careful data selection with advanced AE-variants may appear to be the most practical way to lower the elevated RMS-values which still exist in the residuals between modelled...
Eason, Perri K.; Sherman, Peter T.
2003-01-01
Although the theory of evolution is the foundation of modern biology, students too rarely have an opportunity to watch selection operate in natural populations of animals. This lack may be partially responsible for the unfortunate ignorance of many people regarding the significance of evolution in biology. Laboratory exercises that directly study…
Tackx, M.L.M.; Herman, P.M.J.; Gasparini, S.; Irigoien, X.; Billionesa, R.; Daroa, M.H.
2003-01-01
The copepod Eurytemora affinis generally lives under estuarine conditions, where the suspended particulate matter (SPM) is strongly dominated by non-living particles. This article investigates as to how far E. affinis is capable of feeding selectively on phytoplankton under these extreme
Mild and Selective Protein Release of Cell Wall Deficient Microalgae with Pulsed Electric Field
Lam, 't Gerard; Kolk, van der Jelmer A.; Chordia, Akshita; Vermuë, Marian H.; Olivieri, Giuseppe; Eppink, Michel H.M.; Wijffels, René H.
2017-01-01
Pulsed electric field (PEF) is considered to be a very promising technology for mild cell disruption. The application of PEF for microalgae that have a rigid cell wall, however, is hampered by the presence of that rigid outer cell wall. A cell wall free mutant of C. reinhardtii was used to mimic
Root characteristics of selected field crops: data from the Wageningen Rhizolab (1990-2002)
Smit, A.L.; Groenwold, J.
2005-01-01
Since being built in 1990, the rhizotron facility in Wageningen, the Wageningen Rhizolab, has been used for experiments on crops (e.g. Alfalfa, Brussels sprouts, common velvet grass, field bean, fodder radish, leeks, lupins, maize, potato, beetroot, ryegrass, spinach, spring wheat, winter rye and
Phase selection in capillary break-up in AC electric fields
Malloggi, F.G.J.; van den Ende, Henricus T.M.; Mugele, Friedrich Gunther
2008-01-01
We study the detachment of conductive aqueous drops in ambient oil from an electrode in the presence of ac electric fields. Making use of the electrowetting effect, we determine the charge of the detached sessile drops. Drops are found to be discharged at high ac frequency in line with earlier
2011-06-27
is a physiological indicator also known as vitamin B2, and has a well studied aptamer sequence [33]. We use the riboflavin binding aptamer with the...of Salmonella Infantis with carbon nanotube field effect transistors. Biosens. Bioelectron. 2008, 24, 279-283. 15. Kuang, Z.; Kim, S.; Crookes
Suárez-Serrano, Andrea; Ibáñez, Carles; Lacorte, Silvia; Barata, Carlos
2010-11-01
The aim of this study was to assess the ecotoxicological effects of water coming from untreated organic and conventional rice field production areas in the Ebro Delta (Catalonia, Spain) treated with the herbicides oxadiazon, benzofenap, clomazone and bensulfuron-methyl and the fungicides carbendazim, tricyclazole and flusilazole. Irrigation and drainage channels of the study locations were also included to account for potential toxic effects of water coming in and out of the studied rice fields. Toxicity tests included four species (Pseudokirchneriella subcapitata, Desmodesmus subcapitatus, Chlorella vulgaris and Daphnia magna), three endpoints (microalgae growth, D. magna mortality and feeding rates), and two trophic levels: primary producers (microalgae) and grazers (D. magna). Pesticides in water were analyzed by solid phase extraction-liquid chromatography-electrospray-tandem mass spectrometry (LC-ESI-MS/MS). Negative effects on algae growth and D. magna feeding rates were detected mainly after application of herbicides and fungicides, respectively, in the conventional rice field. Results indicated that most of the observed negative effects in microalgae and D. magna were explained by the presence of herbicides and fungicides. The above mentioned analyses also denoted an inverse relationship between phytoplankton biomass measured as chlorophyll a and herbicides. In summary, this study indicates that in real field situations low to moderate levels of herbicides and fungicides have negative impacts to planktonic organisms and these effects seem to be short-lived.
Radiological impact of oil and Gas Activities in selected oil fields in ...
African Journals Online (AJOL)
A study of the radiological impact of oil and gas exploration activities in the production land area of Delta State has been carried out in-situ using two synchronized and calibrated radiation meters (Digilert 50 and 100) and a geographical positioning system (GPS). Ten oil field facilities were studied. At each facility, nine ...
Field-trip guides to selected volcanoes and volcanic landscapes of the western United States
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2017-06-23
The North American Cordillera is home to a greater diversity of volcanic provinces than any comparably sized region in the world. The interplay between changing plate-margin interactions, tectonic complexity, intra-crustal magma differentiation, and mantle melting have resulted in a wealth of volcanic landscapes. Field trips in this guide book collection (published as USGS Scientific Investigations Report 2017–5022) visit many of these landscapes, including (1) active subduction-related arc volcanoes in the Cascade Range; (2) flood basalts of the Columbia Plateau; (3) bimodal volcanism of the Snake River Plain-Yellowstone volcanic system; (4) some of the world’s largest known ignimbrites from southern Utah, central Colorado, and northern Nevada; (5) extension-related volcanism in the Rio Grande Rift and Basin and Range Province; and (6) the eastern Sierra Nevada featuring Long Valley Caldera and the iconic Bishop Tuff. Some of the field trips focus on volcanic eruptive and emplacement processes, calling attention to the fact that the western United States provides opportunities to examine a wide range of volcanological phenomena at many scales.The 2017 Scientific Assembly of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) in Portland, Oregon, was the impetus to update field guides for many of the volcanoes in the Cascades Arc, as well as publish new guides for numerous volcanic provinces and features of the North American Cordillera. This collection of guidebooks summarizes decades of advances in understanding of magmatic and tectonic processes of volcanic western North America. These field guides are intended for future generations of scientists and the general public as introductions to these fascinating areas; the hope is that the general public will be enticed toward further exploration and that scientists will pursue further field-based research.