Bayesian Wavelet Shrinkage of the Haar-Fisz Transformed Wavelet Periodogram
2015-01-01
It is increasingly being realised that many real world time series are not stationary and exhibit evolving second-order autocovariance or spectral structure. This article introduces a Bayesian approach for modelling the evolving wavelet spectrum of a locally stationary wavelet time series. Our new method works by combining the advantages of a Haar-Fisz transformed spectrum with a simple, but powerful, Bayesian wavelet shrinkage method. Our new method produces excellent and stable spectral estimates and this is demonstrated via simulated data and on differenced infant electrocardiogram data. A major additional benefit of the Bayesian paradigm is that we obtain rigorous and useful credible intervals of the evolving spectral structure. We show how the Bayesian credible intervals provide extra insight into the infant electrocardiogram data. PMID:26381141
A Bayesian Network Approach to Ontology Mapping
National Research Council Canada - National Science Library
Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun
2005-01-01
.... In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs...
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
National Research Council Canada - National Science Library
Lawson, Andrew
2013-01-01
.... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...
Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping
Directory of Open Access Journals (Sweden)
Xu Shizhong
2011-05-01
Full Text Available Abstract Background The Bayesian shrinkage technique has been applied to multiple quantitative trait loci (QTLs mapping to estimate the genetic effects of QTLs on quantitative traits from a very large set of possible effects including the main and epistatic effects of QTLs. Although the recently developed empirical Bayes (EB method significantly reduced computation comparing with the fully Bayesian approach, its speed and accuracy are limited by the fact that numerical optimization is required to estimate the variance components in the QTL model. Results We developed a fast empirical Bayesian LASSO (EBLASSO method for multiple QTL mapping. The fact that the EBLASSO can estimate the variance components in a closed form along with other algorithmic techniques render the EBLASSO method more efficient and accurate. Comparing with the EB method, our simulation study demonstrated that the EBLASSO method could substantially improve the computational speed and detect more QTL effects without increasing the false positive rate. Particularly, the EBLASSO algorithm running on a personal computer could easily handle a linear QTL model with more than 100,000 variables in our simulation study. Real data analysis also demonstrated that the EBLASSO method detected more reasonable effects than the EB method. Comparing with the LASSO, our simulation showed that the current version of the EBLASSO implemented in Matlab had similar speed as the LASSO implemented in Fortran, and that the EBLASSO detected the same number of true effects as the LASSO but a much smaller number of false positive effects. Conclusions The EBLASSO method can handle a large number of effects possibly including both the main and epistatic QTL effects, environmental effects and the effects of gene-environment interactions. It will be a very useful tool for multiple QTL mapping.
Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping.
Cai, Xiaodong; Huang, Anhui; Xu, Shizhong
2011-05-26
The Bayesian shrinkage technique has been applied to multiple quantitative trait loci (QTLs) mapping to estimate the genetic effects of QTLs on quantitative traits from a very large set of possible effects including the main and epistatic effects of QTLs. Although the recently developed empirical Bayes (EB) method significantly reduced computation comparing with the fully Bayesian approach, its speed and accuracy are limited by the fact that numerical optimization is required to estimate the variance components in the QTL model. We developed a fast empirical Bayesian LASSO (EBLASSO) method for multiple QTL mapping. The fact that the EBLASSO can estimate the variance components in a closed form along with other algorithmic techniques render the EBLASSO method more efficient and accurate. Comparing with the EB method, our simulation study demonstrated that the EBLASSO method could substantially improve the computational speed and detect more QTL effects without increasing the false positive rate. Particularly, the EBLASSO algorithm running on a personal computer could easily handle a linear QTL model with more than 100,000 variables in our simulation study. Real data analysis also demonstrated that the EBLASSO method detected more reasonable effects than the EB method. Comparing with the LASSO, our simulation showed that the current version of the EBLASSO implemented in Matlab had similar speed as the LASSO implemented in Fortran, and that the EBLASSO detected the same number of true effects as the LASSO but a much smaller number of false positive effects. The EBLASSO method can handle a large number of effects possibly including both the main and epistatic QTL effects, environmental effects and the effects of gene-environment interactions. It will be a very useful tool for multiple QTL mapping.
Radiation Source Mapping with Bayesian Inverse Methods
Hykes, Joshua Michael
We present a method to map the spectral and spatial distributions of radioactive sources using a small number of detectors. Locating and identifying radioactive materials is important for border monitoring, accounting for special nuclear material in processing facilities, and in clean-up operations. Most methods to analyze these problems make restrictive assumptions about the distribution of the source. In contrast, the source-mapping method presented here allows an arbitrary three-dimensional distribution in space and a flexible group and gamma peak distribution in energy. To apply the method, the system's geometry and materials must be known. A probabilistic Bayesian approach is used to solve the resulting inverse problem (IP) since the system of equations is ill-posed. The probabilistic approach also provides estimates of the confidence in the final source map prediction. A set of adjoint flux, discrete ordinates solutions, obtained in this work by the Denovo code, are required to efficiently compute detector responses from a candidate source distribution. These adjoint fluxes are then used to form the linear model to map the state space to the response space. The test for the method is simultaneously locating a set of 137Cs and 60Co gamma sources in an empty room. This test problem is solved using synthetic measurements generated by a Monte Carlo (MCNP) model and using experimental measurements that we collected for this purpose. With the synthetic data, the predicted source distributions identified the locations of the sources to within tens of centimeters, in a room with an approximately four-by-four meter floor plan. Most of the predicted source intensities were within a factor of ten of their true value. The chi-square value of the predicted source was within a factor of five from the expected value based on the number of measurements employed. With a favorable uniform initial guess, the predicted source map was nearly identical to the true distribution
Nguyen, Thi Huyen Tram; Nguyen, Thu Thuy; Mentré, France
2017-10-01
In mixed models, the relative standard errors (RSE) and shrinkage of individual parameters can be predicted from the individual Bayesian information matrix (M BF ). We proposed an approach accounting for data below the limit of quantification (LOQ) in M BF . M BF is the sum of the expectation of the individual Fisher information (M IF ) which can be evaluated by First-Order linearization and the inverse of random effect variance. We expressed the individual information as a weighted sum of predicted M IF for every possible design composing of measurements above and/or below LOQ. When evaluating M IF , we derived the likelihood expressed as the product of the likelihood of observed data and the probability for data to be below LOQ. The relevance of RSE and shrinkage predicted by M BF in absence or presence of data below LOQ were evaluated by simulations, using a pharmacokinetic/viral kinetic model defined by differential equations. Simulations showed good agreement between predicted and observed RSE and shrinkage in absence or presence of data below LOQ. We found that RSE and shrinkage increased with sparser designs and with data below LOQ. The proposed method based on M BF adequately predicted individual RSE and shrinkage, allowing for evaluation of a large number of scenarios without extensive simulations.
Bayesian QTL mapping using skewed Student-t distributions
Directory of Open Access Journals (Sweden)
von Rohr Peter
2002-01-01
Full Text Available Abstract In most QTL mapping studies, phenotypes are assumed to follow normal distributions. Deviations from this assumption may lead to detection of false positive QTL. To improve the robustness of Bayesian QTL mapping methods, the normal distribution for residuals is replaced with a skewed Student-t distribution. The latter distribution is able to account for both heavy tails and skewness, and both components are each controlled by a single parameter. The Bayesian QTL mapping method using a skewed Student-t distribution is evaluated with simulated data sets under five different scenarios of residual error distributions and QTL effects.
Detecting coevolving amino acid sites using Bayesian mutational mapping
DEFF Research Database (Denmark)
Dimmic, Matthew W.; Hubisz, Melissa J.; Bustamente, Carlos D.
2005-01-01
of coevolving residues in protein families. This method, Bayesian mutational mapping (BMM), assigns mutations to the branches of the evolutionary tree stochastically, and then test statistics are calculated to determine whether a coevolutionary signal exists in the mapping. Posterior predictive P-values provide...
A Bayesian Network Approach to Ontology Mapping
National Research Council Canada - National Science Library
Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun
2005-01-01
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web...
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ0. We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μy. Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager-Machlup functional defined on the Cameron-Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics. © 2013 IOP Publishing Ltd.
Bayesian analysis of log Gaussian Cox processes for disease mapping
DEFF Research Database (Denmark)
Benes, Viktor; Bodlák, Karel; Møller, Jesper
We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis, and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence...... of the risk on the covariates. Instead of using the common area level approaches we consider a Bayesian analysis for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using markov chain Monte Carlo methods...
Bayesian and maximum likelihood estimation of genetic maps
DEFF Research Database (Denmark)
York, Thomas L.; Durrett, Richard T.; Tanksley, Steven
2005-01-01
that makes the Bayesian method applicable to large data sets. We present an extensive simulation study examining the statistical properties of the method and comparing it with the likelihood method implemented in Mapmaker. We show that the Maximum A Posteriori (MAP) estimator of the genetic distances......, corresponding to the maximum likelihood estimator, performs better than estimators based on the posterior expectation. We also show that while the performance is similar between Mapmaker and the MCMC-based method in the absence of genotyping errors, the MCMC-based method has a distinct advantage in the presence...
Inferring the most probable maps of underground utilities using Bayesian mapping model
Bilal, Muhammad; Khan, Wasiq; Muggleton, Jennifer; Rustighi, Emiliano; Jenks, Hugo; Pennock, Steve R.; Atkins, Phil R.; Cohn, Anthony
2018-03-01
Mapping the Underworld (MTU), a major initiative in the UK, is focused on addressing social, environmental and economic consequences raised from the inability to locate buried underground utilities (such as pipes and cables) by developing a multi-sensor mobile device. The aim of MTU device is to locate different types of buried assets in real time with the use of automated data processing techniques and statutory records. The statutory records, even though typically being inaccurate and incomplete, provide useful prior information on what is buried under the ground and where. However, the integration of information from multiple sensors (raw data) with these qualitative maps and their visualization is challenging and requires the implementation of robust machine learning/data fusion approaches. An approach for automated creation of revised maps was developed as a Bayesian Mapping model in this paper by integrating the knowledge extracted from sensors raw data and available statutory records. The combination of statutory records with the hypotheses from sensors was for initial estimation of what might be found underground and roughly where. The maps were (re)constructed using automated image segmentation techniques for hypotheses extraction and Bayesian classification techniques for segment-manhole connections. The model consisting of image segmentation algorithm and various Bayesian classification techniques (segment recognition and expectation maximization (EM) algorithm) provided robust performance on various simulated as well as real sites in terms of predicting linear/non-linear segments and constructing refined 2D/3D maps.
Energy Technology Data Exchange (ETDEWEB)
Terwilliger, Thomas C [Los Alamos National Laboratory; Adams, Paul D [LBNL; Read, Randy J [UNIV OF CAMBRIDGE; Mccoy, Airlie J [UNIV OF CAMBRIDGE
2008-01-01
Ten measures of experimental electron-density-map quality are examined and the skewness of electron density is found to be the best indicator of actual map quality. A Bayesian approach to estimating map quality is developed and used in the PHENIX AutoSol wizard to make decisions during automated structure solution.
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
National Research Council Canada - National Science Library
Lawson, Andrew
2013-01-01
Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas...
GENERALIZED DOUBLE PARETO SHRINKAGE.
Armagan, Artin; Dunson, David B; Lee, Jaeyong
2013-01-01
We propose a generalized double Pareto prior for Bayesian shrinkage estimation and inferences in linear models. The prior can be obtained via a scale mixture of Laplace or normal distributions, forming a bridge between the Laplace and Normal-Jeffreys' priors. While it has a spike at zero like the Laplace density, it also has a Student's t -like tail behavior. Bayesian computation is straightforward via a simple Gibbs sampling algorithm. We investigate the properties of the maximum a posteriori estimator, as sparse estimation plays an important role in many problems, reveal connections with some well-established regularization procedures, and show some asymptotic results. The performance of the prior is tested through simulations and an application.
Bayesian mapping QTL for fruit and growth phenological traits in ...
African Journals Online (AJOL)
STORAGESEVER
2009-01-19
Jan 19, 2009 ... 172 Afr. J. Biotechnol. Table 4. Summary of statistics for espistatic effects obtained with Bayesian model selection on fruit traits and growth phenological traits in the F2 population and F3 lines. Traita. Generation. Position. Heritabilityb. (%) aac ddd ade daf. 2lnBF. PL. F2. LG5[88.5, 163.4]×LG6[60.7, 78.6].
Steinbuch, Luc; Brus, Dick J.; Heuvelink, Gerard B.M.
2018-01-01
One of the first soil forming processes in marine and fluviatile clay soils is ripening, the irreversible change of physical and chemical soil properties, especially consistency, under influence of air. We used Bayesian binomial logistic regression (BBLR) to update the map showing unripened
On Bayesian shared component disease mapping and ecological regression with errors in covariates.
MacNab, Ying C
2010-05-20
Recent literature on Bayesian disease mapping presents shared component models (SCMs) for joint spatial modeling of two or more diseases with common risk factors. In this study, Bayesian hierarchical formulations of shared component disease mapping and ecological models are explored and developed in the context of ecological regression, taking into consideration errors in covariates. A review of multivariate disease mapping models (MultiVMs) such as the multivariate conditional autoregressive models that are also part of the more recent Bayesian disease mapping literature is presented. Some insights into the connections and distinctions between the SCM and MultiVM procedures are communicated. Important issues surrounding (appropriate) formulation of shared- and disease-specific components, consideration/choice of spatial or non-spatial random effects priors, and identification of model parameters in SCMs are explored and discussed in the context of spatial and ecological analysis of small area multivariate disease or health outcome rates and associated ecological risk factors. The methods are illustrated through an in-depth analysis of four-variate road traffic accident injury (RTAI) data: gender-specific fatal and non-fatal RTAI rates in 84 local health areas in British Columbia (Canada). Fully Bayesian inference via Markov chain Monte Carlo simulations is presented. Copyright 2010 John Wiley & Sons, Ltd.
Transport maps and dimension reduction for Bayesian computation
Marzouk, Youssef
2015-01-07
We introduce a new framework for efficient sampling from complex probability distributions, using a combination of optimal transport maps and the Metropolis-Hastings rule. The core idea is to use continuous transportation to transform typical Metropolis proposal mechanisms (e.g., random walks, Langevin methods) into non-Gaussian proposal distributions that can more effectively explore the target density. Our approach adaptively constructs a lower triangular transport map—an approximation of the Knothe-Rosenblatt rearrangement—using information from previous MCMC states, via the solution of an optimization problem. This optimization problem is convex regardless of the form of the target distribution. It is solved efficiently using a Newton method that requires no gradient information from the target probability distribution; the target distribution is instead represented via samples. Sequential updates enable efficient and parallelizable adaptation of the map even for large numbers of samples. We show that this approach uses inexact or truncated maps to produce an adaptive MCMC algorithm that is ergodic for the exact target distribution. Numerical demonstrations on a range of parameter inference problems show order-of-magnitude speedups over standard MCMC techniques, measured by the number of effectively independent samples produced per target density evaluation and per unit of wallclock time. We will also discuss adaptive methods for the construction of transport maps in high dimensions, where use of a non-adapted basis (e.g., a total order polynomial expansion) can become computationally prohibitive. If only samples of the target distribution, rather than density evaluations, are available, then we can construct high-dimensional transformations by composing sparsely parameterized transport maps with rotations of the parameter space. If evaluations of the target density and its gradients are available, then one can exploit the structure of the variational
Sparse Bayesian Information Filters for Localization and Mapping
2008-02-01
on the Unicorn and Caribou AUVs, going to sea on two research cruises, and going to 1369 for coffee in the morning, I’ve been very fortunate to get...map and thereby bound error growth . SLAM is a classic chicken-and-egg problem in which an accurate estimate for the robot’s pose is necessary to...the map that is more succinct. Unlike an occupancy grid rep- resentation, they do not suffer from exponential spatial growth . Instead, the size of
MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control
Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming
2017-09-01
Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.
Empirical Bayesian LASSO-logistic regression for multiple binary trait locus mapping.
Huang, Anhui; Xu, Shizhong; Cai, Xiaodong
2013-02-15
Complex binary traits are influenced by many factors including the main effects of many quantitative trait loci (QTLs), the epistatic effects involving more than one QTLs, environmental effects and the effects of gene-environment interactions. Although a number of QTL mapping methods for binary traits have been developed, there still lacks an efficient and powerful method that can handle both main and epistatic effects of a relatively large number of possible QTLs. In this paper, we use a Bayesian logistic regression model as the QTL model for binary traits that includes both main and epistatic effects. Our logistic regression model employs hierarchical priors for regression coefficients similar to the ones used in the Bayesian LASSO linear model for multiple QTL mapping for continuous traits. We develop efficient empirical Bayesian algorithms to infer the logistic regression model. Our simulation study shows that our algorithms can easily handle a QTL model with a large number of main and epistatic effects on a personal computer, and outperform five other methods examined including the LASSO, HyperLasso, BhGLM, RVM and the single-QTL mapping method based on logistic regression in terms of power of detection and false positive rate. The utility of our algorithms is also demonstrated through analysis of a real data set. A software package implementing the empirical Bayesian algorithms in this paper is freely available upon request. The EBLASSO logistic regression method can handle a large number of effects possibly including the main and epistatic QTL effects, environmental effects and the effects of gene-environment interactions. It will be a very useful tool for multiple QTLs mapping for complex binary traits.
Energy Technology Data Exchange (ETDEWEB)
Terwilliger, T. C.; Adams, P. D.; Read, R. J.; McCoy, A. J.; Moriarty, Nigel W.; Grosse-Kunstleve, R. W.; Afonine, P. V.; Zwart, P. H.; Hung, L.-W.
2009-03-01
Estimates of the quality of experimental maps are important in many stages of structure determination of macromolecules. Map quality is defined here as the correlation between a map and the map calculated based on a final refined model. Here we examine 10 different measures of experimental map quality using a set of 1359 maps calculated by reanalysis of 246 solved MAD, SAD, and MIR datasets. A simple Bayesian approach to estimation of map quality from one or more measures is presented. We find that a Bayesian estimator based on the skew of histograms of electron density is the most accurate of the 10 individual Bayesian estimators of map quality examined, with a correlation between estimated and actual map quality of 0.90. A combination of the skew of electron density with the local correlation of rms density gives a further improvement in estimating map quality, with an overall correlation coefficient of 0.92. The PHENIX AutoSol Wizard carries out automated structure solution based on any combination of SAD, MAD, SIR, or MIR datasets. The Wizard is based on tools from the PHENIX package and uses the Bayesian estimates of map quality described here to choose the highest-quality solutions after experimental phasing.
Energy Technology Data Exchange (ETDEWEB)
Terwilliger, Thomas C., E-mail: terwilliger@lanl.gov [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Adams, Paul D. [Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720 (United States); Read, Randy J.; McCoy, Airlie J. [Department of Haematology, University of Cambridge, Cambridge CB2 0XY (United Kingdom); Moriarty, Nigel W.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Zwart, Peter H. [Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720 (United States); Hung, Li-Wei [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2009-06-01
Ten measures of experimental electron-density-map quality are examined and the skewness of electron density is found to be the best indicator of actual map quality. A Bayesian approach to estimating map quality is developed and used in the PHENIX AutoSol wizard to make decisions during automated structure solution. Estimates of the quality of experimental maps are important in many stages of structure determination of macromolecules. Map quality is defined here as the correlation between a map and the corresponding map obtained using phases from the final refined model. Here, ten different measures of experimental map quality were examined using a set of 1359 maps calculated by re-analysis of 246 solved MAD, SAD and MIR data sets. A simple Bayesian approach to estimation of map quality from one or more measures is presented. It was found that a Bayesian estimator based on the skewness of the density values in an electron-density map is the most accurate of the ten individual Bayesian estimators of map quality examined, with a correlation between estimated and actual map quality of 0.90. A combination of the skewness of electron density with the local correlation of r.m.s. density gives a further improvement in estimating map quality, with an overall correlation coefficient of 0.92. The PHENIX AutoSol wizard carries out automated structure solution based on any combination of SAD, MAD, SIR or MIR data sets. The wizard is based on tools from the PHENIX package and uses the Bayesian estimates of map quality described here to choose the highest quality solutions after experimental phasing.
International Nuclear Information System (INIS)
Terwilliger, Thomas C.; Adams, Paul D.; Read, Randy J.; McCoy, Airlie J.; Moriarty, Nigel W.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Zwart, Peter H.; Hung, Li-Wei
2009-01-01
Ten measures of experimental electron-density-map quality are examined and the skewness of electron density is found to be the best indicator of actual map quality. A Bayesian approach to estimating map quality is developed and used in the PHENIX AutoSol wizard to make decisions during automated structure solution. Estimates of the quality of experimental maps are important in many stages of structure determination of macromolecules. Map quality is defined here as the correlation between a map and the corresponding map obtained using phases from the final refined model. Here, ten different measures of experimental map quality were examined using a set of 1359 maps calculated by re-analysis of 246 solved MAD, SAD and MIR data sets. A simple Bayesian approach to estimation of map quality from one or more measures is presented. It was found that a Bayesian estimator based on the skewness of the density values in an electron-density map is the most accurate of the ten individual Bayesian estimators of map quality examined, with a correlation between estimated and actual map quality of 0.90. A combination of the skewness of electron density with the local correlation of r.m.s. density gives a further improvement in estimating map quality, with an overall correlation coefficient of 0.92. The PHENIX AutoSol wizard carries out automated structure solution based on any combination of SAD, MAD, SIR or MIR data sets. The wizard is based on tools from the PHENIX package and uses the Bayesian estimates of map quality described here to choose the highest quality solutions after experimental phasing
Directory of Open Access Journals (Sweden)
Su Yun Kang
2016-05-01
Full Text Available Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease. Bayesian models have become a standard approach to disease mapping in recent decades. This article aims to provide a basic understanding of the key concepts involved in Bayesian disease mapping methods for areal data. It is anticipated that this will help in interpretation of published maps, and provide a useful starting point for anyone interested in running disease mapping methods for areal data. The article provides detailed motivation and descriptions on disease mapping methods by explaining the concepts, defining the technical terms, and illustrating the utility of disease mapping for epidemiological research by demonstrating various ways of visualising model outputs using a case study. The target audience includes spatial scientists in health and other fields, policy or decision makers, health geographers, spatial analysts, public health professionals, and epidemiologists.
Transport map-accelerated Markov chain Monte Carlo for Bayesian parameter inference
Marzouk, Y.; Parno, M.
2014-12-01
We introduce a new framework for efficient posterior sampling in Bayesian inference, using a combination of optimal transport maps and the Metropolis-Hastings rule. The core idea is to use transport maps to transform typical Metropolis proposal mechanisms (e.g., random walks, Langevin methods, Hessian-preconditioned Langevin methods) into non-Gaussian proposal distributions that can more effectively explore the target density. Our approach adaptively constructs a lower triangular transport map—i.e., a Knothe-Rosenblatt re-arrangement—using information from previous MCMC states, via the solution of an optimization problem. Crucially, this optimization problem is convex regardless of the form of the target distribution. It is solved efficiently using Newton or quasi-Newton methods, but the formulation is such that these methods require no derivative information from the target probability distribution; the target distribution is instead represented via samples. Sequential updates using the alternating direction method of multipliers enable efficient and parallelizable adaptation of the map even for large numbers of samples. We show that this approach uses inexact or truncated maps to produce an adaptive MCMC algorithm that is ergodic for the exact target distribution. Numerical demonstrations on a range of parameter inference problems involving both ordinary and partial differential equations show multiple order-of-magnitude speedups over standard MCMC techniques, measured by the number of effectively independent samples produced per model evaluation and per unit of wallclock time.
Energy Technology Data Exchange (ETDEWEB)
Martínez-García, Eric E. [Cerrada del Rey 40-A, Chimalcoyoc Tlalpan, Ciudad de México, C.P. 14630, México (Mexico); González-Lópezlira, Rosa A.; Bruzual A, Gustavo [Instituto de Radioastronomía y Astrofísica, UNAM, Campus Morelia, Michoacán, C.P. 58089, México (Mexico); Magris C, Gladis, E-mail: martinezgarciaeric@gmail.com [Centro de Investigaciones de Astronomía, Apartado Postal 264, Mérida 5101-A (Venezuela, Bolivarian Republic of)
2017-01-20
Stellar masses of galaxies are frequently obtained by fitting stellar population synthesis models to galaxy photometry or spectra. The state of the art method resolves spatial structures within a galaxy to assess the total stellar mass content. In comparison to unresolved studies, resolved methods yield, on average, higher fractions of stellar mass for galaxies. In this work we improve the current method in order to mitigate a bias related to the resolved spatial distribution derived for the mass. The bias consists in an apparent filamentary mass distribution and a spatial coincidence between mass structures and dust lanes near spiral arms. The improved method is based on iterative Bayesian marginalization, through a new algorithm we have named Bayesian Successive Priors (BSP). We have applied BSP to M51 and to a pilot sample of 90 spiral galaxies from the Ohio State University Bright Spiral Galaxy Survey. By quantitatively comparing both methods, we find that the average fraction of stellar mass missed by unresolved studies is only half what previously thought. In contrast with the previous method, the output BSP mass maps bear a better resemblance to near-infrared images.
DOES GENDER EQUALITY LEAD TO BETTER-PERFORMING ECONOMIES? A BAYESIAN CAUSAL MAP APPROACH
Directory of Open Access Journals (Sweden)
Yelda YÜCEL
2017-01-01
Full Text Available This study explores the existence of relationships between gender inequalities –represented by the components of the World Economic Forum (WEF Global Gender Gap Index– and the major macroeconomic indicators. The relationships within gender inequalities in education, the labour market, health and the political arena, and between gender inequalities and gross macroeconomic aggregates were modelled with the Bayesian Causal Map, an effective tool that is used to analyze cause-effect relations and conditional dependencies between variables. A data set of 128 countries during the period 2007–2011 is used. Findings reveal that some inequalities have high levels of interaction with each other. In addition, eradicating gender inequalities is found to be associated with better economic performance, mainly in the form of higher gross domestic product growth, investment, and competitiveness.
Directory of Open Access Journals (Sweden)
Chris Wallace
2015-06-01
Full Text Available Identification of candidate causal variants in regions associated with risk of common diseases is complicated by linkage disequilibrium (LD and multiple association signals. Nonetheless, accurate maps of these variants are needed, both to fully exploit detailed cell specific chromatin annotation data to highlight disease causal mechanisms and cells, and for design of the functional studies that will ultimately be required to confirm causal mechanisms. We adapted a Bayesian evolutionary stochastic search algorithm to the fine mapping problem, and demonstrated its improved performance over conventional stepwise and regularised regression through simulation studies. We then applied it to fine map the established multiple sclerosis (MS and type 1 diabetes (T1D associations in the IL-2RA (CD25 gene region. For T1D, both stepwise and stochastic search approaches identified four T1D association signals, with the major effect tagged by the single nucleotide polymorphism, rs12722496. In contrast, for MS, the stochastic search found two distinct competing models: a single candidate causal variant, tagged by rs2104286 and reported previously using stepwise analysis; and a more complex model with two association signals, one of which was tagged by the major T1D associated rs12722496 and the other by rs56382813. There is low to moderate LD between rs2104286 and both rs12722496 and rs56382813 (r2 ≃ 0:3 and our two SNP model could not be recovered through a forward stepwise search after conditioning on rs2104286. Both signals in the two variant model for MS affect CD25 expression on distinct subpopulations of CD4+ T cells, which are key cells in the autoimmune process. The results support a shared causal variant for T1D and MS. Our study illustrates the benefit of using a purposely designed model search strategy for fine mapping and the advantage of combining disease and protein expression data.
Directory of Open Access Journals (Sweden)
Nguyen The Vinh The Vinh
2012-09-01
Full Text Available The results of the development of organic-mineral modifiers to the increasing component for high-strength concrete. The effect of modifiers designed for mobility, strength and shrinkage of cement paste.
A Bayesian and Physics-Based Ground Motion Parameters Map Generation System
Ramirez-Guzman, L.; Quiroz, A.; Sandoval, H.; Perez-Yanez, C.; Ruiz, A. L.; Delgado, R.; Macias, M. A.; Alcántara, L.
2014-12-01
We present the Ground Motion Parameters Map Generation (GMPMG) system developed by the Institute of Engineering at the National Autonomous University of Mexico (UNAM). The system delivers estimates of information associated with the social impact of earthquakes, engineering ground motion parameters (gmp), and macroseismic intensity maps. The gmp calculated are peak ground acceleration and velocity (pga and pgv) and response spectral acceleration (SA). The GMPMG relies on real-time data received from strong ground motion stations belonging to UNAM's networks throughout Mexico. Data are gathered via satellite and internet service providers, and managed with the data acquisition software Earthworm. The system is self-contained and can perform all calculations required for estimating gmp and intensity maps due to earthquakes, automatically or manually. An initial data processing, by baseline correcting and removing records containing glitches or low signal-to-noise ratio, is performed. The system then assigns a hypocentral location using first arrivals and a simplified 3D model, followed by a moment tensor inversion, which is performed using a pre-calculated Receiver Green's Tensors (RGT) database for a realistic 3D model of Mexico. A backup system to compute epicentral location and magnitude is in place. A Bayesian Kriging is employed to combine recorded values with grids of computed gmp. The latter are obtained by using appropriate ground motion prediction equations (for pgv, pga and SA with T=0.3, 0.5, 1 and 1.5 s ) and numerical simulations performed in real time, using the aforementioned RGT database (for SA with T=2, 2.5 and 3 s). Estimated intensity maps are then computed using SA(T=2S) to Modified Mercalli Intensity correlations derived for central Mexico. The maps are made available to the institutions in charge of the disaster prevention systems. In order to analyze the accuracy of the maps, we compare them against observations not considered in the
Directory of Open Access Journals (Sweden)
Gogarten J Peter
2002-02-01
Full Text Available Abstract Background Horizontal gene transfer (HGT played an important role in shaping microbial genomes. In addition to genes under sporadic selection, HGT also affects housekeeping genes and those involved in information processing, even ribosomal RNA encoding genes. Here we describe tools that provide an assessment and graphic illustration of the mosaic nature of microbial genomes. Results We adapted the Maximum Likelihood (ML mapping to the analyses of all detected quartets of orthologous genes found in four genomes. We have automated the assembly and analyses of these quartets of orthologs given the selection of four genomes. We compared the ML-mapping approach to more rigorous Bayesian probability and Bootstrap mapping techniques. The latter two approaches appear to be more conservative than the ML-mapping approach, but qualitatively all three approaches give equivalent results. All three tools were tested on mitochondrial genomes, which presumably were inherited as a single linkage group. Conclusions In some instances of interphylum relationships we find nearly equal numbers of quartets strongly supporting the three possible topologies. In contrast, our analyses of genome quartets containing the cyanobacterium Synechocystis sp. indicate that a large part of the cyanobacterial genome is related to that of low GC Gram positives. Other groups that had been suggested as sister groups to the cyanobacteria contain many fewer genes that group with the Synechocystis orthologs. Interdomain comparisons of genome quartets containing the archaeon Halobacterium sp. revealed that Halobacterium sp. shares more genes with Bacteria that live in the same environment than with Bacteria that are more closely related based on rRNA phylogeny . Many of these genes encode proteins involved in substrate transport and metabolism and in information storage and processing. The performed analyses demonstrate that relationships among prokaryotes cannot be accurately
Rahmat, R. F.; Nasution, F. R.; Seniman; Syahputra, M. F.; Sitompul, O. S.
2018-02-01
Weather is condition of air in a certain region at a relatively short period of time, measured with various parameters such as; temperature, air preasure, wind velocity, humidity and another phenomenons in the atmosphere. In fact, extreme weather due to global warming would lead to drought, flood, hurricane and other forms of weather occasion, which directly affects social andeconomic activities. Hence, a forecasting technique is to predict weather with distinctive output, particullary mapping process based on GIS with information about current weather status in certain cordinates of each region with capability to forecast for seven days afterward. Data used in this research are retrieved in real time from the server openweathermap and BMKG. In order to obtain a low error rate and high accuracy of forecasting, the authors use Bayesian Model Averaging (BMA) method. The result shows that the BMA method has good accuracy. Forecasting error value is calculated by mean square error shows (MSE). The error value emerges at minumum temperature rated at 0.28 and maximum temperature rated at 0.15. Meanwhile, the error value of minimum humidity rates at 0.38 and the error value of maximum humidity rates at 0.04. Afterall, the forecasting error rate of wind speed is at 0.076. The lower the forecasting error rate, the more optimized the accuracy is.
Garcia Urquia, E. L.; Braun, A.; Yamagishi, H.
2016-12-01
Tegucigalpa, the capital city of Honduras, experiences rainfall-induced landslides on a yearly basis. The high precipitation regime and the rugged topography the city has been built in couple with the lack of a proper urban expansion plan to contribute to the occurrence of landslides during the rainy season. Thousands of inhabitants live at risk of losing their belongings due to the construction of precarious shelters in landslide-prone areas on mountainous terrains and next to the riverbanks. Therefore, the city is in the need for landslide susceptibility and hazard maps to aid in the regulation of future development. Major challenges in the context of highly dynamic urbanizing areas are the overlap of natural and anthropogenic slope destabilizing factors, as well as the availability and accuracy of data. Data-driven multivariate techniques have proven to be powerful in discovering interrelations between factors, identifying important factors in large datasets, capturing non-linear problems and coping with noisy and incomplete data. This analysis focuses on the creation of a landslide susceptibility map using different methods from the field of data mining, Artificial Neural Networks (ANN), Bayesian Networks (BN) and Decision Trees (DT). The input dataset of the study contains geomorphological and hydrological factors derived from a digital elevation model with a 10 m resolution, lithological factors derived from a geological map, and anthropogenic factors, such as information on the development stage of the neighborhoods in Tegucigalpa and road density. Moreover, a landslide inventory map that was developed in 2014 through aerial photo interpretation was used as target variable in the analysis. The analysis covers an area of roughly 100 km2, while 8.95 km2 are occupied by landslides. In a first step, the dataset was explored by assessing and improving the data quality, identifying unimportant variables and finding interrelations. Then, based on a training
Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods
Wainwright, Haruko M.; Liljedahl, Anna K.; Dafflon, Baptiste; Ulrich, Craig; Peterson, John E.; Gusmeroli, Alessio; Hubbard, Susan S.
2017-04-01
This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).
Cure shrinkage in casting resins
Energy Technology Data Exchange (ETDEWEB)
Spencer, J. Brock [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-02-01
A method is described whereby the shrinkage of a casting resin can be determined. Values for the shrinkage of several resin systems in frequent use by Sandia have been measured. A discussion of possible methods for determining the stresses generated by cure shrinkage and thermal contraction is also included.
The Bayesian Covariance Lasso.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G
2013-04-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Directory of Open Access Journals (Sweden)
Qi Zheng
2016-10-01
Full Text Available Accurate mapping of next-generation sequencing (NGS reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.
Zheng, Qi; Grice, Elizabeth A
2016-10-01
Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.
Directory of Open Access Journals (Sweden)
Giovanna Raso
2007-11-01
Full Text Available There is growing interest in the use of Bayesian geostatistical models for predicting the spatial distribution of parasitic infections, including hookworm, Schistosoma mansoni and co-infections with both parasites. The aim of this study was to predict the spatial distribution of mono-infections with either hookworm or S. mansoni in a setting where both parasites co-exist. School-based cross-sectional parasitological and questionnaire surveys were carried out in 57 rural schools in the Man region, western Côte d’Ivoire. A single stool specimen was obtained from each schoolchild attending grades 3-5. Stool specimens were processed by the Kato-Katz technique and an ether concentration method and examined for the presence of hookworm and S. mansoni eggs. The combined results from the two diagnostic approaches were considered for the infection status of each child. Demographic data (i.e. age and sex were obtained from readily available school registries. Each child’s socio-economic status was estimated, using the questionnaire data following a household-based asset approach. Environmental data were extracted from satellite imagery. The different data sources were incorporated into a geographical information system. Finally, a Bayesian spatial multinomial regression model was constructed and the spatial patterns of S. mansoni and hookworm mono-infections were investigated using Bayesian kriging. Our approach facilitated the production of smooth risk maps for hookworm and S. mansoni mono-infections that can be utilized for targeting control interventions. We argue that in settings where S. mansoni and hookworm co-exist and control efforts are under way, there is a need for both mono- and co-infection risk maps to enhance the cost-effectiveness of control programmes.
Wang, Tingting; Chen, Yi-Ping Phoebe; Bowman, Phil J; Goddard, Michael E; Hayes, Ben J
2016-09-21
Bayesian mixture models in which the effects of SNP are assumed to come from normal distributions with different variances are attractive for simultaneous genomic prediction and QTL mapping. These models are usually implemented with Monte Carlo Markov Chain (MCMC) sampling, which requires long compute times with large genomic data sets. Here, we present an efficient approach (termed HyB_BR), which is a hybrid of an Expectation-Maximisation algorithm, followed by a limited number of MCMC without the requirement for burn-in. To test prediction accuracy from HyB_BR, dairy cattle and human disease trait data were used. In the dairy cattle data, there were four quantitative traits (milk volume, protein kg, fat% in milk and fertility) measured in 16,214 cattle from two breeds genotyped for 632,002 SNPs. Validation of genomic predictions was in a subset of cattle either from the reference set or in animals from a third breeds that were not in the reference set. In all cases, HyB_BR gave almost identical accuracies to Bayesian mixture models implemented with full MCMC, however computational time was reduced by up to 1/17 of that required by full MCMC. The SNPs with high posterior probability of a non-zero effect were also very similar between full MCMC and HyB_BR, with several known genes affecting milk production in this category, as well as some novel genes. HyB_BR was also applied to seven human diseases with 4890 individuals genotyped for around 300 K SNPs in a case/control design, from the Welcome Trust Case Control Consortium (WTCCC). In this data set, the results demonstrated again that HyB_BR performed as well as Bayesian mixture models with full MCMC for genomic predictions and genetic architecture inference while reducing the computational time from 45 h with full MCMC to 3 h with HyB_BR. The results for quantitative traits in cattle and disease in humans demonstrate that HyB_BR can perform equally well as Bayesian mixture models implemented with full MCMC in
Total shrinkage versus partial shrinkage in multiple linear regression ...
African Journals Online (AJOL)
The paper discusses the merits of partial shrinkage of the ordinary least square estimator of the coefficients of the multiple regression model of full rank. Theoretical comparisons of scalar and matrix-valued risks of the partially shrunken and totally shrunken estimators are given. The strategy of partial shrinkage is applied to ...
A new approach for supply chain risk management: Mapping SCOR into Bayesian network
Directory of Open Access Journals (Sweden)
Mahdi Abolghasemi
2015-01-01
Full Text Available Purpose: Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. SCRM has a close relationship with supply chain performance. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are either qualitative or quantitative. Supply chain operation reference (SCOR is a standard model for SCP evaluation which have uncertainty in its metrics. In This paper by combining qualitative and quantitative metrics of SCOR, supply chain performance will be measured by Bayesian Networks. Design/methodology/approach: First qualitative assessment will be done by recognizing uncertain metrics of SCOR model and then by quantifying them, supply chain performance will be measured by Bayesian Networks (BNs and supply chain operations reference (SCOR in which making decision on uncertain variables will be done by predictive and diagnostic capabilities. Findings: After applying the proposed method in one of the biggest automotive companies in Iran, we identified key factors of supply chain performance based on SCOR model through predictive and diagnostic capability of Bayesian Networks. After sensitivity analysis, we find out that ‘Total cost’ and its criteria that include costs of labors, warranty, transportation and inventory have the widest range and most effect on supply chain performance. So, managers should take their importance into account for decision making. We can make decisions simply by running model in different situations. Research limitations/implications: A more precise model consisted of numerous factors but it is difficult and sometimes impossible to solve big models, if we insert all of them in a Bayesian model. We have adopted real world characteristics with our software and method abilities. On the other hand, fewer data exist for some
Underwood, Kristen L.; Rizzo, Donna M.; Schroth, Andrew W.; Dewoolkar, Mandar M.
2017-12-01
Given the variable biogeochemical, physical, and hydrological processes driving fluvial sediment and nutrient export, the water science and management communities need data-driven methods to identify regions prone to production and transport under variable hydrometeorological conditions. We use Bayesian analysis to segment concentration-discharge linear regression models for total suspended solids (TSS) and particulate and dissolved phosphorus (PP, DP) using 22 years of monitoring data from 18 Lake Champlain watersheds. Bayesian inference was leveraged to estimate segmented regression model parameters and identify threshold position. The identified threshold positions demonstrated a considerable range below and above the median discharge—which has been used previously as the default breakpoint in segmented regression models to discern differences between pre and post-threshold export regimes. We then applied a Self-Organizing Map (SOM), which partitioned the watersheds into clusters of TSS, PP, and DP export regimes using watershed characteristics, as well as Bayesian regression intercepts and slopes. A SOM defined two clusters of high-flux basins, one where PP flux was predominantly episodic and hydrologically driven; and another in which the sediment and nutrient sourcing and mobilization were more bimodal, resulting from both hydrologic processes at post-threshold discharges and reactive processes (e.g., nutrient cycling or lateral/vertical exchanges of fine sediment) at prethreshold discharges. A separate DP SOM defined two high-flux clusters exhibiting a bimodal concentration-discharge response, but driven by differing land use. Our novel framework shows promise as a tool with broad management application that provides insights into landscape drivers of riverine solute and sediment export.
D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco P.; Pasquariello, Guido
2018-03-01
High-resolution, remotely sensed images of the Earth surface have been proven to be of help in producing detailed flood maps, thanks to their synoptic overview of the flooded area and frequent revisits. However, flood scenarios can be complex situations, requiring the integration of different data in order to provide accurate and robust flood information. Several processing approaches have been recently proposed to efficiently combine and integrate heterogeneous information sources. In this paper, we introduce DAFNE, a Matlab®-based, open source toolbox, conceived to produce flood maps from remotely sensed and other ancillary information, through a data fusion approach. DAFNE is based on Bayesian Networks, and is composed of several independent modules, each one performing a different task. Multi-temporal and multi-sensor data can be easily handled, with the possibility of following the evolution of an event through multi-temporal output flood maps. Each DAFNE module can be easily modified or upgraded to meet different user needs. The DAFNE suite is presented together with an example of its application.
Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope
2013-11-01
Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.
DEFF Research Database (Denmark)
Ekpo, Uwem F.; Hürlimann, Eveline; Schur, Nadine
2013-01-01
Schistosomiasis prevalence data for Nigeria were extracted from peer-reviewed journals and reports, geo-referenced and collated in a nationwide geographical information system database for the generation of point prevalence maps. This exercise revealed that the disease is endemic in 35 of the cou......Schistosomiasis prevalence data for Nigeria were extracted from peer-reviewed journals and reports, geo-referenced and collated in a nationwide geographical information system database for the generation of point prevalence maps. This exercise revealed that the disease is endemic in 35...
Mapping brucellosis increases relative to elk density using hierarchical Bayesian models.
Directory of Open Access Journals (Sweden)
Paul C Cross
Full Text Available The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km(2; range = [95-10237]. The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.
Mapping brucellosis increases relative to elk density using hierarchical Bayesian models
Cross, Paul C.; Heisey, Dennis M.; Scurlock, Brandon M.; Edwards, William H.; Brennan, Angela; Ebinger, Michael R.
2010-01-01
The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus) in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km2; range = [95–10237]). The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.
Law, Jane; Quick, Matthew
2013-01-01
This paper adopts a Bayesian spatial modeling approach to investigate the distribution of young offender residences in York Region, Southern Ontario, Canada, at the census dissemination area level. Few geographic researches have analyzed offender (as opposed to offense) data at a large map scale (i.e., using a relatively small areal unit of analysis) to minimize aggregation effects. Providing context is the social disorganization theory, which hypothesizes that areas with economic deprivation, high population turnover, and high ethnic heterogeneity exhibit social disorganization and are expected to facilitate higher instances of young offenders. Non-spatial and spatial Poisson models indicate that spatial methods are superior to non-spatial models with respect to model fit and that index of ethnic heterogeneity, residential mobility (1 year moving rate), and percentage of residents receiving government transfer payments are, respectively, the most significant explanatory variables related to young offender location. These findings provide overwhelming support for social disorganization theory as it applies to offender location in York Region, Ontario. Targeting areas where prevalence of young offenders could or could not be explained by social disorganization through decomposing the estimated risk map are helpful for dealing with juvenile offenders in the region. Results prompt discussion into geographically targeted police services and young offender placement pertaining to risk of recidivism. We discuss possible reasons for differences and similarities between the previous findings (that analyzed offense data and/or were conducted at a smaller map scale) and our findings, limitations of our study, and practical outcomes of this research from a law enforcement perspective.
Image denoising using ridgelet shrinkage
Kumar, Pawan; Bhurchandi, Kishore
2015-03-01
Protecting fine details and edges while denoising digital images is a challenging area of research due to changing characteristics of both, noise and signal. Denoising is used to remove noise from corrupted images but in the process fine details like weak edges and textures are hampered. In this paper we propose an algorithm based on Ridgelet transform to denoise images and protect fine details. Here we use cycle spinning on Ridgelet coefficients with soft thresholding and name the algorithm as Ridgelet Shrinkage in order to suppress noise and preserve details. The projections in Ridgelets filter out the noise while protecting the details while the ridgelet shrinkage further suppress noise. The proposed algorithm out performs the Wavelet Shrinkage and Non-local (NL) means denoising algorithms on the basis of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) numerically and visually both.
Wang, Tingting; Chen, Yi-Ping Phoebe; MacLeod, Iona M; Pryce, Jennie E; Goddard, Michael E; Hayes, Ben J
2017-08-15
Using whole genome sequence data might improve genomic prediction accuracy, when compared with high-density SNP arrays, and could lead to identification of casual mutations affecting complex traits. For some traits, the most accurate genomic predictions are achieved with non-linear Bayesian methods. However, as the number of variants and the size of the reference population increase, the computational time required to implement these Bayesian methods (typically with Monte Carlo Markov Chain sampling) becomes unfeasibly long. Here, we applied a new method, HyB_BR (for Hybrid BayesR), which implements a mixture model of normal distributions and hybridizes an Expectation-Maximization (EM) algorithm followed by Markov Chain Monte Carlo (MCMC) sampling, to genomic prediction in a large dairy cattle population with imputed whole genome sequence data. The imputed whole genome sequence data included 994,019 variant genotypes of 16,214 Holstein and Jersey bulls and cows. Traits included fat yield, milk volume, protein kg, fat% and protein% in milk, as well as fertility and heat tolerance. HyB_BR achieved genomic prediction accuracies as high as the full MCMC implementation of BayesR, both for predicting a validation set of Holstein and Jersey bulls (multi-breed prediction) and a validation set of Australian Red bulls (across-breed prediction). HyB_BR had a ten fold reduction in compute time, compared with the MCMC implementation of BayesR (48 hours versus 594 hours). We also demonstrate that in many cases HyB_BR identified sequence variants with a high posterior probability of affecting the milk production or fertility traits that were similar to those identified in BayesR. For heat tolerance, both HyB_BR and BayesR found variants in or close to promising candidate genes associated with this trait and not detected by previous studies. The results demonstrate that HyB_BR is a feasible method for simultaneous genomic prediction and QTL mapping with whole genome sequence in
Karmakar, Mampi; Maiti, Saumen; Singh, Amrita; Ojha, Maheswar; Maity, Bhabani Sankar
2017-07-01
Modeling and classification of the subsurface lithology is very important to understand the evolution of the earth system. However, precise classification and mapping of lithology using a single framework are difficult due to the complexity and the nonlinearity of the problem driven by limited core sample information. Here, we implement a joint approach by combining the unsupervised and the supervised methods in a single framework for better classification and mapping of rock types. In the unsupervised method, we use the principal component analysis (PCA), K-means cluster analysis (K-means), dendrogram analysis, Fuzzy C-means (FCM) cluster analysis and self-organizing map (SOM). In the supervised method, we use the Bayesian neural networks (BNN) optimized by the Hybrid Monte Carlo (HMC) (BNN-HMC) and the scaled conjugate gradient (SCG) (BNN-SCG) techniques. We use P-wave velocity, density, neutron porosity, resistivity and gamma ray logs of the well U1343E of the Integrated Ocean Drilling Program (IODP) Expedition 323 in the Bering Sea slope region. While the SOM algorithm allows us to visualize the clustering results in spatial domain, the combined classification schemes (supervised and unsupervised) uncover the different patterns of lithology such of as clayey-silt, diatom-silt and silty-clay from an un-cored section of the drilled hole. In addition, the BNN approach is capable of estimating uncertainty in the predictive modeling of three types of rocks over the entire lithology section at site U1343. Alternate succession of clayey-silt, diatom-silt and silty-clay may be representative of crustal inhomogeneity in general and thus could be a basis for detail study related to the productivity of methane gas in the oceans worldwide. Moreover, at the 530 m depth down below seafloor (DSF), the transition from Pliocene to Pleistocene could be linked to lithological alternation between the clayey-silt and the diatom-silt. The present results could provide the basis for
The influence of shrinkage reducing admixtures on plastic shrinkage
Directory of Open Access Journals (Sweden)
Mora, J.
2003-12-01
Full Text Available Shrinkage reducing admixtures (SRAs are viable alternatives for reducing plastic shrinkage cracking in concrete. The objective of the present paper is to study early age plastic shrinkage in restrained concrete elements, where three different SRAs have been used. The influence of the admixture is analyzed through the following measurements: capillary pressure, evaporation, temperature evolution, crack evolution and settlement. The tests for studying the cracking and deformation were made on two different configurations (i.e., restrained prisms with reduced cross-section and restrained panel, in a wind tunnel, with controlled wind temperature and velocity. The conclusions obtained indicate the viability of the use of this type of admixture and the usefulness of the test methods.
Los aditivos reductores de retracción (SRAs se plantean, hoy en día, como una alternativa viable para reducir la fisuración por retracción plástica. El objetivo del presente artículo es conocer mejor y predecir el comportamiento a primeras edades de la retracción plástica en elementos estructurales coaccionados, a los que se les ha añadido diversos aditivos reductores de retracción (tres tipos diferentes. Esta influencia se analiza a través de las siguientes propiedades: presión capilar, evaporación, evolución de temperaturas, evolución de fisuración, y deformaciones verticales de asentamiento. Los ensayos para estudiar la fisuración y las deformaciones se han realizado sobre diferentes configuraciones (prisma restringido con estrangulamiento y panel restringido, en un túnel de viento, con temperaturas y velocidades de viento controladas. Las conclusiones obtenidas señalan la viabilidad del empleo de este tipo de aditivos y la bondad de los métodos experimentales utilizados.
Study on effects of solar radiation and rain on shrinkage, shrinkage cracking and creep of concrete
International Nuclear Information System (INIS)
Asamoto, Shingo; Ohtsuka, Ayumu; Kuwahara, Yuta; Miura, Chikako
2011-01-01
In this paper, the effects of actual environmental actions on shrinkage, creep and shrinkage cracking of concrete are studied comprehensively. Prismatic specimens of plain concrete were exposed to three sets of artificial outdoor conditions with or without solar radiation and rain to examine the shrinkage. For the purpose of studying shrinkage cracking behavior, prismatic concrete specimens with reinforcing steel were also subjected to the above conditions at the same time. The shrinkage behavior is described focusing on the effects of solar radiation and rain based on the moisture loss. The significant environment actions to induce shrinkage cracks are investigated from viewpoints of the amount of the shrinkage and the tensile strength. Finally, specific compressive creep behavior according to solar radiation and rainfall is discussed. It is found that rain can greatly inhibit the progresses of concrete shrinkage and creep while solar radiation is likely to promote shrinkage cracking and creep.
Global, Parameterwise and Joint Shrinkage Factor Estimation
Directory of Open Access Journals (Sweden)
Daniela Dunkler
2016-03-01
Full Text Available The predictive value of a statistical model can often be improved by applying shrinkage methods. This can be achieved, e.g., by regularized regression or empirical Bayes approaches. Various types of shrinkage factors can also be estimated after a maximum likelihood fit has been obtained: while global shrinkage modifies all regression coefficients by the same factor, parameterwise shrinkage factors differ between regression coefficients. The latter ones have been proposed especially in the context of variable selection. With variables which are either highly correlated or associated with regard to contents, such as dummy variables coding a categorical variable, or several parameters describing a nonlinear effect, parameterwise shrinkage factors may not be the best choice. For such cases, we extend the present methodology by so-called 'joint shrinkage factors', a compromise between global and parameterwise shrinkage. Shrinkage factors are often estimated using leave-one-out resampling. We also discuss a computationally simple and much faster approximation to resampling-based shrinkage factor estimation, can be easily obtained in most standard software packages for regression analyses. This alternative may be relevant for simulation studies and other computerintensive investigations. Furthermore, we provide an R package shrink implementing the mentioned shrinkage methods for models fitted by linear, generalized linear, or Cox regression, even if these models involve fractional polynomials or restricted cubic splines to estimate the influence of a continuous variable by a nonlinear function. The approaches and usage of the package shrink are illustrated by means of two examples.
Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret
2018-01-01
Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.
Soil shrinkage characteristics in swelling soils
International Nuclear Information System (INIS)
Taboada, M.A.
2004-01-01
The objectives of this presentation are to understand soil swelling and shrinkage mechanisms, and the development of desiccation cracks, to distinguish between soils having different magnitude of swelling, as well as the consequences on soil structural behaviour, to know methods to characterize soil swell/shrink potential and to construct soil shrinkage curves, and derive shrinkage indices, as well to apply them to assess soil management effects
Accounting for PDMS shrinkage when replicating structures
DEFF Research Database (Denmark)
Madsen, Morten Hannibal; Feidenhans'l, Nikolaj Agentoft; Hansen, Poul-Erik
2014-01-01
are seldom applied to counteract the shrinkage of PDMS. Also, to perform metrological measurements using replica techniques one has to take the shrinkage into account. Thus we report a study of the shrinkage of PDMS with several different mixing ratios and curing temperatures. The shrinkage factor, with its...... associated uncertainty, for PDMS in the range 40 to 120 °C is provided. By applying this correction factor, it is possible to replicate structures with a standard uncertainty of less than 0.2% in lateral dimensions using typical curing temperatures and PDMS mixing ratios in the range 1:6 to 1:20 (agent:base)....
Bayesian analysis in plant pathology.
Mila, A L; Carriquiry, A L
2004-09-01
ABSTRACT Bayesian methods are currently much discussed and applied in several disciplines from molecular biology to engineering. Bayesian inference is the process of fitting a probability model to a set of data and summarizing the results via probability distributions on the parameters of the model and unobserved quantities such as predictions for new observations. In this paper, after a short introduction of Bayesian inference, we present the basic features of Bayesian methodology using examples from sequencing genomic fragments and analyzing microarray gene-expressing levels, reconstructing disease maps, and designing experiments.
Bayesian LASSO, scale space and decision making in association genetics.
Pasanen, Leena; Holmström, Lasse; Sillanpää, Mikko J
2015-01-01
LASSO is a penalized regression method that facilitates model fitting in situations where there are as many, or even more explanatory variables than observations, and only a few variables are relevant in explaining the data. We focus on the Bayesian version of LASSO and consider four problems that need special attention: (i) controlling false positives, (ii) multiple comparisons, (iii) collinearity among explanatory variables, and (iv) the choice of the tuning parameter that controls the amount of shrinkage and the sparsity of the estimates. The particular application considered is association genetics, where LASSO regression can be used to find links between chromosome locations and phenotypic traits in a biological organism. However, the proposed techniques are relevant also in other contexts where LASSO is used for variable selection. We separate the true associations from false positives using the posterior distribution of the effects (regression coefficients) provided by Bayesian LASSO. We propose to solve the multiple comparisons problem by using simultaneous inference based on the joint posterior distribution of the effects. Bayesian LASSO also tends to distribute an effect among collinear variables, making detection of an association difficult. We propose to solve this problem by considering not only individual effects but also their functionals (i.e. sums and differences). Finally, whereas in Bayesian LASSO the tuning parameter is often regarded as a random variable, we adopt a scale space view and consider a whole range of fixed tuning parameters, instead. The effect estimates and the associated inference are considered for all tuning parameters in the selected range and the results are visualized with color maps that provide useful insights into data and the association problem considered. The methods are illustrated using two sets of artificial data and one real data set, all representing typical settings in association genetics.
Directory of Open Access Journals (Sweden)
Abdallah Bengueddoudj
2017-05-01
Full Text Available In this paper, we propose a new image fusion algorithm based on two-dimensional Scale-Mixing Complex Wavelet Transform (2D-SMCWT. The fusion of the detail 2D-SMCWT coefficients is performed via a Bayesian Maximum a Posteriori (MAP approach by considering a trivariate statistical model for the local neighboring of 2D-SMCWT coefficients. For the approximation coefficients, a new fusion rule based on the Principal Component Analysis (PCA is applied. We conduct several experiments using three different groups of multimodal medical images to evaluate the performance of the proposed method. The obtained results prove the superiority of the proposed method over the state of the art fusion methods in terms of visual quality and several commonly used metrics. Robustness of the proposed method is further tested against different types of noise. The plots of fusion metrics establish the accuracy of the proposed fusion method.
Mohebbi, Mohammadreza; Wolfe, Rory; Forbes, Andrew
2014-01-01
This paper applies the generalised linear model for modelling geographical variation to esophageal cancer incidence data in the Caspian region of Iran. The data have a complex and hierarchical structure that makes them suitable for hierarchical analysis using Bayesian techniques, but with care required to deal with problems arising from counts of events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present. These considerations lead to nine regression models derived from using three probability distributions for count data: Poisson, generalised Poisson and negative binomial, and three different autocorrelation structures. We employ the framework of Bayesian variable selection and a Gibbs sampling based technique to identify significant cancer risk factors. The framework deals with situations where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. The evidence from applying the modelling methodology suggests that modelling strategies based on the use of generalised Poisson and negative binomial with spatial autocorrelation work well and provide a robust basis for inference. PMID:24413702
Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro
2016-01-01
An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. Copyright © 2015 Elsevier Inc. All rights reserved.
Volumetric polymerization shrinkage of contemporary composite resins
Directory of Open Access Journals (Sweden)
Halim Nagem Filho
2007-10-01
Full Text Available The polymerization shrinkage of composite resins may affect negatively the clinical outcome of the restoration. Extensive research has been carried out to develop new formulations of composite resins in order to provide good handling characteristics and some dimensional stability during polymerization. The purpose of this study was to analyze, in vitro, the magnitude of the volumetric polymerization shrinkage of 7 contemporary composite resins (Definite, Suprafill, SureFil, Filtek Z250, Fill Magic, Alert, and Solitaire to determine whether there are differences among these materials. The tests were conducted with precision of 0.1 mg. The volumetric shrinkage was measured by hydrostatic weighing before and after polymerization and calculated by known mathematical equations. One-way ANOVA (a or = 0.05 was used to determine statistically significant differences in volumetric shrinkage among the tested composite resins. Suprafill (1.87±0.01 and Definite (1.89±0.01 shrank significantly less than the other composite resins. SureFil (2.01±0.06, Filtek Z250 (1.99±0.03, and Fill Magic (2.02±0.02 presented intermediate levels of polymerization shrinkage. Alert and Solitaire presented the highest degree of polymerization shrinkage. Knowing the polymerization shrinkage rates of the commercially available composite resins, the dentist would be able to choose between using composite resins with lower polymerization shrinkage rates or adopting technical or operational procedures to minimize the adverse effects deriving from resin contraction during light-activation.
Volumetric polymerization shrinkage of contemporary composite resins
Nagem Filho, Halim; Nagem, Haline Drumond; Francisconi, Paulo Afonso Silveira; Franco, Eduardo Batista; Mondelli, Rafael Francisco Lia; Coutinho, Kennedy Queiroz
2007-01-01
The polymerization shrinkage of composite resins may affect negatively the clinical outcome of the restoration. Extensive research has been carried out to develop new formulations of composite resins in order to provide good handling characteristics and some dimensional stability during polymerization. The purpose of this study was to analyze, in vitro, the magnitude of the volumetric polymerization shrinkage of 7 contemporary composite resins (Definite, Suprafill, SureFil, Filtek Z250, Fill ...
Autogenous shrinkage, speciality of high performance concretes
Vogrič, Nina
2014-01-01
Autogenous shrinkage is a consequence of self dessication in pores of hardened cement paste and is, at high performance concrete significantly greater than that of the ordinary concretes, mainly due to low water to cement ratio. In the graduation thesis we examined the main mechanisms that cause autogenous shrinkage. It can be reduced by internal curinginternal water reservoirs. As internal water reservoirs we used pre-soaked expanded clay Liapor. On specimens, in which we replaced 12 % of ag...
Guhaniyogi, Rajarshi
2017-11-10
With increasingly abundant spatial data in the form of case counts or rates combined over areal regions (eg, ZIP codes, census tracts, or counties), interest turns to formal identification of difference "boundaries," or barriers on the map, in addition to the estimated statistical map itself. "Boundary" refers to a border that describes vastly disparate outcomes in the adjacent areal units, perhaps caused by latent risk factors. This article focuses on developing a model-based statistical tool, equipped to identify difference boundaries in maps with a small number of areal units, also referred to as small-scale maps. This article proposes a novel and robust nonparametric boundary detection rule based on nonparametric Dirichlet processes, later referred to as Dirichlet process wombling (DPW) rule, by employing Dirichlet process-based mixture models for small-scale maps. Unlike the recently proposed nonparametric boundary detection rules based on false discovery rates, the DPW rule is free of ad hoc parameters, computationally simple, and readily implementable in freely available software for public health practitioners such as JAGS and OpenBUGS and yet provides statistically interpretable boundary detection in small-scale wombling. We offer a detailed simulation study and an application of our proposed approach to a urinary bladder cancer incidence rates dataset between 1990 and 2012 in the 8 counties in Connecticut. Copyright © 2017 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Ying-Si Lai
2017-03-01
Full Text Available Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People's Republic of China (P.R. China. Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions.Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km.We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8-15.8 million people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20% were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang.Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to
Lesaffre, Emmanuel
2012-01-01
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introd
Fytilis, N.; Rizzo, D. M.
2012-12-01
Environmental managers are increasingly required to forecast the long-term effects and the resilience or vulnerability of biophysical systems to human-generated stresses. Mitigation strategies for hydrological and environmental systems need to be assessed in the presence of uncertainty. An important aspect of such complex systems is the assessment of variable uncertainty on the model response outputs. We develop a new classification tool that couples a Naïve Bayesian Classifier with a modified Kohonen Self-Organizing Map to tackle this challenge. For proof-of-concept, we use rapid geomorphic and reach-scale habitat assessments data from over 2500 Vermont stream reaches (~1371 stream miles) assessed by the Vermont Agency of Natural Resources (VTANR). In addition, the Vermont Department of Environmental Conservation (VTDEC) estimates stream habitat biodiversity indices (macro-invertebrates and fish) and a variety of water quality data. Our approach fully utilizes the existing VTANR and VTDEC data sets to improve classification of stream-reach habitat and biological integrity. The combined SOM-Naïve Bayesian architecture is sufficiently flexible to allow for continual updates and increased accuracy associated with acquiring new data. The Kohonen Self-Organizing Map (SOM) is an unsupervised artificial neural network that autonomously analyzes properties inherent in a given a set of data. It is typically used to cluster data vectors into similar categories when a priori classes do not exist. The ability of the SOM to convert nonlinear, high dimensional data to some user-defined lower dimension and mine large amounts of data types (i.e., discrete or continuous, biological or geomorphic data) makes it ideal for characterizing the sensitivity of river networks in a variety of contexts. The procedure is data-driven, and therefore does not require the development of site-specific, process-based classification stream models, or sets of if-then-else rules associated with
Bayesian image reconstruction for improving detection performance of muon tomography.
Wang, Guobao; Schultz, Larry J; Qi, Jinyi
2009-05-01
Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.
Influence of Shrinkage-Reducing Admixtures on the Development of Plastic Shrinkage Cracks
DEFF Research Database (Denmark)
Lura, Pietro; Pease, Bradley Justin; Mazzotta, Guy
2007-01-01
The term plastic shrinkage cracking is generally used to describe cracks that form between the time when concrete is placed and the time when concrete sets. This paper discusses how the evaporation of water causes concave menisci to form on the surface of fresh concrete. These menisci cause both...... settlement of the concrete and tensile stress development in the surface of the concrete, which increase the potential for development of plastic shrinkage cracks. Specifically, this paper studies the development of plastic shrinkage cracks in mortars containing a commercially available shrinkage......-reducing admixture (SRA). Mortars containing SRA show fewer and narrower plastic shrinkage cracks than plain mortars when exposed to the same environmental conditions. It is proposed that the lower surface tension of the pore fluid in the mortars containing SRA results in less evaporation, reduced settlement...
Heat shrinkage of electron beam modified EVA
International Nuclear Information System (INIS)
Datta, S.K.; Chaki, T.K.; Bhowmick, A.K.
1997-01-01
Heat shrinkage of electron beam modified ethylene vinyl acetate copolymer (EVA) has been investigated over a range of times, temperatures, stretching, irradiation doses and trimethylolpropane trimethacrylate (TMPTMA) levels. The irradiated (radiation dose 50 kGy and TMPTMA level 1%) and stretched (100% elongation) sample shrinks to a maximum level when kept at 453K temperature for 60 s. The heat shrinkage of samples irradiated with radiation doses of 20, 50, 100 and 150 kGy increases sharply with increasing stretching in the initial stage. Amnesia rating decreases with increasing radiation dose and TMPTMA level as well as gel content. The high radiation dose and TMPTMA level lower the heat shrinkage due to the chain scission. The effect of temperature at which extension is carried out on heat shrinkage is marginal. The irradiated (radiation dose 50 kGy and TMPTMA level 1%) EVA tubes of different dimensions expanded in a laboratory grade tube expander show similar behaviour at 453K and 60 s. The X-ray and DSC studies reveal that the crystallinity increases on stretching due to orientation of chains and it decreases to a considerable extent on heat shrinking. The theoretical and experimental values of heat shrinkage for tubes and rectangular strips are in good accord, when the radiation dose is 50 kGy and TMPTMA level 1%. (author)
Heat shrinkage of electron beam modified EVA
Energy Technology Data Exchange (ETDEWEB)
Datta, S.K.; Chaki, T.K.; Bhowmick, A.K. [Indian Institute of Technology, Kharagpur (India). Rubber Technology Center; Tikku, V.K.; Pradhan, N.K. [NICCO Corporation Ltd., (Cable Div.), Calcutta (India)
1997-10-01
Heat shrinkage of electron beam modified ethylene vinyl acetate copolymer (EVA) has been investigated over a range of times, temperatures, stretching, irradiation doses and trimethylolpropane trimethacrylate (TMPTMA) levels. The irradiated (radiation dose 50 kGy and TMPTMA level 1%) and stretched (100% elongation) sample shrinks to a maximum level when kept at 453K temperature for 60 s. The heat shrinkage of samples irradiated with radiation doses of 20, 50, 100 and 150 kGy increases sharply with increasing stretching in the initial stage. Amnesia rating decreases with increasing radiation dose and TMPTMA level as well as gel content. The high radiation dose and TMPTMA level lower the heat shrinkage due to the chain scission. The effect of temperature at which extension is carried out on heat shrinkage is marginal. The irradiated (radiation dose 50 kGy and TMPTMA level 1%) EVA tubes of different dimensions expanded in a laboratory grade tube expander show similar behaviour at 453K and 60 s. The X-ray and DSC studies reveal that the crystallinity increases on stretching due to orientation of chains and it decreases to a considerable extent on heat shrinking. The theoretical and experimental values of heat shrinkage for tubes and rectangular strips are in good accord, when the radiation dose is 50 kGy and TMPTMA level 1%. (author).
Dry shrinkage characteristics of buffer materials
Energy Technology Data Exchange (ETDEWEB)
Suzuki, H. [ITC, Tokai, Ibaraki (Japan); Fujita, A.
1999-03-01
Generation of cracks due to drying of compressed bentonite was observed by changing the initial water content to obtain shrinkage constants such as shrinkage limit and shrinking rate. As a result, generation of practically no cracks was observed when the initial water content of samples was below 13%. The volume change due to drying increased with the water content in the sample, and the shrinkage constants were found to depend on the initial water content. Further, the one-dimensional compression strength after drying was compared with that before drying in order to clarify the effect of cracks generated by drying on the mechanical strength. As a result, the dry sample with cracks proved to have large one-dimensional compression strength or E{sub 50} compared to wet samples, so that the mechanical strength was kept even after drying. (H. Baba)
Assessment of concrete creep and shrinkage
International Nuclear Information System (INIS)
Trivedi, Neha; Singh, R.K.
2012-01-01
B-3 model prediction of concrete creep and shrinkage strains on cylindrical specimen and BARC Containment test model (BARCOM) are presented. Experimental shrinkage strain is shown to be in agreement with B-3 model predictions for cylindrical specimen and BARCOM. Creep strain in cylindrical specimen is found to be in agreement with B-3 model. In BARCOM for wall cast in different pores, creep strain is in agreement with B-3 model in hoop direction however in longitudinal direction, observed creep strain in higher than B-3 model. For dome structure cast in a single pour, experimental creep strain shows confirmity with B-3 model both in hoop and longitudinal directions. The study on concrete aging and average longitudinal shrinkage strain is carried out. (author)
Mapping malaria risk among children in Côte d’Ivoire using Bayesian geo-statistical models
Directory of Open Access Journals (Sweden)
Raso Giovanna
2012-05-01
Full Text Available Abstract Background In Côte d’Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged Methods Using different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d’Ivoire, focusing on children aged Plasmodium spp. infection risk for entire Côte d’Ivoire, including uncertainty. Results Overall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged Conclusion The malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d’Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation.
Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage
Directory of Open Access Journals (Sweden)
Yan-long Chen
2014-01-01
Full Text Available The potential application of a quantum-inspired adaptive wavelet shrinkage (QAWS technique to mechanical vibration signals with a focus on noise reduction is studied in this paper. This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT coefficients, and the quantum-inspired probability of noise defined to shrink wavelet coefficients in a Bayesian framework. By combining all these elements, this signal processing scheme incorporating the DTCWT with quantum theory can both reduce noise and preserve signal details. A practical vibration signal measured from a power-shift steering transmission is utilized to evaluate the denoising ability of QAWS. Application results demonstrate the effectiveness of the proposed method. Moreover, it achieves better performance than hard and soft thresholding.
Regression tools for CO2 inversions: application of a shrinkage estimator to process attribution
International Nuclear Information System (INIS)
Shaby, Benjamin A.; Field, Christopher B.
2006-01-01
In this study we perform an atmospheric inversion based on a shrinkage estimator. This method is used to estimate surface fluxes of CO 2 , first partitioned according to constituent geographic regions, and then according to constituent processes that are responsible for the total flux. Our approach differs from previous approaches in two important ways. The first is that the technique of linear Bayesian inversion is recast as a regression problem. Seen as such, standard regression tools are employed to analyse and reduce errors in the resultant estimates. A shrinkage estimator, which combines standard ridge regression with the linear 'Bayesian inversion' model, is introduced. This method introduces additional bias into the model with the aim of reducing variance such that errors are decreased overall. Compared with standard linear Bayesian inversion, the ridge technique seems to reduce both flux estimation errors and prediction errors. The second divergence from previous studies is that instead of dividing the world into geographically distinct regions and estimating the CO 2 flux in each region, the flux space is divided conceptually into processes that contribute to the total global flux. Formulating the problem in this manner adds to the interpretability of the resultant estimates and attempts to shed light on the problem of attributing sources and sinks to their underlying mechanisms
Shrinkage Approach for Gene Expression Data Analysis
Czech Academy of Sciences Publication Activity Database
Haman, Jiří; Valenta, Zdeněk
2013-01-01
Roč. 9, č. 3 (2013), s. 2-8 ISSN 1801-5603 Grant - others:UK(CZ) SVV-2013-266517 Institutional support: RVO:67985807 Keywords : microarray technology * high dimensional data * mean squared error * James-Stein shrinkage estimator * mutual information Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2013/3/Haman_en.pdf
Quantitative analyses of shrinkage characteristics of neem ...
African Journals Online (AJOL)
Quantitative analyses of shrinkage characteristics of neem (Azadirachta indica A. Juss.) wood were carried out. Forty five wood specimens were prepared from the three ecological zones of north eastern Nigeria, viz: sahel savanna, sudan savanna and guinea savanna for the research. The results indicated that the wood ...
Identification of microcracks caused by autogenous shrinkage
DEFF Research Database (Denmark)
Lura, Pietro; Jensen, Ole Mejlhede; Guang, Ye
2005-01-01
Detection and quantification of microcracks caused by restrained autogenous shrinkage in high-performance concrete is difficult. Available techniques either lack the required resolution or may cause further cracks indistinguishable from the original ones. The new technique presented in this paper...
Drying shrinkage problems in high PI subgrade soils.
2014-01-01
The main objective of this study was to investigate the longitudinal cracking in pavements due to drying : shrinkage of high PI subgrade soils. The study involved laboartory soil testing and modeling. The : shrinkage cracks usually occur within the v...
Gutiérrez, J. M.; Natxiondo, A.; Nieves, J.; Zabala, A.; Sertucha, J.
2017-04-01
The study of shrinkage incidence variations in nodular cast irons is an important aspect of manufacturing processes. These variations change the feeding requirements on castings and the optimization of risers' size is consequently affected when avoiding the formation of shrinkage defects. The effect of a number of processing variables on the shrinkage size has been studied using a layout specifically designed for this purpose. The β parameter has been defined as the relative volume reduction from the pouring temperature up to the room temperature. It is observed that shrinkage size and β decrease as effective carbon content increases and when inoculant is added in the pouring stream. A similar effect is found when the parameters selected from cooling curves show high graphite nucleation during solidification of cast irons for a given inoculation level. Pearson statistical analysis has been used to analyze the correlations among all involved variables and a group of Bayesian networks have been subsequently built so as to get the best accurate model for predicting β as a function of the input processing variables. The developed models can be used in foundry plants to study the shrinkage incidence variations in the manufacturing process and to optimize the related costs.
Classification and Methods of Shrinkage Defect Control
Directory of Open Access Journals (Sweden)
N. S. Larichev
2016-01-01
Full Text Available The objective is to put forward a proposal to divide the internal shrinkage defects into the dimensional levels according to defects of certain size and shape.The paper presents the terminology used to describe the internal shrinkage defects in the casting and shows its flaws. These include the lack of well-defined threshold size values and shape of defects. It is shown that in describing defects their sizes and shape are defined qualitatively rather than quantitatively. And it is noted that division of defects into pores and shells is based on the morphological characters.The paper notes that a distinct difference between defects is necessary because of different methods of their elimination from the casting body.The paper presents an overview of control methods to determine the defects of the shrinkage nature in castings. These are methods of destructive and non-destructive testing, such as Xrays, tomography, and metallography. The paper also shows advantages and disadvantages of the considered methods of control. Based on the control method capacities it offers to divide the shrinkage defects into the three dimensional levels.To estimate the shape of defects the paper suggests a new option, that is a shape criterion. By the example of the typical defects of each dimensional level are defined the threshold values of the shape criterion.The paper discusses the basic techniques to estimate the porosity and offers a relationship between the defects of different dimensional levels and a porosity score and percent. It shows that the transition from a dimensional level to another one is in line with not only increasing pore size, but also with a significant deterioration of the mechanical properties of castings.The main conclusions are as follows:1. At present, there is no single unambiguous classification of casting shrinkage defects in the technical literature.2. As follows from the analysis of the classifications of shrinkage defects, their
Shrinkage measurement for holographic recording materials
Fernández, R.; Gallego, S.; Márquez, A.; Francés, J.; Navarro Fuster, V.; Neipp, C.; Ortuño, M.; Beléndez, A.; Pascual, I.
2017-05-01
There is an increasing demand for new holographic recording materials. One of them are photopolymers, which are becoming a classic media in this field. Their versatility is well known and new possibilities are being created by including new components, such as nanoparticles or dispersed liquid crystal molecules in classical formulations, making them interesting for additional applications in which the thin film preparation and the structural modification have a fundamental importance. Prior to obtaining a wide commercialization of displays based on photopolymers, one of the key aspects is to achieve a complete characterization of them. In this sense, one of the main parameters to estimate and control is the shrinkage of these materials. The volume variations change the angular response of the hologram in two aspects, the angular selectivity and the maximum diffraction efficiency. One criteria for the recording material to be used in a holographic data storage application is the shrinkage, maximum of 0.5%. Along this work, we compare two different methods to measure the holographic recording material shrinkage. The first one is measuring the angle of propagation for both diffracted orders +/-1 when slanted gratings are recorded, so that an accurate value of the grating vector can be calculated. The second one is based on interference measurements at zero spatial frequency limit. We calculate the shrinkage for three different photopolymers: a polyvinyl alcohol acrylamide (PVA/AA) based photopolymer, one of the greenest photopolymers whose patent belongs to the Alicante University called Biophotopol and on the last place a holographic-dispersed liquid crystal photopolymer (H-PDLC).
Nearest shrunken centroids via alternative genewise shrinkages.
Directory of Open Access Journals (Sweden)
Byeong Yeob Choi
Full Text Available Nearest shrunken centroids (NSC is a popular classification method for microarray data. NSC calculates centroids for each class and "shrinks" the centroids toward 0 using soft thresholding. Future observations are then assigned to the class with the minimum distance between the observation and the (shrunken centroid. Under certain conditions the soft shrinkage used by NSC is equivalent to a LASSO penalty. However, this penalty can produce biased estimates when the true coefficients are large. In addition, NSC ignores the fact that multiple measures of the same gene are likely to be related to one another. We consider several alternative genewise shrinkage methods to address the aforementioned shortcomings of NSC. Three alternative penalties were considered: the smoothly clipped absolute deviation (SCAD, the adaptive LASSO (ADA, and the minimax concave penalty (MCP. We also showed that NSC can be performed in a genewise manner. Classification methods were derived for each alternative shrinkage method or alternative genewise penalty, and the performance of each new classification method was compared with that of conventional NSC on several simulated and real microarray data sets. Moreover, we applied the geometric mean approach for the alternative penalty functions. In general the alternative (genewise penalties required fewer genes than NSC. The geometric mean of the class-specific prediction accuracies was improved, as well as the overall predictive accuracy in some cases. These results indicate that these alternative penalties should be considered when using NSC.
Nearest shrunken centroids via alternative genewise shrinkages
Choi, Byeong Yeob; Bair, Eric; Lee, Jae Won
2017-01-01
Nearest shrunken centroids (NSC) is a popular classification method for microarray data. NSC calculates centroids for each class and “shrinks” the centroids toward 0 using soft thresholding. Future observations are then assigned to the class with the minimum distance between the observation and the (shrunken) centroid. Under certain conditions the soft shrinkage used by NSC is equivalent to a LASSO penalty. However, this penalty can produce biased estimates when the true coefficients are large. In addition, NSC ignores the fact that multiple measures of the same gene are likely to be related to one another. We consider several alternative genewise shrinkage methods to address the aforementioned shortcomings of NSC. Three alternative penalties were considered: the smoothly clipped absolute deviation (SCAD), the adaptive LASSO (ADA), and the minimax concave penalty (MCP). We also showed that NSC can be performed in a genewise manner. Classification methods were derived for each alternative shrinkage method or alternative genewise penalty, and the performance of each new classification method was compared with that of conventional NSC on several simulated and real microarray data sets. Moreover, we applied the geometric mean approach for the alternative penalty functions. In general the alternative (genewise) penalties required fewer genes than NSC. The geometric mean of the class-specific prediction accuracies was improved, as well as the overall predictive accuracy in some cases. These results indicate that these alternative penalties should be considered when using NSC. PMID:28199352
Polymerization shrinkage assessment of dental resin composites: a literature review.
Kaisarly, Dalia; Gezawi, Moataz El
2016-09-01
Composite restorations are widely used worldwide, but the polymerization shrinkage is their main disadvantage that may lead to clinical failures and adverse consequences. This review reports, currently available in vitro techniques and methods used for assessing the polymerization shrinkage. The focus lies on recent methods employing three-dimensional micro-CT data for the evaluation of polymerization shrinkage: volumetric measurement and the shrinkage vector evaluation through tracing particles before and after polymerization. Original research articles reporting in vitro shrinkage measurements and shrinkage stresses were included in electronic and hand-search. Earlier methods are easier, faster and less expensive. The procedures of scanning the samples in the micro-CT and performing the shrinkage vector evaluation are time consuming and complicated. Moreover, the respective software is not commercially available and the various methods for shrinkage vector evaluation are based on different mathematical principles. Nevertheless, these methods provide clinically relevant information and give insight into the internal shrinkage behavior of composite applied in cavities and how boundary conditions affect the shrinkage vectors. The traditional methods give comparative information on polymerization shrinkage of resin composites, whereas using three-dimensional micro-CT data for volumetric shrinkage measurement and the shrinkage vector evaluation is a highly accurate method. The methods employing micro-CT data give the researchers knowledge related to the application method and the boundary conditions of restorations for visualizing the shrinkage effects that could not be seen otherwise. Consequently, this knowledge can be transferred to the clinical situation to optimize the material manipulation and application techniques for improved outcomes.
Bessiere, Pierre; Ahuactzin, Juan Manuel; Mekhnacha, Kamel
2013-01-01
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an alternative framework to deal with incomplete and uncertain data. Decision-Making Tools and Methods for Incomplete and Uncertain DataEmphasizing probability as an alternative to Boolean
Shrinkage-reducing admixtures and early-age desiccation in cement pastes and mortars
DEFF Research Database (Denmark)
Bentz, D. P.; Geiker, Mette Rica; Hansen, Kurt Kielsgaard
2001-01-01
to map the drying profile, internal relative humidity (RH), and autogenous deformation. Interestingly, although the SRA accelerates the drying of bulk solutions, in cement paste with a water-to-cement (w/c) ratio of 0.35, it actually reduces the measured drying rate. Based on the accompanying X...... to low w/c ratio concretes undergoing self-desiccation, in addition to their normal usage to reduce drying shrinkage....
Computation of shrinkage stresses in prestressed concrete containments
International Nuclear Information System (INIS)
Wu, R.F.; Ouyang, H.
1989-01-01
According to a survey, surface cracking on PCRVs and PCCs under the investigations is confined to drying shrinkage and thermal strain effects and no instances of structurally significant cracking was been found. In this paper, the authors use FEM to compute humidity distribution in drying concrete and shrinkage stresses by internal restraint. Since PCC is built segment by segment in several years, a computational model taking into account construction sequence is presented and shrinkage stresses by external restraints are calculated with the model
Shrinkage, stress, and modulus of dimethacrylate, ormocer, and silorane composites.
Bacchi, Atais; Feitosa, Victor Pinheiro; da Silva Fonseca, Andrea Soares Quirino; Cavalcante, Larissa Maria Assad; Silikas, Nikolaos; Schneider, Luis Felipe Jochins
2015-01-01
to evaluate the shrinkage, polymerization stress, elastic and bulk modulus resulting from composites formulated by siloranes, 2(nd) generation ormocers, and dimethacrylates. The bonded disc method was used to evaluate volumetric shrinkage. The polymerization stress was evaluated by mean of the Bioman. Cylindrical specimens (5 mm thickness and 6 mm diameter) were submitted to gradual loading. Young's and bulk modulus were obtained from the slope of the stress/strain curve. Data were analyzed using one-way analysis of variance and Tukey's test (5%). Grandio and ormocer showed significant higher elastic and bulk modulus. Silorane presented significant lowest bulk modulus and maximum shrinkage. Ormocer and silorane presented lower values for the maximum rate of shrinkage. Extra-low shrinkage (ELS) composite presented the greatest maximum shrinkage. The higher maximum rate of shrinkage was attained by Grandio and ELS, statistically similar from each other. The silorane showed lower values of maximum stress and maximum rate of stress. The higher values of maximum stress were presented by ELS and Grandio, statistical similar between them. Grandio showed the significantly greatest maximum rate of stress. Silorane showed to promote lower shrinkage/stress among the composites, with the lowest elastic modulus. Ormocer showed lower shrinkage/stress than methacrylates despite of its high modulus.
Towards a first classification of aerosol shrinkage events
Alonso-Blanco, E.; Gómez-Moreno, F. J.; Núñez, L.; Pujadas, M.; Cusack, M.; Artíñano, B.
2015-09-01
This work presents for the first time a classification of shrinkage events based on the aerosol processes that precede them. To this end, 3.5 years of continuous measurements (from 2009 to 2012) of aerosol size distributions, obtained with a Scanning Mobility Particle Sizer (SMPS) at an urban background site in Southern Europe, have been interpreted. 48 shrinkage events were identified and analysed, all occurring during spring and summer when the atmospheric conditions are more favourable for their development. In this study the shrinkage events took place mostly towards the end of the day, and their occurrence could be associated to atmospheric dilution conditions and a reduction in photochemical activity. The shrinkage rate (SR) varied between -1.0 and -11.1 nm h-1 (average value of -4.7 ± 2.6 nm h-1). Changes in particle concentrations corresponding to the nucleation and Aitken modes were detected, whereby an increase in the number of particles in the nucleation mode often coincided with a reduction in the Aitken mode. The accumulation mode did not undergo significant changes during these processes. In addition, in some cases, a dilution of the total particle number concentration in the ambient air was observed. Following the proposed methodology, three groups of events have been identified: Group I (NPF + shrinkage), Group II (aerosol growth process + shrinkage) and Group III (pure shrinkage events). The largest number of shrinkage events has been observed in the absence of prior processes, i.e. pure shrinkage events, followed by Group I events and finally Group II events. Although this analysis has confirmed that the triggering of shrinkage events is clearly linked to the atmospheric situation and the characteristics of the measurement area, this classification may contribute to a better understanding of the processes involved and the features that characterize shrinkage events.
SHRINKAGE AND MOISTURE LOSS OF DRIED MELON SEEDS ...
African Journals Online (AJOL)
The study showed that fresh melon seeds dried to 7.4% moisture content(wb) lost 539.2 grams of moisture per kilogram dry matter and the percentage shrinkage of the seeds was 33.9%. Graphs of moisture loss in grams per kilogram dry matter were plotted against percentage shrinkage. A straight line relationship was ...
Dynamics of tissue shrinkage during ablative temperature exposures
International Nuclear Information System (INIS)
Rossmann, Christian; Haemmerich, Dieter; Garrett-Mayer, Elizabeth; Rattay, Frank
2014-01-01
There is a lack of studies that examine the dynamics of heat-induced shrinkage of organ tissues. Clinical procedures such as radiofrequency ablation, microwave ablation or high-intensity focused ultrasound, use heat to treat diseases such as cancer and cardiac arrhythmia. When heat is applied to tissues, shrinkage occurs due to protein denaturation, dehydration and contraction of collagen at temperatures greater 50 °C. This is particularly relevant for image-guided procedures such as tumor ablation, where pre- and post-treatment images are compared and any changes in dimensions must be considered to avoid misinterpretations of the treatment outcome. We present data from ex vivo, isothermal shrinkage tests in porcine liver tissue, where axial changes in tissue length were recorded during 15 min of heating to temperatures between 60 and 95 °C. A mathematical model was developed to accurately describe the time and temperature-dependent shrinkage behavior. The shrinkage dynamics had the same characteristics independent of temperature; the estimated relative shrinkage, adjusted for time since death, after 15 min heating to temperatures of 60, 65, 75, 85 and 95 °C, was 12.3, 13.8, 16.6, 19.2 and 21.7%, respectively. Our results demonstrate the shrinkage dynamics of organ tissues, and suggest the importance of considering tissue shrinkage for thermal ablative treatments. (paper)
International Nuclear Information System (INIS)
Wyrzykowski, Mateusz; Trtik, Pavel; Münch, Beat; Weiss, Jason; Vontobel, Peter; Lura, Pietro
2015-01-01
Water transport in fresh, highly permeable concrete and rapid water evaporation from the concrete surface during the first few hours after placement are the key parameters influencing plastic shrinkage cracking. In this work, neutron tomography was used to determine both the water loss from the concrete surface due to evaporation and the redistribution of fluid that occurs in fresh mortars exposed to external drying. In addition to the reference mortar with a water to cement ratio (w/c) of 0.30, a mortar with the addition of pre-wetted lightweight aggregates (LWA) and a mortar with a shrinkage reducing admixture (SRA) were tested. The addition of SRA reduced the evaporation rate from the mortar at the initial stages of drying and reduced the total water loss. The pre-wetted LWA released a large part of the absorbed water as a consequence of capillary pressure developing in the fresh mortar due to evaporation
Introduction to Bayesian statistics
Bolstad, William M
2017-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Bayesian artificial intelligence
Korb, Kevin B
2003-01-01
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
Bayesian artificial intelligence
Korb, Kevin B
2010-01-01
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente
Directory of Open Access Journals (Sweden)
Mihaela Simionescu
2014-12-01
Full Text Available There are many types of econometric models used in predicting the inflation rate, but in this study we used a Bayesian shrinkage combination approach. This methodology is used in order to improve the predictions accuracy by including information that is not captured by the econometric models. Therefore, experts’ forecasts are utilized as prior information, for Romania these predictions being provided by Institute for Economic Forecasting (Dobrescu macromodel, National Commission for Prognosis and European Commission. The empirical results for Romanian inflation show the superiority of a fixed effects model compared to other types of econometric models like VAR, Bayesian VAR, simultaneous equations model, dynamic model, log-linear model. The Bayesian combinations that used experts’ predictions as priors, when the shrinkage parameter tends to infinite, improved the accuracy of all forecasts based on individual models, outperforming also zero and equal weights predictions and naïve forecasts.
Bayesian Group Bridge for Bi-level Variable Selection.
Mallick, Himel; Yi, Nengjun
2017-06-01
A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.
Alternative methods for determining shrinkage in restorative resin composites.
de Melo Monteiro, Gabriela Queiroz; Montes, Marcos Antonio Japiassú Resende; Rolim, Tiago Vieira; de Oliveira Mota, Cláudia Cristina Brainer; de Barros Correia Kyotoku, Bernardo; Gomes, Anderson Stevens Leônidas; de Freitas, Anderson Zanardi
2011-08-01
The purpose of this study was to evaluate polymerization shrinkage of resin composites using a coordinate measuring machine, optical coherence tomography and a more widely known method, such as Archimedes Principle. Two null hypothesis were tested: (1) there are no differences between the materials tested; (2) there are no differences between the methods used for polymerization shrinkage measurements. Polymerization shrinkage of seven resin-based dental composites (Filtek Z250™, Filtek Z350™, Filtek P90™/3M ESPE, Esthet-X™, TPH Spectrum™/Dentsply 4 Seasons™, Tetric Ceram™/Ivoclar-Vivadent) was measured. For coordinate measuring machine measurements, composites were applied to a cylindrical Teflon mold (7 mm × 2 mm), polymerized and removed from the mold. The difference between the volume of the mold and the volume of the specimen was calculated as a percentage. Optical coherence tomography was also used for linear shrinkage evaluations. The thickness of the specimens was measured before and after photoactivation. Polymerization shrinkage was also measured using Archimedes Principle of buoyancy (n=5). Statistical analysis of the data was performed with ANOVA and the Games-Howell test. The results show that polymerization shrinkage values vary with the method used. Despite numerical differences the ranking of the resins was very similar with Filtek P90 presenting the lowest shrinkage values. Because of the variations in the results, reported values could only be used to compare materials within the same method. However, it is possible rank composites for polymerization shrinkage and to relate these data from different test methods. Independently of the method used, reduced polymerization shrinkage was found for silorane resin-based composite. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Shrinkage covariance matrix approach for microarray data
Karjanto, Suryaefiza; Aripin, Rasimah
2013-04-01
Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
Studies on heat shrinkage PVC tubes
International Nuclear Information System (INIS)
Pyun, Hyung Chick; Kim, Ki Yup; Nho, Young Chang
1991-01-01
Radiation crosslinking of PVC was investigated for the purpose of obtaining a suitable formulation for heat shrinkable tube. PVC was not only compounded with various crosslinking agents and plasticizers to evaluate their effects on the radiation sensitivity, heat shrinkable property and other mechanical properties, but also mixed with NBR, crosslinking agents and plasticizers to obtain efficient crosslinking yield and suitable mechanical properties for heat shrinkable tube. Gel yield of PVC increased with increasing unsaturation levels per molecular weight of crosslinking agents. Among crosslinking agents tested, TMPTMA with three unsaturated groups showed highest gel yield, while PVC containing NBR was more sensitive to crosslinking than PVC itself regardless the types of crosslinking agents and plasticizers. Tensile strength was increased with increasing radiation dose and gel percent, but elongation decreased. It was found that gel percent was increased with increasing radiation dose, heat transformation was decreased with increasing gel percent. When NBR was mixed with PVC, the radiation dosage required for enhancing yield of gel percent and heat transformation were found to be much smaller comparing with the case containing no NBR. Therefore, the addition of NBR to PVC was very effective to increase heat-resisting property of PVC. Heat shrinkage was not much varied with radiation dose, the types of crosslinking agents and plasticizers, but it was increased remarkably with decreasing stretching temperature and increasing annealing temperature. (Author)
STRENGTH SHRINKAGE AND CREEP OF CONCRETE IN TENSION AND COMPRESSION
Directory of Open Access Journals (Sweden)
S A Kristiawan
2006-01-01
Full Text Available Strength, shrinkage and creep of concrete in tension and compression have been determined and the relationship between those properties was studied. Direct tensile tests were applied to measure those properties in tension. The relationship of creep in tension and compression was determined based on the measurement of creep at similar stress and similar stress/strength ratio. It is found that concrete deforms more in tension than in compression. Except for concrete with a higher water/cement ratio, the use of pulverised fuel ash, ground granulated blast furnace slag, superplasticizer and shrinkage reducing admixture has no effect on strength. However, they affect creep and shrinkage of concrete.
Modeling for prediction of restrained shrinkage effect in concrete repair
International Nuclear Information System (INIS)
Yuan Yingshu; Li Guo; Cai Yue
2003-01-01
A general model of autogenous shrinkage caused by chemical reaction (chemical shrinkage) is developed by means of Arrhenius' law and a degree of chemical reaction. Models of tensile creep and relaxation modulus are built based on a viscoelastic, three-element model. Tests of free shrinkage and tensile creep were carried out to determine some coefficients in the models. Two-dimensional FEM analysis based on the models and other constitutions can predict the development of tensile strength and cracking. Three groups of patch-repaired beams were designed for analysis and testing. The prediction from the analysis shows agreement with the test results. The cracking mechanism after repair is discussed
Wetlands shrinkage, fragmentation and their links to agriculture in the Muleng-Xingkai Plain, China.
Song, Kaishan; Wang, Zongming; Li, Lin; Tedesco, Lenore; Li, Fang; Jin, Cui; Du, Jia
2012-11-30
In the past five decades, the wetlands in the Muleng-Xingkai Plain, Northeast China, have experienced rapid shrinkage and fragmentation. In this study, wetlands cover change and agricultural cultivation were investigated through a time series of thematic maps from 1954, and Landsat satellite images representing the last five decades (1976, 1986, 1995, 2000, and 2005). Wetlands shrinkage and fragmentation were studied based on landscape metrics and the land use changes transition matrix. Furthermore, the driving forces were explored according to socioeconomic development and major natural environmental factors. The results indicate a significant decrease in the wetlands area in the past five decades, with an average annual decrease rate of 9004 ha/yr. Of the 625,268 ha of native wetlands in 1954, approximately 64% has been converted to other land use types by 2005, of which conversion to cropland accounts for the largest share (83%). The number of patches decreased from 1272 (1954) to 197 (1986) and subsequently increased to 326 (2005). The mean patch size changed from 480 ha (1954) to 1521 ha (1976), and then steadily decreased to 574 ha (2005). The largest patch index (total core area index) indicates wetlands shrinkage with decreased values from 31.73 (177,935 ha) to 3.45 (39,421 ha) respectively. Climatic changes occurred over the study period, providing a potentially favorable environment for agricultural development. At the same time population, groundwater harvesting, and fertilizer application increased significantly, resulting in wetlands degradation. According to the results, the shrinkage and fragmentation of wetlands could be explained by socioeconomic development and secondarily aided by changing climatic conditions. Copyright © 2012 Elsevier Ltd. All rights reserved.
Mesoscopic analysis of drying shrinkage damage in a cementitious material
DEFF Research Database (Denmark)
Moonen, P.; Pedersen, R.R.; Simone, A.
2008-01-01
Concrete and cement-based materials exhibit shrinkage when exposed to drying. Structural effects and inhomogeneity of material properties adverse free shrinkage, hereby inducing stress concentrations and possibly damage. In this contribution, the magnitude of shrinkage- induced damage during...... a typical sample preparation procedure is assessed. To this extent, a coupled hygro-thermo-mechanical model, incorporating rate-effects, is developed. The constitutive model is applied at a mesoscopic level where the aggregates and the interfacial transition zone (ITZ) are explicitly modelled. Two drying...... temperatures are considered: 35 °C and 50 °C. Significantly more micro-damage and higher internal stresses are found for the latter, revealing the importance of drying shrinkage damage, even at laboratory scale....
Shrinkage and durability study of bridge deck concrete.
2010-12-01
The Mississippi Department of Transportation is incorporating changes to material : specifications and construction procedures for bridge decks in an effort to reduce shrinkage : cracking. These changes are currently being implemented into a limited ...
Prevention of shrinkage cracking in tight concrete structures
International Nuclear Information System (INIS)
Alvaredo, A.M.; Wittmann, F.H.
1995-01-01
It is shown that crack formation and propagation in concrete members subjected to restrained shrinkage can be realistically predicted by means of a comprehensive approach including a diffusion analysis and fracture mechanics considerations. The conditions for stable crack propagation regarding dimensions of the concrete member, degree of restraint to the imposed deformation and material properties are discussed. Guidelines on the prevention of shrinkage cracking of concrete structures are given. (author). 10 refs., 5 figs
Reduction of polyester resin shrinkage by means of epoxy resin
International Nuclear Information System (INIS)
Pietrzak, M.; Brzostowski, A.
1981-01-01
An attempt was made to decrease the shrinkage of unsaturated polyester resin, taking place during radiation-induced curing, by the addition of epoxy resin. In order to combine chemically both resins, the epoxy component was modified with cinnamic and acrylic acids. A composition of 90 parts of polyester resin, 10 parts of epoxy resin modified with cinnamic acid, and 150 parts of a silica filler showed a volume shrinkage of 1.2%. (author)
The measurement of polymerization shrinkage of composite resins with ESPI
Zhang, Zhang; Yang, Guo Biao
2008-09-01
In the current study, we used the method of electronic speckle pattern interferometry (ESPI) to measure polymerization shrinkage of composite resins. Standardized cavities were prepared and placed into the ESPI apparatus before the cavities were filled with composites (n=2) .The ESPI apparatus was constructed to measure the out-of-plane displacement of the resins surface during the polymerization. Experiments demonstrated that the ESPI technique was a viable method to measure the deformation of composite resins. It was responsive and sensitive to dimensional changes. We found that cavity shape, size and C- factor influenced the date of resins shrinkage. And the tooth deformation in response to polymerization of resins was measured by the ESPI too. We concluded that ESPI was a feasible method for assessing resins deformation induced by its polymerization shrinkage when it was bonded in tooth cavities. And the results were greatly influenced by the dimensions of cavities , or interface adhesive and so on. It could also measure the tooth deformation induced by shrinkage of bonded composite resins. We found that resins polymerization shrinkage date may overestimate shrinkage-induced tooth deformation.
Bayesian analysis of RNA sequencing data by estimating multiple shrinkage priors
van de Wiel, M.A.; Leday, G.G.R.; Pardo, L.M.; Rue, H; van der Vaart, A.W.; van Wieringen, W.N.
2013-01-01
Next generation sequencing is quickly replacing microarrays as a technique to probe different molecular levels of the cell, such as DNA or RNA. The technology provides higher resolution, while reducing bias. RNA sequencing results in counts of RNA strands. This type of data imposes new statistical
Bayesian mixture models for partially verified data
DEFF Research Database (Denmark)
Kostoulas, Polychronis; Browne, William J.; Nielsen, Søren Saxmose
2013-01-01
Bayesian mixture models can be used to discriminate between the distributions of continuous test responses for different infection stages. These models are particularly useful in case of chronic infections with a long latent period, like Mycobacterium avium subsp. paratuberculosis (MAP) infection...
Method of Preventing Shrinkage of Aluminum Foam Using Carbonates
Directory of Open Access Journals (Sweden)
Takashi Nakamura
2011-12-01
Full Text Available Metallic foams are commonly produced using titanium hydride as a foaming agent. Carbonates produce aluminum foam with a fine and homogenous cell structure. However, foams produced using carbonates show marked shrinkage, which is clearly different from those produced using titanium hydride. It is essential for practical applications to clarify foam shrinkage and establish a method of preventing it. In this research, cell structures were observed to study the shrinkage of aluminum foam produced using carbonates. The cells of foam produced using dolomite as a foaming agent connected to each other with maximum expansion. It was estimated that foaming gas was released through connected cells to the outside. It was assumed that cell formation at different sites is effective in preventing shrinkage induced by cell connection. The multiple additions of dolomite and magnesium carbonate, which have different decomposition temperatures, were applied. The foam in the case with multiple additions maintained a density of 0.66 up to 973 K, at which the foam produced using dolomite shrank. It was verified that the multiple additions of carbonates are effective in preventing shrinkage.
Plastic and free shrinkages cracking of blended white cement concrete
Energy Technology Data Exchange (ETDEWEB)
Rashad, A.M.; White, T.; Ariaratnam, S.; Knutson, K. [Housing and Building National Research Center, Cairo (Egypt)
2007-07-01
This paper presented the results of a study that investigated the plastic and free shrinkages of white portland cement concrete, concrete incorporating silica fume (SF) and concrete incorporating metakaolin (MK) compared to regular plain gray portland cement concrete. An experimental program was designed to investigate the plastic and free shrinkage of concrete containing gray and white blended cement. The paper discussed the experimental details including materials and cement types such as SF, MK, aggregate, and superplasticizer as well as concrete mixtures and specimen preparation including mixture proportions, preparation and curing of concrete specimens, and test specimens. It also presented the determination of concrete properties such as slump of fresh concrete, plastic shrinkage, and dry shrinkage. Test results and discussion of results were also provided. It was concluded that plain white portland cement concrete showed less number of plastic cracks but slightly higher average crack width compared to other concrete mixtures with MK or SF. In addition, free shrinkage behavior of plain white cement and plain gray cement matrix was comparable. 23 refs.
Geosynthetic clay liners shrinkage under simulated daily thermal cycles.
Sarabadani, Hamid; Rayhani, Mohammad T
2014-06-01
Geosynthetic clay liners are used as part of composite liner systems in municipal solid waste landfills and other applications to restrict the escape of contaminants into the surrounding environment. This is attainable provided that the geosynthetic clay liner panels continuously cover the subsoil. Previous case histories, however, have shown that some geosynthetic clay liner panels are prone to significant shrinkage and separation when an overlying geomembrane is exposed to solar radiation. Experimental models were initiated to evaluate the potential shrinkage of different geosynthetic clay liner products placed over sand and clay subsoils, subjected to simulated daily thermal cycles (60°C for 8 hours and 22°C for 16 hours) modelling field conditions in which the liner is exposed to solar radiation. The variation of geosynthetic clay liner shrinkage was evaluated at specified times by a photogrammetry technique. The manufacturing techniques, the initial moisture content, and the aspect ratio (ratio of length to width) of the geosynthetic clay liner were found to considerably affect the shrinkage of geosynthetic clay liners. The particle size distribution of the subsoil and the associated suction at the geosynthetic clay liner-subsoil interface was also found to have significant effects on the shrinkage of the geosynthetic clay liner. © The Author(s) 2014.
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Angelidou, Elisavet; Kostoulas, Polychronis; Leontides, Leonidas
2016-02-01
A total of 854 paired milk and blood samples were collected from ewes of a Greek flock and used to estimate the sensitivity and specificity of a commercial ELISA for detection of Mycobacterium avium subsp. paratuberculosis (MAP) specific antibodies in each stage of lactation. We implemented Bayesian mixture models to derive the distributions of the test response for the healthy and the infected ewes. In the colostrum period, early, mid and late lactation stage the median values of the area under the curves (AUC) were 0.61 (95% credible interval: 0.50; 0.84), 0.61 (0.51;0.84), 0.65 (0.51;0.91), 0.65(0.51;0.89) for the serum ELISA and and 0.60 (0.50; 0.84), 0.61 (0.50; 0.84), 0.67(0.51; 0.91), 0.66(0.50; 0.90) for the milk ELISA, respectively. Both serum and milk ELISA had low to average overall discriminatory ability as measured by the area under the curves and comparable sensitivities and specificities at the recommended cutoffs. Copyright © 2015 Elsevier B.V. All rights reserved.
Hydration of Portoguese cements, measurement and modelling of chemical shrinkage
DEFF Research Database (Denmark)
Maia, Lino; Geiker, Mette Rica; Figueiras, Joaquim A.
2008-01-01
form of the dispersion model. The development of hydration varied between the investigated cements; based on the measured data the degree of hydration after 24 h hydration at 20 C varied between 40 and 50%. This should be taken into account when comparing properties of concrete made from the different......Development of cement hydration was studied by measuring the chemical shrinkage of pastes. Five types of Portuguese Portland cement were used in cement pastes with . Chemical shrinkage was measured by gravimetry and dilatometry. In gravimeters results were recorded automatically during at least...... seven days, dilatometers were manually recorded during at least 56 days. The dispersion model was applied to fit chemical shrinkage results and to estimate the maximum (or ultimate) value for calculation of degree of hydration. Except for a pure Portland cement best fits were obtained by the general...
Shrinkage calibration method for μPIM manufactured parts
DEFF Research Database (Denmark)
Quagliotti, Danilo; Tosello, Guido; Salaga, J.
2016-01-01
Five green and five sintered parts of a micro mechanical component, produced by micro powder injection moulding, were measured using an optical coordinate measuring machine. The aim was to establish a method for quality assurance of the final produced parts. Initially, the so called “green” parts...... were compared with the sintered parts (final products) calculating the percentage of shrinkage after sintering. Successively, the expanded uncertainty of the measured dimensions were evaluated for each single part as well as for the overall parts. Finally, the estimated uncertainty for the shrinkage...... was evaluated propagating the expanded uncertainty previously stated and considering green and sintered parts correlated. Results showed that the proposed method can be effective instating tolerances if it is assumed that the variability on the dimensions induced by the shrinkage equals the propagated expanded...
Linear Shrinkage Behaviour of Compacted Loam Masonry Blocks
Directory of Open Access Journals (Sweden)
NAWAB ALI LAKHO
2017-04-01
Full Text Available Walls of wet loam, used in earthen houses, generally experience more shrinkage which results in cracks and less compressive strength. This paper presents a technique of producing loam masonry blocks that are compacted in drained state during casting process in order to minimize shrinkage. For this purpose, loam masonry blocks were cast and compacted at a pressure of 6 MPa and then dried in shade by covering them in plastic sheet. The results show that linear shrinkage of 2% occurred which is smaller when compared to un-compacted wet loam walls. This implies that the loam masonry blocks compacted in drained state is expected to perform better than un-compacted wet loam walls.
Shrinkage-stress kinetics of photopolymerised resin-composites
Satterthwaite, Julian D.
The use of directly-placed substances as restorative materials in teeth remains the technique of choice for preserving function and form in teeth that have cavities. The current aesthetic restorative materials of choice are resin-composite materials, although these undergo molecular densification during polymerisation, which has deleterious effects. Although shrinkage-strain is the cause, it is the shrinkage-stress effects that may be seen as being responsible for the problems with adhesive resin-based restorations that are encountered clinically, the bond may fail with separation of the material from the cavity wall, leading to marginal discolouration, pulpal irritation and subsequent necrosis, post operative sensitivity, recurrent caries and eventual failure of restorations. Other outcomes include cohesive fracture of enamel or cusps, cuspal movement (strain) and persistent pain. The aims of this research were to characterise the effects of variations in resin-composite formulation on shrinkage-strain and shrinkage-stress kinetics. In particular, the influence of the size and morphology of the dispersed phase was investigated through the study of experimental formulations. Polymerisation shrinkage-strain kinetics were assessed with the bonded-disk method. It was found that resin-composites with spherical filler particles had significantly lower shrinkage-strain compared to those with irregular filler particles. Additionally, shrinkage-strain was found to be dependent on the size of filler particle, and this trend was related, in part, to differences in the degree of conversion. The data were also used to calculate the activation energy for each material, and a relationship between this and filler particle size for the irregular fillers was demonstrated. A fixed-compliance cantilever beam instrument (Bioman) was used for characterisation of shrinkage-stress kinetics. Significant differences were identified between materials in relation to filler particle size and
Effect of a weightlifting belt on spinal shrinkage.
Bourne, N D; Reilly, T
1991-01-01
Spinal loading during weightlifting results in a loss of stature which has been attributed to a decrease in height of the intervertebral discs--so-called 'spinal shrinkage'. Belts are often used during the lifting of heavy weights, purportedly to support, stabilize and thereby attenuate the load on the spine. The purpose of this study was to examine the effects of a standard weightlifting belt in attenuating spinal shrinkage. Eight male subjects with a mean age of 24.8 years performed two seq...
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
is largely due to the availability of efficient inference algorithms for answering probabilistic queries about the states of the variables in the network. Furthermore, to support the construction of Bayesian network models, learning algorithms are also available. We give an overview of the Bayesian network...
Kleibergen, F.R.; Kleijn, R.; Paap, R.
2000-01-01
We propose a novel Bayesian test under a (noninformative) Jeffreys'priorspecification. We check whether the fixed scalar value of the so-calledBayesian Score Statistic (BSS) under the null hypothesis is aplausiblerealization from its known and standardized distribution under thealternative. Unlike
Yuan, Ying; MacKinnon, David P.
2009-01-01
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…
Directory of Open Access Journals (Sweden)
Nguyen Quangphu
2008-12-01
Full Text Available High-performance concrete (HPC has specific performance advantages over conventional concrete in strength and durability. HPC mixtures are usually produced with water/binder mass ratios (mW/mB in the range of 0.2–0.4, so volume changes of concrete as a result of drying, chemical reactions, and temperature change cannot be avoided. For these reasons, shrinkage and cracking are frequent phenomena. It is necessary to add some types of admixture for reduction of shrinkage and cracking of HPC. This study used
Validity Shrinkage in Ridge Regression: A Simulation Study.
Faden, Vivian; Bobko, Philip
1982-01-01
Ridge regression offers advantages over ordinary least squares estimation when a validity shrinkage criterion is considered. Comparisons of cross-validated multiple correlations indicate that ridge estimation is superior when the predictors are multicollinear, the number of predictors is large relative to sample size, and the population multiple…
Shrinkage of Newly Formed Particles in an Urban Environment
Czech Academy of Sciences Publication Activity Database
Škrabalová, Lenka; Zíková, Naděžda; Ždímal, Vladimír
2015-01-01
Roč. 15, č. 4 (2015), s. 1313-1324 ISSN 1680-8584 R&D Projects: GA ČR GAP209/11/1342 Institutional support: RVO:67985858 Keywords : aerosol dynamics * ultrafine particles * particle shrinkage Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.393, year: 2015
Effect of processing conditions on shrinkage in injection moulding
Jansen, K.M.B.; van Dijk, D.J.; Husselman, M.H.
1998-01-01
A systematic study on the effect of processing conditions on mold shrinkage was undertaken for seven common thermoplastic polymers. It turned out that the holding pressure was always the key parameter. The effect of the melt temperature is slightly less important. Injection velocity and mold
Drying and radial shrinkage characteristics and changes in color ...
African Journals Online (AJOL)
Drying and radial shrinkage characteristics and changes in color and shape of carrots tissues during air drying were studied. Slices dimensions were obtained by computer vision and the color was quantified by chroma, hue, whitening index and total carotenoids contents. The drying time became shorter of 1 h when ...
The Shrinkage Cracking Behavior in Reinforced Reactive Powder Concrete Walls
Directory of Open Access Journals (Sweden)
Samir A. Al-Mashhadi
2017-07-01
Full Text Available In this study, the reduced scale wall models were used (they are believed to resemble as much as possible the field conditions to study the shrinkage behavior of reactive powder concrete (RPC base restrained walls. Six base restrained RPC walls were casted in different length/height ratios of two ratios of steel fiber by volume in Summer. These walls were restrained by reinforced concrete bases to provide the continuous base restraint to the walls. The mechanical properties of reactive powder concrete investigated were; compressive strength between (75.3 – 140.1 MPa, splitting tensile strength between (5.7 – 13.9 MPa, flexural tensile strength (7.7 – 24.5 MPa, and static modulus of elasticity (32.7 – 47.1GPa. Based on the observations of this work, it was found that the cracks did not develop in the reduced scale of the reactive powder concrete (RPC walls restrained from movement at their bases for different L/H ratios (2, 5, and 10 and for two ratio of steel fiber (1% & 2% during 90 days period of drying conditions. Moreover, the shrinkage values increase toward the edges. Based on the results of this work, the increase in the maximum shrinkage values of walls with 1% steel fiber were (29%, 28%, 28% of the maximum shrinkage values of walls with 2% steel fiber of length/height ratios of (2, 5, and 10 respectively. The experimental observation in beam specimens showed that the free shrinkage, tensile strain capacity and elastic tensile strain capacity (at date of cracking of beams with 1% steel fiber were higher than the beams with 2% steel fiber by about (24%, (45% and (42% respectively
Characterisation of tissue shrinkage during microwave thermal ablation.
Farina, Laura; Weiss, Noam; Nissenbaum, Yitzhak; Cavagnaro, Marta; Lopresto, Vanni; Pinto, Rosanna; Tosoratti, Nevio; Amabile, Claudio; Cassarino, Simone; Goldberg, S Nahum
2014-11-01
The aim of this study was to characterise changes in tissue volume during image-guided microwave ablation in order to arrive at a more precise determination of the true ablation zone. The effect of power (20-80 W) and time (1-10 min) on microwave-induced tissue contraction was experimentally evaluated in various-sized cubes of ex vivo liver (10-40 mm ± 2 mm) and muscle (20 and 40 mm ± 2 mm) embedded in agar phantoms (N = 119). Post-ablation linear and volumetric dimensions of the tissue cubes were measured and compared with pre-ablation dimensions. Subsequently, the process of tissue contraction was investigated dynamically during the ablation procedure through real-time X-ray CT scanning. Overall, substantial shrinkage of 52-74% of initial tissue volume was noted. The shrinkage was non-uniform over time and space, with observed asymmetry favouring the radial (23-43 % range) over the longitudinal (21-29%) direction. Algorithmic relationships for the shrinkage as a function of time were demonstrated. Furthermore, the smallest cubes showed more substantial and faster contraction (28-40% after 1 min), with more considerable volumetric shrinkage (>10%) in muscle than in liver tissue. Additionally, CT imaging demonstrated initial expansion of the tissue volume, lasting in some cases up to 3 min during the microwave ablation procedure, prior to the contraction phenomenon. In addition to an asymmetric substantial shrinkage of the ablated tissue volume, an initial expansion phenomenon occurs during MW ablation. Thus, complex modifications of the tissue close to a radiating antenna will likely need to be taken into account for future methods of real-time ablation monitoring.
F.M.V. Bastos Gonçalves (Frederico); H. Baderkhan (H.); H.J.M. Verhagen (Hence); A. Wanhainen (A.); E. Björck (Erik); R.J. Stolker (Robert); S.E. Hoeks (Sanne); A.R. Mani (Ali)
2014-01-01
textabstractBackground Aneurysm shrinkage has been proposed as a marker of successful endovascular aneurysm repair (EVAR). Patients with early postoperative shrinkage may experience fewer subsequent complications, and consequently require less intensive surveillance. Methods Patients undergoing EVAR
ANALYSIS OF CRACKING DUE TO SHRINKAGE RESTRAINT ON THE MECHANICAL BEHAVIOUR OF REINFORCED CONCRETE
Michou , A.; Hilaire , A.; Benboudjema , F.; NAHAS , G; WYNIECKI , P; Berthaud , Y.
2016-01-01
International audience; Shrinkage may lead to tensile stresses and cracking in reinforced concrete structures due to several mechanisms: gradients of drying shrinkage, restraint of autogeneous and drying shrinkage by reinforcement or concrete members of different thickness or ages etc. This contribution focuses on the effect of drying shrinkage on the behavior of concrete tie members, with a focus on the restraint by reinforcement. It is showed that, if it is not taken into account, numerical...
Bayesian data analysis for newcomers.
Kruschke, John K; Liddell, Torrin M
2018-02-01
This article explains the foundational concepts of Bayesian data analysis using virtually no mathematical notation. Bayesian ideas already match your intuitions from everyday reasoning and from traditional data analysis. Simple examples of Bayesian data analysis are presented that illustrate how the information delivered by a Bayesian analysis can be directly interpreted. Bayesian approaches to null-value assessment are discussed. The article clarifies misconceptions about Bayesian methods that newcomers might have acquired elsewhere. We discuss prior distributions and explain how they are not a liability but an important asset. We discuss the relation of Bayesian data analysis to Bayesian models of mind, and we briefly discuss what methodological problems Bayesian data analysis is not meant to solve. After you have read this article, you should have a clear sense of how Bayesian data analysis works and the sort of information it delivers, and why that information is so intuitive and useful for drawing conclusions from data.
Bukovinszky, Katalin; Molnár, Lilla; Bakó, József; Szalóki, Melinda; Hegedus, Csaba
2014-03-01
The polymerization shrinkage and shrinkage stress of dental composites are in the center of the interest of researchers and manufacturers. It is a great challenge to minimize this important property as low as possible. Many factors are related and are in complicated correlation with each other affecting the polymerization shrinkage. Polymerization shrinkage stress degree of conversion and elasticity has high importance from this aspect. Our aim was to study the polymerization shrinkage and related properties (modulus of elasticity, degree of conversion, shrinkage stress) of three flowable composite (Charisma Opal Flow, SDR, Filtek Ultimate) and an unfilled composite resin. Modulus of elasticity was measured using three point flexure tests on universal testing machine. The polymerization shrinkage stress was determined using bonded-disc technique. The degree of conversion measurements were performed by FT-IR spectroscopy. And the volumetric shrinkage was investigated using Archimedes principle and was measured on analytical balance with special additional equipment. The unfilled resin generally showed higher shrinkage (8,26%), shrinkage stress (0,8 MPa) and degree of conversion (38%), and presented the lowest modulus of elasticity (3047,02MPa). Highest values of unfilled resin correspond to the literature. The lack of fillers enlarges the shrinkage, and the shrinkage stress, but gives the higher flexibility and higher degree of conversion. Further investigations needs to be done to understand and reveal the differences between the composites.
Study of ‘real’ shrinkage by ESEM observations and digital image analysis
Jankovic, D.
2007-01-01
Defining the 'real' shrinkage values of concrete is still a subject of much debate. In shrinkage experiments size effects are inherently present. Through an attempt to determine the real shrinkage of cement-based materials, these size effects have to be eliminated or at least reduced as much a
Bayesian methods for data analysis
Carlin, Bradley P.
2009-01-01
Approaches for statistical inference Introduction Motivating Vignettes Defining the Approaches The Bayes-Frequentist Controversy Some Basic Bayesian Models The Bayes approach Introduction Prior Distributions Bayesian Inference Hierarchical Modeling Model Assessment Nonparametric Methods Bayesian computation Introduction Asymptotic Methods Noniterative Monte Carlo Methods Markov Chain Monte Carlo Methods Model criticism and selection Bayesian Modeling Bayesian Robustness Model Assessment Bayes Factors via Marginal Density Estimation Bayes Factors
Statistics: a Bayesian perspective
National Research Council Canada - National Science Library
Berry, Donald A
1996-01-01
...: it is the only introductory textbook based on Bayesian ideas, it combines concepts and methods, it presents statistics as a means of integrating data into the significant process, it develops ideas...
Noncausal Bayesian Vector Autoregression
DEFF Research Database (Denmark)
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...
Granade, Christopher; Combes, Joshua; Cory, D. G.
2016-03-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of-the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we address all three problems. First, we use modern statistical methods, as pioneered by Huszár and Houlsby (2012 Phys. Rev. A 85 052120) and by Ferrie (2014 New J. Phys. 16 093035), to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first priors on quantum states and channels that allow for including useful experimental insight. Finally, we develop a method that allows tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
Bayesian phylogeography finds its roots.
Directory of Open Access Journals (Sweden)
Philippe Lemey
2009-09-01
Full Text Available As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
Variational Bayesian Filtering
Czech Academy of Sciences Publication Activity Database
Šmídl, Václav; Quinn, A.
2008-01-01
Roč. 56, č. 10 (2008), s. 5020-5030 ISSN 1053-587X R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian filtering * particle filtering * Variational Bayes Subject RIV: BC - Control Systems Theory Impact factor: 2.335, year: 2008 http://library.utia.cas.cz/separaty/2008/AS/smidl-variational bayesian filtering.pdf
Bayesian Networks An Introduction
Koski, Timo
2009-01-01
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include:.: An introduction to Dirichlet Distribution, Exponential Families and their applications.; A detailed description of learni
Non-linear Bayesian update of PCE coefficients
Litvinenko, Alexander
2014-01-06
Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(?), a measurement operator Y (u(q), q), where u(q, ?) uncertain solution. Aim: to identify q(?). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(!) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a unctional approximation, e.g. polynomial chaos expansion (PCE). New: We apply Bayesian update to the PCE coefficients of the random coefficient q(?) (not to the probability density function of q).
Polymerisation efficiency and shrinkage effects in resin based dental restoratives
Al-Hindi, Abdusalam M.
The aim of this study was to investigate the polymerisation efficiency and shrinkage effects in resin based dental restorative materials. The study highlights factors affecting the polymerisation efficiency, but the efficiency of the light curing units was first measured. The output light intensity and the temperature rise produced by two units were measured using a radiometer with a flat-response characteristic. The units were the Elipar Highlight (Espe Dental AG) and XL3000 (3M Co). The former unit has a dual-intensity mode of operation: 10 slow plus 30 s high (termed "soft-start") and a Ml-intensity mode: 40 s high. Its "high" intensity was significantly greater than the XL3000 Unit, and produced correspondingly greater temperature rises. One of the hypotheses to be tested was whether any useful network-conversion (polymerisation) was attained by application of the 10 slow-intensity phase of the "soft-start" mode. To address this question, the polymerisation efficiency of three representative resin-based restorative materials was studied by measuring depth-of-cure, exotherm, surface hardness and degree of conversion. The Elipar Unit was used principally m these studies, with four modes of radiation: "full" and "soft- start", as above, and either 10 s or 40 s of low intensity light. Most measurements were performed at 23°C, but some specimen groups were also pre-conditioned at 37°C. Depth-of-cure values obtained by "soft-start" were as great as with "full" radiation. Low- intensity irradiation alone gave significantly reduced, but non-zero cure-depths. The exotherm of the specimens cured by "soft-start" was lower than those cured by "full" light-intensity. This pattern was also apparent when the lower-intensity (XL3000) Unit was deployed. Surface hardness was measured on upper and lower surfaces of specimens radiated by different modes. The hardness was greater at upper, relative to lower surfaces with "full" intensity. The lower-surface hardness with low
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
Analysis of Shrinkage on Thick Plate Part using Genetic Algorithm
Directory of Open Access Journals (Sweden)
Najihah S.N.
2016-01-01
Full Text Available Injection moulding is the most widely used processes in manufacturing plastic products. Since the quality of injection improves plastic parts are mostly influenced by process conditions, the method to determine the optimum process conditions becomes the key to improving the part quality. This paper presents a systematic methodology to analyse the shrinkage of the thick plate part during the injection moulding process. Genetic Algorithm (GA method was proposed to optimise the process parameters that would result in optimal solutions of optimisation goals. Using the GA, the shrinkage of the thick plate part was improved by 39.1% in parallel direction and 17.21% in the normal direction of melt flow.
Cracking in cement paste induced by autogenous shrinkage
DEFF Research Database (Denmark)
Lura, Pietro; Jensen, Ole Mejlhede; Weiss, Jason
2009-01-01
Detection and quantification of microcracks caused by restrained autogenous shrinkage in high-performance concrete is a difficult task. Available techniques either lack the required resolution or may produce additional cracks that are indistinguishable from the original ones. A recently developed...... technique allows identification of microcracks while avoiding artefacts induced by unwanted restraint, drying, or temperature variations during sample preparation. Small cylindrical samples of cement paste are cast with steel rods of different diameters in their centre. The rods restrain the autogenous...... shrinkage of the paste and may cause crack formation. The crack pattern is identified by impregnation with gallium and analyzed by optical and scanning electron microscopy. In this study, a non-linear numerical analysis of the samples was performed. Autogenous strain, elastic modulus, fracture energy...
Modeling Restrained Shrinkage Induced Cracking in Concrete Rings Using the Thick Level Set Approach
Directory of Open Access Journals (Sweden)
Rebecca Nakhoul
2018-03-01
Full Text Available Modeling restrained shrinkage-induced damage and cracking in concrete is addressed herein. The novel Thick Level Set (TLS damage growth and crack propagation model is used and adapted by introducing shrinkage contribution into the formulation. The TLS capacity to predict damage evolution, crack initiation and growth triggered by restrained shrinkage in absence of external loads is evaluated. A study dealing with shrinkage-induced cracking in elliptical concrete rings is presented herein. Key results such as the effect of rings oblateness on stress distribution and critical shrinkage strain needed to initiate damage are highlighted. In addition, crack positions are compared to those observed in experiments and are found satisfactory.
Clay Mineralogy of Brazilian Oxisols with Shrinkage Properties
Directory of Open Access Journals (Sweden)
Samara Alves Testoni
2017-08-01
Full Text Available ABSTRACT Shrinkage capacity (caráter retrátil in Portuguese is a new diagnostic characteristic recently introduced in the Brazilian System of Soil Classification (SiBCS to indicate shrink and swell properties observed in subtropical soils from highland plateaus in southern Brazil, specifically in Oxisols with brown colors. In soils located in road cuts exposed to drying for some weeks, strong shrinkage of soil volume is observed in these soils, resulting in the formation of pronounced vertical cracks and large and very large prismatic structures, which crumble in blocks when handled. We hypothesize that such properties are related to their clay mineralogy, although there are no conclusive studies about this, the motive for the present study. Samples of the A and B horizons from six Oxisols with expansive capacity from the states of Santa Catarina and Rio Grande do Sul were analyzed. One Rhodic Hapludox, from the state of Paraná, without expansive capacity, was used for comparison. All the soils are very clayey, originated from basalt, and have similar iron oxide content. For identification of clay mineralogy, X-ray diffraction techniques were employed, together with the use of NEWMOD® software to investigate and describe the interstratified minerals. The results showed that most expansive soils have a similar mineralogical composition, with kaolinite, interstratified kaolinite-smectite (K-S, and hydroxy-Al interlayered smectites (HIS, unlike the non-expansive Rhodic Hapludox, which exhibited kaolinite with significant amounts of gibbsite and low amount of interstratified K-S. According to the mineralogical assemblage identified in the expansive soils, we can affirm that the mechanism of smectite expansion and contraction is related to the shrinkage capacity of the soil, considering that the level of hydroxy-Al intercalation is low. In addition, these mechanisms also are related to the presence of quasicrystals and domains that control the
The Process of Shrinkage as a Challenge to Urban Governance
Directory of Open Access Journals (Sweden)
Stryjakiewicz Tadeusz
2016-06-01
Full Text Available For many decades most researchers, planners and local authorities have been focusing almost exclusively on urban growth and its socio-economic and spatial consequences. However, in the current debate concerning the future of cities and regions in Europe the process of their shrinkage starts to attract more attention. In the conditions of a declining population, urban governance is an important challenge for local authorities, being usually much more difficult than during the periods of population growth.
Comparative analysis of the shrinkage stress of composite resins
Directory of Open Access Journals (Sweden)
Rosana Aparecida Pereira
2008-02-01
Full Text Available The aim of this study was to compare the shrinkage stress of composite resins by three methods. In the first method, composites were inserted between two stainless steel plates. One of the plates was connected to a 20 kgf load cell of a universal testing machine (EMIC-DL-500. In the second method, disk-shaped cavities were prepared in 2-mm-thick Teflon molds and filled with the different composites. Gaps between the composites and molds formed after polymerization were evaluated microscopically. In the third method, the wall-to-wall shrinkage stress of the resins that were placed in bovine dentin cavities was evaluated. The gaps were measured microscopically. Data were analyzed by one-way ANOVA and Tukey's test (alpha=0.05. The obtained contraction forces were: Grandio = 12.18 ± 0.428N; Filtek Z 250 = 11.80 ± 0.760N; Filtek Supreme = 11.80 ± 0.707 N; and Admira = 11.89 ± 0.647 N. The gaps obtained between composites and Teflon molds were: Filtek Z 250 = 0.51 ± 0.0357%; Filtek Supreme = 0.36 ± 0.0438%; Admira = 0.25 ± 0.0346% and Grandio = 0.16 ± 0.008%. The gaps obtained in wall-to-wall contraction were: Filtek Z 250 = 11.33 ± 2.160 µm; Filtek Supreme = 10.66 ± 1.211µm; Admira = 11.16 ± 2.041 µm and Grandio = 10.50 ± 1.224 µm. There were no significant differences among the composite resins obtained with the first (shrinkage stress generated during polymerization and third method (wall-to-wall shrinkage. The composite resins obtained with the second method (Teflon method differed significantly regarding gap formation.
Comparative analysis of the shrinkage stress of composite resins.
Pereira, Rosana Aparecida; Araujo, Paulo Amarante de; Castañeda-Espinosa, Juan Carlos; Mondelli, Rafael Francisco Lia
2008-01-01
The aim of this study was to compare the shrinkage stress of composite resins by three methods. In the first method, composites were inserted between two stainless steel plates. One of the plates was connected to a 20 kgf load cell of a universal testing machine (EMIC-DL-500). In the second method, disk-shaped cavities were prepared in 2-mm-thick Teflon molds and filled with the different composites. Gaps between the composites and molds formed after polymerization were evaluated microscopically. In the third method, the wall-to-wall shrinkage stress of the resins that were placed in bovine dentin cavities was evaluated. The gaps were measured microscopically. Data were analyzed by one-way ANOVA and Tukey's test (alpha=0.05). The obtained contraction forces were: Grandio = 12.18 +/- 0.428N; Filtek Z 250 = 11.80 +/- 0.760N; Filtek Supreme = 11.80 +/- 0.707 N; and Admira = 11.89 +/- 0.647 N. The gaps obtained between composites and Teflon molds were: Filtek Z 250 = 0.51 +/- 0.0357%; Filtek Supreme = 0.36 +/- 0.0438%; Admira = 0.25 +/- 0.0346% and Grandio = 0.16 +/- 0.008%. The gaps obtained in wall-to-wall contraction were: Filtek Z 250 = 11.33 +/- 2.160 microm; Filtek Supreme = 10.66 +/- 1.211 microm; Admira = 11.16 +/- 2.041 microm and Grandio = 10.50 +/- 1.224 microm. There were no significant differences among the composite resins obtained with the first (shrinkage stress generated during polymerization) and third method (wall-to-wall shrinkage). The composite resins obtained with the second method (Teflon method) differed significantly regarding gap formation.
Super-resolution optical telescopes with local light diffraction shrinkage
Wang, Changtao; Tang, Dongliang; Wang, Yanqin; Zhao, Zeyu; Wang, Jiong; Pu, Mingbo; Zhang, Yudong; Yan, Wei; Gao, Ping; Luo, Xiangang
2015-01-01
Suffering from giant size of objective lenses and infeasible manipulations of distant targets, telescopes could not seek helps from present super-resolution imaging, such as scanning near-field optical microscopy, perfect lens and stimulated emission depletion microscopy. In this paper, local light diffraction shrinkage associated with optical super-oscillatory phenomenon is proposed for real-time and optically restoring super-resolution imaging information in a telescope system. It is found ...
Simulation of shrinkage and warpage of semi-crystalline thermoplastics
Hopmann, Ch.; Borchmann, N.; Spekowius, M.; Weber, M.; Schöngart, M.
2015-05-01
Today, the simulation of the injection molding process is state of the art. Besides the simulation of the manufacturing process, commercial simulation tools allow a prediction of the structural properties of the final part. Especially the complex shrinkage and warpage behavior is of interest as it significantly influences the part quality. Although modern simulation tools provide qualitatively correct results for several materials and processing conditions, significant deviations from the real component's behavior can occur for semi-crystalline thermoplastics. One underlying reason is the description on the macro scale used in these simulation tools. However, in semi-crystalline materials significant effects take place on the micro scale, e.g. crystalline superstructures that cannot be neglected. As part of a research project at IKV, investigations are carried out to improve the simulation accuracy of shrinkage and warpage. To point out differences in the accuracy of commercially available simulation tools, a reference part is computed for the materials polypropylene and polyoxymethylene. The results are validated by injection molding experiments. The shrinkage and warpage behavior is characterized by optical measuring technology. In future, models for the description of the pvT behavior of semi-crystalline thermoplastics will be implemented into the software package SphäroSim which was developed at IKV. With this software, crystallization kinetics for semi-crystalline thermoplastics can be calculated on the micro scale. With the newly implemented pvT models the calculation of shrinkage and warpage for semi-crystalline thermoplastics will be enabled on the micro scale.
Experimental Analysis on Shrinkage and Swelling in Ordinary Concrete
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Barbara Kucharczyková
2017-01-01
Full Text Available The paper deals with the experimental determination of shrinkage development during concrete ageing. Three concrete mixtures were made. They differed in the amount of cement in the fresh mixture, 300, 350, and 400 kg/m3. In order to determine the influence of plasticiser on the progress of volume changes, another three concrete mixtures were prepared with plasticiser in the amount of 0.25% by cement mass. Measurements were performed with the goal of observing the influence of cement and plasticiser content on the overall development of volume changes in the concrete. Changes in length and mass losses of the concrete during ageing were measured simultaneously. The continuous measurement of concrete mass losses caused by drying of the specimen’s surface proved useful during the interpretation of results obtained from the concrete shrinkage measurement. During the first 24 hours of ageing, all the concrete mixtures exhibited swelling. Its magnitude and progress were influenced by cement, water, and plasticiser content. However, a loss of mass caused by water evaporation from the surface of the specimens was also recorded in this stage. The measured progress of shrinkage corresponded well to the progress of mass loss.
PREDIKSI SHRINKAGE UNTUK MENGHINDARI CACAT PRODUK PADA PLASTIC INJECTION
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Agus Dwi Anggono
2015-05-01
Full Text Available Plastic injection merupakan proses manufactur untuk membuat produk dengan bahan dasar plastic atau dalam kesempatan ini polypropylene. Pada proses tersebut seringkali terjadi cacat produk seperti pengerutan, retak, dimensi tidak sesuai dan kerusakan saat produk keluar dari mould, sehingga banyak material yang terbuang percuma. Meskipun cacat produk tersebut dipengaruhi banyak factor, tetapi yang paling utama adalah masalah shrinkage, atau penyusutan material setelah terjadi pendinginan. Sangat penting untuk melakukan prediksi lebih awal terjadinya penyusutan setelah pendinginan untuk menghindari cacat produk. Dalam penelitian ini akan dilakukan prediksi shrinkage yang akan digunakan untuk material polypropylene dengan cara perhitungan standar. Pembuatan modeling dalam bentuk 3D (tiga dimensi injection molding baik cavity maupun corenya dengan menggunakan CATIA, kemudian dilakukan analisis dengan software MoldFlow untuk pembuatan mesh dan memberikan batasan panas pada komponen sehingga dapat diketahui mode penyusutannya. Analisis ini akan memberikan gambaran tentang distribusi panas pada mould dan memberikan tentang gambaran aliran fluida. Pada analisis tersebut dapat dilihat gejala terjadinya cacat produk, jika hal itu terjadi maka perlu dilakukan perubahan shrinkage, sampai diperoleh hasil analisis yang baik.
Controlled Shrinkage of Expanded Glass Particles in Metal Syntactic Foams
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Kadhim Al-Sahlani
2017-09-01
Full Text Available Metal matrix syntactic foams have been fabricated via counter-gravity infiltration of a packed bed of recycled expanded glass particles (EG with A356 aluminum alloy. Particle shrinkage was studied and has been utilized to increase the particles’ strength and tailor the mechanical properties of the expanded glass/metal syntactic foam (EG-MSF. The crushing strength of particles could be doubled by shrinking them for 20 min at 700 °C. Owing to the low density of EG (0.20–0.26 g/cm3, the resulting foam exhibits a low density (1.03–1.19 g/cm3 that increases slightly due to particle shrinkage. Chemical and physical analyses of EG particles and the resulting foams were conducted. Furthermore, metal syntactic foam samples were tested in uni-axial compression tests. The stress-strain curves obtained exhibit three distinct regions: elastic deformation followed by a stress plateau and densification commencing at 70–80% macroscopic strain. Particle shrinkage increased the mechanical strength of the foam samples and their average plateau stress increased from 15.5 MPa to 26.7 MPa.
Evaluation of shrinkage and cracking in concrete of ring test by acoustic emission method
Watanabe, Takeshi; Hashimoto, Chikanori
2015-03-01
Drying shrinkage of concrete is one of the typical problems related to reduce durability and defilation of concrete structures. Lime stone, expansive additive and low-heat Portland cement are used to reduce drying shrinkage in Japan. Drying shrinkage is commonly evaluated by methods of measurement for length change of mortar and concrete. In these methods, there is detected strain due to drying shrinkage of free body, although visible cracking does not occur. In this study, the ring test was employed to detect strain and age cracking of concrete. The acoustic emission (AE) method was adopted to detect micro cracking due to shrinkage. It was recognized that in concrete using lime stone, expansive additive and low-heat Portland cement are effective to decrease drying shrinkage and visible cracking. Micro cracking due to shrinkage of this concrete was detected and evaluated by the AE method.
DEFF Research Database (Denmark)
Snoeck, D.; Jensen, Ole Mejlhede; De Belie, N.
2015-01-01
shrinkage was determined by manual and automated shrinkage measurements. Autogenous shrinkage was reduced in cement pastes with the supplementary cementitious materials versus Portland cement pastes. At later ages, the rate of autogenous shrinkage is higher due to the pozzolanic activity. Internal curing...
Bayesian Exploratory Factor Analysis
DEFF Research Database (Denmark)
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
Berliner, M.
2017-12-01
Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517
Polymerization shrinkage stress of composite resins and resin cements - What do we need to know?
Soares, Carlos José; Faria-E-Silva, André Luis; Rodrigues, Monise de Paula; Vilela, Andomar Bruno Fernandes; Pfeifer, Carmem Silvia; Tantbirojn, Daranee; Versluis, Antheunis
2017-08-28
Polymerization shrinkage stress of resin-based materials have been related to several unwanted clinical consequences, such as enamel crack propagation, cusp deflection, marginal and internal gaps, and decreased bond strength. Despite the absence of strong evidence relating polymerization shrinkage to secondary caries or fracture of posterior teeth, shrinkage stress has been associated with post-operative sensitivity and marginal stain. The latter is often erroneously used as a criterion for replacement of composite restorations. Therefore, an indirect correlation can emerge between shrinkage stress and the longevity of composite restorations or resin-bonded ceramic restorations. The relationship between shrinkage and stress can be best studied in laboratory experiments and a combination of various methodologies. The objective of this review article is to discuss the concept and consequences of polymerization shrinkage and shrinkage stress of composite resins and resin cements. Literature relating to polymerization shrinkage and shrinkage stress generation, research methodologies, and contributing factors are selected and reviewed. Clinical techniques that could reduce shrinkage stress and new developments on low-shrink dental materials are also discussed.
Effect of a weightlifting belt on spinal shrinkage.
Bourne, N D; Reilly, T
1991-01-01
Spinal loading during weightlifting results in a loss of stature which has been attributed to a decrease in height of the intervertebral discs--so-called 'spinal shrinkage'. Belts are often used during the lifting of heavy weights, purportedly to support, stabilize and thereby attenuate the load on the spine. The purpose of this study was to examine the effects of a standard weightlifting belt in attenuating spinal shrinkage. Eight male subjects with a mean age of 24.8 years performed two sequences of circuit weight-training, one without a belt and on a separate occasion with a belt. The circuit training regimen consisted of six common weight-training exercises. These were performed in three sets of ten with a change of exercise after each set of ten repetitions. A stadiometer sensitive to within 0.01 mm was used to record alterations in stature. Measurements of stature were taken before and after completion of the circuit. The absolute visual analogue scale (AVAS) was used to measure the discomfort and pain intensity resulting from each of the two conditions. The circuit weight-training caused stature losses of 3.59mm without the belt and 2.87 mm with the belt (P greater than 0.05). The subjects complained of significantly less discomfort when the belt was worn (P less than 0.05). The degree of shrinkage was significantly correlated (r = 0.752, P less than 0.05) with perceived discomfort but only when the belt was not worn. These results suggest the potential benefits of wearing a weightlifting belt and support the hypothesis that the belt can help in stabilizing the trunk. Images Figure 1 PMID:1810615
Postoperative sensitivity associated with low shrinkage versus conventional composites
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Ivanović Vladimir
2013-01-01
Full Text Available Introduction. Postoperative sensitivity in restorative dentistry can be related to preparation trauma, dentin adhesives’ ability to seal open dentinal tubules, deformation of restorations under occlusal stresses and microleakage. Objective. The study assessed possible reduction in postoperative sensitivity with low shrinkage compared to conventional composites using different bonding agents and the influence of the operator skill on the incidence of postoperative sensitivity. Methods. Nine hundred and sixty permanent premolars and molars with primary carious lesions from patients 21 to 40 years old were used. Cavities 2 to 3 mm deep and with margins in enamel were prepared by four operators. Two operators had five years (A and B and two had over 20 years (C and D of clinical experience. Teeth were divided into eight groups each contained 120 restorations: (1 Els®+James-2 (original formula, (2 Els®+James-2 (new formula, (3 Els®+Excite, (4 InTenSe®+James-2 (original formula, (5 InTenSe®+James-2 (new formula, (6 InTenSe®+Excite, (7 Tetric Ceram®+Excite, and (8 Point 4®+OptiBond Solo Plus. At 14 days postoperatively, two independent operators, who did not take part in the clinical procedure, assessed postoperative teeth sensitivity using special questionnaires. Data were analyzed using non-parametric chi-square, Mann-Whitney and ANOVA tests. Results. Group 8 showed significantly higher score than the other groups. Less postoperative sensitivity was reported with two low-shrinkage composites (groups 2, 3, and 5 but with no significant difference. There was no statistical difference between groups 1, 2, 3, 4, 5, 6 and 7. Operator A had the highest postoperative sensitivity score compared to the other three. Conclusion. Conventional composite material Point 4® with its bonding agent caused significantly more postoperative sensitivity than low shrinkage composites combined with different adhesives. Operator skill influenced the incidence of
Sonar target enhancement by shrinkage of incoherent wavelet coefficients.
Hunter, Alan J; van Vossen, Robbert
2014-01-01
Background reverberation can obscure useful features of the target echo response in broadband low-frequency sonar images, adversely affecting detection and classification performance. This paper describes a resolution and phase-preserving means of separating the target response from the background reverberation noise using a coherence-based wavelet shrinkage method proposed recently for de-noising magnetic resonance images. The algorithm weights the image wavelet coefficients in proportion to their coherence between different looks under the assumption that the target response is more coherent than the background. The algorithm is demonstrated successfully on experimental synthetic aperture sonar data from a broadband low-frequency sonar developed for buried object detection.
Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding
Desmal, Abdulla
2015-04-13
A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.
Bayesian methods for hackers probabilistic programming and Bayesian inference
Davidson-Pilon, Cameron
2016-01-01
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples a...
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Bayesian statistical inference
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Bruno De Finetti
2017-04-01
Full Text Available This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D. Cocchi, Clueb, Bologna, 1993.Bayesian statistical Inference is one of the last fundamental philosophical papers in which we can find the essential De Finetti's approach to the statistical inference.
DEFF Research Database (Denmark)
Snoeck, Didier; Jensen, Ole Mejlhede; De Belie, Nele
2016-01-01
shrinkage in materials blended with fly ash or blast-furnace slag remain scarce, especially after one week of age. This paper focuses on the autogenous shrinkage by performing manual and automated shrinkage measurements up to one month of age. Without superabsorbent polymers, autogenous shrinkage......A promising way to mitigate autogenous shrinkage in cementitious materials with a low water-to-binder ratio is internal curing by the use of superabsorbent polymers. Superabsorbent polymers are able to absorb multiple times their weight in water and can be applied as an internal water reservoir...... was reduced in cement pastes with the supplementary cementitious materials versus Portland cement pastes. At later ages, the rate of autogenous shrinkage is higher due to the pozzolanic activity of the supplementary cementitious materials. Internal curing by means of superabsorbent polymers is successful...
Macropores generated during shrinkage in two paddy soils using X-ray micro-computed tomography
Bottinelli, Nicolas; Zhou, H.; Boivin, P.; Zhang, Z. B.; Jouquet, Pascal; Hartmann, Christian; Peng, X.
2016-01-01
Soil shrinkage curve represents a decrease of total porosity or an increase of bulk density with water loss. However, our knowledge of the dynamics of pores and their geometry during soil shrinkage is scarce, partially due to lack of reliable methods for determining soil pores in relation to change in soil water. This study aimed to investigate the dynamics of macropores (>30 mu m) of paddy soils during shrinkage. Two, paddy soils, which were sampled from one paddy field cultivated for 20 yea...
Meat cooking shrinkage: Measurement of a new meat quality parameter.
Barbera, S; Tassone, S
2006-07-01
A parameter, meat cooking shrinkage (MCS), has been introduced based on investigations carried out on meat shrinkage caused by heat during cooking. MCS is the difference between the raw and cooked areas of the meat sample, expressed as a percentage of the raw area. The method uses a disk of meat (10mm thick and 55mm wide) measured before and after cooking in a hot air oven at 165°C for 10min, the meat having reached an internal temperature of 70°C. Video image analysis was used to measure the meat sample area. The proposed MCS protocol permits us to measure cooking loss and to reduce cost and variability, moreover it could be improved to obtain color and marbling measurements by developing the image analysis software. Analysing two or more parameters on the same sample, the correlations among them should improve analysis efficacy. A detailed description of the measurement protocol of MCS is reported as well as its application to beef and pork.
Investigation of Shrinkage Defect in Castings by Quantitative Ishikawa Diagram
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Chokkalingam B.
2017-03-01
Full Text Available Metal casting process involves processes such as pattern making, moulding and melting etc. Casting defects occur due to combination of various processes even though efforts are taken to control them. The first step in the defect analysis is to identify the major casting defect among the many casting defects. Then the analysis is to be made to find the root cause of the particular defect. Moreover, it is especially difficult to identify the root causes of the defect. Therefore, a systematic method is required to identify the root cause of the defect among possible causes, consequently specific remedial measures have to be implemented to control them. This paper presents a systematic procedure to identify the root cause of shrinkage defect in an automobile body casting (SG 500/7 and control it by the application of Pareto chart and Ishikawa diagram. with quantitative Weightage. It was found that the root causes were larger volume section in the cope, insufficient feeding of riser and insufficient poured metal in the riser. The necessary remedial measures were taken and castings were reproduced. The shrinkage defect in the castings was completely eliminated.
Response Predicting LTCC Firing Shrinkage: A Response Surface Analysis Study
Energy Technology Data Exchange (ETDEWEB)
Girardi, Michael; Barner, Gregg; Lopez, Cristie; Duncan, Brent; Zawicki, Larry
2009-02-25
The Low Temperature Cofired Ceramic (LTCC) technology is used in a variety of applications including military/space electronics, wireless communication, MEMS, medical and automotive electronics. The use of LTCC is growing due to the low cost of investment, short development time, good electrical and mechanical properties, high reliability, and flexibility in design integration (3 dimensional (3D) microstructures with cavities are possible)). The dimensional accuracy of the resulting x/y shrinkage of LTCC substrates is responsible for component assembly problems with the tolerance effect that increases in relation to the substrate size. Response Surface Analysis was used to predict product shrinkage based on specific process inputs (metal loading, layer count, lamination pressure, and tape thickness) with the ultimate goal to optimize manufacturing outputs (NC files, stencils, and screens) in achieving the final product design the first time. Three (3) regression models were developed for the DuPont 951 tape system with DuPont 5734 gold metallization based on green tape thickness.
Bayesian optimization for materials science
Packwood, Daniel
2017-01-01
This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science. Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While re...
Effect of low-shrinkage monomers on the physicochemical properties of experimental composite resin.
He, Jingwei; Garoushi, Sufyan; Vallittu, Pekka K; Lassila, Lippo
2018-01-01
This study was conducted to determine whether novel experimental low-shrinkage dimethacrylate co-monomers could provide low polymerization shrinkage composites without sacrifice to degree of conversion, and mechanical properties of the composites. Experimental composites were prepared by mixing 28.6 wt% of bisphenol-A-glycidyl dimethacrylate based resin matrix ( bis -GMA) with various weight-fractions of co-monomers; tricyclo decanedimethanol dacrylate (SR833s) and isobornyl acrylate (IBOA) to 71.4 wt% of particulate-fillers. A composite based on bis -GMA/TEGDMA (triethylene glycol dimethacrylate) was used as a control. Fracture toughness and flexural strength were determined for each experimental material following international standards. Degree of monomer-conversion (DC%) was determined by FTIR spectrometry. The volumetric shrinkage in percent was calculated as a buoyancy change in distilled water by means of the Archimedes' principle. Polymerization shrinkage-strain and -stress of the specimens were measured using the strain-gage technique and tensilometer, respectively with respect to time. Statistical analysis revealed that control group had the highest double-bond conversion ( p .05). Volumetric shrinkage and shrinkage stress decreased with increasing IBOA concentration. Replacing TEGDMA with SR833s and IBOA can decrease the volumetric shrinkage, shrinkage strain, and shrinkage stress of composite resins without affecting the mechanical properties. However, the degree of conversion was also decreased.
Effect of resin-composite filler particle size and shape on shrinkage-stress.
Satterthwaite, Julian D; Maisuria, Amit; Vogel, Karin; Watts, David C
2012-06-01
The aim of this study was to investigate the effect of variations in filler particle size and shape on the polymerization shrinkage-stress kinetics of resin-composites. A model series of 12 VLC resin-composites were studied. The particulate dispersed phase volume fraction was 56.7%: these filler particles were systematically graded in size, and further were either spherical or irregular. A Bioman instrument (cantilever beam method) was employed to determine the shrinkage-stress kinetics following 40s irradiation (600 mW/cm(2)) at 23°C (n=3). All data were captured for 60 min and the final shrinkage-stress calculated. Shrinkage-stress varied between 3.86 MPa (SD 0.14) for S3 (spherical filler particles of 500 nm) and 8.44 MPa (SD 0.41) for I1 (irregular filler particles of 450 nm). The shrinkage-stress values were generally lower for those composites with spherical filler particles than those with irregular filler particles. The differences in shrinkage-stress with filler particle size and shape were statistically significant (pparticles exhibit lower shrinkage-stress values compared to those with irregular filler particles. Shrinkage-stress and shrinkage-stress rate vary in a complex manner with variations in the size of the dispersed phase particles: a hypothesized explanation for the effect of filler particle size and shape is presented. Copyright © 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
The leaf-area shrinkage effect can bias paleoclimate and ecology research.
Blonder, Benjamin; Buzzard, Vanessa; Simova, Irena; Sloat, Lindsey; Boyle, Brad; Lipson, Rebecca; Aguilar-Beaucage, Brianna; Andrade, Angelina; Barber, Benjamin; Barnes, Chris; Bushey, Dharma; Cartagena, Paulina; Chaney, Max; Contreras, Karina; Cox, Mandarava; Cueto, Maya; Curtis, Cannon; Fisher, Mariah; Furst, Lindsey; Gallegos, Jessica; Hall, Ruby; Hauschild, Amelia; Jerez, Alex; Jones, Nadja; Klucas, Aaron; Kono, Anita; Lamb, Mary; Matthai, Jacob David Ruiz; McIntyre, Colten; McKenna, Joshua; Mosier, Nicholas; Navabi, Maya; Ochoa, Alex; Pace, Liam; Plassmann, Ryland; Richter, Rachel; Russakoff, Ben; Aubyn, Holden St; Stagg, Ryan; Sterner, Marley; Stewart, Emily; Thompson, Ting Ting; Thornton, Jake; Trujillo, Parker J; Volpe, Trevor J; Enquist, Brian J
2012-11-01
Leaf area is a key trait that links plant form, function, and environment. Measures of leaf area can be biased because leaf area is often estimated from dried or fossilized specimens that have shrunk by an unknown amount. We tested the common assumption that this shrinkage is negligible. We measured shrinkage by comparing dry and fresh leaf area in 3401 leaves of 380 temperate and tropical species and used phylogenetic and trait-based approaches to determine predictors of this shrinkage. We also tested the effects of rehydration and simulated fossilization on shrinkage in four species. We found that dried leaves shrink in area by an average of 22% and a maximum of 82%. Shrinkage in dried leaves can be predicted by multiple morphological traits with a standard deviation of 7.8%. We also found that mud burial, a proxy for compression fossilization, caused negligible shrinkage, and that rehydration, a potential treatment of dried herbarium specimens, eliminated shrinkage. Our findings indicate that the amount of shrinkage is driven by variation in leaf area, leaf thickness, evergreenness, and woodiness and can be reversed by rehydration. The amount of shrinkage may also be a useful trait related to ecologically and physiological differences in drought tolerance and plant life history.
[Measurement of casting shrinkage with U-type tungsten die (author's transl)].
Nakai, A; Nakamura, K; Seki, S; Kakuta, K; Kawashima, J
1980-04-01
A simple method was developed for the accurate measurement of casting shrinkage using a U-type tungsten die. A wax pattern was prepared on the die and both were invested together in phosphate bonded investment. Cobalt-chromium alloy, Regalloy shot 2, was cast and its shrinkage was calculated from the distance of the gap created between the die and the cast piece. In order to evaluate the effects of some manipulative variables on the cast shrinkage value of the alloy, mold temperature, kind of liquid for the investment and powder/liquid ratio were varied and shrinkage values were obtained. The results showed that the shrinkage value was not affected by the kind of liquid and the power/liquid ratio, but significantly decreased as the mold temperature raised up to 600 degree C. However, this effect was eliminated by means of substractive correction of the thermal expansion of the tungsten die. Thus, the casting shrinkage of the cobalt-chromium alloy, Regalloy shot 2, was calculated to be 2.08 +/- 0.02%. The casting shrinkage of pure gold was also measured with the same procedure. The casting shrinkage was calculated to be 1.73 +/- 0.04% and highly consistent with the value (1.74%) reported by R. Earnshaw. This suggested that the developed method was sufficiently effective for the accurate measurement of casting shrinkage.
Directory of Open Access Journals (Sweden)
Pang Herbert
2010-10-01
Full Text Available Abstract Breast cancer tumours among African Americans are usually more aggressive than those found in Caucasian populations. African-American patients with breast cancer also have higher mortality rates than Caucasian women. A better understanding of the disease aetiology of these breast cancers can help to improve and develop new methods for cancer prevention, diagnosis and treatment. The main goal of this project was to identify genes that help differentiate between oestrogen receptor-positive and -negative samples among a small group of African-American patients with breast cancer. Breast cancer microarrays from one of the largest genomic consortiums were analysed using 13 African-American and 201 Caucasian samples with oestrogen receptor status. We used a shrinkage-based classification method to identify genes that were informative in discriminating between oestrogen receptor-positive and -negative samples. Subset analysis and permutation were performed to obtain a set of genes unique to the African-American population. We identified a set of 156 probe sets, which gave a misclassification rate of 0.16 in distinguishing between oestrogen receptor-positive and -negative patients. The biological relevance of our findings was explored through literature-mining techniques and pathway mapping. An independent dataset was used to validate our findings and we found that the top ten genes mapped onto this dataset gave a misclassification rate of 0.15. The described method allows us best to utilise the information available from small sample size microarray data in the context of ethnic minorities.
Pang, Herbert; Ebisu, Keita; Watanabe, Emi; Sue, Laura Y; Tong, Tiejun
2010-10-01
Breast cancer tumours among African Americans are usually more aggressive than those found in Caucasian populations. African-American patients with breast cancer also have higher mortality rates than Caucasian women. A better understanding of the disease aetiology of these breast cancers can help to improve and develop new methods for cancer prevention, diagnosis and treatment. The main goal of this project was to identify genes that help differentiate between oestrogen receptor-positive and -negative samples among a small group of African-American patients with breast cancer. Breast cancer microarrays from one of the largest genomic consortiums were analysed using 13 African-American and 201 Caucasian samples with oestrogen receptor status. We used a shrinkage-based classification method to identify genes that were informative in discriminating between oestrogen receptor-positive and -negative samples. Subset analysis and permutation were performed to obtain a set of genes unique to the African-American population. We identified a set of 156 probe sets, which gave a misclassification rate of 0.16 in distinguishing between oestrogen receptor-positive and -negative patients. The biological relevance of our findings was explored through literature-mining techniques and pathway mapping. An independent dataset was used to validate our findings and we found that the top ten genes mapped onto this dataset gave a misclassification rate of 0.15. The described method allows us best to utilise the information available from small sample size microarray data in the context of ethnic minorities.
Bayesian estimation of covariance matrices: Application to market risk management at EDF
International Nuclear Information System (INIS)
Jandrzejewski-Bouriga, M.
2012-01-01
In this thesis, we develop new methods of regularized covariance matrix estimation, under the Bayesian setting. The regularization methodology employed is first related to shrinkage. We investigate a new Bayesian modeling of covariance matrix, based on hierarchical inverse-Wishart distribution, and then derive different estimators under standard loss functions. Comparisons between shrunk and empirical estimators are performed in terms of frequentist performance under different losses. It allows us to highlight the critical importance of the definition of cost function and show the persistent effect of the shrinkage-type prior on inference. In a second time, we consider the problem of covariance matrix estimation in Gaussian graphical models. If the issue is well treated for the decomposable case, it is not the case if you also consider non-decomposable graphs. We then describe a Bayesian and operational methodology to carry out the estimation of covariance matrix of Gaussian graphical models, decomposable or not. This procedure is based on a new and objective method of graphical-model selection, combined with a constrained and regularized estimation of the covariance matrix of the model chosen. The procedures studied effectively manage missing data. These estimation techniques were applied to calculate the covariance matrices involved in the market risk management for portfolios of EDF (Electricity of France), in particular for problems of calculating Value-at-Risk or in Asset Liability Management. (author)
Bayesian Independent Component Analysis
DEFF Research Database (Denmark)
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...... in a Matlab toolbox, is demonstrated for non-negative decompositions and compared with non-negative matrix factorization.......In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...
Arregui, Iñigo
2018-01-01
In contrast to the situation in a laboratory, the study of the solar atmosphere has to be pursued without direct access to the physical conditions of interest. Information is therefore incomplete and uncertain and inference methods need to be employed to diagnose the physical conditions and processes. One of such methods, solar atmospheric seismology, makes use of observed and theoretically predicted properties of waves to infer plasma and magnetic field properties. A recent development in solar atmospheric seismology consists in the use of inversion and model comparison methods based on Bayesian analysis. In this paper, the philosophy and methodology of Bayesian analysis are first explained. Then, we provide an account of what has been achieved so far from the application of these techniques to solar atmospheric seismology and a prospect of possible future extensions.
Mørup, Morten; Schmidt, Mikkel N
2012-09-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled.
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
Energy Technology Data Exchange (ETDEWEB)
Andrews, Stephen A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sigeti, David E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-11-15
These are a set of slides about Bayesian hypothesis testing, where many hypotheses are tested. The conclusions are the following: The value of the Bayes factor obtained when using the median of the posterior marginal is almost the minimum value of the Bayes factor. The value of τ^{2} which minimizes the Bayes factor is a reasonable choice for this parameter. This allows a likelihood ratio to be computed with is the least favorable to H_{0}.
Bayesian networks in reliability
Energy Technology Data Exchange (ETDEWEB)
Langseth, Helge [Department of Mathematical Sciences, Norwegian University of Science and Technology, N-7491 Trondheim (Norway)]. E-mail: helgel@math.ntnu.no; Portinale, Luigi [Department of Computer Science, University of Eastern Piedmont ' Amedeo Avogadro' , 15100 Alessandria (Italy)]. E-mail: portinal@di.unipmn.it
2007-01-15
Over the last decade, Bayesian networks (BNs) have become a popular tool for modelling many kinds of statistical problems. We have also seen a growing interest for using BNs in the reliability analysis community. In this paper we will discuss the properties of the modelling framework that make BNs particularly well suited for reliability applications, and point to ongoing research that is relevant for practitioners in reliability.
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimental...... economics, with careful controls for the confounding effects of risk aversion. Our results show that risk aversion significantly alters inferences on deviations from Bayes’ Rule....
Approximate Bayesian recursive estimation
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav
2014-01-01
Roč. 285, č. 1 (2014), s. 100-111 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
Bayesian depth estimation from monocular natural images.
Su, Che-Chun; Cormack, Lawrence K; Bovik, Alan C
2017-05-01
Estimating an accurate and naturalistic dense depth map from a single monocular photographic image is a difficult problem. Nevertheless, human observers have little difficulty understanding the depth structure implied by photographs. Two-dimensional (2D) images of the real-world environment contain significant statistical information regarding the three-dimensional (3D) structure of the world that the vision system likely exploits to compute perceived depth, monocularly as well as binocularly. Toward understanding how this might be accomplished, we propose a Bayesian model of monocular depth computation that recovers detailed 3D scene structures by extracting reliable, robust, depth-sensitive statistical features from single natural images. These features are derived using well-accepted univariate natural scene statistics (NSS) models and recent bivariate/correlation NSS models that describe the relationships between 2D photographic images and their associated depth maps. This is accomplished by building a dictionary of canonical local depth patterns from which NSS features are extracted as prior information. The dictionary is used to create a multivariate Gaussian mixture (MGM) likelihood model that associates local image features with depth patterns. A simple Bayesian predictor is then used to form spatial depth estimates. The depth results produced by the model, despite its simplicity, correlate well with ground-truth depths measured by a current-generation terrestrial light detection and ranging (LIDAR) scanner. Such a strong form of statistical depth information could be used by the visual system when creating overall estimated depth maps incorporating stereopsis, accommodation, and other conditions. Indeed, even in isolation, the Bayesian predictor delivers depth estimates that are competitive with state-of-the-art "computer vision" methods that utilize highly engineered image features and sophisticated machine learning algorithms.
Analysis of gene set using shrinkage covariance matrix approach
Karjanto, Suryaefiza; Aripin, Rasimah
2013-09-01
Microarray methodology has been exploited for different applications such as gene discovery and disease diagnosis. This technology is also used for quantitative and highly parallel measurements of gene expression. Recently, microarrays have been one of main interests of statisticians because they provide a perfect example of the paradigms of modern statistics. In this study, the alternative approach to estimate the covariance matrix has been proposed to solve the high dimensionality problem in microarrays. The extension of traditional Hotelling's T2 statistic is constructed for determining the significant gene sets across experimental conditions using shrinkage approach. Real data sets were used as illustrations to compare the performance of the proposed methods with other methods. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
Creep and shrinkage effects on integral abutment bridges
Munuswamy, Sivakumar
Integral abutment bridges provide bridge engineers an economical design alternative to traditional bridges with expansion joints owing to the benefits, arising from elimination of expensive joints installation and reduced maintenance cost. The superstructure for integral abutment bridges is cast integrally with abutments. Time-dependent effects of creep, shrinkage of concrete, relaxation of prestressing steel, temperature gradient, restraints provided by abutment foundation and backfill and statical indeterminacy of the structure introduce time-dependent variations in the redundant forces. An analytical model and numerical procedure to predict instantaneous linear behavior and non-linear time dependent long-term behavior of continuous composite superstructure are developed in which the redundant forces in the integral abutment bridges are derived considering the time-dependent effects. The redistributions of moments due to time-dependent effects have been considered in the analysis. The analysis includes nonlinearity due to cracking of the concrete, as well as the time-dependent deformations. American Concrete Institute (ACI) and American Association of State Highway and Transportation Officials (AASHTO) models for creep and shrinkage are considered in modeling the time dependent material behavior. The variations in the material property of the cross-section corresponding to the constituent materials are incorporated and age-adjusted effective modulus method with relaxation procedure is followed to include the creep behavior of concrete. The partial restraint provided by the abutment-pile-soil system is modeled using discrete spring stiffness as translational and rotational degrees of freedom. Numerical simulation of the behavior is carried out on continuous composite integral abutment bridges and the deformations and stresses due to time-dependent effects due to typical sustained loads are computed. The results from the analytical model are compared with the
Shrinkage reduction of dental composites by addition of expandable zirconia filler
DEFF Research Database (Denmark)
Skovgaard, M.; Almdal, Kristoffer; Sørensen, Bent F.
2011-01-01
A problem with dental resin composites is the polymerization shrinkage, which makes the filling loosen from the tooth or induces crack formation. We have developed an expandable metastable tetragonal zirconia filler, which upon reaction with water, is able to counter the polymer shrinkage...
Hardness, density, and shrinkage characteristics of silk-oak from Hawaii
R. L. Youngs
1964-01-01
Shrinkage, specific gravity, and hardness of two shipments of silk-oak (Grevillea robusta) from Hawaii were evaluated to provide basic information pertinent to the use of the wood for cabinet and furniture purposes. The wood resembles Hawaii-grown shamel ash (Fraxinus uhdei ) in the properties evaluated. Shrinkage compares well with that of black cherry, silver maple,...
Van Mier, J.G.M.; Jankovic, D.
2005-01-01
Numerical modeling of moisture flow, drying shrinkage and crack phenomena in cement microstructure, by coupling a Lattice Gas Automaton and a Lattice Fracture Model, highlighted the importance of a shrinkage coefficient (?sh) as the most significant parameter for achieving realistic numerical
Aerosol particle shrinkage event phenomenology in a South European suburban area during 2009-2015
Alonso-Blanco, E.; Gómez-Moreno, F. J.; Núñez, L.; Pujadas, M.; Cusack, M.; Artíñano, B.
2017-07-01
A high number of aerosol particle shrinkage cases (70) have been identified and analyzed from an extensive and representative database of aerosol size distributions obtained between 2009 and 2015 at an urban background site in Madrid (Spain). A descriptive classification based on the process from which the shrinkage began is proposed according which shrinkage events were divided into three groups: (1) NPF + shrinkage (NPF + S) events, (2) aerosol particle growth process + shrinkage (G + S) events, and (3) pure shrinkage (S) events. The largest number of shrinkages corresponded to the S-type followed by NPF + S, while the G + S events were the least frequent group recorded. Duration of shrinkages varied widely from 0.75 to 8.5 h and SR from -1.0 to -11.1 nm h-1. These processes typically occurred in the afternoon, around 18:00 UTC, caused by two situations: i) a wind speed increase usually associated with a change in the wind direction (over 60% of the observations) and ii) the reduction of photochemical activity at the end of the day. All shrinkages were detected during the warm period, mainly between May and August, when local meteorological conditions (high solar irradiance and temperature and low relative humidity), atmospheric processes (high photochemical activity) and availability of aerosol-forming precursors were favorable for their development. As a consequence of these processes, the particles concentration corresponding to the Aitken mode decreased into the nucleation mode. The accumulation mode did not undergo significant changes during these processes. In some cases, a dilution of the particulate content in the ambient air was observed. This work, goes further than others works dealing with aerosol particles shrinkages, as it incorporates as a main novelty a classification methodology for studying these processes. Moreover, compared to other studies, it is supported by a high and representative number of observations. Thus, this study contributes to
Bicalho, Aline Aredes; de Souza, Silas Júnior Boaventura; de Rosatto, Camila Maria Peres; Tantbirojn, Daranee; Versluis, Antheunis; Soares, Carlos José
2015-12-01
Evaluate the effect of environment on post-gel shrinkage (Shr), cuspal strains (CS), microtensile bond strength (μTBS), elastic modulus (E) and shrinkage stress in molars with large class II restorations. Sixty human molars received standardized Class II mesio-oclusal-distal cavity preparations. Restorations were made with two composites (CHA, Charisma Diamond, Heraus Kulzer and IPS Empress Direct, Ivoclar-Vivadent) using three environment conditions (22°C/50% humidity, 37°C/50% humidity and 37°C/90% humidity) simulated in custom developed chamber. Shr was measured using the strain gauge technique (n=10). CS was measured using strain gauges. Half of the teeth (n=5) were used to assess the elastic modulus (E) and Knoop hardness (KHN) at different depths using microhardness indentation. The other half (n=5) was used to measure the μTBS. The composites and environment conditions were simulated in a two-dimensional finite element analysis of a tooth restoration. Polymerization shrinkage was modeled using Shr data. The Shr, CS, μTBS, KHN and E data were statistically analyzed using two-way ANOVA and Tukey test (significance level: 0.05). Both composites had similar Shr, CS, μTBS and shrinkage stress. CHA had higher elastic modulus than IPS. Increasing temperature and humidity significantly increased Shr, CS and shrinkage stress. μTBS were similar for groups with lower humidity, irrespective of temperature, and higher with higher humidity. E and KHN were constant through the depth for CHA. E and KHN values were affected by environment only for IPS, mainly deeper in the cavity. Shrinkage stress at dentin/composite interface had high inverse correlation with μTBS. Shrinkage stress in enamel had high correlation with CS. Increasing temperature and humidity caused higher post-gel shrinkage and cusp deformation with higher shrinkage stresses in the tooth structure and tooth/restoration interface for both composites tested. The chamber developed for simulating the
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Bayesian geostatistics in health cartography: the perspective of malaria.
Patil, Anand P; Gething, Peter W; Piel, Frédéric B; Hay, Simon I
2011-06-01
Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision.
Directory of Open Access Journals (Sweden)
Suresh Mitthra
2017-01-01
Full Text Available Background: Understanding the mechanical properties is important in predicting the clinical behavior of composites. Finite element analysis (FEA evaluates properties of materials replicating clinical scenario. Aim: This study evaluated polymerization shrinkage and stress, wear resistance (WR, and compressive strength (CS of silorane in comparison with two methacrylate resins. Settings and Design: This study design was a numerical study using FEA. Materials and Methods: Three-dimensional (3D models of maxillary premolar with Class I cavities (2 mm depth, 4 mm length, and 2.5 mm width created and restored with silorane, nanohybrid, and microhybrid; Groups I, II, and III, respectively. Loads of 200–600 N were applied. Polymerization shrinkage was first determined by displacement produced in the X, Y, and Z planes. Maximum stress distribution due to shrinkage was calculated using AN SYS software. 3D cube models of composite resins were simulated with varying filler particle size. Similar loads were applied. WR and compressive stress were calculated: K W L/H and load/cross-sectional area, respectively. Statistical analysis done using one-way ANOVA, Kruskal–Wallis, and Tukey's honestly significant difference test (P < 0.05. Results: Polymerization shrinkage (0.99% and shrinkage stress (233.21 Mpa of silorane were less compared to microhybrid (2.14% and 472.43 Mpa and nanohybrid (2.32% and 464.88 Mpa. Silorane (7.92×/1011 μm/mm3 and nanohybrid (7.79×/1011 showed superior WR than microhybrid (1.113×/1017. There was no significant difference in compressive stress among the groups. Conclusion: Silorane exhibited less polymerization shrinkage and shrinkage stress compared to methacrylates. Silorane and nanohybrid showed greater WR compared to microhybrid. CS of all groups was similar.
Classification using Bayesian neural nets
J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)
1995-01-01
textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to
Bayesian Data Analysis (lecture 1)
CERN. Geneva
2018-01-01
framework but we will also go into more detail and discuss for example the role of the prior. The second part of the lecture will cover further examples and applications that heavily rely on the bayesian approach, as well as some computational tools needed to perform a bayesian analysis.
Bayesian Data Analysis (lecture 2)
CERN. Geneva
2018-01-01
framework but we will also go into more detail and discuss for example the role of the prior. The second part of the lecture will cover further examples and applications that heavily rely on the bayesian approach, as well as some computational tools needed to perform a bayesian analysis.
Approximate Bayesian computation.
Directory of Open Access Journals (Sweden)
Mikael Sunnåker
Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.
Bayesian inference with ecological applications
Link, William A
2009-01-01
This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context. The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists. Engagingly written text specifically designed to demystify a complex subject Examples drawn from ecology and wildlife research An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference Companion website with analyt...
Bayesian Inference on Gravitational Waves
Directory of Open Access Journals (Sweden)
Asad Ali
2015-12-01
Full Text Available The Bayesian approach is increasingly becoming popular among the astrophysics data analysis communities. However, the Pakistan statistics communities are unaware of this fertile interaction between the two disciplines. Bayesian methods have been in use to address astronomical problems since the very birth of the Bayes probability in eighteenth century. Today the Bayesian methods for the detection and parameter estimation of gravitational waves have solid theoretical grounds with a strong promise for the realistic applications. This article aims to introduce the Pakistan statistics communities to the applications of Bayesian Monte Carlo methods in the analysis of gravitational wave data with an overview of the Bayesian signal detection and estimation methods and demonstration by a couple of simplified examples.
Compositional Changes for Reduction of Polymerisation-Induced Shrinkage in Holographic Photopolymers
Directory of Open Access Journals (Sweden)
D. Cody
2016-01-01
Full Text Available Polymerisation-induced shrinkage is one of the main reasons why many photopolymer materials are not used for certain applications including holographic optical elements and holographic data storage. Here, two compositional changes for the reduction of shrinkage in an acrylamide-based photopolymer are reported. A holographic interferometric technique was used to study changes in the dynamics of the shrinkage processes occurring in the modified photopolymer during holographic recording in real time. Firstly, the effect of the replacement of the acrylamide monomer in the photopolymer composition with a larger monomer molecule, diacetone acrylamide, on polymerisation-induced shrinkage has been studied. A reduction in relative shrinkage of 10–15% is obtained using this compositional change. The second method tested for shrinkage reduction involved the incorporation of BEA-type zeolite nanoparticles in the acrylamide-based photopolymer. A reduction in relative shrinkage of 13% was observed for acrylamide photopolymer layers doped with 2.5% wt. BEA zeolites in comparison to the undoped photopolymer.
Directory of Open Access Journals (Sweden)
Luana da Silva
Full Text Available ABSTRACT Brown Nitossolos (Nitisols and Latossolos (Ferralsols, according to the Brazilian System of Soil Classification (SiBCS, have a “caráter retrátil” as their distinctive property. Because this is a new topic, it is necessary to propose methods for evaluation. The objectives of this study were to evaluate methodologies for quantifying the shrinkage of soil using the Syringe Method and the Metallic Mercury Method, and to propose a new one, the “Ring with Sand Method”. Soil samples from eight pedons were used, with six Nitossolos and Latossolos with shrinkage, a Latossolo without shrinkage, and a Vertissolo (Vertissol with admittedly high shrinkage and expansion. The methods were effective in identifying the greater degree of shrinkage of the Vertissolo . However, the Ring with Sand Method was the only one to indicate significant differences between the Vertissolo and the Latossolo without shrinkage, and this method differentiated the shrinkable soils as to the intensity of the characteristic. The proposed method was effective and can serve as a standard to quantify shrinkage.
Effect of the Key Mixture Parameters on Shrinkage of Reactive Powder Concrete
Directory of Open Access Journals (Sweden)
Shamsad Ahmad
2014-01-01
Full Text Available Reactive powder concrete (RPC mixtures are reported to have excellent mechanical and durability characteristics. However, such concrete mixtures having high amount of cementitious materials may have high early shrinkage causing cracking of concrete. In the present work, an attempt has been made to study the simultaneous effects of three key mixture parameters on shrinkage of the RPC mixtures. Considering three different levels of the three key mixture factors, a total of 27 mixtures of RPC were prepared according to 33 factorial experiment design. The specimens belonging to all 27 mixtures were monitored for shrinkage at different ages over a total period of 90 days. The test results were plotted to observe the variation of shrinkage with time and to see the effects of the key mixture factors. The experimental data pertaining to 90-day shrinkage were used to conduct analysis of variance to identify significance of each factor and to obtain an empirical equation correlating the shrinkage of RPC with the three key mixture factors. The rate of development of shrinkage at early ages was higher. The water to binder ratio was found to be the most prominent factor followed by cement content with the least effect of silica fume content.
Directory of Open Access Journals (Sweden)
J. Mutwil
2009-07-01
Full Text Available Shrinkage phenomena during solidification and cooling of hypereutectic aluminium-silicon alloys (AlSi18, AlSi21 have been examined. A vertical shrinkage rod casting with circular cross-section (constant or fixed: tapered has been used as a test sample. Two type of experiments have been conducted: 1 on development of the test sample linear dimension changes (linear expansion/contraction, 2 on development of shrinkage stresses in the test sample. By the linear contraction experiments the linear dimension changes of the test sample and the metal test mould as well a temperature in six points of the test sample have been registered. By shrinkage stresses examination a shrinkage tension force and linear dimension changes of the test sample as well a temperature in three points of the test sample have been registered. Registered time dependences of the test bar and the test mould linear dimension changes have shown, that so-called pre-shrinkage extension has been mainly by mould thermal extension caused. The investigation results have shown that both: the linear contraction as well as the shrinkage stresses development are evident dependent on metal temperature in a warmest region the sample (thermal centre.
Influence of fly ash fineness on water requirement and shrinkage of blended cement mortars
Directory of Open Access Journals (Sweden)
Vanissorn Vimonsatit
2015-12-01
Full Text Available In this paper, the influence of fly ash fineness on water requirement and shrinkage of blended cement mortar was studied. The results indicate that the water requirement and shrinkage characteristic of the blended cement mortar are dependent on fly ash fineness and replacement level. The use of coarse fly ash slightly reduces the water requirement but greatly reduced the drying and the autogenous shrinkage of the blended cement mortars and the reduction is more with an increase in the fly ash replacement level. The finer fly ashes further reduce the water requirement, but increase the drying and the autogenous shrinkages as compared with coarser fly ash. The incorporation of superplasticizer drastically reduces the water requirement, but the effect on the drying and autogenous shrinkages of the normal Portland cement mortar is small. However, for the fly ash mortar, the use of superplasticizer results in a decrease in drying shrinkage and in a substantial increase in the autogenous shrinkage particularly for the fine fly ash at a high replacement level.
Polymerisation shrinkage versus layer thickness of a dentine bonding resin: Method development
Directory of Open Access Journals (Sweden)
Jafarzadeh T
2002-07-01
Full Text Available Dentine bonding systems are usually unfilled, and so their shrinkage may be significant. High"nshrinkage may cause internal stress at the interface between resin-composite restoration and the dentine"nsubstrate. Failure of the adhesive interface may be observed due to the interna! stress. The aims of this"nstudy were:"nA To obtain a suitable method for measuring the kinetics of polymerisation shrinkage in unfilled resm at different thicknesses, particularly for thin films."nB Consideraing the effect of thickness on shrinkage."nScotchbond Multipurpose (3M adhesive bond resin was used. To overcome the particular challenges presented by thin films, a filled-ring measurement procedure was used. Also, a non-contact laser analogue displacement sensor system was developed and applied to measure polymerisation shrinkage. Regression analysis was performed on a complete data set. Non-linear regression analysis established a logarithmic relationship between polymerisation shrinkage and layer thickness. The method applied in this study was found to be sensitive and accurate procedure for determining photo-polymerisation shrinkage of thin films. Polymerisation shrinkage increased with logarithmic of the adhesive thickness.
Shrinkage/swelling of compacted clayey loose and dense soils
Nowamooz, Hossein; Masrouri, Farimah
2009-11-01
This Note presents an experimental study performed on expansive compacted loose and dense samples using osmotic oedometers. Several successive wetting and drying cycles were applied in a suction range between 0 and 8 MPa under different values of constant net vertical stress (15, 30, and 60 kPa). During the suction cycles, the dense samples showed cumulative swelling strains, while the loose samples showed volumetric shrinkage accumulation. At the end of the suction cycles, the volumetric strains converged to an equilibrium stage that indicated elastic behavior of the swelling soil for any further hydraulic variations. At this stage, the compression curves for the studied soil at the different imposed suctions (0, 2, and 8 MPa) converged towards the saturated state curve for the high applied vertical stresses. We defined this pressure as the saturation stress(P). The compression curves provided sufficient data to examine the soil mechanical behavior at the equilibrium stage. To cite this article: H. Nowamooz, F. Masrouri, C. R. Mecanique 337 (2009).
Polymerization Shrinkage and Flexural Modulus of Flowable Dental Composites
Directory of Open Access Journals (Sweden)
Janaína Cavalcanti Xavier
2010-09-01
Full Text Available Linear polymerization shrinkage (LPS, flexural strength (FS and modulus of elasticity (ME of low-viscosity resin composites (Admira Flow™, Grandio Flow™/VOCO; Filtek Z350 Flow™/3M ESPE; Tetric Flow™/Ivoclar-Vivadent was evaluated using a well-established conventional micro-hybrid composite as a standard (Filtek Z250™/3M ESPE. For the measurement of LPS, composites were applied to a cylindrical metallic mould and polymerized (n = 8. The gap formed at the resin/mould interface was observed using SEM (1500×. For FS and ME, specimens were prepared according to the ISO 4049 specifications (n = 10. Statistical analysis of the data was performed with one-way ANOVA and the Tukey test. The conventional resin presented significantly lower LPS associated with high FS and ME, but only the ME values of the conventional resin differed significantly from the low-viscosity composites. The relationship between ME and LPS of low-viscosity resin composites when used as restorative material is a critical factor in contraction stress relief and marginal leakage.
Super-resolution optical telescopes with local light diffraction shrinkage
Wang, Changtao; Tang, Dongliang; Wang, Yanqin; Zhao, Zeyu; Wang, Jiong; Pu, Mingbo; Zhang, Yudong; Yan, Wei; Gao, Ping; Luo, Xiangang
2015-01-01
Suffering from giant size of objective lenses and infeasible manipulations of distant targets, telescopes could not seek helps from present super-resolution imaging, such as scanning near-field optical microscopy, perfect lens and stimulated emission depletion microscopy. In this paper, local light diffraction shrinkage associated with optical super-oscillatory phenomenon is proposed for real-time and optically restoring super-resolution imaging information in a telescope system. It is found that fine target features concealed in diffraction-limited optical images of a telescope could be observed in a small local field of view, benefiting from a relayed metasurface-based super-oscillatory imaging optics in which some local Fourier components beyond the cut-off frequency of telescope could be restored. As experimental examples, a minimal resolution to 0.55 of Rayleigh criterion is obtained, and imaging complex targets and large targets by superimposing multiple local fields of views are demonstrated as well. This investigation provides an access for real-time, incoherent and super-resolution telescopes without the manipulation of distant targets. More importantly, it gives counterintuitive evidence to the common knowledge that relayed optics could not deliver more imaging details than objective systems. PMID:26677820
Development of a coal shrinkage-swelling model accounting for water content in the micropores
Energy Technology Data Exchange (ETDEWEB)
Prob Thararoop; Zuleima T. Karpyn; Turgay Ertekin [Pennsylvania State University, University Park, PA (United States). Petroleum and Natural Gas Engineering
2009-07-01
Changes in cleat permeability of coal seams are influenced by internal stress, and release or adsorption of gas in the coal matrix during production/injection processes. Coal shrinkage-swelling models have been proposed to quantify such changes; however none of the existing models incorporates the effect of the presence of water in the micropores on the gas sorption of coalbeds. This paper proposes a model of coal shrinkage and swelling, incorporating the effect of water in the micropores. The proposed model was validated using field permeability data from San Juan basin coalbeds and compared with coal shrinkage and swelling models existing in the literature.
Effects of drying conditions, admixtures and specimen size on shrinkage strains
International Nuclear Information System (INIS)
Al-Saleh, Saleh A.; Al-Zaid, Rajeh Z.
2006-01-01
The paper presents the results of an experimental investigation on the effects of drying conditions, specimen size and presence of plasticizing admixture on the development of shrinkage strains. The measurements are taken in a harsh (50 deg. C and 5% R.H.) and a moderate environment (28 deg. C and 50% R.H.). The results include strain development at various levels of cross sections of concrete prisms. The drying conditions are found to be the dominant parameter affecting the shrinkage strain development particularly in specimens of smaller sizes. The effect of plasticizing admixture on shrinkage strains is negligible
Marginal adaptation of a low-shrinkage silorane-based composite: A SEM-analysis
DEFF Research Database (Denmark)
Schmidt, Malene; Bindslev, Preben Hørsted; Poulsen, Sven
2012-01-01
Introduction. Shrinkage during polymerization of resin-based composite materials may lead to gap formation and hamper the marginal adaptaion of the restorations. To reduce the problem of polymerization shrinkage, a new composite material (Filtek™ Silorane, 3M-ESPE, Germany), with a reduced...... restorations in molars were included in the study. The restorations originated from a randomized clinical trial, conducted in 2007-2009 which compared the clinical performance of a low-shrinkage composite material (Filtek™ Silorane) with that of a methacrylate-based composite material (Ceram•X™mono). Epon...
Bayesian nonparametric hierarchical modeling.
Dunson, David B
2009-04-01
In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...... represents the spatial coordinates of the grid nodes. Knowledge of how grid nodes are depicted in the observed image is described through the observation model. The prior consists of a node prior and an arc (edge) prior, both modeled as Gaussian MRFs. The node prior models variations in the positions of grid...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Bayesian supervised dimensionality reduction.
Gönen, Mehmet
2013-12-01
Dimensionality reduction is commonly used as a preprocessing step before training a supervised learner. However, coupled training of dimensionality reduction and supervised learning steps may improve the prediction performance. In this paper, we introduce a simple and novel Bayesian supervised dimensionality reduction method that combines linear dimensionality reduction and linear supervised learning in a principled way. We present both Gibbs sampling and variational approximation approaches to learn the proposed probabilistic model for multiclass classification. We also extend our formulation toward model selection using automatic relevance determination in order to find the intrinsic dimensionality. Classification experiments on three benchmark data sets show that the new model significantly outperforms seven baseline linear dimensionality reduction algorithms on very low dimensions in terms of generalization performance on test data. The proposed model also obtains the best results on an image recognition task in terms of classification and retrieval performances.
Bayesian Geostatistical Design
DEFF Research Database (Denmark)
Diggle, Peter; Lophaven, Søren Nymand
2006-01-01
This paper describes the use of model-based geostatistics for choosing the set of sampling locations, collectively called the design, to be used in a geostatistical analysis. Two types of design situation are considered. These are retrospective design, which concerns the addition of sampling...... locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model...... parameter values are unknown. The results show that in this situation a wide range of interpoint distances should be included in the design, and the widely used regular design is often not the best choice....
Nitta, Keiko; Nomoto, Rie; Tsubota, Yuji; Tsuchikawa, Masuji; Hayakawa, Tohru
2017-11-29
The purpose of this study was to evaluate polymerization shrinkage and other physical properties of newly-developed cavity base materials for bulk filling technique, with the brand name BULK BASE (BBS). Polymerization shrinkage was measured according to ISO/FDIS 17304. BBS showed the significantly lowest polymerization shrinkage and significantly higher depth of cure than conventional flowable resin composites (p<0.05). The Knoop hardness, flexural strength and elastic modulus of that were significantly lower than conventional flowable resin composites (p<0.05). BBS had the significantly greatest filler content (p<0.05). SEM images of the surface showed failure of fillers. The lowest polymerization shrinkage was due to the incorporation of a new type of low shrinkage monomer, which has urethane moieties. There were no clear correlations between inorganic filler contents and polymerization shrinkage, flexural strength and elastic modulus. In conclusion, the low polymerization shrinkage of BBS will be useful for cavity treatment in dental clinics.
2012-08-01
Concrete specimens were fabricated for shrinkage, creep, and abrasion resistance : testing. Variations of self-consolidating concrete (SCC) and conventional concrete were : all tested. The results were compared to previous similar testing programs an...
Directory of Open Access Journals (Sweden)
Yasushi Mochizuki
2018-03-01
Full Text Available A 60-year-old male displayed sudden shrinkage of a left free rectus abdominis musculocutaneous flap, which had been grafted to his left maxilla 15 years previously. No post-reconstructive irradiation had been performed, and no late occlusion of the vascular anastomosis, local infection, recurrence of the maxillary cancer, or body weight loss was observed. However, the shrinkage amounted to approximately 50%. This is considerably more than previously reported cases of shrinkage of various free flaps, which ranged between 10% and 25%. The resultant depression was successfully augmented with a right free deep inferior epigastric artery perforator flap. The residual fat volume of the previously grafted shrunken flap was revealed to be compatible with that of the newly harvested contralateral perforator flap. Thus, the volume of the previously grafted flap may reflect the status of the intact contralateral donor site, although the mechanism of sudden flap shrinkage is unclear.
Influence of fly ash, slag cement and specimen curing on shrinkage of bridge deck concrete.
2014-12-01
Cracks occur in bridge decks due to restrained shrinkage of concrete materials. Concrete materials shrink as : cementitious materials hydrate and as water that is not chemically bonded to cementitious materials : migrates from the high humid environm...
Drying shrinkage problems in high-plastic clay soils in Oklahoma.
2013-08-01
Longitudinal cracking in pavements due to drying shrinkage of high-plastic subgrade soils has been a major : problem in Oklahoma. Annual maintenance to seal and repair these distress problems costs significant amount of : money to the state. The long...
DEFF Research Database (Denmark)
Stang, Henrik
1996-01-01
used in high performance cementitious composite materials.Assuming a Coulomb type of friction on the fiber/matrix interface andusing typical values for the frictional coefficient it is shownthat the shrinkage induced clamping pressure could be one of the mostimportant factors determining the frictional......The present paper accesses the significance of shrinkage inducedclamping pressure in fiber/matrix bonding mechanisms incementitious composite materials. The paper contains a description of an experimental setup whichallows mbox{measurement} of the clamping pressure which develops on anelastic...... inhomogeneity embedded in a matrix consisting of acementitious material undergoing shrinkage during hydration(autogenous shrinkage). Furthermore, the paperpresents the analysis necessary to perform an interpretation of the experimental results and which allows for thedetermination of the clamping pressure...
Strength and Drying Shrinkage of Alkali-Activated Slag Paste and Mortar
Directory of Open Access Journals (Sweden)
Mao-chieh Chi
2012-01-01
Full Text Available The aim of this study is to investigate the strengths and drying shrinkage of alkali-activated slag paste and mortar. Compressive strength, tensile strength, and drying shrinkage of alkali-activated slag paste and mortar were measured with various liquid/slag ratios, sand/slag ratios, curing ages, and curing temperatures. Experimental results show that the higher compressive strength and tensile strength have been observed in the higher curing temperature. At the age of 56 days, AAS mortars show higher compressive strength than Portland cement mortars and AAS mortars with liquid/slag ratio of 0.54 have the highest tensile strength in all AAS mortars. In addition, AAS pastes of the drying shrinkage are higher than AAS mortars. Meanwhile, higher drying shrinkage was observed in AAS mortars than that observed comparable Portland cement mortars.
Bayesian adaptive methods for clinical trials
Berry, Scott M; Muller, Peter
2010-01-01
Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer's disease and multiple sclerosis to obesity, diabetes, hepatitis C, and HIV. Written by leading pioneers of Bayesian clinical trial designs, Bayesian Adaptive Methods for Clinical Trials explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis. The book first summarizes the current state of clinical trial design and analysis and introduces the main ideas and potential benefits of a Bayesian alternative. It then gives an overview of basic Bayesian methodological and computational tools needed for Bayesian clinical trials. With a focus on Bayesian designs that achieve good power and Type I error, the next chapters present Bayesian tools useful in early (Phase I) and middle (Phase II) clinical trials as well as two recent Bayesian adaptive Phase II studies: the BATTLE and ISP...
The use of a dual gamma scanner to observe the shrinkage of clay
International Nuclear Information System (INIS)
Groenevelt, P.H.
1974-01-01
Using two gamma beams of different energy, bulk densities of water and clay in a clay-water-air mixture were measured simultaneously. From these data the void ratio and the moisture ratio were obtained by calculation. The graph of the void ratio vs the moisture ratio characterizes the shrinkage of the mixture. This shrinkage curve was measured for a bentonite-water-air mixture. Questions concerning the geometry of the sample are discussed
Experimental drying shrinkage of hardened cement pastes as a function of relative humidity
DEFF Research Database (Denmark)
Hansen, Kurt Kielsgaard; Baroghel, V.B.
1996-01-01
The results of an experimental study concerning drying shrinkage measured as a function of relative humidity on thin specimens of mature hardened cement pastes are presented. The results obtained at two laboratories are compared.......The results of an experimental study concerning drying shrinkage measured as a function of relative humidity on thin specimens of mature hardened cement pastes are presented. The results obtained at two laboratories are compared....
Cohen, L. M.
1984-01-01
A method is shown analytically which reduces the effects of epoxy shrinkage for an ultra-high precision X-ray telescope to within the system error budget. The three-dimensional shrinkage effects are discussed with reference to this telescope. The results of the analysis point to the use of an interrupted rather than continuous bond line as the best solution. Discussion of the finite element modelling techniques is included.
Directory of Open Access Journals (Sweden)
Wei Liu
2017-03-01
Full Text Available Shrinkage porosity is a type of random distribution defects and exists in most large castings. Different from the periodic symmetry defects or certain distribution defects, shrinkage porosity presents a random “cloud-like” configuration, which brings difficulties in quantifying the effective performance of defected casting. In this paper, the influences of random shrinkage porosity on the equivalent elastic modulus of QT400-18 casting were studied by a numerical statistics approach. An improved random algorithm was applied into the lattice model to simulate the “cloud-like” morphology of shrinkage porosity. Then, a large number of numerical samples containing random levels of shrinkage were generated by the proposed algorithm. The stress concentration factor and equivalent elastic modulus of these numerical samples were calculated. Based on a statistical approach, the effects of shrinkage porosity’s distribution characteristics, such as area fraction, shape, and relative location on the casting’s equivalent mechanical properties were discussed respectively. It is shown that the approach with randomly distributed defects has better predictive capabilities than traditional methods. The following conclusions can be drawn from the statistical simulations: (1 the effective modulus decreases remarkably if the shrinkage porosity percent is greater than 1.5%; (2 the average Stress Concentration Factor (SCF produced by shrinkage porosity is about 2.0; (3 the defect’s length across the loading direction plays a more important role in the effective modulus than the length along the loading direction; (4 the surface defect perpendicular to loading direction reduces the mean modulus about 1.5% more than a defect of other position.
Shrinkage Behaviour of Fibre Reinforced Concrete with Recycled Tyre Polymer Fibres
Marijana Serdar; Ana Baričević; Marija Jelčić Rukavina; Martina Pezer; Dubravka Bjegović; Nina Štirmer
2015-01-01
Different types of fibres are often used in concrete to prevent microcracking due to shrinkage, and polypropylene fibres are among the most often used ones. If not prevented, microcracks can lead to the development of larger cracks as drying shrinkage occurs, enabling penetration of aggressive substances from the environment and reducing durability of concrete structures. The hypothesis of the present research is that polypropylene fibres, used in concrete for controlling formation of microcr...
The effect of mucosal cuff shrinkage around dental implants during healing abutment replacement.
Nissan, J; Zenziper, E; Rosner, O; Kolerman, R; Chaushu, L; Chaushu, G
2015-10-01
Soft tissue shrinkage during the course of restoring dental implants may result in biological and prosthodontic difficulties. This study was conducted to measure the continuous shrinkage of the mucosal cuff around dental implants following the removal of the healing abutment up to 60 s. Individuals treated with implant-supported fixed partial dentures were included. Implant data--location, type, length, diameter and healing abutments' dimensions--were recorded. Mucosal cuff shrinkage, following removal of the healing abutments, was measured in bucco-lingual direction at four time points--immediately after 20, 40 and 60 s. anova was used to for statistical analysis. Eighty-seven patients (49 women and 38 men) with a total of 311 implants were evaluated (120 maxilla; 191 mandible; 291 posterior segments; 20 anterior segments). Two-hundred and five (66%) implants displayed thick and 106 (34%) thin gingival biotype. Time was the sole statistically significant parameter affecting mucosal cuff shrinkage around dental implants (P < 0.001). From time 0 to 20, 40 and 60 s, the mean diameter changed from 4.1 to 4.07, 3.4 and 2.81 mm, respectively. The shrinkage was 1%, 17% and 31%, respectively. The gingival biotype had no statistically significant influence on mucosal cuff shrinkage (P = 0.672). Time required replacing a healing abutment with a prosthetic element should be minimised (up to 20/40 s), to avoid pain, discomfort and misfit. © 2015 John Wiley & Sons Ltd.
Digital image analysis of radial shrinkage of fresh spruce (Picea abies L.) wood.
Hansmann, Christian; Konnerth, Johannes; Rosner, Sabine
2011-03-21
Contact-free digital image analysis was performed of the radial shrinkage of fresh, fully saturated small spruce wood beams. An experimental test set-up was developed to ensure constant distance from the charge-coupled device camera to the sample surface as well as constant climate and light conditions during the whole experiment. Dimensional changes were observed immediately after the drying process began. An unexpected distinct effect could be observed which could not be explained by drying surface layers only. After a fast initial radial shrinkage a slowing down of the dimensional changes occurred at high mean moisture contents. A complete interruption of any dimensional changes followed. Finally, a recovery from shrinkage was even observed. It is assumed that strong negative pressure occurred in the fully saturated capillaries owing to dehydration which led to additional dimensional changes. As a consequence, the break of the water column and aeration in these capillaries finally resulted in a recovery period in the shrinkage rate due to the pressure release. After this effect, the dehydration was characterized by a phase of fast and almost linear shrinkage due to drying surface layers. Finally, the shrinkage slowed down to zero when reaching equilibrium moisture content.
Wang, Jing; Ye, Xiao-Fei; Guo, Xiao-Jing; Zhu, Tian-Tian; Qi, Na; Hou, Yong-Fang; Zhang, Tian-Yi; Shi, Wen-Tao; Wei, Xin; Liu, Yu-Zhou; Wu, Gui-Zhi; He, Jia
2015-09-01
Statistical shrinkage is a potential statistical method to improve the accuracy of signal detection results and avoid spurious associations detected by disproportionality analyses. In this study, we introduced statistical shrinkage influence on disproportionality methods in spontaneous reporting system in China. We added the shrinkage parameters in the numerator and denominator, denoted as in the formula of disproportionality analysis. The shrinkage parameters were subjectively set to between 0 and 5, with an interval of 0.1. Adverse drug reaction product label database was deemed as a proxy of golden standard to evaluate the effect of statistical shrinkage. Reports in the years of 2010-2011 were extracted from the national spontaneous reporting system database as the data source for analysis in this study. When α was around 0.5, the Youden index reached the maximum for each disproportionality methods in this study. The value of 0.6 was suggested as the most appropriate statistical shrinkage parameter for reporting odds ratio and proportional reporting ratio and 0.2 for information component based on the spontaneous reporting system of China. Copyright © 2015 John Wiley & Sons, Ltd.
High temperature grain shrinkage under different pre-strains: a phase-field-crystal study
Hu, Shi; Wang, Song; Chen, Zheng; Xi, Wen; Zhang, Ting-Hui
2018-01-01
In this work, we use the phase-field-crystal method to study high temperature grain shrinkage. A circular grain embedded in a symmetric tilt planar grain boundary (GB) is constructed as the simulation system. Misorientation angle of the circular GB has influence on the specific evolution process. Difference between low and high misorientation angle systems is explored. In low misorientation angle system, grain shrinkage is first enabled by dislocation migration. Then dislocation rearrangement process in trijunction areas triggers the further shrinkage of inner grain. The free energy density (FED) curve has a rising stage during the overall decline process. For high misorientation angle system, dissociation and recombination reaction of dislocations is the primary way to shrink inner grain. The FED curve monotonically declines. Additionally, we apply pre-strain to simulation system. The influence of pre-strain on grain shrinkage in low and high misorientation angle systems is also investigated. When pre-strain is relatively small, the evolution process has no difference with unstrained situation, but grain shrinkage is impeded. Further increasing pre-strain, dislocations are emitted from circular GB. Grain shrinkage is accelerated and the inner grain eventually disappears prior to the grain disappearance in unstrained system. There exists a critical pre-strain to control the emission of dislocations.
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
Bayesian Inference: with ecological applications
Link, William A.; Barker, Richard J.
2010-01-01
This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.
Bayesian image restoration, using configurations
Thorarinsdottir, Thordis
2006-01-01
In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the re...
Minimum mean square error estimation and approximation of the Bayesian update
Litvinenko, Alexander
2015-01-07
Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(w), a measurement operator Y (u(q); q), where u(q; w) uncertain solution. Aim: to identify q(w). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(w) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a functional approximation, e.g. polynomial chaos expansion (PCE). New: We derive linear, quadratic etc approximation of full Bayesian update.
Inamdar, Amir; Merlo-Pich, Emilio; Gee, Michelle; Makumi, Clare; Mistry, Prafull; Robertson, Jon; Steinberg, Erik; Zamuner, Stefano; Learned, Susan; Alexander, Robert; Ratti, Emiliangelo
2014-06-01
Pro-inflammatory cytokines (PICs) may play important pathophysiological roles in some forms of Major Depressive Disorder (MDD). The p38 MAPK inhibitor losmapimod (GW856553) attenuates the pro-inflammatory response in humans by reducing PIC production. Losmapimod (7.5 mg BD) was administered for 6 weeks in two randomised, placebo-controlled trials in subjects with MDD enriched with symptoms of loss of energy/interest and psychomotor retardation (Studies 574 and 009). Primary efficacy endpoints were the Bech 6-item depression subscale of the HAMD-17 (the 'Bech,') for Study 009; and the Bech, Inventory of Depressive Symptomatology-Clinician Rated (IDS-C), HAMD-17, and Quick Inventory of Depressive Symptomatology (self-rated) (QIDS-SR) for Study 574. Key cytokine biomarker levels were also measured. Study 574 (n=24) was terminated prematurely in light of emerging data from an internal study in rheumatoid arthritis. Efficacy results available at termination favoured losmapimod (Bech, 6 weeks: endpoint drug vs. placebo difference = -4.10; 95% CI, -7.36, -0.83; p=0.017). A subsequent study, Study 009 (n=128), designed using a Bayesian approach based on a prior derived from Study 574, showed no advantage for losmapimod (Bech, 6 weeks: endpoint drug vs. placebo difference = 1.11; 95% credible interval, -0.22, 2.50). Biomarker data showed no significant changes. In conclusion 7.5 mg BID losmapimod was not effective in MDD. © The Author(s) 2014.
Attention as a Bayesian inference process
Chikkerur, Sharat; Serre, Thomas; Tan, Cheston; Poggio, Tomaso
2011-03-01
David Marr famously defined vision as "knowing what is where by seeing". In the framework described here, attention is the inference process that solves the visual recognition problem of what is where. The theory proposes a computational role for attention and leads to a model that performs well in recognition tasks and that predicts some of the main properties of attention at the level of psychophysics and physiology. We propose an algorithmic implementation a Bayesian network that can be mapped into the basic functional anatomy of attention involving the ventral stream and the dorsal stream. This description integrates bottom-up, feature-based as well as spatial (context based) attentional mechanisms. We show that the Bayesian model predicts well human eye fixations (considered as a proxy for shifts of attention) in natural scenes, and can improve accuracy in object recognition tasks involving cluttered real world images. In both cases, we found that the proposed model can predict human performance better than existing bottom-up and top-down computational models.
Image-based modeling of tumor shrinkage in head and neck radiation therapy
International Nuclear Information System (INIS)
Chao Ming; Xie Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing Lei
2010-01-01
Purpose: Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the ''ground truth'' with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.
Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data.
Jun, Sung C; George, John S; Paré-Blagoev, Juliana; Plis, Sergey M; Ranken, Doug M; Schmidt, David M; Wood, C C
2005-10-15
Recently, we described a Bayesian inference approach to the MEG/EEG inverse problem that used numerical techniques to estimate the full posterior probability distributions of likely solutions upon which all inferences were based [Schmidt, D.M., George, J.S., Wood, C.C., 1999. Bayesian inference applied to the electromagnetic inverse problem. Human Brain Mapping 7, 195; Schmidt, D.M., George, J.S., Ranken, D.M., Wood, C.C., 2001. Spatial-temporal bayesian inference for MEG/EEG. In: Nenonen, J., Ilmoniemi, R. J., Katila, T. (Eds.), Biomag 2000: 12th International Conference on Biomagnetism. Espoo, Norway, p. 671]. Schmidt et al. (1999) focused on the analysis of data at a single point in time employing an extended region source model. They subsequently extended their work to a spatiotemporal Bayesian inference analysis of the full spatiotemporal MEG/EEG data set. Here, we formulate spatiotemporal Bayesian inference analysis using a multi-dipole model of neural activity. This approach is faster than the extended region model, does not require use of the subject's anatomical information, does not require prior determination of the number of dipoles, and yields quantitative probabilistic inferences. In addition, we have incorporated the ability to handle much more complex and realistic estimates of the background noise, which may be represented as a sum of Kronecker products of temporal and spatial noise covariance components. This reduces the effects of undermodeling noise. In order to reduce the rigidity of the multi-dipole formulation which commonly causes problems due to multiple local minima, we treat the given covariance of the background as uncertain and marginalize over it in the analysis. Markov Chain Monte Carlo (MCMC) was used to sample the many possible likely solutions. The spatiotemporal Bayesian dipole analysis is demonstrated using simulated and empirical whole-head MEG data.
Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations
International Nuclear Information System (INIS)
Chen, Peng; Schwab, Christoph
2016-01-01
We extend the reduced basis (RB) accelerated Bayesian inversion methods for affine-parametric, linear operator equations which are considered in [16,17] to non-affine, nonlinear parametric operator equations. We generalize the analysis of sparsity of parametric forward solution maps in [20] and of Bayesian inversion in [48,49] to the fully discrete setting, including Petrov–Galerkin high-fidelity (“HiFi”) discretization of the forward maps. We develop adaptive, stochastic collocation based reduction methods for the efficient computation of reduced bases on the parametric solution manifold. The nonaffinity and nonlinearity with respect to (w.r.t.) the distributed, uncertain parameters and the unknown solution is collocated; specifically, by the so-called Empirical Interpolation Method (EIM). For the corresponding Bayesian inversion problems, computational efficiency is enhanced in two ways: first, expectations w.r.t. the posterior are computed by adaptive quadratures with dimension-independent convergence rates proposed in [49]; the present work generalizes [49] to account for the impact of the PG discretization in the forward maps on the convergence rates of the Quantities of Interest (QoI for short). Second, we propose to perform the Bayesian estimation only w.r.t. a parsimonious, RB approximation of the posterior density. Based on the approximation results in [49], the infinite-dimensional parametric, deterministic forward map and operator admit N-term RB and EIM approximations which converge at rates which depend only on the sparsity of the parametric forward map. In several numerical experiments, the proposed algorithms exhibit dimension-independent convergence rates which equal, at least, the currently known rate estimates for N-term approximation. We propose to accelerate Bayesian estimation by first offline construction of reduced basis surrogates of the Bayesian posterior density. The parsimonious surrogates can then be employed for online data
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Bayesian microsaccade detection
Mihali, Andra; van Opheusden, Bas; Ma, Wei Ji
2017-01-01
Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package. PMID:28114483
Kernel Bayesian ART and ARTMAP.
Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan
2018-02-01
Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
Drying Shrinkage of Mortar Incorporating High Volume Oil Palm Biomass Waste
Shukor Lim, Nor Hasanah Abdul; Samadi, Mostafa; Rahman Mohd. Sam, Abdul; Khalid, Nur Hafizah Abd; Nabilah Sarbini, Noor; Farhayu Ariffin, Nur; Warid Hussin, Mohd; Ismail, Mohammed A.
2018-03-01
This paper studies the drying shrinkage of mortar incorporating oil palm biomass waste including Palm Oil Fuel Ash, Oil Palm Kernel Shell and Oil Palm Fibre. Nano size of palm oil fuel ash was used up to 80 % as cement replacement by weight. The ash has been treated to improve the physical and chemical properties of mortar. The mass ratio of sand to blended ashes was 3:1. The test was carried out using 25 × 25 × 160 mm prism for drying shrinkage tests and 70 × 70 ×70 mm for compressive strength test. The results show that the shrinkage value of biomass mortar is reduced by 31% compared with OPC mortar thus, showing better performance in restraining deformation of the mortar while the compressive strength increased by 24% compared with OPC mortar at later age. The study gives a better understanding of how the biomass waste affect on mortar compressive strength and drying shrinkage behaviour. Overall, the oil palm biomass waste can be used to produce a better performance mortar at later age in terms of compressive strength and drying shrinkage.
Shrinkage Behaviour of Fibre Reinforced Concrete with Recycled Tyre Polymer Fibres
Directory of Open Access Journals (Sweden)
Marijana Serdar
2015-01-01
Full Text Available Different types of fibres are often used in concrete to prevent microcracking due to shrinkage, and polypropylene fibres are among the most often used ones. If not prevented, microcracks can lead to the development of larger cracks as drying shrinkage occurs, enabling penetration of aggressive substances from the environment and reducing durability of concrete structures. The hypothesis of the present research is that polypropylene fibres, used in concrete for controlling formation of microcracks due to shrinkage, can be replaced with recycled polymer fibres obtained from end-of-life tyres. To test the hypothesis, concrete mixtures containing polypropylene fibres and recycled tyre polymer fibres were prepared and tested. Experimental programme focused on autogenous, free, and restrained shrinkage. It was shown that PP fibres can be substituted with higher amount of recycled tyre polymer fibres obtaining concrete with similar shrinkage behaviour. The results indicate promising possibilities of using recycled tyre polymer fibres in concrete products. At the same time, such applications would contribute to solving the problem of waste tyre disposal.
Gholamhoseini, Alireza
2016-03-01
Relatively little research has been reported on the time-dependent in-service behavior of composite concrete slabs with profiled steel decking as permanent formwork and little guidance is available for calculating long-term deflections. The drying shrinkage profile through the thickness of a composite slab is greatly affected by the impermeable steel deck at the slab soffit, and this has only recently been quantified. This paper presents the results of long-term laboratory tests on composite slabs subjected to both drying shrinkage and sustained loads. Based on laboratory measurements, a design model for the shrinkage strain profile through the thickness of a slab is proposed. The design model is based on some modifications to an existing creep and shrinkage prediction model B3. In addition, an analytical model is developed to calculate the time-dependent deflection of composite slabs taking into account the time-dependent effects of creep and shrinkage. The calculated deflections are shown to be in good agreement with the experimental measurements.
A generalized DEMATEL theory with a shrinkage coefficient for an indirect relation matrix
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Liu Hsiang-Chuan
2017-01-01
Full Text Available In this paper, a novel decision-making trial and evaluation laboratory (DEMATEL theory with a shrinkage coefficient of indirect relation matrix is proposed, and a useful validity index, called Liu’s validity index, is also proposed for evaluating the performance of any DEMATEL model. If the shrinkage coefficient of an indirect relation matrix is equal to 1, then this new theory is identical to the traditional theory; in other words, it is a generalization of the traditional theory. Furthermore, the indirect relation is always considerably greater than the direct one in traditional DEMATEL theory, which is unreasonable and unfair because it overemphasizes the influence of the indirect relation. We prove in this paper that if the shrinkage coefficient is equal to 0.5, then the indirect relation is less than its direct relation. Because the shrinkage coefficient belongs to [0.5, 1], according to Liu’s validity index, we can find a more appropriate shrinkage coefficient to obtain a more efficient DEMATEL method. Some crucial properties of this new theory are discussed, and a simple example is provided to illustrate the advantages of the proposed theory.
Analytical Understanding of the Materials Design with Well-Described Shrinkages on Multiscale.
Ma, Qiang; Dutta, Saikat; Wu, Kevin C-W; Kimura, Tatsuo
2017-12-05
Shrinkages derived from condensation of frameworks are one of the significant steps for fabricating demanded materials having unique morphologies and properties. Enormous efforts have been dedicated to understanding their mechanisms that are quite useful for the materials design. In this context, diversified measuring and observing tools have been facilitated to evaluate structural contractions and corresponding driving forces. All of the investigations are crucial to encourage the utilization of such shrinkages for the precise design of nanomaterials. In this review, we summarize significant works how to analyze shrinkages in multiscale during the synthesis of materials, which will be useful as a follow-up review to our latest contribution. Well-defined porous materials are also selected as a good candidate for understanding well-described shrinkages. This review aims to provide a detailed glimpse of the development of analyses on shrinking behaviors in multiscale for the materials design. Shrinking degree and direction in multiscale, which are driven by condensation of frameworks, are predominant for understanding and/or predicting final nanostructures of materials after shrinkages. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Directory of Open Access Journals (Sweden)
Amin Noushini
2014-01-01
Full Text Available The current study assesses the drying shrinkage behaviour of polyvinyl alcohol fibre reinforced concrete (PVA-FRC containing short-length (6 mm and long-length (12 mm uncoated monofilament PVA fibres at 0.125%, 0.25%, 0.375%, and 0.5% volumetric fractions. Fly ash is also used as a partial replacement of Portland cement in all mixes. PVA-FRC mixes have been compared to length change of control concrete (devoid of fibres at 3 storage intervals: early-age (0–7 days, short-term (0–28 days, and long-term (28–112 days intervals. The shrinkage results of FRC and control concrete up to 112 days indicated that all PVA-FRC mixes exhibited higher drying shrinkage than control. The shrinkage exhibited by PVA-FRC mixes ranged from 449 to 480 microstrain, where this value was only 427 microstrain in the case of control. In addition, the longer fibres exhibited higher mass loss, thus potentially contributing to higher shrinkage.
Measurement of linear polymerization shrinkage in light cure Ideal Makoo composite resin
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Ghavam M.
2001-09-01
Full Text Available "nAbstract: Polymerization shrinkage of light cure composite resins causes many complications in conservative and esthetic restorations. The objective of this in-vitro study was to evaluate the polymerization shrinkage, degree of conversion and the amount of filler in IDM and tetric ceram composites. Ten disk shaped, uncured specimens (8mm×1.547mm of each composite were placed on glass slide in the center of the metal attached to it. Then specimens were light cured for 60s from underneath. After 30 minutes, the thickness of specimens, using a micrometer and the percent of the polymerization shrinkage of each sample were measured. Statistical analysis was carried out by t-test (P<0.05. Also the degree of conversion of specimens was evaluated with FTIR and the mineral filler content was measured by burning in electric oven. Polymerization shrinkage in IDM and tetric ceram was not significantly different. Degree of conversion and mineral filler content in tetric ceram was greater than that of IDM. "nIt is assumed that the low degree of conversion in IDM is due to its chemical composition and filler content. Also, the similarity in linear polymerization shrinkage between IDM and tetric ceram may be caused by the low degree of conversion in IDM.
Directory of Open Access Journals (Sweden)
Tae-Yub Kwon
2014-01-01
Full Text Available Dental modeling resins have been developed for use in areas where highly precise resin structures are needed. The manufacturers claim that these polymethyl methacrylate/methyl methacrylate (PMMA/MMA resins show little or no shrinkage after polymerization. This study examined the polymerization shrinkage of five dental modeling resins as well as one temporary PMMA/MMA resin (control. The morphology and the particle size of the prepolymerized PMMA powders were investigated by scanning electron microscopy and laser diffraction particle size analysis, respectively. Linear polymerization shrinkage strains of the resins were monitored for 20 minutes using a custom-made linometer, and the final values (at 20 minutes were converted into volumetric shrinkages. The final volumetric shrinkage values for the modeling resins were statistically similar (P>0.05 or significantly larger (P<0.05 than that of the control resin and were related to the polymerization kinetics (P<0.05 rather than the PMMA bead size (P=0.335. Therefore, the optimal control of the polymerization kinetics seems to be more important for producing high-precision resin structures rather than the use of dental modeling resins.
Directory of Open Access Journals (Sweden)
Yih-Dean Jan
2014-04-01
Conclusion: Conjugation of diisocyanate side chains to dimethacrylate represents an effective means of reducing polymerization shrinkage and increasing the surface hardness of dental composite resins.
Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.
Aitkenhead, M J; Aalders, I H
2009-01-01
Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.
Bayesian analysis of CCDM models
Energy Technology Data Exchange (ETDEWEB)
Jesus, J.F. [Universidade Estadual Paulista (Unesp), Câmpus Experimental de Itapeva, Rua Geraldo Alckmin 519, Vila N. Sra. de Fátima, Itapeva, SP, 18409-010 Brazil (Brazil); Valentim, R. [Departamento de Física, Instituto de Ciências Ambientais, Químicas e Farmacêuticas—ICAQF, Universidade Federal de São Paulo (UNIFESP), Unidade José Alencar, Rua São Nicolau No. 210, Diadema, SP, 09913-030 Brazil (Brazil); Andrade-Oliveira, F., E-mail: jfjesus@itapeva.unesp.br, E-mail: valentim.rodolfo@unifesp.br, E-mail: felipe.oliveira@port.ac.uk [Institute of Cosmology and Gravitation—University of Portsmouth, Burnaby Road, Portsmouth, PO1 3FX United Kingdom (United Kingdom)
2017-09-01
Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3α H {sub 0} model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.
Bayesian modeling using WinBUGS
Ntzoufras, Ioannis
2009-01-01
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all ...
Ottevaere, H.; Tabak, M.; Chah, K.; Mégret, P.; Thienpont, H.
2012-04-01
Polymerization shrinkage of dental composite materials is recognized as one of the main reasons for the development of marginal leakage between a tooth and filling material. As an alternative to conventional measurement methods, we propose optical fiber Bragg grating (FBG) based sensors to perform real-time strain and shrinkage measurements during the curing process of dental resin cements. We introduce a fully automated set-up to measure the Bragg wavelength shift of the FBG strain sensors and to accurately monitor the linear strain and shrinkage of dental resins during curing. Three different dental resin materials were studied in this work: matrix-filled BisGMA-based resins, glass ionomers and organic modified ceramics.
Calcium silicate structure and carbonation shrinkage of a tobermorite-based material
International Nuclear Information System (INIS)
Matsushita, Fumiaki; Aono, Yoshimichi; Shibata, Sumio
2004-01-01
Carbonated autoclaved aerated concretes (AACs) show no shrinkage at a degree of carbonation approximately less than 20%. The 29 Si MAS NMR spectrum showed that at a degree of carbonation less than 25%, the typical double-chain silicate anion structure of tobermorite-11A was well maintained and interlayer Ca ions were exchanged with protons. This corresponded to the absence of carbonation shrinkage at a degree of carbonation less than 20%. When the degree of carbonation increased from 25% to 50% up to 60%, the double-chain silicate anion structure of tobermorite-11A was decomposed and Ca ions in the Ca-O layers were dissolved, showing a possible mechanism of carbonation shrinkage
DEFF Research Database (Denmark)
Luo, Yangjun; Wang, Michael Yu; Zhou, Mingdong
2015-01-01
-dependent force. Under multi-axial stress conditions, the concrete failure surface is well fitted by two Drucker-Prager yield functions. The optimization problem aims at minimizing the cost function under yield strength constraints on concrete elements and a structural shrinkage volume constraint. In conjunction......To take into account the shrinkage effect in the early stage of Reinforced Concrete (RC) design, an effective continuum topology optimization method is presented in this paper. Based on the power-law interpolation, shrinkage of concrete is numerically simulated by introducing an additional design...... with the adjoint-variable sensitivity information, the enhanced aggregation method is utilized to efficiently reduce the computational effort arisen from large-scale strength constraints. Numerical results reveal that the proposed approach can produce a reasonable solution with the least steel reinforcements...
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary...... configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary...... configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian variable selection in regression
Energy Technology Data Exchange (ETDEWEB)
Mitchell, T.J.; Beauchamp, J.J.
1987-01-01
This paper is concerned with the selection of subsets of ''predictor'' variables in a linear regression model for the prediction of a ''dependent'' variable. We take a Bayesian approach and assign a probability distribution to the dependent variable through a specification of prior distributions for the unknown parameters in the regression model. The appropriate posterior probabilities are derived for each submodel and methods are proposed for evaluating the family of prior distributions. Examples are given that show the application of the Bayesian methodology. 23 refs., 3 figs.
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees a...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....... and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last...
Bayesian methods for proteomic biomarker development
Directory of Open Access Journals (Sweden)
Belinda Hernández
2015-12-01
In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Bayesian variable order Markov models: Towards Bayesian predictive state representations
Dimitrakakis, C.
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more
The humble Bayesian : Model checking from a fully Bayesian perspective
Morey, Richard D.; Romeijn, Jan-Willem; Rouder, Jeffrey N.
Gelman and Shalizi (2012) criticize what they call the usual story in Bayesian statistics: that the distribution over hypotheses or models is the sole means of statistical inference, thus excluding model checking and revision, and that inference is inductivist rather than deductivist. They present
Song, Q Chelsea; Wee, Serena; Newman, Daniel A
2017-12-01
To reduce adverse impact potential and improve diversity outcomes from personnel selection, one promising technique is De Corte, Lievens, and Sackett's (2007) Pareto-optimal weighting strategy. De Corte et al.'s strategy has been demonstrated on (a) a composite of cognitive and noncognitive (e.g., personality) tests (De Corte, Lievens, & Sackett, 2008) and (b) a composite of specific cognitive ability subtests (Wee, Newman, & Joseph, 2014). Both studies illustrated how Pareto-weighting (in contrast to unit weighting) could lead to substantial improvement in diversity outcomes (i.e., diversity improvement), sometimes more than doubling the number of job offers for minority applicants. The current work addresses a key limitation of the technique-the possibility of shrinkage, especially diversity shrinkage, in the Pareto-optimal solutions. Using Monte Carlo simulations, sample size and predictor combinations were varied and cross-validated Pareto-optimal solutions were obtained. Although diversity shrinkage was sizable for a composite of cognitive and noncognitive predictors when sample size was at or below 500, diversity shrinkage was typically negligible for a composite of specific cognitive subtest predictors when sample size was at least 100. Diversity shrinkage was larger when the Pareto-optimal solution suggested substantial diversity improvement. When sample size was at least 100, cross-validated Pareto-optimal weights typically outperformed unit weights-suggesting that diversity improvement is often possible, despite diversity shrinkage. Implications for Pareto-optimal weighting, adverse impact, sample size of validation studies, and optimizing the diversity-job performance tradeoff are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Influence of resin cement polymerization shrinkage on stresses in porcelain crowns.
May, Liliana G; Kelly, J Robert
2013-10-01
The aim of this study was to analyze the influence of polymerization shrinkage of the cement layer on stresses within feldspathic ceramic crowns, using experimentally validated FEA models for (1) increasing occlusal cement thickness; and, (2) bonded versus non-bonded ceramic-cement interfaces. 2-D axial symmetric models simulated stylized feldspathic crowns (1.5mm occlusal thickness) cemented with resin-cement layers of 50-500μm on dentin preparations, being loaded (500N) or not. Ceramic-cement interface was either bonded or not. Cement was bonded to the dentin in all models. Maximum axial shrinkage of 0%, 1%, 2%, 3%, 4% and 4.65% were simulated. The first principal stresses developing in the cementation surface at the center and at the occluso-axial line-angle of the crown were registered. Polymerization shrinkage of the cement increased tensile stresses in the ceramic, especially in loaded non-bonded crowns for thicker cement layers. Stresses in loaded non-bonded crowns increased as much as 87% when cement shrinkage increased from 0% to 4.65% (100-187MPa), for a 500μm-thick cement. Increasing polymerization shrinkage strain raised the tensile stresses, especially at the internal occlusal-axial line-angle, for bonded crowns. Changes in the polymerization shrinkage strain (from 0% to 4.65%) have little effect on the tensile stresses generated at the cementation surface of the ceramic crowns, when the occlusal cement thickness is thin (approx. 50μm for bonded crowns). However, as the cement becomes thicker stresses within the ceramic become significant. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Shibasaki, S; Takamizawa, T; Nojiri, K; Imai, A; Tsujimoto, A; Endo, H; Suzuki, S; Suda, S; Barkmeier, W W; Latta, M A; Miyazaki, M
The present study determined the mechanical properties and volumetric polymerization shrinkage of different categories of resin composite. Three high viscosity bulk fill resin composites were tested: Tetric EvoCeram Bulk Fill (TB, Ivoclar Vivadent), Filtek Bulk Fill posterior restorative (FB, 3M ESPE), and Sonic Fill (SF, Kerr Corp). Two low-shrinkage resin composites, Kalore (KL, GC Corp) and Filtek LS Posterior (LS, 3M ESPE), were used. Three conventional resin composites, Herculite Ultra (HU, Kerr Corp), Estelite ∑ Quick (EQ, Tokuyama Dental), and Filtek Supreme Ultra (SU, 3M ESPE), were used as comparison materials. Following ISO Specification 4049, six specimens for each resin composite were used to determine flexural strength, elastic modulus, and resilience. Volumetric polymerization shrinkage was determined using a water-filled dilatometer. Data were evaluated using analysis of variance followed by Tukey's honestly significant difference test (α=0.05). The flexural strength of the resin composites ranged from 115.4 to 148.1 MPa, the elastic modulus ranged from 5.6 to 13.4 GPa, and the resilience ranged from 0.70 to 1.0 MJ/m 3 . There were significant differences in flexural properties between the materials but no clear outliers. Volumetric changes as a function of time over a duration of 180 seconds depended on the type of resin composite. However, for all the resin composites, apart from LS, volumetric shrinkage began soon after the start of light irradiation, and a rapid decrease in volume during light irradiation followed by a slower decrease was observed. The low shrinkage resin composites KL and LS showed significantly lower volumetric shrinkage than the other tested materials at the measuring point of 180 seconds. In contrast, the three bulk fill resin composites showed higher volumetric change than the other resin composites. The findings from this study provide clinicians with valuable information regarding the mechanical properties and
Bayesian Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Bayesian models in cognitive neuroscience: A tutorial
O'Reilly, J.X.; Mars, R.B.
2015-01-01
This chapter provides an introduction to Bayesian models and their application in cognitive neuroscience. The central feature of Bayesian models, as opposed to other classes of models, is that Bayesian models represent the beliefs of an observer as probability distributions, allowing them to
A Bayesian framework for risk perception
van Erp, H.R.N.
2017-01-01
We present here a Bayesian framework of risk perception. This framework encompasses plausibility judgments, decision making, and question asking. Plausibility judgments are modeled by way of Bayesian probability theory, decision making is modeled by way of a Bayesian decision theory, and relevancy
Cell shrinkage as a signal to apoptosis in NIH 3T3 fibroblasts
DEFF Research Database (Denmark)
Friis, Martin B; Friborg, Christel R; Schneider, Linda
2005-01-01
Cell shrinkage is a hallmark of the apoptotic mode of programmed cell death, but it is as yet unclear whether a reduction in cell volume is a primary activation signal of apoptosis. Here we studied the effect of an acute elevation of osmolarity (NaCl or sucrose additions, final osmolarity 687...... mosmol l(-1)) on NIH 3T3 fibroblasts to identify components involved in the signal transduction from shrinkage to apoptosis. After 1.5 h the activity of caspase-3 started to increase followed after 3 h by the appearance of many apoptotic-like bodies. The caspase-3 activity increase was greatly enhanced...
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method
Desmal, Abdulla
2014-07-01
A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE.
Xie, Xianchao; Kou, S C; Brown, Lawrence
2016-03-01
This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results.
Experimental investigation on shrinkage and surface replication of injection moulded ceramic parts
DEFF Research Database (Denmark)
Islam, Aminul; Giannekas, Nikolaos; Marhöfer, David Maximilian
2014-01-01
Ceramic moulded parts are increasingly being used in advanced components and devices due to their unprecedented material and performance attributes. The surface finish, replication quality and material shrinkage are of immense importance for moulded ceramic parts intended for precision applications....... The current paper presents a thorough investigation on the process of ceramic moulding where it systematically characterizes the surface replication and shrinkage behaviours of precision moulded ceramic components. The test parts are moulded from Catamold TZP-A which is Y2O3-stabilised ZrO2 having widespread...... distribution for the moulded ceramic parts is presented....
Directory of Open Access Journals (Sweden)
Rodrigo R. Maia
2015-06-01
Full Text Available Purpose. This study tested the null hypothesis that different classes of direct restorative dental materials: silorane-based resin, low-shrinkage and conventional (non-flowable and flowable resin-based composite (RBC do not differ from each other with regard to polymerization shrinkage, depth of cure or microhardness.Methods. 140 RBC samples were fabricated and tested by one calibrated operator. Polymerization shrinkage was measured using a gas pycnometer both before and immediately after curing with 36 J/cm2 light energy density. Depth of cure was determined, using a penetrometer and the Knoop microhardness was tested from the top surface to a depth of 5 mm.Results. Considering polymerization shrinkage, the authors found significant differences (p < 0.05 between different materials: non-flowable RBCs showed lower values compared to flowable RBCs, with the silorane-based resin presenting the smallest shrinkage. The low shrinkage flowable composite performed similarly to non-flowable with significant statistical differences compared to the two other flowable RBCs. Regarding to depth of cure, low-shrinkage flowable RBC, were most effective compared to other groups. Microhardness was generally higher for the non-flowable vs. flowable RBCs (p < 0.05. However, the values for low-shrinkage flowable did not differ significantly from those of non-flowable, but were significantly higher than those of the other flowable RBCs.Clinical Significance. RBCs have undergone many modifications as they have evolved and represent the most relevant restorative materials in today’s dental practice. This study of low-shrinkage RBCs, conventional RBCs (non-flowable and flowable and silorane-based composite—by in vitro evaluation of volumetric shrinkage, depth of cure and microhardness—reveals that although filler content is an important determinant of polymerization shrinkage, it is not the only variable that affects properties of materials that were tested in
Bayesian geostatistical modeling of leishmaniasis incidence in Brazil.
Directory of Open Access Journals (Sweden)
Dimitrios-Alexios Karagiannis-Voules
Full Text Available BACKGROUND: Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries. METHODOLOGY: We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010. Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis. PRINCIPAL FINDINGS: For both types of leishmaniasis, precipitation and socioeconomic proxies were identified as important risk factors. The predicted number of cases in 2010 were 30,189 (standard deviation [SD]: 7,676 for cutaneous leishmaniasis and 4,889 (SD: 288 for visceral leishmaniasis. Our risk maps predicted the highest numbers of infected people in the states of Minas Gerais and Pará for visceral and cutaneous leishmaniasis, respectively. CONCLUSIONS/SIGNIFICANCE: Our spatially explicit, high-resolution incidence maps identified priority areas where leishmaniasis control efforts should be targeted with the ultimate goal to reduce disease incidence.
Differentiated Bayesian Conjoint Choice Designs
Z. Sándor (Zsolt); M. Wedel (Michel)
2003-01-01
textabstractPrevious conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about
Bayesian networks in levee reliability
Roscoe, K.; Hanea, A.
2015-01-01
We applied a Bayesian network to a system of levees for which the results of traditional reliability analysis showed high failure probabilities, which conflicted with the intuition and experience of those managing the levees. We made use of forty proven strength observations - high water levels with
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic...... dimensionality. The built classi er is tested on standard and non-standard images...
Computational Neuropsychology and Bayesian Inference.
Parr, Thomas; Rees, Geraint; Friston, Karl J
2018-01-01
Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine 'prior' beliefs with a generative (predictive) model to explain the causes of sensations. Under this view, neuropsychological deficits can be thought of as false inferences that arise due to aberrant prior beliefs (that are poor fits to the real world). This draws upon the notion of a Bayes optimal pathology - optimal inference with suboptimal priors - and provides a means for computational phenotyping. In principle, any given neuropsychological disorder could be characterized by the set of prior beliefs that would make a patient's behavior appear Bayes optimal. We start with an overview of some key theoretical constructs and use these to motivate a form of computational neuropsychology that relates anatomical structures in the brain to the computations they perform. Throughout, we draw upon computational accounts of neuropsychological syndromes. These are selected to emphasize the key features of a Bayesian approach, and the possible types of pathological prior that may be present. They range from visual neglect through hallucinations to autism. Through these illustrative examples, we review the use of Bayesian approaches to understand the link between biology and computation that is at the heart of neuropsychology.
Bayesian Alternation During Tactile Augmentation
Directory of Open Access Journals (Sweden)
Caspar Mathias Goeke
2016-10-01
Full Text Available A large number of studies suggest that the integration of multisensory signals by humans is well described by Bayesian principles. However, there are very few reports about cue combination between a native and an augmented sense. In particular, we asked the question whether adult participants are able to integrate an augmented sensory cue with existing native sensory information. Hence for the purpose of this study we build a tactile augmentation device. Consequently, we compared different hypotheses of how untrained adult participants combine information from a native and an augmented sense. In a two-interval forced choice (2 IFC task, while subjects were blindfolded and seated on a rotating platform, our sensory augmentation device translated information on whole body yaw rotation to tactile stimulation. Three conditions were realized: tactile stimulation only (augmented condition, rotation only (native condition, and both augmented and native information (bimodal condition. Participants had to choose one out of two consecutive rotations with higher angular rotation. For the analysis, we fitted the participants’ responses with a probit model and calculated the just notable difference (JND. Then we compared several models for predicting bimodal from unimodal responses. An objective Bayesian alternation model yielded a better prediction (χred2 = 1.67 than the Bayesian integration model (χred2= 4.34. Slightly higher accuracy showed a non-Bayesian winner takes all model (χred2= 1.64, which either used only native or only augmented values per subject for prediction. However the performance of the Bayesian alternation model could be substantially improved (χred2= 1.09 utilizing subjective weights obtained by a questionnaire. As a result, the subjective Bayesian alternation model predicted bimodal performance most accurately among all tested models. These results suggest that information from augmented and existing sensory modalities in
Topics in Bayesian statistics and maximum entropy
International Nuclear Information System (INIS)
Mutihac, R.; Cicuttin, A.; Cerdeira, A.; Stanciulescu, C.
1998-12-01
Notions of Bayesian decision theory and maximum entropy methods are reviewed with particular emphasis on probabilistic inference and Bayesian modeling. The axiomatic approach is considered as the best justification of Bayesian analysis and maximum entropy principle applied in natural sciences. Particular emphasis is put on solving the inverse problem in digital image restoration and Bayesian modeling of neural networks. Further topics addressed briefly include language modeling, neutron scattering, multiuser detection and channel equalization in digital communications, genetic information, and Bayesian court decision-making. (author)
Bayesian analysis of rare events
Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang
2016-06-01
In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.
Polytomies and Bayesian phylogenetic inference.
Lewis, Paul O; Holder, Mark T; Holsinger, Kent E
2005-04-01
Bayesian phylogenetic analyses are now very popular in systematics and molecular evolution because they allow the use of much more realistic models than currently possible with maximum likelihood methods. There are, however, a growing number of examples in which large Bayesian posterior clade probabilities are associated with very short branch lengths and low values for non-Bayesian measures of support such as nonparametric bootstrapping. For the four-taxon case when the true tree is the star phylogeny, Bayesian analyses become increasingly unpredictable in their preference for one of the three possible resolved tree topologies as data set size increases. This leads to the prediction that hard (or near-hard) polytomies in nature will cause unpredictable behavior in Bayesian analyses, with arbitrary resolutions of the polytomy receiving very high posterior probabilities in some cases. We present a simple solution to this problem involving a reversible-jump Markov chain Monte Carlo (MCMC) algorithm that allows exploration of all of tree space, including unresolved tree topologies with one or more polytomies. The reversible-jump MCMC approach allows prior distributions to place some weight on less-resolved tree topologies, which eliminates misleadingly high posteriors associated with arbitrary resolutions of hard polytomies. Fortunately, assigning some prior probability to polytomous tree topologies does not appear to come with a significant cost in terms of the ability to assess the level of support for edges that do exist in the true tree. Methods are discussed for applying arbitrary prior distributions to tree topologies of varying resolution, and an empirical example showing evidence of polytomies is analyzed and discussed.
Huang, H.; Ye, G.; Fehling, Ekkehard; Middendorf, Bernhard; Thiemicke, Jenny
2016-01-01
It is well recognized that the high risk of early age micro-crack of HPC/UHPC is attributed to the large magnitude of early age autogenous shrinkage caused by self-desiccation in binder hydration. Over the years, several methods have been proposed to mitigate autogenous shrinkage based on internal
Katsen-Globa, Alisa; Puetz, Norbert; Gepp, Michael M; Neubauer, Julia C; Zimmermann, Heiko
2016-11-01
One of the often reported artefacts during cell preparation to scanning electron microscopy (SEM) is the shrinkage of cellular objects, that mostly occurs at a certain time-dependent stage of cell drying. Various methods of drying for SEM, such as critical point drying, freeze-drying, as well as hexamethyldisilazane (HMDS)-drying, were usually used. The latter becomes popular since it is a low cost and fast method. However, the correlation of drying duration and real shrinkage of objects was not investigated yet. In this paper, cell shrinkage at each stage of preparation for SEM was studied. We introduce a shrinkage coefficient using correlative light microscopy (LM) and SEM of the same human mesenchymal stem cells (hMSCs). The influence of HMDS-drying duration on the cell shrinkage is shown: the longer drying duration, the more shrinkage is observed. Furthermore, it was demonstrated that cell shrinkage is inversely proportional to cultivation time: the longer cultivation time, the more cell spreading area and the less cell shrinkage. Our results can be applicable for an exact SEM quantification of cell size and determination of cell spreading area in engineering of artificial cellular environments using biomaterials. SCANNING 38:625-633, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.
Bayesian methods for measures of agreement
Broemeling, Lyle D
2009-01-01
Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation...
Shrinkages in heavy-sized cast components of nodular cast iron – NDT and fatigue
Directory of Open Access Journals (Sweden)
Bleicher Christoph
2014-06-01
Full Text Available Material defects like shrinkages, dross, pores and chunky graphite are likely to occur in thick-walled castings and are a challenge for the foundries and their customers. These defects are mostly detected with handheld ultrasonic testing (UT or X-ray analysis. Within a research project done at the Fraunhofer Institute for Structural Durability and System Reliability LBF, the fatigue of Dross, shrinkages and chunky graphite in thick-walled cast material GGG-40 was estimated based on X-ray and fatigue tests on bending specimens. High fatigue reductions were received for the different material imperfections. Based on these impressions a further research project was executed at the Fraunhofer LBF to get an estimation of the informational value of UT in relation to fatigue of shrinkages in thick-walled castings of the material EN-GJS-400-18U-LT, EN-GJS-450-18 and EN-GJS-700-2. With the help of X-ray analysis and the UT technique Sampling Phased Array (SPA information about geometry and density were derived for a numerical analysis of shrinkages in thick-walled castings concerning fatigue. The following text summarizes the fatigue results achieved in the two research projects with the help of the X-ray and UT analysis.
Influence of rare earths on shrinkage porosity in thin walled ductile cast iron
DEFF Research Database (Denmark)
Pedersen, Karl Martin; Tiedje, Niels Skat
2009-01-01
Ductile cast iron has been cast in test bars with thickness from 2 to 10 mm. The rare earth elements La and Ce have been added to some of the castings to evaluate their influence on microstructure and shrinkage tendency. Both La and Ce increased the graphite nodule count, especially for thickness...
Autogenous shrinkage of Ducorit S5R ASTM C 1698-09 test method
DEFF Research Database (Denmark)
Damkilde, Lars
The report deals with experimental measurement of autogenous shrinkage of Ducorit S5R according to the test method ASTM C 1698-09. This test method measures the bulk strain of a sealed cementitious specimen, at constant temperature and not subjected to external forces, from the time of final...
The effect of mold surface topography on plastic parat in-process shrinkage in injection molding
DEFF Research Database (Denmark)
Arlø, Uffe Rolf; Hansen, Hans Nørgaard; Kjær, Erik Michael
2003-01-01
An experimental study of the effect of mold surface roughness on in-process in-flow linear part shrinkage in injection molding has been carried out. The investigation is based on an experimental two-cavity tool, where the cavities have different surface topographies, but are otherwise identical...
Danielson, Christian; Mehrnezhad, Ali; YekrangSafakar, Ashkan; Park, Kidong
2017-06-14
Self-folding or micro-origami technologies are actively investigated as a novel manufacturing process to fabricate three-dimensional macro/micro-structures. In this paper, we present a simple process to produce a self-folding structure with a biaxially oriented polystyrene sheet (BOPS) or Shrinky Dinks. A BOPS sheet is known to shrink to one-third of its original size in plane, when it is heated above 160 °C. A grid pattern is engraved on one side of the BOPS film with a laser engraver to decrease the thermal shrinkage of the engraved side. The thermal shrinkage of the non-engraved side remains the same and this unbalanced thermal shrinkage causes folding of the structure as the structure shrinks at high temperature. We investigated the self-folding mechanism and characterized how the grid geometry, the grid size, and the power of the laser engraver affect the bending curvature. The developed fabrication process to locally modulate thermomechanical properties of the material by engraving the grid pattern and the demonstrated design methodology to harness the unbalanced thermal shrinkage can be applied to develop complicated self-folding macro/micro structures.
DEFF Research Database (Denmark)
Stang, Henrik
1996-01-01
used in high performance cementitious composite materials.Assuming a Coulomb type of friction on the fiber/matrix interface andusing typical values for the frictional coefficient it is shownthat the shrinkage induced clamping pressure could be one of the mostimportant factors determining the frictional...
Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space
DEFF Research Database (Denmark)
Østby, Ivar; Øyehaug, Leiv; Einevoll, Gaute T
2009-01-01
, astrocyte uptake of potassium, sodium, and chloride in passive channels, action of the Na/K/ATPase pump, and osmotically driven transport of water through the astrocyte membrane together seem sufficient for generating ECS shrinkage as such. However, when taking into account ECS and astrocyte ion...
Correcting the axial shrinkage of skeletal muscle thick sections visualized by confocal microscopy
Czech Academy of Sciences Publication Activity Database
Janáček, Jiří; Kreft, M.; Čebašek, V.; Eržen, I.
2012-01-01
Roč. 246, č. 2 (2012), s. 107-112 ISSN 0022-2720 R&D Projects: GA MŠk(CZ) MEB090910; GA MŠk(CZ) LC06063 Institutional research plan: CEZ:AV0Z50110509 Keywords : capillaries * confocal microscopy * sample deformation * shrinkage * skeletal muscle * 3D Subject RIV: FH - Neurology Impact factor: 1.633, year: 2012
The evolution of shrinkage strain of pet-mortar composite eco ...
African Journals Online (AJOL)
Concretes and mortars are subjected to several kinds of shrinkage strains which represent the volumic variations resulting from the cement hydration and are governed by various physical and chemical aspects. The use of polyethylene terephthalate PET plastic wastes which are available in quantity and within low cost in ...
Carneiro, Vanda S. M.; Mota, Cláudia C. B. O.; Souza, Alex F.; Cajazeira, Marlus R. R.; Gerbi, Marleny E. M. M.; Gomes, Anderson S. L.
2018-02-01
This study evaluated the polymerization shrinkage of two experimental flowable composite resins (CR) with different proportions of Urethane dimethacrylate (UDMA)/triethylene glycol dimethacrylate (TEGDMA) monomers in the organic matrix (50:50 and 60:40, respectively). A commercially available flowable CR, Tetric N-Flow (Ivoclair Vivadent, Liechtenstein, Germany), was employed as the control group. The resins were inserted in a cylindrical teflon mold (7 mm diameter, 0.6 mm height) and scanned with OCT before photoactivation, immediately after and 15 minutes after light-curing (Radii-Cal, SDI, Australia, 1,200 mW/cm2 ) exposure. A Callisto SD-OCT system (Thorlabs Inc, USA), operating at 930 nm central wavelength was employed for imaging acquisition. Cross-sectional OCT images were captured with 8 mm transverse scanning (2000x512 matrix), and processed by the ImageJ software, for comparison between the scanning times and between groups. Pearson correlation showed significant shrinkage for all groups in each time analyzed. Kruskal-Wallis test showed greater polymerization shrinkage for the 50:50 UDMA/TEGDMA group (p=0.001), followed by the control group (p=0.018). TEGDMA concentration was proportionally related to the polymerization shrinkage of the flowable composite resins.
Nam, Jeongsoo; Kim, Gyuyong; Yoo, Jaechul; Choe, Gyeongcheol; Kim, Hongseop; Choi, Hyeonggil; Kim, Youngduck
2016-02-26
This paper presents an experimental study conducted to investigate the effect of fiber reinforcement on the mechanical properties and shrinkage cracking of recycled fine aggregate concrete (RFAC) with two types of fiber-polyvinyl alcohol (PVA) and nylon. A small fiber volume fraction, such as 0.05% or 0.1%, in RFAC with polyvinyl alcohol or nylon fibers was used for optimum efficiency in minimum quantity. Additionally, to make a comparative evaluation of the mechanical properties and shrinkage cracking, we examined natural fine aggregate concrete as well. The test results revealed that the addition of fibers and fine aggregates plays an important role in improving the mechanical performance of the investigated concrete specimens as well as controlling their cracking behavior. The mechanical properties such as compressive strength, splitting tensile strength, and flexural strength of fiber-reinforced RFAC were slightly better than those of non-fiber-reinforced RFAC. The shrinkage cracking behavior was examined using plat-ring-type and slab-type tests. The fiber-reinforced RFAC showed a greater reduction in the surface cracks than non-fiber-reinforced concrete. The addition of fibers at a small volume fraction in RFAC is more effective for drying shrinkage cracks than for improving mechanical performance.
Linear shrinkage test: justification for its reintroduction as a standard South African test method
CSIR Research Space (South Africa)
Sampson, LR
2009-06-04
Full Text Available Several problems with the linear shrinkage test specified in Method A4 of the THM 1 1979 were addressed as part of this investigation in an effort to improve the alleged poor reproducibility of the test and justify its reintroduction into THM 1. A...
Setting shrinkage strains of chemical-cured glass ionomer-based ...
African Journals Online (AJOL)
Shrinkage strains are exhibited by the current formulations of chemical-cured dental restorative systems. In resin-modified glass ionomer systems, these have been linked to filler contents, types and quantity of monomer. Post-gelation rigid contraction that follows onset of cure leading to marginal defects is a clinically ...
SEM-induced shrinkage and site-selective modification of single-crystal silicon nanopores
Chen, Qi; Wang, Yifan; Deng, Tao; Liu, Zewen
2017-07-01
Solid-state nanopores with feature sizes around 5 nm play a critical role in bio-sensing fields, especially in single molecule detection and sequencing of DNA, RNA and proteins. In this paper we present a systematic study on shrinkage and site-selective modification of single-crystal silicon nanopores with a conventional scanning electron microscope (SEM). Square nanopores with measurable sizes as small as 8 nm × 8 nm and rectangle nanopores with feature sizes (the smaller one between length and width) down to 5 nm have been obtained, using the SEM-induced shrinkage technique. The analysis of energy dispersive x-ray spectroscopy and the recovery of the pore size and morphology reveal that the grown material along with the edge of the nanopore is the result of deposition of hydrocarbon compounds, without structural damage during the shrinking process. A simplified model for pore shrinkage has been developed based on observation of the cross-sectional morphology of the shrunk nanopore. The main factors impacting on the task of controllably shrinking the nanopores, such as the accelerating voltage, spot size, scanned area of e-beam, and the initial pore size have been discussed. It is found that single-crystal silicon nanopores shrink linearly with time under localized irradiation by SEM e-beam in all cases, and the pore shrinkage rate is inversely proportional to the initial equivalent diameter of the pore under the same e-beam conditions.
Nam, Jeongsoo; Kim, Gyuyong; Yoo, Jaechul; Choe, Gyeongcheol; Kim, Hongseop; Choi, Hyeonggil; Kim, Youngduck
2016-01-01
This paper presents an experimental study conducted to investigate the effect of fiber reinforcement on the mechanical properties and shrinkage cracking of recycled fine aggregate concrete (RFAC) with two types of fiber—polyvinyl alcohol (PVA) and nylon. A small fiber volume fraction, such as 0.05% or 0.1%, in RFAC with polyvinyl alcohol or nylon fibers was used for optimum efficiency in minimum quantity. Additionally, to make a comparative evaluation of the mechanical properties and shrinkage cracking, we examined natural fine aggregate concrete as well. The test results revealed that the addition of fibers and fine aggregates plays an important role in improving the mechanical performance of the investigated concrete specimens as well as controlling their cracking behavior. The mechanical properties such as compressive strength, splitting tensile strength, and flexural strength of fiber-reinforced RFAC were slightly better than those of non-fiber-reinforced RFAC. The shrinkage cracking behavior was examined using plat-ring-type and slab-type tests. The fiber-reinforced RFAC showed a greater reduction in the surface cracks than non-fiber-reinforced concrete. The addition of fibers at a small volume fraction in RFAC is more effective for drying shrinkage cracks than for improving mechanical performance. PMID:28773256
Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space.
Directory of Open Access Journals (Sweden)
Ivar Østby
2009-01-01
Full Text Available Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astrocyte function, the phenomenon remains unexplained. Here we present a dynamic model that accounts for current experimental data related to the shrinkage phenomenon in wild-type as well as in gene knockout individuals. We find that neuronal release of potassium and uptake of sodium during stimulation, astrocyte uptake of potassium, sodium, and chloride in passive channels, action of the Na/K/ATPase pump, and osmotically driven transport of water through the astrocyte membrane together seem sufficient for generating ECS shrinkage as such. However, when taking into account ECS and astrocyte ion concentrations observed in connection with neuronal stimulation, the actions of the Na(+/K(+/Cl(- (NKCC1 and the Na(+/HCO(3 (- (NBC cotransporters appear to be critical determinants for achieving observed quantitative levels of ECS shrinkage. Considering the current state of knowledge, the model framework appears sufficiently detailed and constrained to guide future key experiments and pave the way for more comprehensive astroglia-neuron interaction models for normal as well as pathophysiological situations.
A numerical analysis method on thermal and shrinkage stress of concrete
International Nuclear Information System (INIS)
Takiguchi, Katsuki; Hotta, Hisato
1991-01-01
Thermal stress often causes cracks in large scale concrete such as that for dam construction. The drying shrinkage of concrete causes cracks in concrete structures. These thermal stress and drying shrinkage stress may be the main reasons cracks occur in concrete, however there is few research which dealt with both stresses together. The problems on the thermal stress and the drying shrinkage are not independent, and should be dealt with together, because both temperature and water content of concrete affect hydration reaction, and the degree of hydration determines all the characteristics of concrete at early age. In this study, the degree of hydration is formulated experimentally, and a numerical stress analysis method taking the hydration reaction in consideration is presented. The formulation of the rate of hydration reaction, the method of analyzing thermal and drying shrinkage stresses, the analytical results for a concrete column and the influence that continuous load exerted to the tensile strength of concrete are reported. The relatively high stress nearly equal to the tensile strength of concrete arises near the surface. (K.I.)
Ultra high performance concrete made with rice husk ash for reduced autogenous shrinkage
Van Breugel, K.; Van Tuan, N.
2014-01-01
Ultra High Strength Concrete (UHPC) is generally made with low w/c mixtures and by adding silica fume. Low w/c mixtures, however, exhibit high autogenous shrinkage, while a high amount of silica fume increases the price of these mixtures. For designing ultra high strength mixtures with low
Moisture migration and shrinkage of hardened cement paste at elevated temperatures
International Nuclear Information System (INIS)
Numao, Tatsuya; Mihashi, Hirozo.
1991-01-01
The drying shrinkage of concrete is caused by the loss of water in the concrete. The moisture diffusion behavior influences the mechanical properties of concrete. When concrete is exposed to high temperature, the rate of moisture migration becomes fast, and moisture gradient is formed. This gradient causes cracks on the concrete surface. Accordingly, it is important to study on the relation between the drying shrinkage and the water diffusion in concrete when its mechanical properties at elevated temperature are discussed. In this paper, the results of the experiment which was carried out by using thin-walled cylinder specimens kept at different temperature and stress are reported. The specimens, the drying shrinkage of concrete and acoustic emission (AE), the thermal expansion of hardened cement paste, the influence that temperature change exerted to the drying shrinkage, and the influence that compressive stress and temperature exerted to water migration are described. The thin-walled cylinder specimens were useful for these experimental studies. (K.I.)
Porous stainless steel hollow fibers with shrinkage-controlled small radial dimensions
Luiten-Olieman, Maria W.J.; Raaijmakers, Michiel; Raaijmakers, Michiel J.T.; Winnubst, Aloysius J.A.; Wessling, Matthias; Nijmeijer, Arian; Benes, Nieck Edwin
2011-01-01
A method is presented for the preparation of thin (∼250 μm) porous stainless steel hollow fiber membranes based on dry–wet spinning of a particle-loaded polymer solution followed by heat treatment. Extraordinarily small radial dimensions were achieved by controlled shrinkage during thermal
Wiechmann, Thorsten; Pallagst, Karina M
2012-01-01
Many American and European cities have to deal with demographic and economic trajectories leading to urban shrinkage. According to official data, 13% of urban regions in the US and 54% of those in the EU have lost population in recent years. However, the extent and spatial distribution of declining populations differ significantly between Europe and the US. In Germany, the situation is driven by falling birth rates and the effects of German reunification. In the US, shrinkage is basically related to long-term industrial transformation. But the challenges of shrinking cities seldom appeared on the agendas of politicians and urban planners until recently. This article provides a critical overview of the development paths and local strategies of four shrinking cities: Schwedt and Dresden in eastern Germany; Youngstown and Pittsburgh in the US. A typology of urban growth and shrinkage, from economic and demographic perspectives, enables four types of city to be differentiated and the differences between the US and eastern Germany to be discussed. The article suggests that a new transatlantic debate on policy and planning strategies for restructuring shrinking cities is needed to overcome the dominant growth orientation that in most cases intensifies the negative consequences of shrinkage.
Zainudin, A.; Sia, C. K.; Ong, P.; Narong, O. L. C.; Nor, N. H. M.
2017-01-01
In the preparation of triaxial porcelain from Palm Oil Fuel Ash (POFA), a new parameter variable must be determined. The parameters involved are the particle size of POFA, percentage of POFA in triaxial porcelain composition, moulding pressure, sintering temperature and soaking time. Meanwhile, the shrinkage is the dependent variable. The optimization process was investigated using a hybrid Taguchi design and flower pollination algorithm (FPA). The interaction model of shrinkage was derived from regression analysis and found that the shrinkage is highly dependent on the sintering temperature followed by POFA composition, moulding pressure, POFA particle size and soaking time. The interaction between sintering temperature and soaking time highly affects the shrinkage. From the FPA process, targeted shrinkage approaching zero values were predicted for 142 μm particle sizes of POFA, 22.5 wt% of POFA, 3.4 tonne moulding pressure, 948.5 °C sintering temperature and 264 minutes soaking time.
Shrinkage of dental composite in simulated cavity measured with digital image correlation.
Li, Jianying; Thakur, Preetanjali; Fok, Alex S L
2014-07-21
Polymerization shrinkage of dental resin composites can lead to restoration debonding or cracked tooth tissues in composite-restored teeth. In order to understand where and how shrinkage strain and stress develop in such restored teeth, Digital Image Correlation (DIC) was used to provide a comprehensive view of the displacement and strain distributions within model restorations that had undergone polymerization shrinkage. Specimens with model cavities were made of cylindrical glass rods with both diameter and length being 10 mm. The dimensions of the mesial-occlusal-distal (MOD) cavity prepared in each specimen measured 3 mm and 2 mm in width and depth, respectively. After filling the cavity with resin composite, the surface under observation was sprayed with first a thin layer of white paint and then fine black charcoal powder to create high-contrast speckles. Pictures of that surface were then taken before curing and 5 min after. Finally, the two pictures were correlated using DIC software to calculate the displacement and strain distributions. The resin composite shrunk vertically towards the bottom of the cavity, with the top center portion of the restoration having the largest downward displacement. At the same time, it shrunk horizontally towards its vertical midline. Shrinkage of the composite stretched the material in the vicinity of the "tooth-restoration" interface, resulting in cuspal deflections and high tensile strains around the restoration. Material close to the cavity walls or floor had direct strains mostly in the directions perpendicular to the interfaces. Summation of the two direct strain components showed a relatively uniform distribution around the restoration and its magnitude equaled approximately to the volumetric shrinkage strain of the material.
Predicting shrinkage and warpage in injection molding: Towards automatized mold design
Zwicke, Florian; Behr, Marek; Elgeti, Stefanie
2017-10-01
It is an inevitable part of any plastics molding process that the material undergoes some shrinkage during solidification. Mainly due to unavoidable inhomogeneities in the cooling process, the overall shrinkage cannot be assumed as homogeneous in all volumetric directions. The direct consequence is warpage. The accurate prediction of such shrinkage and warpage effects has been the subject of a considerable amount of research, but it is important to note that this behavior depends greatly on the type of material that is used as well as the process details. Without limiting ourselves to any specific properties of certain materials or process designs, we aim to develop a method for the automatized design of a mold cavity that will produce correctly shaped moldings after solidification. Essentially, this can be stated as a shape optimization problem, where the cavity shape is optimized to fulfill some objective function that measures defects in the molding shape. In order to be able to develop and evaluate such a method, we first require simulation methods for the diffierent steps involved in the injection molding process that can represent the phenomena responsible for shrinkage and warpage ina sufficiently accurate manner. As a starting point, we consider the solidification of purely amorphous materials. In this case, the material slowly transitions from fluid-like to solid-like behavior as it cools down. This behavior is modeled using adjusted viscoelastic material models. Once the material has passed a certain temperature threshold during cooling, any viscous effects are neglected and the behavior is assumed to be fully elastic. Non-linear elastic laws are used to predict shrinkage and warpage that occur after this point. We will present the current state of these simulation methods and show some first approaches towards optimizing the mold cavity shape based on these methods.
2012-10-01
The main objective of this study was to determine the effect on shrinkage, creep, : and abrasion resistance of high-volume fly ash (HVFA) concrete. The HVFA concrete : test program consisted of comparing the shrinkage, creep, and abrasion performance...
Bayesian Model Averaging for Propensity Score Analysis.
Kaplan, David; Chen, Jianshen
2014-01-01
This article considers Bayesian model averaging as a means of addressing uncertainty in the selection of variables in the propensity score equation. We investigate an approximate Bayesian model averaging approach based on the model-averaged propensity score estimates produced by the R package BMA but that ignores uncertainty in the propensity score. We also provide a fully Bayesian model averaging approach via Markov chain Monte Carlo sampling (MCMC) to account for uncertainty in both parameters and models. A detailed study of our approach examines the differences in the causal estimate when incorporating noninformative versus informative priors in the model averaging stage. We examine these approaches under common methods of propensity score implementation. In addition, we evaluate the impact of changing the size of Occam's window used to narrow down the range of possible models. We also assess the predictive performance of both Bayesian model averaging propensity score approaches and compare it with the case without Bayesian model averaging. Overall, results show that both Bayesian model averaging propensity score approaches recover the treatment effect estimates well and generally provide larger uncertainty estimates, as expected. Both Bayesian model averaging approaches offer slightly better prediction of the propensity score compared with the Bayesian approach with a single propensity score equation. Covariate balance checks for the case study show that both Bayesian model averaging approaches offer good balance. The fully Bayesian model averaging approach also provides posterior probability intervals of the balance indices.
Pedestrian dynamics via Bayesian networks
Venkat, Ibrahim; Khader, Ahamad Tajudin; Subramanian, K. G.
2014-06-01
Studies on pedestrian dynamics have vital applications in crowd control management relevant to organizing safer large scale gatherings including pilgrimages. Reasoning pedestrian motion via computational intelligence techniques could be posed as a potential research problem within the realms of Artificial Intelligence. In this contribution, we propose a "Bayesian Network Model for Pedestrian Dynamics" (BNMPD) to reason the vast uncertainty imposed by pedestrian motion. With reference to key findings from literature which include simulation studies, we systematically identify: What are the various factors that could contribute to the prediction of crowd flow status? The proposed model unifies these factors in a cohesive manner using Bayesian Networks (BNs) and serves as a sophisticated probabilistic tool to simulate vital cause and effect relationships entailed in the pedestrian domain.
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...... primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples...
BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS
Directory of Open Access Journals (Sweden)
Thordis Linda Thorarinsdottir
2011-05-01
Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.
Bayesian Inference on Proportional Elections
Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio
2015-01-01
Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259
Bayesian analyses of cognitive architecture.
Houpt, Joseph W; Heathcote, Andrew; Eidels, Ami
2017-06-01
The question of cognitive architecture-how cognitive processes are temporally organized-has arisen in many areas of psychology. This question has proved difficult to answer, with many proposed solutions turning out to be spurious. Systems factorial technology (Townsend & Nozawa, 1995) provided the first rigorous empirical and analytical method of identifying cognitive architecture, using the survivor interaction contrast (SIC) to determine when people are using multiple sources of information in parallel or in series. Although the SIC is based on rigorous nonparametric mathematical modeling of response time distributions, for many years inference about cognitive architecture has relied solely on visual assessment. Houpt and Townsend (2012) recently introduced null hypothesis significance tests, and here we develop both parametric and nonparametric (encompassing prior) Bayesian inference. We show that the Bayesian approaches can have considerable advantages. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Deep Learning and Bayesian Methods
Directory of Open Access Journals (Sweden)
Prosper Harrison B.
2017-01-01
Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.
Bayesian inference on proportional elections.
Directory of Open Access Journals (Sweden)
Gabriel Hideki Vatanabe Brunello
Full Text Available Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software.
Space Shuttle RTOS Bayesian Network
Morris, A. Terry; Beling, Peter A.
2001-01-01
With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Reliability analysis with Bayesian networks
Zwirglmaier, Kilian Martin
2017-01-01
Bayesian networks (BNs) represent a probabilistic modeling tool with large potential for reliability engineering. While BNs have been successfully applied to reliability engineering, there are remaining issues, some of which are addressed in this work. Firstly a classification of BN elicitation approaches is proposed. Secondly two approximate inference approaches, one of which is based on discretization and the other one on sampling, are proposed. These approaches are applicable to hybrid/con...
Interim Bayesian Persuasion: First Steps
Perez, Eduardo
2015-01-01
This paper makes a first attempt at building a theory of interim Bayesian persuasion. I work in a minimalist model where a low or high type sender seeks validation from a receiver who is willing to validate high types exclusively. After learning her type, the sender chooses a complete conditional information structure for the receiver from a possibly restricted feasible set. I suggest a solution to this game that takes into account the signaling potential of the sender's choice.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
. This allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion....... It is shown how half-cell potential measurements may be utilized to update the probability of excessive repair after 50 years....
Computational Neuropsychology and Bayesian Inference
Directory of Open Access Journals (Sweden)
Thomas Parr
2018-02-01
Full Text Available Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine ‘prior’ beliefs with a generative (predictive model to explain the causes of sensations. Under this view, neuropsychological deficits can be thought of as false inferences that arise due to aberrant prior beliefs (that are poor fits to the real world. This draws upon the notion of a Bayes optimal pathology – optimal inference with suboptimal priors – and provides a means for computational phenotyping. In principle, any given neuropsychological disorder could be characterized by the set of prior beliefs that would make a patient’s behavior appear Bayes optimal. We start with an overview of some key theoretical constructs and use these to motivate a form of computational neuropsychology that relates anatomical structures in the brain to the computations they perform. Throughout, we draw upon computational accounts of neuropsychological syndromes. These are selected to emphasize the key features of a Bayesian approach, and the possible types of pathological prior that may be present. They range from visual neglect through hallucinations to autism. Through these illustrative examples, we review the use of Bayesian approaches to understand the link between biology and computation that is at the heart of neuropsychology.
Bayesian methods applied to GWAS.
Fernando, Rohan L; Garrick, Dorian
2013-01-01
Bayesian multiple-regression methods are being successfully used for genomic prediction and selection. These regression models simultaneously fit many more markers than the number of observations available for the analysis. Thus, the Bayes theorem is used to combine prior beliefs of marker effects, which are expressed in terms of prior distributions, with information from data for inference. Often, the analyses are too complex for closed-form solutions and Markov chain Monte Carlo (MCMC) sampling is used to draw inferences from posterior distributions. This chapter describes how these Bayesian multiple-regression analyses can be used for GWAS. In most GWAS, false positives are controlled by limiting the genome-wise error rate, which is the probability of one or more false-positive results, to a small value. As the number of test in GWAS is very large, this results in very low power. Here we show how in Bayesian GWAS false positives can be controlled by limiting the proportion of false-positive results among all positives to some small value. The advantage of this approach is that the power of detecting associations is not inversely related to the number of markers.
Kim, L U; Kim, J W; Kim, C K
2006-09-01
To prepare a dental composite that has a low amount of curing shrinkage and excellent mechanical strength, various 2,2-bis[4-(2-hydroxy-3-methacryloyloxy propoxy) phenyl] propane (Bis-GMA) derivatives were synthesized via molecular structure design, and afterward, properties of their mixtures were explored. Bis-GMA derivatives, which were obtained by substituting methyl groups for hydrogen on the phenyl ring in the Bis-GMA, exhibited lower curing shrinkage than Bis-GMA, whereas their viscosities were higher than that of Bis-GMA. Other Bis-GMA derivatives, which contained a glycidyl methacrylate as a molecular end group exhibited reduced curing shrinkage and viscosity. Methoxy substitution for hydroxyl groups on the Bis-GMA derivatives was performed for the further reduction of the viscosity and curing shrinkage. Various resin mixtures, which had the same viscosity as the commercial one, were prepared, and their curing shrinkage was examined. A resin mixture containing 2,2-bis[3,5-dimethyl, 4-(2-methoxy-3-methacryloyloxy propoxy) phenyl] propane] (TMBis-M-GMA) as a base resin and 4-tert-butylphenoxy-2-methyoxypropyl methacrylate (t-BP-M-GMA) as a diluent exhibited the lowest curing shrinkage among them. The composite prepared from this resin mixture also exhibited the lowest curing shrinkage along with enhanced mechanical properties.
International Nuclear Information System (INIS)
Briffaut, M.; Benboudjema, F.; Torrenti, J.M.; Nahas, G.
2011-01-01
In massive concrete structures, cracking may occur during hardening, especially if autogenous and thermal strains are restrained. The concrete permeability due to this cracking may rise significantly and thus increase leakage (in tank, nuclear containment...) and reduce the durability. The restrained shrinkage ring test is used to study the early age concrete behaviour (delayed strains evolution and cracking). This test shows, at 20 o C and without drying, for a concrete mix which is representative of a French nuclear power plant containment vessel (w/c ratio equal to 0.57), that the amplitude of autogenous shrinkage (about 40 μm/m for the studied concrete mix) is not high enough to cause cracking. Indeed, in this configuration, thermal shrinkage is not significant, whereas this is a major concern for massive structures. Therefore, an active test has been developed to study cracking due to restrained thermal shrinkage. This test is an evolution of the classical restrained shrinkage ring test. It allows to take into account both autogenous and thermal shrinkages. Its principle is to create the thermal strain effects by increasing the temperature of the brass ring (by a fluid circulation) in order to expand it. With this test, the early age cracking due to restrained shrinkage, the influence of reinforcement and construction joints have been experimentally studied. It shows that, as expected, reinforcement leads to an increase of the number of cracks but a decrease of crack widths. Moreover, cracking occurs preferentially at the construction joint.
Early age volume changes in concrete due to chemical shrinkage of cement paste
Directory of Open Access Journals (Sweden)
Ebensperger, L.
1991-12-01
Full Text Available Unrestrained early age volume changes due to chemical shrinkage in cement pastes, mortars and concretes have been determined. The measurements were performed on sealed and unsealed samples which were stored under water.
The chemical shrinkage of unsealed specimens represents the amount of absorbed water due to the chemical reaction of the cement It depends only on the cement content of the sample and does not lead to changes of the external dimensions. However the chemical shrinkage of sealed specimens is connected with a real volume change due to self-desiccation and the effect of internal pressures. The shrinkage depends in this case on the restraining effect of coarse aggregates as well as the cement content. The chemical shrinkage measured on sealed concretes was much higher than the one expected to ocurr on concretes, because normally an equalization of pressure takes place to some extent in the interior of the concrete.
The use of expansive additives showed that they may compensate the chemical shrinkage, but its dosage is very sensitive and should be defined exactly for each case particularly.
Se han determinado los cambios volumétricos que ocurren en pastas de cemento, morteros y hormigones a edad temprana debido al efecto de la retracción química. Las mediciones se realizaron en probetas selladas y no selladas sumergidas bajo agua.
La retracción química en probetas no selladas representa la cantidad de agua absorbida debido a la reacción química del cemento. Depende solamente del contenido de cemento de la probeta y no produce ningún cambio en las dimensiones de la probeta. Por el contrario, la retracción química en probetas selladas está relacionada con un cambio volumétrico real debido al efecto de la autodesecación y presiones internas. La retracción en este caso depende tanto de la restricción que imponen los áridos, como del contenido de cemento. La retracción química medida en hormigones sellados
Modified permeability modeling of coal incorporating sorption-induced matrix shrinkage
Soni, Aman
The variation in the cleat permeability of coalbed methane (CBM) reservoirs is attributed primarily to two cardinal processes, with opposing effects. Increase in effective stresses with reduction in pore pressure tends to decrease the cleat permeability, whereas the sorption-induced coal matrix shrinkage actuates reduction in the effective stresses which increases the reservoir permeability. The net effect of the two processes determines the pressure-dependent-permeability and, hence, the overall trend of CBM production with depletion. Several analytical models have been developed and used to predict the dynamic behavior of CBM reservoir permeability during production through pressure depletion, all based on combining the two effects. The purpose of this study was to introduce modifications to two most commonly used permeability models, namely the Palmer and Mansoori, and Shi and Durucan, for permeability variation and evaluate their performance when projecting gas production. The basis for the modification is the linear relationship between the volume of sorbed gas and the associated matrix shrinkage. Hence, the impact of matrix shrinkage is incorporated as a function of the amount of gas produced, or that remaining in coal, at any time during production. Since the exact production from a reservoir is known throughout its life, this significantly simplifies the process of permeability modeling. Furthermore, the modification is also expected to streamline the process of modeling by classifying the shrinkage parameters for coals of different regions, but with similar characteristics. A good analogy is the San Juan basin, where sorption characteristics of coal are so well understood and defined that operators no longer carry out laboratory sorption work. The goal is to achieve the same for incorporation of the matrix shrinkage behavior. Another modification is to incorporate the matrix, or grain, compressibility effect of coal as a correction factor in the Shi and
12th Brazilian Meeting on Bayesian Statistics
Louzada, Francisco; Rifo, Laura; Stern, Julio; Lauretto, Marcelo
2015-01-01
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesia...
Setting kinetics and shrinkage of self-adhesive resin cements depend on cure-mode and temperature.
Kitzmüller, Karin; Graf, Alexandra; Watts, David; Schedle, Andreas
2011-06-01
To investigate the influence of curing mode and temperature on the shrinkage kinetics of self-adhesive resin cements in comparison to a conventional multi-step resin cement. The shrinkage of self-adhesive resin cements Maxcem Elite (MX), Speedcem (SPC), Smartcem2 (SMC), iCem (IC) and RelyX Unicem (RX) and Nexus Third Generation (NX3) as a multi-step resin cement was measured continuously for 1h using the bonded disk method. All materials were tested with dual-curing (dc) and self-curing (sc) mode. All measurements (n=5 per group) were conducted at room temperature (23°C) as well as at body temperature (37°C). Shrinkage time constants were obtained from a simple exponential growth model. Data were statistically analyzed by ANOVA and the p-values were adjusted for multiplicity according to Hothorn et al. (2008) using the R-package "multcomp". Shrinkages ranged between 1.84 (RX sc23) and 7.09 (IC sc37). The curing-mode changing from sc to dc had the dominant effect for several materials, especially RX, both on final shrinkage and time constant for setting. Temperature increase had an effect on setting and shrinkage for all materials except RX. Final shrinkage for SPC, SMC and NX3 was statistically equivalent (p>0.05). The 3-fold variation in final shrinkage for these materials is significant for clinical material selection. Light curing can lead to a 10-fold increase in the rate of setting. A self-adhesive universal resin cement (RX) had the lowest shrinkage in the groups examined. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Kwag, Shinyoung [North Carolina State University, Raleigh, NC 27695 (United States); Korea Atomic Energy Research Institute, Daejeon 305-353 (Korea, Republic of); Gupta, Abhinav, E-mail: agupta1@ncsu.edu [North Carolina State University, Raleigh, NC 27695 (United States)
2017-04-15
Highlights: • This study presents the development of Bayesian framework for probabilistic risk assessment (PRA) of structural systems under multiple hazards. • The concepts of Bayesian network and Bayesian inference are combined by mapping the traditionally used fault trees into a Bayesian network. • The proposed mapping allows for consideration of dependencies as well as correlations between events. • Incorporation of Bayesian inference permits a novel way for exploration of a scenario that is likely to result in a system level “vulnerability.” - Abstract: Conventional probabilistic risk assessment (PRA) methodologies (USNRC, 1983; IAEA, 1992; EPRI, 1994; Ellingwood, 2001) conduct risk assessment for different external hazards by considering each hazard separately and independent of each other. The risk metric for a specific hazard is evaluated by a convolution of the fragility and the hazard curves. The fragility curve for basic event is obtained by using empirical, experimental, and/or numerical simulation data for a particular hazard. Treating each hazard as an independently can be inappropriate in some cases as certain hazards are statistically correlated or dependent. Examples of such correlated events include but are not limited to flooding induced fire, seismically induced internal or external flooding, or even seismically induced fire. In the current practice, system level risk and consequence sequences are typically calculated using logic trees to express the causative relationship between events. In this paper, we present the results from a study on multi-hazard risk assessment that is conducted using a Bayesian network (BN) with Bayesian inference. The framework can consider statistical dependencies among risks from multiple hazards, allows updating by considering the newly available data/information at any level, and provide a novel way to explore alternative failure scenarios that may exist due to vulnerabilities.
International Nuclear Information System (INIS)
Kwag, Shinyoung; Gupta, Abhinav
2017-01-01
Highlights: • This study presents the development of Bayesian framework for probabilistic risk assessment (PRA) of structural systems under multiple hazards. • The concepts of Bayesian network and Bayesian inference are combined by mapping the traditionally used fault trees into a Bayesian network. • The proposed mapping allows for consideration of dependencies as well as correlations between events. • Incorporation of Bayesian inference permits a novel way for exploration of a scenario that is likely to result in a system level “vulnerability.” - Abstract: Conventional probabilistic risk assessment (PRA) methodologies (USNRC, 1983; IAEA, 1992; EPRI, 1994; Ellingwood, 2001) conduct risk assessment for different external hazards by considering each hazard separately and independent of each other. The risk metric for a specific hazard is evaluated by a convolution of the fragility and the hazard curves. The fragility curve for basic event is obtained by using empirical, experimental, and/or numerical simulation data for a particular hazard. Treating each hazard as an independently can be inappropriate in some cases as certain hazards are statistically correlated or dependent. Examples of such correlated events include but are not limited to flooding induced fire, seismically induced internal or external flooding, or even seismically induced fire. In the current practice, system level risk and consequence sequences are typically calculated using logic trees to express the causative relationship between events. In this paper, we present the results from a study on multi-hazard risk assessment that is conducted using a Bayesian network (BN) with Bayesian inference. The framework can consider statistical dependencies among risks from multiple hazards, allows updating by considering the newly available data/information at any level, and provide a novel way to explore alternative failure scenarios that may exist due to vulnerabilities.
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...... and differentiating these circuits in time linear in their size. We report on experimental results showing the successful compilation, and efficient inference, on relational Bayesian networks whose {\\primula}--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Bayesian Posterior Distributions Without Markov Chains
Cole, Stephen R.; Chu, Haitao; Greenland, Sander; Hamra, Ghassan; Richardson, David B.
2012-01-01
Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976–1983) assessing the relation between residential ex...
Franco, Ana Paula G. O.; Karam, Leandro Z.; Galvão, José R.; Kalinowski, Hypolito J.
2015-09-01
The aim of the present study was evaluate the shrinkage polymerization and temperature of different acrylic resins used to splinting transfer copings in indirect impression technique. Two implants were placed in an artificial bone, with the two transfer copings joined with dental floss and acrylic resins; two dental resins are used. Measurements of deformation and temperature were performed with Fiber Braggs grating sensor for 17 minutes. The results revealed that one type of resin shows greater values of polymerization shrinkage than the other. Pattern resins did not present lower values of shrinkage, as usually reported by the manufacturer.
Mechanisms of activation of NHE by cell shrinkage and by calyculin A in Ehrlich ascites tumor cells
DEFF Research Database (Denmark)
Pedersen, Stine Helene Falsig; Varming, Camilla; Hoffmann, E K
2002-01-01
compartments. Osmotic cell shrinkage elicited a rapid intracellular alkalinization, the sensitivity of which to EIPA (IC50 0.19 microM) and HOE 642 (IC50 0.85 microM) indicated that it predominantly reflected activation of NHE1. NHE activation by osmotic shrinkage was inhibited by the protein kinase C......-inhibitable intracellular alkalinization, indicating NHE1 activation. Similarly, shrinkage-induced NHE activation was potentiated by calyculin A. The calyculin A-induced alkalinization was not associated with an increase in the free, intracellular calcium concentration, but was abolished by chelerythrine...
3rd Bayesian Young Statisticians Meeting
Lanzarone, Ettore; Villalobos, Isadora; Mattei, Alessandra
2017-01-01
This book is a selection of peer-reviewed contributions presented at the third Bayesian Young Statisticians Meeting, BAYSM 2016, Florence, Italy, June 19-21. The meeting provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and postdocs dealing with Bayesian statistics to connect with the Bayesian community at large, to exchange ideas, and to network with others working in the same field. The contributions develop and apply Bayesian methods in a variety of fields, ranging from the traditional (e.g., biostatistics and reliability) to the most innovative ones (e.g., big data and networks).
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learn....... An automated procedure for specifying prior distributions for the parameters in a dynamic Bayesian network is presented. It is a simple extension of the procedure for the ordinary Bayesian networks. Finally the W¨olfer?s sunspot numbers are analyzed....
Minimal volume regulation after shrinkage of red blood cells from five species of reptiles
DEFF Research Database (Denmark)
Kristensen, Karina; Berenbrink, Michael; Koldkjær, Pia
2008-01-01
Red blood cells (RBCs) from most vertebrates restore volume upon hypertonic shrinkage and the mechanisms underlying this regulatory volume increase (RVI) have been studied extensively in these cells. Despite the phylogenetically interesting position of reptiles, very little is known about their red......) or the Na+/K+/2Cl- co-transporter (NKCC) or insentive transporters. Deoxygenation of RBCs from A. mississippiensis and T. merianae did not significantly affect RVI upon shrinkage. Deoxygenation per se of red blood cells from T. merianae elicited a slow volume increase, but the mechanism...... was not characterized. It seems, therefore, that the RVI response based on NHE activation was lost among the early sauropsids that gave rise to modern reptiles and birds, while it was retained in mammals. An RVI response has then reappeared in birds, but based on activation of the NKCC. Alternatively, the absence...
Effectiveness of shrinkage-reducing admixtures on Portland pozzolan cement concrete
Directory of Open Access Journals (Sweden)
Videla, C.
2005-06-01
Full Text Available Drying shrinkage causes tensile stress in restrained concrete members. Since all structural elements are subject to some degree of restraint, drying shrinkage is regarded to be one of the main causes of concrete cracking. The purpose of the present study was to evaluate the effectiveness of SRA in reducing drying shrinkage strain in Portland pozzolan cement concrete. The major variables examined included slump, admixture type and dose, and specimen size. The measured results indicate that any of the admixtures used in the study significantly reduced shrinkage. Concrete manufactured with shrinkage reducing admixtures shrank an average of 43% less than concrete without admixtures. As a rule, the higher the dose of admixture, the higher was its shrinkage reduction performance. The experimental results were compared to the shrinkage strain estimated with the ACI 209, CEB MC 90, B3, GL 2000, Sakata 1993 and Sakata 2001 models. Although none of these models was observed to accurately describe the behaviour of Portland pozzolan cement concrete with shrinkage reducing admixtures, the Sakata 2001 model, with a weighted coefficient of variation of under 30%, may be regarded to be roughly adequate.
La retracción por secado es un fenómeno intrínseco del hormigón que produce tensiones de tracción en elementos restringidos de hormigón. Puesto que todos los elementos presentan algún grado de retracción, se considera a la retracción por secado como una de las principales causas de agrietamiento en proyectos de construcción en hormigón. Por lo tanto, el objetivo de esta investigación fue evaluar la efectividad de los aditivos reductores de retracción (SRA en hormigones fabricados con cemento Portland puzolánico. Las variables principales estudiadas incluyen el asentamiento de cono de Abrams, marca y dosis de aditivo reductor de retracción, y tamaño de espécimen de hormigón. Los resultados obtenidos permiten concluir que el uso de
Preparation and properties of shrinkage-free ZrSiO4-ceramics
International Nuclear Information System (INIS)
Hennige, V.D.; Ritzhaupt-Kleissl, H.-J.; Hausselt, J.H.
1998-01-01
Ceramics of the ZrSiO 4 -type, which show no shrinkage during the sintering process can be produced using a reaction bonding process. This process is based on the compensation of the sinter shrinkage by a volume expanding reaction of one of the starting components during the thermal treatment. By this method, net shape ceramics with high precision can be produced. The resulting ceramic parts show very high density and good mechanical properties. Therefore, this processing route has a high potential with respect of production of ceramic microcomponents especially in the field of microsystem technology. A further promising field of application is dentistry. Exactly fitting all-ceramic bridges, crowns and inlays can be manufactured. (orig.)
Cell Shrinkage is Essential in Lysophosphatidic Acid Signaling in Ehrlich Ascites
DEFF Research Database (Denmark)
Pedersen, Susanne; Hoffmann, Else Kay; Hougaard, Charlotte
2000-01-01
The present study aimed at elucidating the initial intracellular lysophosphatidic acid (LPA)-induced signaling events, in order to investigate the sequence in which LPA affects the intracellular concentration of free, cytosolic Ca(2+), [Ca(2+)](i), ion channels, the F-actin cytoskeleton, cell...... volume and the Na(+)/H(+) exchanger. We found that stimulation of Ehrlich cells with LPA induced a transient, concentration-dependent increase in [Ca(2+)](i), which is due to Ca(2+) release from intracellular Ins(1,4,5)P(3)-sensitive stores as well as an influx of Ca(2+). The EC(50) values for LPA......; (ii) a subsequent cell shrinkage and increased polymerization of F-actin, and (iii) activation of a Na(+)/H(+) exchange, resulting in a concentration-dependent intracellular alkalinization. The EC(50) value for the LPA-induced rate of alkalinization was estimated at 0. 37 nm LPA. When cell shrinkage...
Durability of a low shrinkage TEGDMA/HEMA-free resin composite system in Class II restorations
DEFF Research Database (Denmark)
van Dijken, Jan WV; Pallesen, Ulla
2017-01-01
Objective: The objective of this randomized controlled prospective trial was to evaluate the durability of a low shrinkage and TEGDMA/HEMA-free resin composite system in posterior restorations in a 6-year follow up. Material and methods: 139 Class II restorations were placed in 67 patients...... with a mean age of 53 years (range 29-82). Each participant received at random two, as similar as possible, Class II restorations. In the first cavity of each pair the TEGDMA/HEMA-free resin composite system was placed with its 3-step etch-and-rinse adhesive (cmf-els). In the second cavity a 1-step HEMA...... for failure were fracture followed by recurrent caries. Most fractures and all caries lesions were found in high risk participants. Significance: The tested Class II resin composite restorations performed with the new TEGDMA/HEMA-free low shrinkage resin composite system showed good durability over six years....
Experimental Study of ABS Material Shrinkage and Deformation Based on Fused Deposition Modeling
Directory of Open Access Journals (Sweden)
Xu Yaodong
2016-01-01
Full Text Available The CAD model can be directly converted into physical model by rapid prototyping , which provides more convenient means for concurrent design in physical verification. However, the deformation of the material shrinkage can cause large deviation of the molding size in CAD model transforming to physical model. In order to ensure the reasonable assembly of the rapid prototyping part, the forming experiment of ABS material was carried out by the principle of FDM. Through regression analysis, a linear relationship with the molding shrinkage and model size was found Meanwhile, deforming mechanism of prototyping parts was analyzed. The rationality of assembly and quality of print parts can be ensured by these law of pre-process.
The effect of using hybrid nanomaterials on drying shrinkage and strength of cement pastes
Directory of Open Access Journals (Sweden)
Saaid I. Zaki
2016-04-01
Full Text Available The aim of this work is to study the effect of nanomaterials on the properties of cement paste, the experimental program included three parts: a- two types of nanosilica, locally produced NS1 and imported NS2, b- nanoclay (NC and c- Hybrid nanoparticles (NS1 & NC. In each part, cement paste was used with different percentages of nanoparticles. Compressive strength and drying shrinkage tests were applied in each part on the cured and uncured samples. The results showed that the compressive strength improved in the cement paste mixtures in the cured condition, the optimum percentages was 1% for NS1, 1% for NS2, 5% for NC, and 5% (0.5%NS1 & 4.5%NC for hybrid nanoparticles. The drying shrinkage increases with adding nanosilica and hybrid nanoparticles, while it decreases when adding NC.
International Nuclear Information System (INIS)
Sant, Gaurav; Lothenbach, Barbara; Juilland, Patrick; Le Saout, Gwenn; Weiss, Jason; Scrivener, Karen
2011-01-01
Studies on the early-age shrinkage behavior of cement pastes, mortars, and concretes containing shrinkage reducing admixtures (SRAs) have indicated these mixtures frequently exhibit an expansion shortly after setting. While the magnitude of the expansion has been noted to be a function of the chemistry of the cement and the admixture dosage; the cause of the expansion is not clearly understood. This investigation uses measurements of autogenous deformation, X-ray diffraction, pore solution analysis, thermogravimetry, and scanning electron microscopy to study the early-age properties and describe the mechanism of the expansion in OPC pastes made with and without SRA. The composition of the pore solution indicates that the presence of the SRA increases the portlandite oversaturation level in solution which can result in higher crystallization stresses which could lead to an expansion. This observation is supported by deformation calculations for the systems examined.
Early age shrinkage pattern of concrete on replacement of fine aggregate with industrial by-product
Directory of Open Access Journals (Sweden)
R.K. Mishra
2016-10-01
Full Text Available This is an experimental work carried out to investigate early age shrinkage pattern of concrete, prepared, on 50% replacement of industrial by-product (like pond ash and granulated blast furnace slag as fine aggregate using OPC, PPC and PSC as a binder. This is to observe the effect of pond ash and slag as they are having some cementitious properties and effect of cement type is also discussed. All the mixes were prepared keeping in view of pumpable concrete without any super plasticizers. Higher shrinkage value indicates the presence of more bleed water or internal moisture. It is concluded that slag is the best option for fine aggregate replacement for concrete making and durable structure.
A moment projection method for population balance dynamics with a shrinkage term
Energy Technology Data Exchange (ETDEWEB)
Wu, Shaohua [Department of Mechanical Engineering, National University of Singapore, Engineering Block EA, Engineering Drive 1, 117576 (Singapore); Yapp, Edward K.Y.; Akroyd, Jethro; Mosbach, Sebastian [Department of Chemical Engineering and Biotechnology, University of Cambridge, New Museums Site, Pembroke Street, Cambridge, CB2 3RA (United Kingdom); Xu, Rong [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459 (Singapore); Yang, Wenming [Department of Mechanical Engineering, National University of Singapore, Engineering Block EA, Engineering Drive 1, 117576 (Singapore); Kraft, Markus, E-mail: mk306@cam.ac.uk [Department of Chemical Engineering and Biotechnology, University of Cambridge, New Museums Site, Pembroke Street, Cambridge, CB2 3RA (United Kingdom); School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459 (Singapore)
2017-02-01
A new method of moments for solving the population balance equation is developed and presented. The moment projection method (MPM) is numerically simple and easy to implement and attempts to address the challenge of particle shrinkage due to processes such as oxidation, evaporation or dissolution. It directly solves the moment transport equation for the moments and tracks the number of the smallest particles using the algorithm by Blumstein and Wheeler (1973) . The performance of the new method is measured against the method of moments (MOM) and the hybrid method of moments (HMOM). The results suggest that MPM performs much better than MOM and HMOM where shrinkage is dominant. The new method predicts mean quantities which are almost as accurate as a high-precision stochastic method calculated using the established direct simulation algorithm (DSA).
Experimental Study of ABS Material Shrinkage and Deformation Based on Fused Deposition Modeling
Xu Yaodong
2016-01-01
The CAD model can be directly converted into physical model by rapid prototyping , which provides more convenient means for concurrent design in physical verification. However, the deformation of the material shrinkage can cause large deviation of the molding size in CAD model transforming to physical model. In order to ensure the reasonable assembly of the rapid prototyping part, the forming experiment of ABS material was carried out by the principle of FDM. Through regression analysis, a li...
Method for determining the formation of shrinkage defects in the castings
R. Dyja; N. Sczygiol
2011-01-01
Simple simulations of solidification of metals and alloys generally provide results for determining the temperature distribut ion in a given time or solidification time for the specific locations of the casting. These data allow to unambiguously determine the position of thermal centers. However, knowledge about the location of thermal centers is not synonymous with the information about the location of any shrinkage defects in the casting, because the physical behaviour of molten metal shoul...
Effects of moisture migration on shrinkage, pore pressure and other concrete properties
International Nuclear Information System (INIS)
Chapman, D.A.; England, G.L.
1977-01-01
This work investigates the uniaxial migration of moisture in long, upright, limestone concrete cylinders, sealed at the base and sides, and open at the top. The design represents a section through a concrete pressure vessel wall. The cylinders are subjected to a sustained temperature difference between their ends, with maximum temperatures between 105 0 C and 200 0 C. Readings of pore pressure, water content and temperature are taken at various positions along the axis of the cylinders. In one cylinder transverse and longitudinal shrinkage readings are also recorded. The results for the cylinders show that moisture migration is away from the hot face of the specimens, causing reduction in both pore pressure and water content values in this region. The moisture migration creates a drying front which moves slowly up the specimens. Evaporation drying takes place from the unsealed end of the specimen. A drying front moves into the concrete and considerable weight loss is recorded as moisture escapes to the atmosphere. The rate of movement of the drying front is slower than that of the hot front and is proportional to the temperature difference between the top of the specimen and the surrounding atmosphere. In the shrinkage specimen, values of transverse and longitudinal shrinkage reflect the water content results. The specimen indicates that shrinkage occurs in a concrete pressure vessel, in the regions where moisture is lost. The restraint of the mass of concrete surrounding these regions sets up a three dimensional state of internal tensile stress. The areas into which the moisture migrates tend to swell, creating an internal stress situation, which is this
Controlled shrinkage and re-expansion of a single aqueous droplet inside an optical vortex trap.
Jeffries, Gavin D M; Kuo, Jason S; Chiu, Daniel T
2007-03-22
This paper describes the shrinkage and re-expansion of individual femtoliter-volume aqueous droplets that were suspended in an organic medium and held in an optical vortex trap. To elucidate the mechanism behind this phenomenon, we constructed a heat- and mass-transfer model and carried out experimental verifications of our model. From these studies, we conclude that an evaporation mechanism sufficiently describes the shrinkage of aqueous droplets held in a vortex trap, whereas a mechanism based on the supersaturation of the organic phase by water that surrounds the droplet adequately explains the re-expansion of the shrunk droplet. The proposed mechanisms correlated well with experimental observations using different organic media, when H2O was replaced with D2O and when an optical tweezer was used to induce droplet shrinkage rather than an optical vortex trap. For H2O droplets, the temperature rise within the droplet during shrinkage was on the order of 1 K or less, owing to the rapid thermal conduction of heat away from the droplet at the microscale and the sharp increase in solubility for water by the organic phase with slight elevations in temperature. Because most chemical species confined to droplets can be made impenetrable to the aqueous/organic interface, a change in the volume of aqueous droplets translates into a change in concentration of the dissolved species within the droplets. Therefore, this phenomenon should find use in the study of fundamental chemical processes that are sensitive to concentration, such as macromolecular crowding and protein nucleation and crystallization.
Bortolotto, Tissiana; Prando, Federico; Dietschi, Didier; Krejci, Ivo
2014-07-01
The aim of the study was to evaluate the marginal adaptation and shrinkage stress development of a micro hybrid restorative composite as a function of energy density. Linear displacement and shrinkage forces were measured with custom-made devices for energies of 4,000, 8,000, 16,000 and 32,000 mJ/cm(2) at a constant power density of 800 mW/cm(2). Marginal adaptation of composite restorations cured with the same energy density was evaluated before and after mechanical loading with 300,000 cycles at 70 N. The group "4,000 mJ/cm(2)" showed the lowest shrinkage force [2.9(0.2) kg] and linear displacement [23.5(0.7) μm] but led to the worst marginal adaptation after loading [46.4(23.5) %CM] probably due to under-curing. When the maximum energy of 32,000 mJ/cm(2) was applied, a slight increase in shrinkage forces [3.6(0.2) kg and 29.2(0.8) μm], and a slight decrease in marginal adaptation after loading [75.4(11.5) %CM] were observed, but these changes were not significantly different in comparison to groups cured with energies of 8,000 and 16,000 mJ/cm(2). For the resin composite tested in this study, no differences in marginal adaptation could be detected above the energy threshold of 8,000 mJ/cm(2).
Influence of paste volume on shrinkage cracking and fracture properties of self-compacting concrete
Rozière, Emmanuel; Granger, Sébastien; Turcry, Philippe; Loukili, Ahmed
2007-01-01
International audience; Self-compacting concrete (SCC) mixtures are usually designed with higher volumes of paste than vibrated concrete mixtures. The results reported in this paper come from a study of nine SCC concrete mixtures. Volume of paste was varied between 291 and 457 l/m3. One of the mixtures had already been used in a large scale test, and the others were designed by varying several parameters of the reference concrete mixture. Mechanical properties, shrinkage, fracture parameters ...
Drying Shrinkage Characteristics of Concrete Reinforced With Oil Palm Trunk Fiber
Zakiah Ahmad; Azmi Ibrahim,; Paridah MD Tahir
2010-01-01
Concrete is subject to some form of restraint, such as steel reinforcement, forms or adjacent members. As concrete begins to lose volume, the restraint inhibits movement, which then induces tensile stress in the concrete. Once the tensile capacity of the concrete has been exceeded, it will crack. Therefore this paper reports on a study of shrinkage of plain and concrete reinforced with bio-waste fiber namely oil palm trunk fiber (OPTF). Metallic rings are the most widely used devices to test ...
Cigarette filter material and polypropylene fibres in concrete to control drying shrinkage
Richardson, Alan
2012-01-01
Due to a reduction in demand for cigarette filter material (North East UK), significant quantities have arisen that have little commercial value. The filter manufacturers have been looking for another outlet for their product and polypropylene fibre replacement in concrete was considered. The purpose of adding Type 1 polypropylene fibres (BS-EN14889) to concrete is to control plastic shrinkage and reduce bleeding. A paired comparison test was carried out to examine concrete cured under extrem...
The shrinkage behavior and surface topographical investigation for micro metal injection molding
Islam, A.; Giannekas, N.; Marhöfer, D. M.; Tosello, G.; Hansen, H. N.
2015-05-01
Metal injection molding (MIM) is a near net shape manufacturing technology that can produce highly complex and dimensionally stable parts for high end engineering applications. Despite the recent growth and industrial interest, micro metal molding is yet to be the field of extensive research especially when it is compared with micro molding of thermoplastics. The current paper presents a thorough investigation on the process of metal injection molding where it systematically characterizes the effects of important process conditions on the shrinkage and surface quality of molded parts with micro features. Effects of geometrical factors like feature dimensions and distance from the gate on the replication quality are studied. The influence of process conditions on the achievable roughness for the final metal parts is discussed based on the experimental findings. The test geometry is characterized by 2½D surface structures containing thin ribs of different aspect ratios and thicknesses in the sub-mm dimensional range. The test parts were molded from Catamold 316L with a conventional injection molding machine. Afterwards, the parts were de-binded and sintered to produce the final test samples. Among the different process parameters studied, the melt temperature was the most influential parameters for better replication and dimensional stability of the final part. The results presented in the paper clearly show that the shrinkage in metal part is not uniform in the micro scale. It depends on the feature dimensions and also on the process conditions. A thin section of the part exhibits higher relative shrinkage compared with a thicker section. Based on these findings, it can be concluded that a micro part molded by MIM process will have higher relative shrinkage compared to a macro part made with the same process.
International Nuclear Information System (INIS)
Fan Changjun
2012-01-01
Pillarless sublevel caving mining method was used to mining ores in a uranium mine. Because ore-rock interface changed greatly, this part of ores can not be recovered effectively in the mining process, resulting in the permanent loss of these ores. Aimed at the problem, a combined shrinkage stoping and pillarless sublevel caving mining method is presented. Practices show that the ore recovery is increased, dilution rate is declined, and mining safety is improved greatly by using the combined method. (authors)
Large-proportional shrunken bio-replication of shark skin based on UV-curing shrinkage
Chen, Huawei; Che, Da; Zhang, Xin; Yue, Yue; Zhang, Deyuan
2015-01-01
The shark skin effect has attracted worldwide attention because of its superior drag reduction. As the product of natural selection, the maximum drag reduction of shark skin is found in its normal living environment. Large-proportional shrinkage of shark skin morphology is greatly anticipated for its adaptation to faster fluid flow. One novel approach, large-proportional shrunken bio-replication, is proposed as a method to adjust the optimal drag reduction region of shark skin based on the shrinkage of UV-cured material. The shark skin is taken as a replica template to allow large-proportional shrinking in the drag reduction morphology by taking advantage of the shrinkage of UV-curable material. The accuracy of the large-proportional shrunken bio-replication approach is verified by a comparison between original and shrunken bio-replicated shark skin, which shows that the shrinking ratio can reach 23% and the bio-replication accuracy is higher than 95%. In addition, the translation of the optimum drag reduction peak of natural surface function to various applications and environments is proved by drag reduction experiments.
Large-proportional shrunken bio-replication of shark skin based on UV-curing shrinkage
International Nuclear Information System (INIS)
Chen, Huawei; Che, Da; Zhang, Xin; Yue, Yue; Zhang, Deyuan
2015-01-01
The shark skin effect has attracted worldwide attention because of its superior drag reduction. As the product of natural selection, the maximum drag reduction of shark skin is found in its normal living environment. Large-proportional shrinkage of shark skin morphology is greatly anticipated for its adaptation to faster fluid flow. One novel approach, large-proportional shrunken bio-replication, is proposed as a method to adjust the optimal drag reduction region of shark skin based on the shrinkage of UV-cured material. The shark skin is taken as a replica template to allow large-proportional shrinking in the drag reduction morphology by taking advantage of the shrinkage of UV-curable material. The accuracy of the large-proportional shrunken bio-replication approach is verified by a comparison between original and shrunken bio-replicated shark skin, which shows that the shrinking ratio can reach 23% and the bio-replication accuracy is higher than 95%. In addition, the translation of the optimum drag reduction peak of natural surface function to various applications and environments is proved by drag reduction experiments. (technical note)
International Nuclear Information System (INIS)
Lassabatere, Thierry
1994-01-01
The target of this research is to set up a unified and coherent working frame based upon the rigorous principles of thermodynamics and making it possible to model a large class of physical phenomena acting in unsaturated porous media, as well as the related interactions with the mechanical state of the structures. This class corresponds to reactive phenomena among which one finds the phase change (desiccation) for which the whole of its subsequent actions (creep but essentially shrinkage) is modelled and which will be treated as a specific application example. The first chapter recalls the bases of the adopted description of the porous medium as well as the global thermodynamical frame which underlays the whole modelling. Chapter II deals with the mainly new formulation and the identification of a non linear elastic constitutive law of the medium involved. Various reflexion elements related to the microscopic behaviours of the components and to experiments have orientated the model towards some more limitative hypotheses making it possible to have a complete and explicit determination of a law for the macroscopic behaviour. Chapter IV and V are examples of application: chapter IV studies the problem of shrinkage and creep in a coupled linear elastic behaviour. Chapter V is limited to the case of shrinkage treated by a numerical application of the whole non-linear elastic model. The results obtained are in good agreement with the corresponding experiments. (author) [fr
Shrinkage of the Toona ciliata wood from three counties in the south of Minas Gerais state
Directory of Open Access Journals (Sweden)
Alessandra de Oliveira Ribeiro
2014-09-01
Full Text Available The study aimed to evaluate the shrinkage, in the bottom-up and pith-bark direction, of the australian cedar wood from three Counties in the south of Minas Gerais state, and also to check the variation in chemical composition of wood due the location of planting. The australian cedar wood was obtained with four years of age and in three cities in the south of Minas Gerais state (Campo Belo, Cana Verde and Santo Antonio do Amparo. The chemical constituents of wood, shrinkage values (tangential, radial, longitudinal and volumetric and the anisotropy coefficient. According to the results, there was no significant variation in the levels of holocellulose were determined, lignin, extractives and ashes between the three plantation sites evaluated. For the shrinkage of the wood in the bottom-up direction, there was no significant variation of the radial and longitudinal contractions for the three locations evaluated. However, significant variation was observed for the tangential and volumetric contractions for cities of Campo Belo and Cana Verde, and significant variation of Tangential contraction for the plantation of Santo Antonio do Amparo. In the pith-bark direction, significant variation was observed only on the radial contraction and the coefficient of anisotropy for location of Cana Verde.
Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection
Karjanto, Suryaefiza; Ramli, Norazan Mohamed; Ghani, Nor Azura Md; Aripin, Rasimah; Yusop, Noorezatty Mohd
2015-02-01
Microarray involves of placing an orderly arrangement of thousands of gene sequences in a grid on a suitable surface. The technology has made a novelty discovery since its development and obtained an increasing attention among researchers. The widespread of microarray technology is largely due to its ability to perform simultaneous analysis of thousands of genes in a massively parallel manner in one experiment. Hence, it provides valuable knowledge on gene interaction and function. The microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints. Therefore, the sample covariance matrix in Hotelling's T2 statistic is not positive definite and become singular, thus it cannot be inverted. In this research, the Hotelling's T2 statistic is combined with a shrinkage approach as an alternative estimation to estimate the covariance matrix to detect significant gene sets. The use of shrinkage covariance matrix overcomes the singularity problem by converting an unbiased to an improved biased estimator of covariance matrix. Robust trimmed mean is integrated into the shrinkage matrix to reduce the influence of outliers and consequently increases its efficiency. The performance of the proposed method is measured using several simulation designs. The results are expected to outperform existing techniques in many tested conditions.
Using four-phase Eulerian volume averaging approach to model macrosegregation and shrinkage cavity
Wu, M.; Kharicha, A.; Ludwig, A.
2015-06-01
This work is to extend a previous 3-phase mixed columnar-equiaxed solidification model to treat the formation of shrinkage cavity by including an additional phase. In the previous model the mixed columnar and equiaxed solidification with consideration of multiphase transport phenomena (mass, momentum, species and enthalpy) is proposed to calculate the as- cast structure including columnar-to-equiaxed transition (CET) and formation of macrosegregation. In order to incorporate the formation of shrinkage cavity, an additional phase, i.e. gas phase or covering liquid slag phase, must be considered in addition to the previously introduced 3 phases (parent melt, solidifying columnar dendrite trunks and equiaxed grains). No mass and species transfer between the new and other 3 phases is necessary, but the treatment of the momentum and energy exchanges between them is crucially important for the formation of free surface and shrinkage cavity, which in turn influences the flow field and formation of segregation. A steel ingot is preliminarily calculated to exam the functionalities of the model.
Calabrese, Barbara; Saffin, Jean-Michel; Halpain, Shelley
2014-01-01
A current model posits that cofilin-dependent actin severing negatively impacts dendritic spine volume. Studies suggested that increased cofilin activity underlies activity-dependent spine shrinkage, and that reduced cofilin activity induces activity-dependent spine growth. We suggest instead that both types of structural plasticity correlate with decreased cofilin activity. However, the mechanism of inhibition determines the outcome for spine morphology. RNAi in rat hippocampal cultures demonstrates that cofilin is essential for normal spine maintenance. Cofilin-F-actin binding and filament barbed-end production decrease during the early phase of activity-dependent spine shrinkage; cofilin concentration also decreases. Inhibition of the cathepsin B/L family of proteases prevents both cofilin loss and spine shrinkage. Conversely, during activity-dependent spine growth, LIM kinase stimulates cofilin phosphorylation, which activates phospholipase D-1 to promote actin polymerization. These results implicate novel molecular mechanisms and prompt a revision of the current model for how cofilin functions in activity-dependent structural plasticity. PMID:24740405
Directory of Open Access Journals (Sweden)
Gabriela Queiroz de Melo Monteiro
2010-03-01
Full Text Available Linear polymerization shrinkage (LPS, flexural strength (FS and modulus of elasticity (ME of 7 dental composites (Filtek Z350™, Filtek Z250™/3M ESPE; Grandio™, Polofil Supra™/VOCO; TPH Spectrum™, TPH3™, Esthet-X™/Denstply were measured. For the measurement of LPS, composites were applied to a cylindrical metallic mold and polymerized (n = 8. The gap formed at the resin/mold interface was observed using scanning electron microscopy (1500×. For FS and ME, specimens were prepared according to the ISO 4049 specifications (n = 10. Statistical analysis of the data was performed with one-way ANOVA and the Tukey test. TPH Spectrum presented significantly higher LPS values (29.45 µm. Grandio had significantly higher mean values for FS (141.07 MPa and ME (13.91 GPa. The relationship between modulus of elasticity and polymerization shrinkage is the main challenge for maintenance of the adhesive interface, thus composites presenting high shrinkage values, associated with a high modulus of elasticity tend to disrupt the adhesive interface under polymerization.
Development of shrinkage and fracture parameters in selected fine-grained cement-based composites
Directory of Open Access Journals (Sweden)
Kucharczyková Barbara
2017-01-01
Full Text Available The paper summarizes results of a pilot study aimed at the evaluation of an experimental investigation focused on determination of the material characteristics development of selected fine-grained cement-based composites during their ageing. The composition of composites being investigated differed only in a water to cement (w/c ratio and in amount of superplasticizer. Quite extensive experiments were performed with the aim to determine shrinkage, dynamic a static modulus of elasticity and fracture properties on test specimens exposed to free drying during the whole time of its ageing (including the early stage of setting and hardening. The article presents especially results (including their statistical evaluation of shrinkage and fracture parameters development within 90 days of composites’ ageing. Experimental results show the dependence of the investigated characteristics on the value of w/c ratio. The most visible effect was observed in the case of shrinkage development. The curing conditions were reflected especially in high variability of the test results.
Kim, Tae-Wan; Lee, Jang-Hoon; Jeong, Seung-Hwa; Ko, Ching-Chang; Kim, Hyung-Il; Kwon, Yong Hoon
2015-04-01
The purpose of the present study was to investigate the usefulness of 457 and 473 nm lasers for the curing of composite resins during the restoration of damaged tooth cavity. Monochromaticity and coherence are attractive features of laser compared with most other light sources. Better polymerization of composite resins can be expected. Eight composite resins were light cured using these two lasers and a light-emitting diode (LED) light-curing unit (LCU). To evaluate the degrees of polymerization achieved, polymerization shrinkage and flexural and compressive properties were measured and compared. Polymerization shrinkage values by 457 and 473 nm laser, and LED ranged from 10.9 to 26.8, from 13.2 to 26.1, and from 11.5 to 26.3 μm, respectively. The values by 457 nm laser was significantly different from those by 473 and LED LCU (p0.05). For the tested LCUs, no specific LCU could consistently achieve highest strength and modulus from the specimens tested. Two lasers (457 and 473 nm) can polymerize composite resins to the level that LED LCU can achieve despite inconsistent trends of polymerization shrinkage and flexural and compressive properties of the tested specimens.
Low shrinkage composite resins: influence on sealing ability in unfavorable C-factor cavities
Directory of Open Access Journals (Sweden)
Eliza Burlamaqui Klautau
2011-02-01
Full Text Available The present investigation observed the sealing ability of low shrinkage composite resins in large and deep cavities, placed and photocured in one increment. Large, deep cavities (5.0 mm diameter and 2.5 mm deep surrounded by enamel were prepared in bovine teeth, which were then divided into five groups. Groups 1, 2, 3 and 4: acid conditioning + Adper Single Bond (3M/ESPE, St Paul, MN, USA and restoration with Aelite LS Posterior (BISCO Inc. Schaumburg, IL, USA (G1; Filtek Z-350 (3M/ESPE,St Paul, MN, USA (G2; Filtek Z-350 Flow (3M/ESPE, St Paul, MN, USA (G3; Premisa (KERR Corporation, Orange, CA, USA (G4. Group 5: Silorane Adhesive system (3M/ESPE, St Paul, MN, USA + restoration with Filtek Low Shrinkage Posterior P90 (3M/ESPE, St Paul, MN, USA. After polymerization, the teeth were immersed in 0.5% basic fuchsine solution and immediately washed. Using the Imagetool Software, the extent of dye along the margins was calculated as a percentage of total perimeter. The restorations were then transversally sectioned and the depth of dye penetration was calculated in mm, using the same software. Kruskal-Wallis analysis for all groups showed no statistical differences for extent (p = 0.54 or depth (p = 0.8364 of dye penetration. According to this methodology, the so-called low shrinkage composite resins had the same sealing ability compared to regular and flowable nanocomposite materials.
Tang, S. Y.; Lee, J. S.; Loh, S. P.; Tham, H. J.
2017-06-01
The objectives of this study were to use Artificial Neural Network (ANN) to predict colour change, shrinkage and texture of osmotically dehydrated pumpkin slices. The effects of process variables such as concentration of osmotic solution, immersion temperature and immersion time on the above mentioned physical properties were studied. The colour of the samples was measured using a colorimeter and the net colour difference changes, ΔE were determined. The texture was measured in terms of hardness by using a Texture Analyzer. As for the shrinkage, displacement of volume method was applied and percentage of shrinkage was obtained in terms of volume changes. A feed-forward backpropagation network with sigmoidal function was developed and best network configuration was chosen based on the highest correlation coefficients between the experimental values versus predicted values. As a comparison, Response Surface Methodology (RSM) statistical analysis was also employed. The performances of both RSM and ANN modelling were evaluated based on absolute average deviation (AAD), correlation of determination (R2) and root mean square error (RMSE). The results showed that ANN has higher prediction capability as compared to RSM. The relative importance of the variables on the physical properties were also determined by using connection weight approach in ANN. It was found that solution concentration showed the highest influence on all three physical properties.
Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data
Dong, Kai
2015-09-16
DNA sequencing techniques bring novel tools and also statistical challenges to genetic research. In addition to detecting differentially expressed genes, testing the significance of gene sets or pathway analysis has been recognized as an equally important problem. Owing to the “large pp small nn” paradigm, the traditional Hotelling’s T2T2 test suffers from the singularity problem and therefore is not valid in this setting. In this paper, we propose a shrinkage-based diagonal Hotelling’s test for both one-sample and two-sample cases. We also suggest several different ways to derive the approximate null distribution under different scenarios of pp and nn for our proposed shrinkage-based test. Simulation studies show that the proposed method performs comparably to existing competitors when nn is moderate or large, but it is better when nn is small. In addition, we analyze four gene expression data sets and they demonstrate the advantage of our proposed shrinkage-based diagonal Hotelling’s test.
The Comfort Properties of Two Differential-Shrinkage Polyester Warp Knitted Fabrics
Directory of Open Access Journals (Sweden)
Chen Qing
2016-06-01
Full Text Available Single-layered warp knitted fabrics were produced by the 60D/36F (containing 36 filaments polyester yarn with differential shrinkage (DS property in this study. Due to the differential shrinkage property, the fabric becomes curly and bulkier, simulating cotton fabric in terms of its appearance and fabric handle. The performance and appearance of these DS polyester warp knitted fabrics were evaluated objectively and subjectively. The testing results demonstrated that the DS polyester warp knitted fabric had better abrasion property, worse pilling resistance due to the mechanical property of polyester yarn when compared with 100% cotton warp knitted fabric. Meanwhile, lower water vapour permeability and air resistance were found for DS polyester warp knitted fabric resulting from the dense structure of yarn shrinkage after heat-moisture treatment. Besides, the fabric handle was evaluated by Kawabata evaluation system and subject to trial under dry and wet fabric condition. DS polyester warp knitted fabrics provide better recovery under low stress mechanical pressure. The subjective evaluation result shows that the warp knitted fabrics made of DS polyester had similar handle against cotton warp knitted fabric in terms of prickle, smooth, comfort and dry feeling in both dry and wet testing conditions.
Influence of Aggregate Wettability with Different Lithology Aggregates on Concrete Drying Shrinkage
Directory of Open Access Journals (Sweden)
Yuanchen Guo
2015-01-01
Full Text Available The correlation of the wettability of different lithology aggregates and the drying shrinkage of concrete materials is studied, and some influential factors such as wettability and wetting angle are analyzed. A mercury porosimeter is used to measure the porosities of different lithology aggregates accurately, and the pore size ranges that significantly affect the drying shrinkage of different lithology aggregate concretes are confirmed. The pore distribution curve of the different coarse aggregates is also measured through a statistical method, and the contact angle of different coarse aggregates and concrete is calculated according to the linear fitting relationship. Research shows that concrete strength is determined by aggregate strength. Aggregate wettability is not directly correlated with concrete strength, but wettability significantly affects concrete drying shrinkage. In all types’ pores, the greatest impacts on wettability are capillary pores and gel pores, especially for the pores of the size locating 2.5–50 nm and 50–100 nm two ranges.
Bayesian flood forecasting methods: A review
Han, Shasha; Coulibaly, Paulin
2017-08-01
Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
, and include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...... settings, where cues shape expectations about a small number of upcoming stimuli and thus convey "prior" information about clearly defined objects. While operationally consistent with the experiments it seeks to describe, this view of attention as prior seems to miss many essential elements of both its...
Directory of Open Access Journals (Sweden)
Hamid Kermanshah
2016-01-01
Conclusion: Silorane did not provide better marginal seal than the low shrinkage methacrylate-based composites (except Aelite. In addition, cyclic loading did not affect the marginal microleakage of evaluated composite restorations .
Bonfatti, V; Tiezzi, F; Miglior, F; Carnier, P
2017-09-01
The objective of this study was to compare the prediction accuracy of 92 infrared prediction equations obtained by different statistical approaches. The predicted traits included fatty acid composition (n = 1,040); detailed protein composition (n = 1,137); lactoferrin (n = 558); pH and coagulation properties (n = 1,296); curd yield and composition obtained by a micro-cheese making procedure (n = 1,177); and Ca, P, Mg, and K contents (n = 689). The statistical methods used to develop the prediction equations were partial least squares regression (PLSR), Bayesian ridge regression, Bayes A, Bayes B, Bayes C, and Bayesian least absolute shrinkage and selection operator. Model performances were assessed, for each trait and model, in training and validation sets over 10 replicates. In validation sets, Bayesian regression models performed significantly better than PLSR for the prediction of 33 out of 92 traits, especially fatty acids, whereas they yielded a significantly lower prediction accuracy than PLSR in the prediction of 8 traits: the percentage of C18:1n-7 trans-9 in fat; the content of unglycosylated κ-casein and its percentage in protein; the content of α-lactalbumin; the percentage of α S2 -casein in protein; and the contents of Ca, P, and Mg. Even though Bayesian methods produced a significant enhancement of model accuracy in many traits compared with PLSR, most variations in the coefficient of determination in validation sets were smaller than 1 percentage point. Over traits, the highest predictive ability was obtained by Bayes C even though most of the significant differences in accuracy between Bayesian regression models were negligible. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Shrinkage stress kinetics of Bulk Fill resin-based composites at tooth temperature and long time.
Kalliecharan, David; Germscheid, William; Price, Richard B; Stansbury, Jeffrey; Labrie, Daniel
2016-11-01
To determine the shrinkage stress kinetics at up to 12h after light exposure and at tooth temperature during placement of selected Bulk Fill resin-based composites (RBCs). Five representative Bulk Fill RBCs from four companies were chosen with a wide range of viscosity and filler volume content. The shrinkage stress kinetics at T=33°C was measured continuously over a period of 12h using a modified tensometer with the ability to measure the cantilever beam deflection to better than 40nm accuracy at a sampling rate of up to 200 samples/s, and thermally stable resulting in a measurement accuracy better than 0.05MPa at 12h. The tensometer compliance was 0.105μm/N. A custom made heater was used to control the RBC sample temperature at T=33°C with a temperature gradient across the sample of less than 1°C. The samples were irradiated for 20s with irradiance of 1.1W/cm 2 and total energy density of 22J/cm 2 . Three samples (n=3) were used for each RBCs. The shrinkage stress at 12h for the five Bulk Fill RBCs ranged from 2.21 to 3.05MPa, maximum stress rate ((dS/dt) M ) varied from 0.18 to 0.41MPa/s, time at which the maximum stress rate occurred (t Max ) were between 1.42 to 3.24s and effective gel time (t gel ) varied from 50 to 770ms. Correlations were observed between (dS/dt) M and t Max (r=-0.946), t Max and filler volume fraction (r=-0.999), and between the shrinkage stress at 12h and t gel (r=0.994). However, no correlation was observed between the stress at 12h and filler volume fraction. The shrinkage stress for four of the five Bulk Fill RBCs were not significantly different (p<0.05) at 6h and beyond after photo-curing and that fully developed stress induced by photo-cured RBCs may only be reached at times longer than 12h. Copyright © 2016 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Temperature-dependent polymerization shrinkage stress kinetics of resin-composites.
Watts, D C; Alnazzawi, A
2014-06-01
To determine temperature dependence of shrinkage stress kinetics for a set of resin composites formulated with dimethacrylate monomer matrices. Six representative resin composites with a range of resin matrices were selected. Two of them were considered as low shrinking resin composites: Kalore and Venus Diamond. The shrinkage stress kinetics at 23°C and 37°C were measured continuously using a Bioman instrument for 60min. Stress levels between materials were compared at two intervals: 2min and 60min. Specimen temperatures were controlled by a newly designed heating device. Stress measurements were monitored for 1h, after irradiation for 40s at 550mW/cm(2) (energy density=22J/cm(2)). Three specimens (n=3) were used at each temperature per material. Shrinkage stress at 23°C ranged from 2.93MPa to 4.71MPa and from 3.57MPa to 5.42MPa for 2min and 60min after photo-activation, respectively. The lowest stress-rates were recorded for Kalore and Venus Diamond (0.34MPas(-1)), whereas the highest was recorded for Filtek Supreme XTE (0.63MPas(-1)). At 37°C, shrinkage stress ranged from 3.27MPa to 5.35MPa and from 3.36MPa to 5.49MPa for 2min and 60min after photo-activation, respectively. Kalore had the lowest stress-rate (0.44MPas(-1)), whereas Filtek Supreme XTE had the highest (0.85MPas(-1)). Materials exhibited a higher stress at 37°C than 23°C except for Kalore and Venus Diamond. Positive correlations were found between shrinkage stress and stress-rate at 23°C and 37°C (r=0.70 and 0.92, respectively). Resin-composites polymerized at elevated temperature (37°C) completed stress build up more rapidly than specimens held at 23°C. Two composites exhibited atypical reduced stress magnitudes at the higher temperature. Copyright © 2014 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Robust bayesian inference of generalized Pareto distribution ...
African Journals Online (AJOL)
Abstract. In this work, robust Bayesian estimation of the generalized Pareto distribution is proposed. The methodology is presented in terms of oscillation of posterior risks of the Bayesian estimators. By using a Monte Carlo simulation study, we show that, under a suitable generalized loss function, we can obtain a robust ...
Bayesian Decision Theoretical Framework for Clustering
Chen, Mo
2011-01-01
In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…
Using Bayesian belief networks in adaptive management.
J.B. Nyberg; B.G. Marcot; R. Sulyma
2006-01-01
Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to...
Calibration in a Bayesian modelling framework
Jansen, M.J.W.; Hagenaars, T.H.J.
2004-01-01
Bayesian statistics may constitute the core of a consistent and comprehensive framework for the statistical aspects of modelling complex processes that involve many parameters whose values are derived from many sources. Bayesian statistics holds great promises for model calibration, provides the
Particle identification in ALICE: a Bayesian approach
Adam, J.; Adamova, D.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anticic, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnafoeldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Bathen, B.; Batigne, G.; Camejo, A. Batista; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Benacek, P.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Boggild, H.; Boldizsar, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossu, F.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Cai, X.; Caines, H.; Diaz, L. Calero; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortes Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deisting, A.; Deloff, A.; Denes, E.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Corchero, M. A. Diaz; Dietel, T.; Dillenseger, P.; Divia, R.; Djuvsland, O.; Dobrin, A.; Gimenez, D. Domenicis; Doenigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernandez Tellez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhoje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glaessel, P.; Gomez Coral, D. M.; Ramirez, A. Gomez; Gonzalez, A. S.; Gonzalez, V.; Gonzalez-Zamora, P.; Gorbunov, S.; Goerlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Haake, R.; Haaland, O.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbaer, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Horak, D.; Hosokawa, R.; Hristov, P.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Incani, E.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacazio, N.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Bustamante, R. T. Jimenez; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kaplin, V.; Kar, S.; Uysal, A. Karasu; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Khan, M. Mohisin; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, J. S.; Kim, M.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein-Boesing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kostarakis, P.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Meethaleveedu, G. Koyithatta; Kralik, I.; Kravcakova, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kucera, V.; Kuijer, P. G.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; Monzon, I. Leon; Leon Vargas, H.; Leoncino, M.; Levai, P.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; Torres, E. Lopez; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mares, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marin, A.; Markert, C.; Marquard, M.; Martin, N. A.; Blanco, J. Martin; Martinengo, P.; Martinez, M. I.; Garcia, G. Martinez; Pedreira, M. Martinez; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Perez, J. Mercado; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montano Zetina, L.; Montes, E.; De Godoy, D. A. Moreira; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Muehlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, D.; Pagano, P.; Paic, G.; Pal, S. K.; Pan, J.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Da Costa, H. Pereira; Peresunko, D.; Lara, C. E. Perez; Lezama, E. Perez; Peskov, V.; Pestov, Y.; Petracek, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Raesaenen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodriguez Cahuantzi, M.; Manso, A. Rodriguez; Roed, K.; Rogochaya, E.; Rohr, D.; Roehrich, D.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Montero, A. J. Rubio; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Safarik, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sandor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarkar, N.; Sarma, P.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Sefcik, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shahzad, M. I.; Shangaraev, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; de Souza, R. D.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Sumbera, M.; Sumowidagdo, S.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Munoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thaeder, J.; Thakur, D.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Palomo, L. Valencia; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vyvre, P. Vande; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Vercellin, E.; Vergara Limon, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Baillie, O. Villalobos; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Voelkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrlakova, J.; Vulpescu, B.; Wagner, B.; Wagner, J.; Wang, H.; Watanabe, D.; Watanabe, Y.; Weiser, D. F.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yang, H.; Yano, S.; Yasin, Z.; Yokoyama, H.; Yoo, I. -K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Zavada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, C.; Zhao, C.; Zhigareva, N.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.; Collaboration, ALICE
2016-01-01
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian
Bayesian Network for multiple hypthesis tracking
Zajdel, W.P.; Kröse, B.J.A.; Blockeel, H.; Denecker, M.
2002-01-01
For a flexible camera-to-camera tracking of multiple objects we model the objects behavior with a Bayesian network and combine it with the multiple hypohesis framework that associates observations with objects. Bayesian networks offer a possibility to factor complex, joint distributions into a
Bayesian learning theory applied to human cognition.
Jacobs, Robert A; Kruschke, John K
2011-01-01
Probabilistic models based on Bayes' rule are an increasingly popular approach to understanding human cognition. Bayesian models allow immense representational latitude and complexity. Because they use normative Bayesian mathematics to process those representations, they define optimal performance on a given task. This article focuses on key mechanisms of Bayesian information processing, and provides numerous examples illustrating Bayesian approaches to the study of human cognition. We start by providing an overview of Bayesian modeling and Bayesian networks. We then describe three types of information processing operations-inference, parameter learning, and structure learning-in both Bayesian networks and human cognition. This is followed by a discussion of the important roles of prior knowledge and of active learning. We conclude by outlining some challenges for Bayesian models of human cognition that will need to be addressed by future research. WIREs Cogn Sci 2011 2 8-21 DOI: 10.1002/wcs.80 For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.
Properties of the Bayesian Knowledge Tracing Model
van de Sande, Brett
2013-01-01
Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
and secondly, to gain efficiency during modification of an object oriented Bayesian network. To accomplish these two goals we have exploited a mechanism allowing local triangulation of instances to develop a method for updating the junction trees associated with object oriented Bayesian networks in highly...
Using Bayesian Networks to Improve Knowledge Assessment
Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra
2013-01-01
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…
Bayesian models: A statistical primer for ecologists
Hobbs, N. Thompson; Hooten, Mevin B.
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Qin, Yanhua; Liu, Yumin; Liu, Jianyi; Yu, Zhongyuan
2018-01-16
Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to resolve more sources than the number of physical sensors. The sparse-based DOA estimation can deteriorate the detection and estimation performance because the sources may be off the search grid no matter how fine the grid is. This dictionary mismatch problem can be well resolved by the SBL using fixed point updates. The SBL can automatically choose sparsity and approximately resolve the non-convex optimizaton problem. Numerical simulations are conducted to validate the effectiveness of the underdetermined wideband DOA estimation via SBL based on coprime array. It is clear that SBL can obtain good performance in detection and estimation compared to least absolute shrinkage and selection operator (LASSO), simultaneous orthogonal matching pursuit least squares (SOMP-LS) , simultaneous orthogonal matching pursuit total least squares (SOMP-TLS) and off-grid sparse Bayesian inference (OGSBI).
Flexible Bayesian Human Fecundity Models.
Kim, Sungduk; Sundaram, Rajeshwari; Buck Louis, Germaine M; Pyper, Cecilia
2012-12-01
Human fecundity is an issue of considerable interest for both epidemiological and clinical audiences, and is dependent upon a couple's biologic capacity for reproduction coupled with behaviors that place a couple at risk for pregnancy. Bayesian hierarchical models have been proposed to better model the conception probabilities by accounting for the acts of intercourse around the day of ovulation, i.e., during the fertile window. These models can be viewed in the framework of a generalized nonlinear model with an exponential link. However, a fixed choice of link function may not always provide the best fit, leading to potentially biased estimates for probability of conception. Motivated by this, we propose a general class of models for fecundity by relaxing the choice of the link function under the generalized nonlinear model framework. We use a sample from the Oxford Conception Study (OCS) to illustrate the utility and fit of this general class of models for estimating human conception. Our findings reinforce the need for attention to be paid to the choice of link function in modeling conception, as it may bias the estimation of conception probabilities. Various properties of the proposed models are examined and a Markov chain Monte Carlo sampling algorithm was developed for implementing the Bayesian computations. The deviance information criterion measure and logarithm of pseudo marginal likelihood are used for guiding the choice of links. The supplemental material section contains technical details of the proof of the theorem stated in the paper, and contains further simulation results and analysis.
Bayesian Nonparametric Longitudinal Data Analysis.
Quintana, Fernando A; Johnson, Wesley O; Waetjen, Elaine; Gold, Ellen
2016-01-01
Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.
BELM: Bayesian extreme learning machine.
Soria-Olivas, Emilio; Gómez-Sanchis, Juan; Martín, José D; Vila-Francés, Joan; Martínez, Marcelino; Magdalena, José R; Serrano, Antonio J
2011-03-01
The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap; and presents high generalization capabilities. Bayesian ELM is benchmarked against classical ELM in several artificial and real datasets that are widely used for the evaluation of machine learning algorithms. Achieved results show that the proposed approach produces a competitive accuracy with some additional advantages, namely, automatic production of CIs, reduction of probability of model overfitting, and use of a priori knowledge.
Directory of Open Access Journals (Sweden)
Rhandyka Rafli
2015-12-01
Full Text Available This study was performed to determine the correlation between aldehyde dehydrogenase-1A1 (ALDH1A1 level and tumor shrinkage after chemoradiation in locally advanced rectal cancer. This is a retrospective study of 14 locally advanced rectal cancer patients with long course neoadjuvant chemoradiation. ALDH1A1 level was measured using ELISA from paraffin embedded tissue. Tumor shrinkage was measured from computed tomography (CT scan or magnetic resonance imaging (MRI based on Response Evaluation Criteria in Solid Tumor v1.1 (RECIST v1.1. The mean of ALDH1A1 level was 9.014 ± 3.3 pg/mL and the mean of tumor shrinkage was 7.89 ± 35.7%. Partial response proportion was 28.6%, stable disease proportion was 50% and progressive disease proportion was 21.4%. There was a significant strong negative correlation (r = –0.890, plt; 0.001 between ALDH1A1 and tumor shrinkage. In conclusion, tumor shrinkage in locally advanced rectal cancer after preoperative chemoradiation was influenced by ALDH1A1 level. Higher level of ALDH1A1 suggests decreased tumor shrinkage after preoperative chemoradiation.
2nd Bayesian Young Statisticians Meeting
Bitto, Angela; Kastner, Gregor; Posekany, Alexandra
2015-01-01
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session ...
Bayesian natural language semantics and pragmatics
Zeevat, Henk
2015-01-01
The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice's contributions to pragmatics or in interpretation by abduction.
Crystal structure prediction accelerated by Bayesian optimization
Yamashita, Tomoki; Sato, Nobuya; Kino, Hiori; Miyake, Takashi; Tsuda, Koji; Oguchi, Tamio
2018-01-01
We propose a crystal structure prediction method based on Bayesian optimization. Our method is classified as a selection-type algorithm which is different from evolution-type algorithms such as an evolutionary algorithm and particle swarm optimization. Crystal structure prediction with Bayesian optimization can efficiently select the most stable structure from a large number of candidate structures with a lower number of searching trials using a machine learning technique. Crystal structure prediction using Bayesian optimization combined with random search is applied to known systems such as NaCl and Y2Co17 to discuss the efficiency of Bayesian optimization. These results demonstrate that Bayesian optimization can significantly reduce the number of searching trials required to find the global minimum structure by 30-40% in comparison with pure random search, which leads to much less computational cost.
International Nuclear Information System (INIS)
Gomes, Many R.S.; Melo, Paulo F.F.F. e
2015-01-01
This work models by Bayesian networks the residual heat removal system (SRCR) of Angra I nuclear power plant, using fault tree mapping for systematically identifying all possible modes of occurrence caused by a large loss of coolant accident (large LOCA). The focus is on dependent events, such as the bridge system structure of the residual heat removal system and the occurrence of common-cause failures. We used the Netica™ tool kit, Norsys Software Corporation and Python 2.7.5 for modeling Bayesian networks and Microsoft Excel for modeling fault trees. Working with dependent events using Bayesian networks is similar to the solutions proposed by other models, beyond simple understanding and ease of application and modification throughout the analysis. The results obtained for the unavailability of the system were satisfactory, showing that in most cases the system will be available to mitigate the effects of an accident as described above. (author)
Bayesian Approach to Inverse Problems
2008-01-01
Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation. The concept of inverse problems precisely originates from the idea of inverting the laws of physics to recover a quantity of interest from measurable data.Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise. Regularization is the key concept to solve inverse problems.The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image estimation
Bayesian modelling of fusion diagnostics
Fischer, R.; Dinklage, A.; Pasch, E.
2003-07-01
Integrated data analysis of fusion diagnostics is the combination of different, heterogeneous diagnostics in order to improve physics knowledge and reduce the uncertainties of results. One example is the validation of profiles of plasma quantities. Integration of different diagnostics requires systematic and formalized error analysis for all uncertainties involved. The Bayesian probability theory (BPT) allows a systematic combination of all information entering the measurement descriptive model that considers all uncertainties of the measured data, calibration measurements, physical model parameters and measurement nuisance parameters. A sensitivity analysis of model parameters allows crucial uncertainties to be found, which has an impact on both diagnostic improvement and design. The systematic statistical modelling within the BPT is used for reconstructing electron density and electron temperature profiles from Thomson scattering data from the Wendelstein 7-AS stellarator. The inclusion of different diagnostics and first-principle information is discussed in terms of improvements.
Bayesian networks in educational assessment
Almond, Russell G; Steinberg, Linda S; Yan, Duanli; Williamson, David M
2015-01-01
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as ...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...... sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning...... under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented on model construction and verification, modeling techniques and tricks, learning...
On Bayesian System Reliability Analysis
Energy Technology Data Exchange (ETDEWEB)
Soerensen Ringi, M.
1995-05-01
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person`s state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Bayesian Kernel Mixtures for Counts.
Canale, Antonio; Dunson, David B
2011-12-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.
On Bayesian System Reliability Analysis
International Nuclear Information System (INIS)
Soerensen Ringi, M.
1995-01-01
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person's state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs
A Bayesian Reflection on Surfaces
Directory of Open Access Journals (Sweden)
David R. Wolf
1999-10-01
Full Text Available Abstract: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data, is presented.
Early daily trunk shrinkage is highly sensitive to water stress in nectarine trees
Pérez-Pastor, Alejandro; De la Rosa, Jose M.; Dodd, Ian C.; Conesa, María R.; Domingo, Rafael
2014-05-01
The sensitivity to water stress of different plant water status indicators was evaluated during two consecutive years in early nectarine trees grown in a semi-arid region. Measurements were made post-harvest and two irrigation treatments were applied: a control treatment (CTL), irrigated at 120% of crop evapotranspiration demand to achieve non-limiting water conditions, and a deficit irrigation treatment (DI), that applied around 37% less water than CTL during late postharvest. The plant water status indicators evaluated were midday stem water potential (Ψstem) and parameters derived from trunk diameter fluctuations (TDF): maximum daily shrinkage (MDS), trunk daily growth rate (TGR), early daily shrinkage measured between 0900 and 1200 h solar time (EDS), and late daily shrinkage (LDS) that occurred between 1200 h solar time and the moment that minimum trunk diameter was reached (typically 1600 h solar time). The most sensitive (highest ratio of signal intensity (SI) to noise) indicators to water stress were Ψstem together with EDS. The SI of EDS was greater than that of Ψstem, although with greater variability. EDS was a better indicator than MDS, with higher SI and similar variability. Although MDS was linearly related to Ψstem down to -1.5 MPa, thereafter MDS decreased with increasing water stress. In contrast, EDS was linearly related to Ψstem, although the slope of the regression decreased as the season progressed, as in the case of MDS. Further studies are needed to determine whether EDS is a sensitive indicator of water stress in a range of species.
Maiotti, Marco; Massoni, Carlo; Tarantino, Umberto
2005-06-01
The aim of this study was to evaluate the preliminary results of arthroscopic thermal capsular shrinkage performed for chronic lateral ankle instability in soccer players. Case series. We reviewed 22 male soccer players (average age, 18 years) with chronic lateral ankle instability who underwent arthroscopic thermal shrinkage between 1997 and 1998. The only exclusion criterion for this study was the failure of previous surgery. Before surgery, all patients had participated in a physical rehabilitation program consisting of peroneal strengthening exercises and proprioceptive training for several months, without any relief of their symptoms. All patients were characterized by repeated episodes of giving way, a positive anterior drawer sign, and positive stress radiographs. The stress radiographs consisted of a sagittal stress and talar tilt by the TELOS device (Fallston, MD). The Karlsson and Peterson ankle function scoring scale was used to assess these patients for their current activity level as well as activity before surgery. Patients were reviewed at a mean of 42 months (range, 32 to 56 months); 19 patients (86.3%) reported a good or excellent functional outcome as assessed by the Karlsson and Peterson ankle function scoring scale. Eighteen of the 22 patients presented no evidence of ankle instability on physical examination or on stress radiographs. Only 1 patient was not able to return to his previous level of sports activity and complained of ankle instability when walking on uneven ground. This study suggests that arthroscopic thermal capsular shrinkage is a valid and safe procedure for treatment of chronic lateral ankle instability. Longer follow-up is needed, however, to see how these results may change with time in high-demand athletes. Level IV.
Mechanical Properties, Shrinkage Behavior and Water Absorption of PA6/PP/CaCO3 Nanocomposites
Directory of Open Access Journals (Sweden)
Karim Shelesh-Nezhad
2013-01-01
Full Text Available Nanocomposites based on polyamide 6/polypropylene PA6/PP 67/33 blend containing 2.5 to 10 phr of nano-CaCO3 and 5 phr of maleated polypropylene PP-g-MAH as compatibilizer were prepared by melt compounding followed by injection molding. The mechanical properties, water absorption, as well as shrinkage behavior were characterized and the morphology was studied using scanning electron microscopy. The presence of PP, PP-g-MAH and nano-CaCO3 lowered the amount of water absorption as high as 72 wt%. Morphology analysis indicated that the addition of PP-g-MAH can signifcantly improve the adhesion between PA6 and PP phases. The incorporation of PP-g-MAH led to 24% increase in fexural and impact strength, 27% rise in tensile strength and approximately 100% increase in elongation-at-break. The addition of nano-CaCO3 particles increased the impact resistance and fexural strength. The results of experiments indicated that the maximum fexural strength was achieved by adding 5 phr of nano-CaCO3 which was 16% greater than pure PA6, and the maximum impact strength was attained by adding 7.5 phr of nano-CaCO3 which was 29% superior compared to pure PA6. The incorporation of 10 phr of nano-CaCO3 particles led to fller agglomeration and, consequently, the impact strength was dramatically dropped. Dimensional characterization of molded samples revealed that the incorporation of PP-g-MAH can raise the shrinkage, but the addition of nano-CaCO3 has not had any considerable effect on the shrinkage of nanocomposites.
WASICA: An effective wavelet-shrinkage based ICA model for brain fMRI data analysis.
Wang, Nizhuan; Zeng, Weiming; Shi, Yingchao; Ren, Tianlong; Jing, Yanshan; Yin, Jun; Yang, Jiajun
2015-05-15
Researches declared that the super-Gaussian property contributed to the success of some spatial independent component analysis (ICA) algorithms in brain fMRI source separation (e.g., Infomax and FastICA), which implied that sparse approximation transforming the sources (super-Gaussian or Gaussian-like) with stronger super-Gaussian feature would possibly improve the separation performance of these algorithms. This paper presented a novel wavelet-shrinkage based ICA (WASICA) model, an extension of our previous SACICA, for single-subject analysis. In contrast, two main aspects had been effectively enhanced: (1) sparse approximation coefficients set formation, made up of two sub-procedures: the wavelet-shrinkage of wavelet packet (WP) tree nodes, and the automatic nodes selection and integration based on the relative WP energy; (2) ICA-based decomposition and reconstruction, composed of temporal dynamics extraction using ICA, WP reconstruction based on the sparse approximation coefficients set and least-square-based functional networks reconstruction. The wavelet-shrinkage and the automatic nodes selection and integration simultaneously transformed both the mixtures and underlying sources into effective sparse approximation coefficients sets, exhibiting stronger super-Gaussian distribution; WP projected-back approximation with nuisance-exclusion contributed to networks reconstruction. Simulation 1 revealed WASICA successfully recovered super-Gaussian and some Gaussian-like sources. Simulation 2 and hybrid data experiments showed that WASICA with good temporal performance had stronger source recovery ability and signal detection sensitivity spatially than FastICA, Infomax and SACICA did; the higher intra-consistency in task-related experiments denoted WASICA occupied stronger spatial robustness against smooth kernels. WASICA was a promising brain signal separation model with charming spatial-temporal performance. Copyright © 2015 Elsevier B.V. All rights reserved.
Shrinkage stress compensation in composite-restored teeth: relaxation or hygroscopic expansion?
Meriwether, Laurel A; Blen, Bernard J; Benson, Jarred H; Hatch, Robert H; Tantbirojn, Daranee; Versluis, Antheunis
2013-05-01
Polymerization of composite restorations causes shrinkage, which deforms and thus stresses restored teeth. This shrinkage deformation, however, has been shown to decrease over time. The objective was to investigate whether this reduction was caused by hygroscopic expansion or stress relaxation of the composite/tooth complex. Extracted molars were mounted in rigid stainless steel rings with four spherical reference areas. Twelve molars were prepared with large mesioocclusodistal slots, etched, bonded, and restored with a composite material (Filtek Supreme, 3M ESPE) in two horizontal layers. Ten intact molars were the controls. The teeth were stored either in deionized water or silicone oil. They were scanned after preparation (baseline), restoration (0-week), and after 1, 2, and 4 weeks storage. Scanned tooth surfaces were aligned with the baseline using the unchanged reference areas. Cuspal flexure was calculated from lingual and buccal surface deformation. To verify that the restorations had remained bonded, dye penetration at the interfaces was assessed using basic fuchsin dye. Statistical assessment was done by ANOVA followed by Student-Newman-Keuls post hoc test (p=0.05). Substantial cuspal contraction was found for restored teeth after the composite was cured (13-14 μm cuspal flexure). After 4 weeks cuspal contraction decreased significantly for restored teeth stored in water (7.3 ± 3.2) but not for those stored in silicone oil (11.4 ± 5.0). Dye penetration of the occlusal interface was minimal in both groups (106 ± 87 and 21 ± 28 μm in water and silicone oil, respectively). The results suggest that hygroscopic expansion was the main mechanism for shrinkage stress compensation. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Robust bayesian analysis of an autoregressive model with ...
African Journals Online (AJOL)
In this work, robust Bayesian analysis of the Bayesian estimation of an autoregressive model with exponential innovations is performed. Using a Bayesian robustness methodology, we show that, using a suitable generalized quadratic loss, we obtain optimal Bayesian estimators of the parameters corresponding to the ...
C-O-H-S magmatic fluid system in shrinkage bubbles of melt inclusions
Robidoux, P.; Frezzotti, M. L.; Hauri, E. H.; Aiuppa, A.
2016-12-01
Magmatic volatiles include multiple phases in the C-O-H-S system of shrinkage bubbles for which a conceptual model is still unclear during melt inclusion formation [1,2,3,4]. The present study aims to qualitatively explore the evolution of the volatile migration, during and after the formation of the shrinkage bubble in melt inclusions trapped by olivines from Holocene to present at San Cristóbal volcano (Nicaragua), Central American Volcanic Arc (CAVA). Combined scanning electron microscope (SEM) and Raman spectroscopy observations allow to define the mineral-fluid phases inside typical shrinkage bubbles at ambient temperature. The existence of residual liquid water is demonstrated in the shrinkage bubbles of naturally quenched melt inclusion and this water could represents the principal agent for chemical reactions with other dissolved ionic species (SO42-, CO32-, etc.) and major elements (Mg, Fe, Cu, etc.) [4,5]. With the objective of following the cooling story of the bubble-inclusion system, the new methodological approach here estimate the interval of equilibrium temperatures for each SEM-Raman identified mineral phase (carbonates, hydrous carbonates, sulfurs, sulfates, etc.). Finally, two distinct mechanisms are proposed to describe the evolution of this heterogeneous fluid system in bubble samples at San Cristóbal which imply a close re-examination for similar volcanoes in subduction zone settings: (1) bubbles are already contracted and filled by volatiles by diffusion processes from the glass and leading to a C-O-H-S fluid-glass reaction enriched in Mg-Fe-Cu elements (2) bubbles are formed by oversaturation of the volatiles from the magma which is producing an immiscible metal-rich fluid. [1]Moore et al. (2015). Am. Mineral. 100, 806-823 [2]Wallace et al. (2015). Am. Mineral. 100, 787-794 [3]Lowenstern (2015). Am. Mineral. 100, 672-673 [4]Esposito, et al. (2016). Am. Mineral. 101, 1691-1708 [5]Kamenetsky et al. (2001). Earth Planet. Sci. Lett. 184, 685-702
Ye, Y. J.; Liang, T.; Ding, D. X.; Lei, B.; Su, H.; Zhang, Y. F.
2017-07-01
A calculation model for radon concentration in shrinkage mining stopes under various ventilation conditions was established in this study. The model accounts for the influence of permeability and area of the blasted ore heap, ventilation air quantity, and airflow direction on radon concentration in a confined workspace; these factors work together to allow the engineer to optimize the ventilation design. The feasibility and effectiveness of the model was verified by applying it to mines with elevated radon radiation exposure. The model was found to accurately changes in radon concentration according to the array of influence factors in underground uranium mines.
Urban shrinkage, local housing markets and the role of voluntary community organisations
DEFF Research Database (Denmark)
Larsen, Jacob Norvig
Since the beginning of the crisis in 2007-08 urban shrinkage has hit a large number of Danish municipalities, towns and villages outside the two major metropolitan areas in the country .Abandoned homes, plunging property prices and out-migration are among the major symptoms. As a consequence...... why and how communities’ social capital enables voluntary initiatives to grow and if there are options available to local government to encourage and strengthen voluntary community-based organisations. Evidence from two case studies shows a number of successful initiatives by both municipalities...
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...... by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose PRIMULA--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Bayesian inversion of refraction seismic traveltime data
Ryberg, T.; Haberland, Ch
2018-03-01
We apply a Bayesian Markov chain Monte Carlo (McMC) formalism to the inversion of refraction seismic, traveltime data sets to derive 2-D velocity models below linear arrays (i.e. profiles) of sources and seismic receivers. Typical refraction data sets, especially when using the far-offset observations, are known as having experimental geometries which are very poor, highly ill-posed and far from being ideal. As a consequence, the structural resolution quickly degrades with depth. Conventional inversion techniques, based on regularization, potentially suffer from the choice of appropriate inversion parameters (i.e. number and distribution of cells, starting velocity models, damping and smoothing constraints, data noise level, etc.) and only local model space exploration. McMC techniques are used for exhaustive sampling of the model space without the need of prior knowledge (or assumptions) of inversion parameters, resulting in a large number of models fitting the observations. Statistical analysis of these models allows to derive an average (reference) solution and its standard deviation, thus providing uncertainty estimates of the inversion result. The highly non-linear character of the inversion problem, mainly caused by the experiment geometry, does not allow to derive a reference solution and error map by a simply averaging procedure. We present a modified averaging technique, which excludes parts of the prior distribution in the posterior values due to poor ray coverage, thus providing reliable estimates of inversion model properties even in those parts of the models. The model is discretized by a set of Voronoi polygons (with constant slowness cells) or a triangulated mesh (with interpolation within the triangles). Forward traveltime calculations are performed by a fast, finite-difference-based eikonal solver. The method is applied to a data set from a refraction seismic survey from Northern Namibia and compared to conventional tomography. An inversion test
Radiation dose reduction in computed tomography perfusion using spatial-temporal Bayesian methods
Fang, Ruogu; Raj, Ashish; Chen, Tsuhan; Sanelli, Pina C.
2012-03-01
In current computed tomography (CT) examinations, the associated X-ray radiation dose is of significant concern to patients and operators, especially CT perfusion (CTP) imaging that has higher radiation dose due to its cine scanning technique. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) parameter as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and degrade CT perfusion maps greatly if no adequate noise control is applied during image reconstruction. To capture the essential dynamics of CT perfusion, a simple spatial-temporal Bayesian method that uses a piecewise parametric model of the residual function is used, and then the model parameters are estimated from a Bayesian formulation of prior smoothness constraints on perfusion parameters. From the fitted residual function, reliable CTP parameter maps are obtained from low dose CT data. The merit of this scheme exists in the combination of analytical piecewise residual function with Bayesian framework using a simpler prior spatial constrain for CT perfusion application. On a dataset of 22 patients, this dynamic spatial-temporal Bayesian model yielded an increase in signal-tonoise-ratio (SNR) of 78% and a decrease in mean-square-error (MSE) of 40% at low dose radiation of 43mA.
Simultaneous estimation of QTL parameters for mapping multiple traits
Indian Academy of Sciences (India)
Z
The analysis of quantitative trait loci (QTLs) aims at mapping and estimating the positions and effects of the genes that may affect ... Besides, Bayesian Mapping of quantitative trait loci for multiple traits was also considered by some researchers (Liu et .... random error of the ith trait value of the jth subject, with mean zero and.
Directory of Open Access Journals (Sweden)
Virgilio Tattini Jr
2007-03-01
Full Text Available Bovine pericardium bioprosthesis has become a commonly accepted device for heart valve replacement. Present practice relies on the measurement of shrinkage temperature, observed as a dramatic shortening of tissue length. Several reports in the last decade have utilized differential scanning calorimetry (DSC as an alternative method to determine the shrinkage temperature, which is accompanied by the absorption of heat, giving rise to an endothermic peak over the shrinkage temperature range of biological tissues. Usually, freeze-drying microscope is used to determine collapse temperature during the lyophilization of solutions. On this experiment we used this technique to study the shrinkage event. The aim of this work was to compare the results of shrinkage temperature obtained by DSC with the results obtained by freeze-drying microscopy. The results showed that both techniques provided excellent sensitivity and reproducibility, and gave information on the thermal shrinkage transition via the thermodynamical parameters inherent of each method.
Bayesian estimation and modeling: Editorial to the second special issue on Bayesian data analysis.
Chow, Sy-Miin; Hoijtink, Herbert
2017-12-01
This editorial accompanies the second special issue on Bayesian data analysis published in this journal. The emphases of this issue are on Bayesian estimation and modeling. In this editorial, we outline the basics of current Bayesian estimation techniques and some notable developments in the statistical literature, as well as adaptations and extensions by psychological researchers to better tailor to the modeling applications in psychology. We end with a discussion on future outlooks of Bayesian data analysis in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Jan, Yih-Dean; Lee, Bor-Shiunn; Lin, Chun-Pin; Tseng, Wan-Yu
2014-04-01
Polymerization shrinkage is one of the main causes of dental restoration failure. This study tried to conjugate two diisocyanate side chains to dimethacrylate resins in order to reduce polymerization shrinkage and increase the hardness of composite resins. Diisocyanate, 2-hydroxyethyl methacrylate, and bisphenol A dimethacrylate were reacted in different ratios to form urethane-modified new resin matrices, and then mixed with 50 wt.% silica fillers. The viscosities of matrices, polymerization shrinkage, surface hardness, and degrees of conversion of experimental composite resins were then evaluated and compared with a non-modified control group. The viscosities of resin matrices increased with increasing diisocyanate side chain density. Polymerization shrinkage and degree of conversion, however, decreased with increasing diisocyanate side chain density. The surface hardness of all diisocyanate-modified groups was equal to or significantly higher than that of the control group. Conjugation of diisocyanate side chains to dimethacrylate represents an effective means of reducing polymerization shrinkage and increasing the surface hardness of dental composite resins. Copyright © 2012. Published by Elsevier B.V.
Directory of Open Access Journals (Sweden)
Mehmet Gesoglu
2015-01-01
Full Text Available This paper addresses durability and shrinkage performance of the self-compacting concretes (SCCs in which natural coarse aggregate (NCA and/or natural fine aggregate (NFA were replaced by recycled coarse aggregate (RCA and/or recycled fine aggregate (RFA, respectively. A total of 16 SCCs were produced and classified into four series, each of which included four mixes designed with two water to binder (w/b ratios of 0.3 and 0.43 and two silica fume replacement levels of 0 and 10%. Durability properties of SCCs were tested for rapid chloride penetration, water sorptivity, gas permeability, and water permeability at 56 days. Also, drying shrinkage accompanied by the water loss and restrained shrinkage of SCCs were monitored over 56 days of drying period. Test results revealed that incorporating recycled coarse and/or fine aggregates aggravated the durability properties of SCCs tested in this study. The drying shrinkage and restrained shrinkage cracking of recycled aggregate (RA concretes had significantly poorer performance than natural aggregate (NA concretes. The time of cracking greatly prolonged as the RAs were used along with the increase in water/binder ratio.
Müller, Dominik; Technow, Frank; Melchinger, Albrecht E
2015-04-01
We evaluated several methods for computing shrinkage estimates of the genomic relationship matrix and demonstrated their potential to enhance the reliability of genomic estimated breeding values of training set individuals. In genomic prediction in plant breeding, the training set constitutes a large fraction of the total number of genotypes assayed and is itself subject to selection. The objective of our study was to investigate whether genomic estimated breeding values (GEBVs) of individuals in the training set can be enhanced by shrinkage estimation of the genomic relationship matrix. We simulated two different population types: a diversity panel of unrelated individuals and a biparental family of doubled haploid lines. For different training set sizes (50, 100, 200), number of markers (50, 100, 200, 500, 2,500) and heritabilities (0.25, 0.5, 0.75), shrinkage coefficients were computed by four different methods. Two of these methods are novel and based on measures of LD, the other two were previously described in the literature, one of which was extended by us. Our results showed that shrinkage estimation of the genomic relationship matrix can significantly improve the reliability of the GEBVs of training set individuals, especially for a low number of markers. We demonstrate that the number of markers is the primary determinant of the optimum shrinkage coefficient maximizing the reliability and we recommend methods eligible for routine usage in practical applications.
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
Buslik, A.
1994-01-01
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
Bayesian analysis for the social sciences
Jackman, Simon
2009-01-01
Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using WinBUGS - the most-widely used Bayesian analysis software in the world - and R - an open-source statistical software. The book is supported by a Website featuring WinBUGS and R code, and data sets.
Bayesian optimization for computationally extensive probability distributions.
Tamura, Ryo; Hukushima, Koji
2018-01-01
An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribution. Our Bayesian optimization technique is applied to the posterior distribution in the effective physical model estimation, which is a computationally extensive probability distribution. Even when the number of sampling points on the posterior distributions is fixed to be small, the Bayesian optimization provides a better maximizer of the posterior distributions in comparison to those by the random search method, the steepest descent method, or the Monte Carlo method. Furthermore, the Bayesian optimization improves the results efficiently by combining the steepest descent method and thus it is a powerful tool to search for a better maximizer of computationally extensive probability distributions.
新家, 健精
1991-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
An overview on Approximate Bayesian computation*
Directory of Open Access Journals (Sweden)
Baragatti Meïli
2014-01-01
Full Text Available Approximate Bayesian computation techniques, also called likelihood-free methods, are one of the most satisfactory approach to intractable likelihood problems. This overview presents recent results since its introduction about ten years ago in population genetics.
Implementing the Bayesian paradigm in risk analysis
International Nuclear Information System (INIS)
Aven, T.; Kvaloey, J.T.
2002-01-01
The Bayesian paradigm comprises a unified and consistent framework for analyzing and expressing risk. Yet, we see rather few examples of applications where the full Bayesian setting has been adopted with specifications of priors of unknown parameters. In this paper, we discuss some of the practical challenges of implementing Bayesian thinking and methods in risk analysis, emphasizing the introduction of probability models and parameters and associated uncertainty assessments. We conclude that there is a need for a pragmatic view in order to 'successfully' apply the Bayesian approach, such that we can do the assignments of some of the probabilities without adopting the somewhat sophisticated procedure of specifying prior distributions of parameters. A simple risk analysis example is presented to illustrate ideas
A Bayesian concept learning approach to crowdsourcing
DEFF Research Database (Denmark)
Viappiani, P.; Zilles, S.; Hamilton, H.J.
2011-01-01
We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...
An Intuitive Dashboard for Bayesian Network Inference
International Nuclear Information System (INIS)
Reddy, Vikas; Farr, Anna Charisse; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K D V
2014-01-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
Modeling of Flexible Polyurethane Foam Shrinkage for Bra Cup Moulding Process Control
Directory of Open Access Journals (Sweden)
Long Wu
2018-04-01
Full Text Available Nowadays, moulding technology has become a remarkable manufacturing process in the intimate apparel industry. Polyurethane (PU foam sheets are used to mould three-dimensional (3D seamless bra cups of various softness and shapes, which eliminate bulky seams and reduce production costs. However, it has been challenging to accurately and effectively control the moulding process and bra cup thickness. In this study, the theoretical mechanism of heat transfer and the thermal conductivity of PU foams are first examined. Experimental studies are carried out to investigate the changes in foam materials at various moulding conditions (viz., temperatures, and lengths of dwell time in terms of surface morphology and thickness by using electron and optical microscopy. Based on the theoretical and experimental investigations of the thermal conductivity of the foam materials, empirical equations of shrinkage ratio and thermal conduction of foam materials were established. A regression model to predict flexible PU foam shrinkage during the bra cup moulding process was formulated by using the Levenberg-Marquardt method of nonlinear least squares algorithm and verified for accuracy. This study therefore provides an effective approach that optimizes control of the bra cup moulding process and assures the ultimate quality and thickness of moulded foam cups.
Autogenous shrinkage in high-performance cement paste: An evaluation of basic mechanisms
International Nuclear Information System (INIS)
Lura, Pietro; Jensen, Ole Mejlhede; Breugel, Klaas van
2003-01-01
In this paper, various mechanisms suggested to cause autogenous shrinkage are presented. The mechanisms are evaluated from the point of view of their soundness and applicability to quantitative modeling of autogenous shrinkage. The capillary tension approach is advantageous, because it has a sound mechanical and thermodynamical basis. Furthermore, this mechanism is easily applicable in a numerical model when dealing with a continuously changing microstructure. In order to test the numerical model, autogenous deformation and internal relative humidity (RH) of a Portland cement paste were measured during the first week of hardening. The isothermal heat evolution was also recorded to monitor the progress of hydration and the elastic modulus in compression was measured. RH change, degree of hydration and elastic modulus were used as input data for the calculation of autogenous deformation based on the capillary tension approach. Because a part of the RH drop in the cement paste is due to dissolved salts in the pore solution, a method is suggested to separate this effect from self-desiccation and to calculate the actual stress in the pore fluid associated with menisci formation
Effects of poison panel shrinkage and gaps on fuel storage rack reactivity
International Nuclear Information System (INIS)
Boyd, W.A.; Mueller, D.E.
1988-01-01
Fixed poison panels are used in spent fuel rack designs to increase enrichment limits and reduce cell spacing; therefore, assurances that the maximum rack reactivity will meet the design limit (0.95) throughout the lifetime of the racks depend on the continued effectiveness of the poison with time. Industry data have shown that poison panels will shrink under irradiated conditions. From recent data, however, poison panels have been found to have gaps spanning their width after relatively short operating periods. This paper presents results of studies showing the fuel rack reactivity changes associated with poison panel shrinkage and formation of gaps. The discovery of gaps in the fuel rack poison panels at an operating plant raises concerns regarding the effectiveness of the poison over the lifetime of the fuel racks. Studies performed to evaluate the effect of the poison panel shrinkage on reactivity show that reactivity changes from zero to several percent are possible depending on the initial panel size. Results of recent studies show that some gaps can be accommodated in the fuel rack poison panels at the fuel midplane without causing the fuel rack K eff limit to be exceeded. With worst-case assumptions concerning gap size and the number of panels affected, other actions will likely be required to show that the rack K eff design limit will not be exceeded
Stan, S.; Chisamera, M.; Riposan, I.; Neacsu, L.; Cojocaru, A. M.; Stan, I.
2017-06-01
With the more widespread adoption of thermal analysis testing, thermal analysis data have become an indicator of cast iron quality. The cooling curve and its first derivative display patterns that can be used to predict the characteristics of a cast iron. An experimental device was developed with a technique to simultaneously evaluate cooling curves and expansion or contraction of cast metals during solidification. Its application is illustrated with results on shrinkage tendency of ductile iron treated with FeSiMgRECa master alloy and inoculated with FeSi based alloys, as affected by mould rigidity (green sand and resin sand moulds). Undercooling at the end of solidification relative to the metastable (carbidic) equilibrium temperature and the expansion within the solidification sequence appear to have a strong influence on the susceptibility to macro - and micro - shrinkage in ductile iron castings. Green sand moulds, as less rigid moulds, encourage the formation of contraction defects, not only because of high initial expansion values, but also because of a higher cooling rate during solidification, and consequently, increased undercooling below the metastable equilibrium temperature up to the end of solidification.
Deindustrialization and Urban Shrinkage in Romania. What Lessons for the Spatial Policy?
Directory of Open Access Journals (Sweden)
Claudia POPESCU
2014-06-01
Full Text Available After remodeling the economies of the Western world all along the 1980s, deindustrialization abruptly hit the former socialist countries in the early 1990s. Deindustrialization with destructuring meant the disintegration of the economic structure and industrial cities, and regions entered a downsizing spiral of population loss after the breakdown of traditional industries, outmigration and suburbanization. Post-socialist Europe forms a new ‘pole of shrinkage’. Set within the regional context, deindustrialization and urban shrinkage show a solid cause-effect relationship in the Romanian case. The industrial change of cities creates a pattern of uneven growth which stays at the core of understanding the emerging urban shrinkage. The paper finds out that 122 out of 260 towns had an above average Location Quotient (LQ of industrial employment in 1992 and about 5 million urban dwellers were under the threat of forthcoming deindustrialization. Towns of all demographic sizes were above average industrialized but mostly were medium-small and medium-big towns. They lost more than one quarter of the 1992 population number, significantly higher than in towns with below average LQ of industrial employment. At a large extent, the mix of urban, regional and industrial policies failed to reduce the social costs of deindustrialization. The policy response of spatial strategies, while avoiding the ‘one size fits all’ perspective, should be focused on placebased approach and should be built on economic diversification, complementarity and cooperation within the specific territorial context of small and medium-sized towns.
Influence of nano-material on the expansive and shrinkage soil behavior
International Nuclear Information System (INIS)
Taha, Mohd Raihan; Taha, Omer Muhie Eldeen
2012-01-01
This paper presents an experimental study performed on four types of soils mixed with three types of nano-material of different percentages. The expansion and shrinkage tests were conducted to investigate the effect of three type of nano-materials (nano-clay, nano-alumina, and nano-copper) additive on repressing strains in compacted residual soil mixed with different ratios of bentonite (S1 = 0 % bentonite, S2 = 5 % bentonite, S3 = 10 % bentonite, and S4 = 20 % bentonite). The soil specimens were compacted under the condition of maximum dry unit weight and optimum water content (w opt ) using standard compaction test. The physical and mechanical results of the treated samples were determined. The untreated soil values were used as control points for comparison purposes. It was found that with the addition of optimum percentage of nano-material, both the swell strain and shrinkage strain reduced. The results show that nano-material decreases the development of desiccation cracks on the surface of compacted samples without decrease in the hydraulic conductivity.
Method for determining the formation of shrinkage defects in the castings
Directory of Open Access Journals (Sweden)
R. Dyja
2011-10-01
Full Text Available Simple simulations of solidification of metals and alloys generally provide results for determining the temperature distribut ion in a given time or solidification time for the specific locations of the casting. These data allow to unambiguously determine the position of thermal centers. However, knowledge about the location of thermal centers is not synonymous with the information about the location of any shrinkage defects in the casting, because the physical behaviour of molten metal should be still considered. This paper presents authors’ own method of predicting the formation of shrinkage defects in the castings, basing on solidification simulation results, taking into account the basic rulesof behaviour of the molten metal. The effectiveness of the method has been tested on the basis of example simulations performed for the flat shape of the casting inlet systems. The advantage of the method is that it requires little additional computational effort. The article is summarized by conclusions reached on the basis of simulations, as well as the program for further work containing possible improvements of the algorithm.
Effect of Polyvinyl Acetate Stabilization on the Swelling-Shrinkage Properties of Expansive Soil
Directory of Open Access Journals (Sweden)
Jin Liu
2017-01-01
Full Text Available Polyvinyl acetate constitutes a class of polymers that can entirely dissolve in water to form a solution. In this study, polyvinyl acetate as a nontraditional chemical stabilizer was used in soil improvement. Laboratory tests were carried out to evaluate the effect of polyvinyl acetate on swelling-shrinkage properties of expansive soil. A series of shrink/swell tests were performed with adding polyvinyl acetate as amendment at a concentration 3 g/cm3 to four aggregate sizes in the range of 0–0.5 mm, 0.5–1 mm, 1-2 mm, and 2–5 mm and five concentrations 1.5 g/cm3, 3 g/cm3, 4.5 g/cm3, 6 g/cm3, and 9 g/cm3 to soils with aggregate size in the range of 0.5–1 mm for comparison of results with those of untreated soils. The results show that all the linear swelling ratio (LSWR and linear shrinkage ratio (LSHR values of the treated specimens decrease. SEM images and the test results indicate the achieved reduction in volume change of the soil tested using soil pore filling and particle encapsulation.
Influence of calcined mud on the mechanical properties and shrinkage of self-compacting concrete
Directory of Open Access Journals (Sweden)
Fatima Taieb
2018-01-01
Full Text Available The use of SCC has a particular interest in terms of sustainable development. Indeed, their specific formulation leads to a greater volume of dough than for common concretes, thus, a larger quantity of cement. However, for economical, ecological and technical reasons, it is sought to limit their cement content [1]. It is therefore necessary to almost always use mineral additions as a partial replacement for cement because the technology of self-compacting concretes can consume large quantities of fines, in this case calcinated mud issued from dams dredging sediments that can give and/or ameliorate characteristics and performances of this type of concretes. Four SCCs had been formulated from the same composition where the only percentage of calcinated mud of Chorfa (west of Algeria dam changed (0%, 10%, 20% and 30%. The effect of calcinated mud on characteristics at fresh state of SCC according to AFGC was quantified. Mechanical strengths and shrinkage deformation (total, autogenous, drying were evaluated. The results show the possibility to make SCCs with different dosages of calcinated mud having strengths that can defy those of the control SCC. The analysis of free deformations indicates the beneficial impact of the mud by contributing to decrease the amplitudes of the shrinkage compared to those of the control SCC.
Assessment and prediction of drying shrinkage cracking in bonded mortar overlays
International Nuclear Information System (INIS)
Beushausen, Hans; Chilwesa, Masuzyo
2013-01-01
Restrained drying shrinkage cracking was investigated on composite beams consisting of substrate concrete and bonded mortar overlays, and compared to the performance of the same mortars when subjected to the ring test. Stress development and cracking in the composite specimens were analytically modeled and predicted based on the measurement of relevant time-dependent material properties such as drying shrinkage, elastic modulus, tensile relaxation and tensile strength. Overlay cracking in the composite beams could be very well predicted with the analytical model. The ring test provided a useful qualitative comparison of the cracking performance of the mortars. The duration of curing was found to only have a minor influence on crack development. This was ascribed to the fact that prolonged curing has a beneficial effect on tensile strength at the onset of stress development, but is in the same time not beneficial to the values of tensile relaxation and elastic modulus. -- Highlights: •Parameter study on material characteristics influencing overlay cracking. •Analytical model gives good quantitative indication of overlay cracking. •Ring test presents good qualitative indication of overlay cracking. •Curing duration has little effect on overlay cracking
Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
Chen, Yi-Hau
2009-03-01
Case-control association studies often aim to investigate the role of genes and gene-environment interactions in terms of the underlying haplotypes (i.e., the combinations of alleles at multiple genetic loci along chromosomal regions). The goal of this article is to develop robust but efficient approaches to the estimation of disease odds-ratio parameters associated with haplotypes and haplotype-environment interactions. We consider "shrinkage" estimation techniques that can adaptively relax the model assumptions of Hardy-Weinberg-Equilibrium and gene-environment independence required by recently proposed efficient "retrospective" methods. Our proposal involves first development of a novel retrospective approach to the analysis of case-control data, one that is robust to the nature of the gene-environment distribution in the underlying population. Next, it involves shrinkage of the robust retrospective estimator toward a more precise, but model-dependent, retrospective estimator using novel empirical Bayes and penalized regression techniques. Methods for variance estimation are proposed based on asymptotic theories. Simulations and two data examples illustrate both the robustness and efficiency of the proposed methods.
A 3D Lattice Modelling Study of Drying Shrinkage Damage in Concrete Repair Systems
Directory of Open Access Journals (Sweden)
Mladena Luković
2016-07-01
Full Text Available Differential shrinkage between repair material and concrete substrate is considered to be the main cause of premature failure of repair systems. The magnitude of induced stresses depends on many factors, for example the degree of restraint, moisture gradients caused by curing and drying conditions, type of repair material, etc. Numerical simulations combined with experimental observations can be of great use when determining the influence of these parameters on the performance of repair systems. In this work, a lattice type model was used to simulate first the moisture transport inside a repair system and then the resulting damage as a function of time. 3D simulations were performed, and damage patterns were qualitatively verified with experimental results and cracking tendencies in different brittle and ductile materials. The influence of substrate surface preparation, bond strength between the two materials, and thickness of the repair material were investigated. Benefits of using a specially tailored fibre reinforced material, namely strain hardening cementitious composite (SHCC, for controlling the damage development due to drying shrinkage in concrete repairs was also examined.
A 3D Lattice Modelling Study of Drying Shrinkage Damage in Concrete Repair Systems.
Luković, Mladena; Šavija, Branko; Schlangen, Erik; Ye, Guang; van Breugel, Klaas
2016-07-14
Differential shrinkage between repair material and concrete substrate is considered to be the main cause of premature failure of repair systems. The magnitude of induced stresses depends on many factors, for example the degree of restraint, moisture gradients caused by curing and drying conditions, type of repair material, etc. Numerical simulations combined with experimental observations can be of great use when determining the influence of these parameters on the performance of repair systems. In this work, a lattice type model was used to simulate first the moisture transport inside a repair system and then the resulting damage as a function of time. 3D simulations were performed, and damage patterns were qualitatively verified with experimental results and cracking tendencies in different brittle and ductile materials. The influence of substrate surface preparation, bond strength between the two materials, and thickness of the repair material were investigated. Benefits of using a specially tailored fibre reinforced material, namely strain hardening cementitious composite (SHCC), for controlling the damage development due to drying shrinkage in concrete repairs was also examined.
Influence of vertical holes on creep and shrinkage of railway prestressed concrete sleepers
Li, Dan; Ngamkhanong, Chayut; Kaewunruen, Sakdirat
2017-09-01
Railway prestressed concrete sleepers (or railroad ties) must successfully perform two critical duties: first, to carry wheel loads from the rails to the ground; and second, to secure rail gauge for dynamic safe movements of trains. The second duty is often fouled by inappropriate design of the time-dependent behaviors due to their creep, shrinkage and elastic shortening responses of the materials. In addition, the concrete sleepers are often modified on construction sites to fit in other systems such as cables, signalling gears, drainage pipes, etc. Accordingly, this study is the world first to investigate creep and shrinkage effects on the railway prestressed concrete sleepers with vertical holes. This paper will highlight constitutive models of concrete materials within the railway sleepers under different environmental conditions over time. It will present a comparative investigation using a variety of methods to evaluate shortening effects in railway prestressed concrete sleepers. The outcome of this study will improve material design, which is very critical to the durability of railway track components.
A Nonparametric Bayesian Approach For Emission Tomography Reconstruction
International Nuclear Information System (INIS)
Barat, Eric; Dautremer, Thomas
2007-01-01
We introduce a PET reconstruction algorithm following a nonparametric Bayesian (NPB) approach. In contrast with Expectation Maximization (EM), the proposed technique does not rely on any space discretization. Namely, the activity distribution--normalized emission intensity of the spatial poisson process--is considered as a spatial probability density and observations are the projections of random emissions whose distribution has to be estimated. This approach is nonparametric in the sense that the quantity of interest belongs to the set of probability measures on R k (for reconstruction in k-dimensions) and it is Bayesian in the sense that we define a prior directly on this spatial measure. In this context, we propose to model the nonparametric probability density as an infinite mixture of multivariate normal distributions. As a prior for this mixture we consider a Dirichlet Process Mixture (DPM) with a Normal-Inverse Wishart (NIW) model as base distribution of the Dirichlet Process. As in EM-family reconstruction, we use a data augmentation scheme where the set of hidden variables are the emission locations for each observed line of response in the continuous object space. Thanks to the data augmentation, we propose a Markov Chain Monte Carlo (MCMC) algorithm (Gibbs sampler) which is able to generate draws from the posterior distribution of the spatial intensity. A difference with EM is that one step of the Gibbs sampler corresponds to the generation of emission locations while only the expected number of emissions per pixel/voxel is used in EM. Another key difference is that the estimated spatial intensity is a continuous function such that there is no need to compute a projection matrix. Finally, draws from the intensity posterior distribution allow the estimation of posterior functionnals like the variance or confidence intervals. Results are presented for simulated data based on a 2D brain phantom and compared to Bayesian MAP-EM
Smartphone technologies and Bayesian networks to assess shorebird habitat selection
Zeigler, Sara; Thieler, E. Robert; Gutierrez, Ben; Plant, Nathaniel G.; Hines, Megan K.; Fraser, James D.; Catlin, Daniel H.; Karpanty, Sarah M.
2017-01-01
Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, >30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection
Predicting coastal cliff erosion using a Bayesian probabilistic model
Hapke, Cheryl J.; Plant, Nathaniel G.
2010-01-01
Regional coastal cliff retreat is difficult to model due to the episodic nature of failures and the along-shore variability of retreat events. There is a growing demand, however, for predictive models that can be used to forecast areas vulnerable to coastal erosion hazards. Increasingly, probabilistic models are being employed that require data sets of high temporal density to define the joint probability density function that relates forcing variables (e.g. wave conditions) and initial conditions (e.g. cliff geometry) to erosion events. In this study we use a multi-parameter Bayesian network to investigate correlations between key variables that control and influence variations in cliff retreat processes. The network uses Bayesian statistical methods to estimate event probabilities using existing observations. Within this framework, we forecast the spatial distribution of cliff retreat along two stretches of cliffed coast in Southern California. The input parameters are the height and slope of the cliff, a descriptor of material strength based on the dominant cliff-forming lithology, and the long-term cliff erosion rate that represents prior behavior. The model is forced using predicted wave impact hours. Results demonstrate that the Bayesian approach is well-suited to the forward modeling of coastal cliff retreat, with the correct outcomes forecast in 70–90% of the modeled transects. The model also performs well in identifying specific locations of high cliff erosion, thus providing a foundation for hazard mapping. This approach can be employed to predict cliff erosion at time-scales ranging from storm events to the impacts of sea-level rise at the century-scale.
Bayesian networks for management of industrial risk
International Nuclear Information System (INIS)
Munteanu, P.; Debache, G.; Duval, C.
2008-01-01
This article presents the outlines of Bayesian networks modelling and argues for their interest in the probabilistic studies of industrial risk and reliability. A practical case representative of this type of study is presented in support of the argumentation. The article concludes on some research tracks aiming at improving the performances of the methods relying on Bayesian networks and at widening their application area in risk management. (authors)
MCMC for parameters estimation by bayesian approach
International Nuclear Information System (INIS)
Ait Saadi, H.; Ykhlef, F.; Guessoum, A.
2011-01-01
This article discusses the parameter estimation for dynamic system by a Bayesian approach associated with Markov Chain Monte Carlo methods (MCMC). The MCMC methods are powerful for approximating complex integrals, simulating joint distributions, and the estimation of marginal posterior distributions, or posterior means. The MetropolisHastings algorithm has been widely used in Bayesian inference to approximate posterior densities. Calibrating the proposal distribution is one of the main issues of MCMC simulation in order to accelerate the convergence.
Fully probabilistic design of hierarchical Bayesian models
Czech Academy of Sciences Publication Activity Database
Quinn, A.; Kárný, Miroslav; Guy, Tatiana Valentine
2016-01-01
Roč. 369, č. 1 (2016), s. 532-547 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Fully probabilistic design * Ideal distribution * Minimum cross- entropy principle * Bayesian conditioning * Kullback-Leibler divergence * Bayesian nonparametric modelling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.832, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0463052.pdf
Capturing Business Cycles from a Bayesian Viewpoint
大鋸, 崇
2011-01-01
This paper is a survey of empirical studies analyzing business cycles from the perspective of Bayesian econometrics. Kim and Nelson (1998) use a hybrid model; Dynamic factor model of Stock and Watson (1989) and Markov switching model of Hamilton (1989). From the point of view, it is more important dealing with non-linear and non-Gaussian econometric models, recently. Although the classical econometric approaches have difficulty in these models, the Bayesian's do easily. The fact leads heavy u...
Variations on Bayesian Prediction and Inference
2016-05-09
inference 2.2.1 Background There are a number of statistical inference problems that are not generally formulated via a full probability model...problem of inference about an unknown parameter, the Bayesian approach requires a full probability 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...the problem of inference about an unknown parameter, the Bayesian approach requires a full probability model/likelihood which can be an obstacle
A Bayesian classifier for symbol recognition
Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick
2007-01-01
URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...
Bayesian Inference of Tumor Hypoxia
Gunawan, R.; Tenti, G.; Sivaloganathan, S.
2009-12-01
Tumor hypoxia is a state of oxygen deprivation in tumors. It has been associated with aggressive tumor phenotypes and with increased resistance to conventional cancer therapies. In this study, we report on the application of Bayesian sequential analysis in estimating the most probable value of tumor hypoxia quantification based on immunohistochemical assays of a biomarker. The `gold standard' of tumor hypoxia assessment is a direct measurement of pO2 in vivo by the Eppendorf polarographic electrode, which is an invasive technique restricted to accessible sites and living tissues. An attractive alternative is immunohistochemical staining to detect proteins expressed by cells during hypoxia. Carbonic anhydrase IX (CAIX) is an enzyme expressed on the cell membrane during hypoxia to balance the immediate extracellular microenvironment. CAIX is widely regarded as a surrogate marker of chronic hypoxia in various cancers. The study was conducted with two different experimental procedures. The first data set was a group of three patients with invasive cervical carcinomas, from which five biopsies were obtained. Each of the biopsies was fully sectioned and from each section, the proportion of CAIX-positive cells was estimated. Measurements were made by image analysis of multiple deep sections cut through these biopsies, labeled for CAIX using both immunofluorescence and immunohistochemical techniques [1]. The second data set was a group of 24 patients, also with invasive cervical carcinomas, from which two biopsies were obtained. Bayesian parameter estimation was applied to obtain a reliable inference about the proportion of CAIX-positive cells within the carcinomas, based on the available biopsies. From the first data set, two to three biopsies were found to be sufficient to infer the overall CAIX percentage in the simple form: best estimate±uncertainty. The second data-set led to a similar result in 70% of the cases. In the remaining cases Bayes' theorem warned us
Philosophy and the practice of Bayesian statistics.
Gelman, Andrew; Shalizi, Cosma Rohilla
2013-02-01
A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. © 2012 The British Psychological Society.
Philosophy and the practice of Bayesian statistics
Gelman, Andrew; Shalizi, Cosma Rohilla
2015-01-01
A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. PMID:22364575
Doskey, Steven Craig
2014-01-01
This research presents an innovative means of gauging Systems Engineering effectiveness through a Systems Engineering Relative Effectiveness Index (SE REI) model. The SE REI model uses a Bayesian Belief Network to map causal relationships in government acquisitions of Complex Information Systems (CIS), enabling practitioners to identify and…
Power Mapping and Noise Reduction for Financial Correlations
International Nuclear Information System (INIS)
Andersson, P.-J.; Oeberg, A.; Guhr, T.
2005-01-01
The spectral properties of financial correlation matrices can show features known from completely random matrices. A major reason is noise originating from the finite lengths of the financial time series used to compute the correlation matrix elements. In recent years, various methods have been proposed to reduce this noise, i.e. to clean the correlation matrices. This is of direct practical relevance for risk management in portfolio optimization. In this contribution, we discuss in detail the power mapping, a new shrinkage method. We show that the relevant parameter is, to a certain extent, self-determined. Due to the 'hirality' and the normalization of the correlation matrix, the optimal shrinkage parameter is fixed. We apply the power mapping and the well-known filtering method to market data and compare them by optimizing stock portfolios. We address the role of constraints by excluding short selling in the optimization. (author)
Directory of Open Access Journals (Sweden)
Chepurnenko Anton Sergeevich
2016-12-01
Full Text Available The task of comprehensive analysis presented in this article is a development of theory of calculation of shrinkage stresses in cellular concrete wall panels; such stresses occur due to carbonation of concrete because of the creep of material. Analytical dependences characterizing the influence of carbonation on the modulus of elasticity, shrinkage and creep of autoclaved cellular concrete, as well as the regularity of variation of carbonation degree as per thickness of the wall panels depending on time, were obtained. The proposed theory of calculation of shrinkage stresses in cellular concrete wall panels, with account of concrete creep, makes it possible to predict the influence of carbonation processes on crack resistance thereof, and thus to develop measures of technological and structural nature, in order to improve their operational reliability and durability.
DEFF Research Database (Denmark)
Schmidt, Malene; Dige, Irene; Kirkevang, Lise-Lotte
2015-01-01
Objectives The aim of the present study was to investigate the clinical performance of a low-shrinkage silorane-based composite material (Filtek™ Silorane, 3 M-Espe) by comparing it with a methacrylate-based composite material (Ceram•X™, Dentsply DeTrey). Material and methods A number of 72patients...... caries was found in two teeth (Filtek™ Silorane). One tooth showed hypersensitivity (Ceram•X™). Conclusion Restorations of both materials were clinically acceptable after 5 years. This study did not find any advantage of the silorane-based composite over the methacrylate-based composite, which indicates...... that the low-shrinkage of Filtek™ Silorane may not be a determinant factor for clinical success in class II cavities. Clinical relevance This paper is the first to evaluate the 5-year clinical performance of a low-shrinkage composite material....
First time observation of local current shrinkage during the MARFE behavior on the J-TEXT tokamak
Shi, Peng; Zhuang, G.; Gentle, K.; Hu, Qiming; Chen, Jie; Li, Qiang; Liu, Yang; Gao, Li; Zhang, Xiaolong; Liu, Hai; Chen, Zhipeng; Zhu, Lizhi; Li, Fuming; Zhou, Yinan; Zeng, Zhong; Liu, Linzi; He, Jiyang
2017-11-01
Multifaceted asymmetric radiation as well as strong poloidal asymmetry of the electron density from the edge, dubbed as ‘MARFE’, has been observed in high electron density Ohmically heated plasmas on J-TEXT tokamak. Equilibrium reconstruction based on the measured data from the 17-channel FIR polarimeter-interferometer indicates that an asymmetric plasma current density distribution forms at the edge region and the plasma current shrinkage locates at the MARFE affected region. Furthermore, associated with the localized plasma current shrinkage, a locked mode MHD activity is excited, which then terminate the discharge with a major disruption. Localized plasma current shrinkage at the MARFE region is considered to be the direct cause for the density limit disruptions, and the proposed interpretation is consistent with the experimental observations.
EXONEST: The Bayesian Exoplanetary Explorer
Directory of Open Access Journals (Sweden)
Kevin H. Knuth
2017-10-01
Full Text Available The fields of astronomy and astrophysics are currently engaged in an unprecedented era of discovery as recent missions have revealed thousands of exoplanets orbiting other stars. While the Kepler Space Telescope mission has enabled most of these exoplanets to be detected by identifying transiting events, exoplanets often exhibit additional photometric effects that can be used to improve the characterization of exoplanets. The EXONEST Exoplanetary Explorer is a Bayesian exoplanet inference engine based on nested sampling and originally designed to analyze archived Kepler Space Telescope and CoRoT (Convection Rotation et Transits planétaires exoplanet mission data. We discuss the EXONEST software package and describe how it accommodates plug-and-play models of exoplanet-associated photometric effects for the purpose of exoplanet detection, characterization and scientific hypothesis testing. The current suite of models allows for both circular and eccentric orbits in conjunction with photometric effects, such as the primary transit and secondary eclipse, reflected light, thermal emissions, ellipsoidal variations, Doppler beaming and superrotation. We discuss our new efforts to expand the capabilities of the software to include more subtle photometric effects involving reflected and refracted light. We discuss the EXONEST inference engine design and introduce our plans to port the current MATLAB-based EXONEST software package over to the next generation Exoplanetary Explorer, which will be a Python-based open source project with the capability to employ third-party plug-and-play models of exoplanet-related photometric effects.
Maximum entropy and Bayesian methods
International Nuclear Information System (INIS)
Smith, C.R.; Erickson, G.J.; Neudorfer, P.O.
1992-01-01
Bayesian probability theory and Maximum Entropy methods are at the core of a new view of scientific inference. These 'new' ideas, along with the revolution in computational methods afforded by modern computers allow astronomers, electrical engineers, image processors of any type, NMR chemists and physicists, and anyone at all who has to deal with incomplete and noisy data, to take advantage of methods that, in the past, have been applied only in some areas of theoretical physics. The title workshops have been the focus of a group of researchers from many different fields, and this diversity is evident in this book. There are tutorial and theoretical papers, and applications in a very wide variety of fields. Almost any instance of dealing with incomplete and noisy data can be usefully treated by these methods, and many areas of theoretical research are being enhanced by the thoughtful application of Bayes' theorem. Contributions contained in this volume present a state-of-the-art overview that will be influential and useful for many years to come
Data Assimilation with Optimal Maps
El Moselhy, T.; Marzouk, Y.
2012-12-01
Tarek El Moselhy and Youssef Marzouk Massachusetts Institute of Technology We present a new approach to Bayesian inference that entirely avoids Markov chain simulation and sequential importance resampling, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. The map is written as a multivariate polynomial expansion and computed efficiently through the solution of a stochastic optimization problem. While our previous work [1] focused on static Bayesian inference problems, we now extend the map-based approach to sequential data assimilation, i.e., nonlinear filtering and smoothing. One scheme involves pushing forward a fixed reference measure to each filtered state distribution, while an alternative scheme computes maps that push forward the filtering distribution from one stage to the other. We compare the performance of these schemes and extend the former to problems of smoothing, using a map implementation of the forward-backward smoothing formula. Advantages of a map-based representation of the filtering and smoothing distributions include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent uniformly-weighted posterior samples without additional evaluations of the dynamical model. Perhaps the main advantage, however, is that the map approach inherently avoids issues of sample impoverishment, since it explicitly represents the posterior as the pushforward of a reference measure, rather than with a particular set of samples. The computational complexity of our algorithm is comparable to state-of-the-art particle filters. Moreover, the accuracy of the approach is controlled via the convergence criterion of the underlying optimization problem. We demonstrate the efficiency and accuracy of the map approach via data assimilation in