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Sample records for bayesian shrinkage mapping

  1. 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...

  2. 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.

  3. Radiation Source Mapping with Bayesian Inverse Methods

    Science.gov (United States)

    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

  4. Bayesian and maximum likelihood estimation of genetic maps

    DEFF Research Database (Denmark)

    York, Thomas L.; Durrett, Richard T.; Tanksley, Steven

    2005-01-01

    There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods...... of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances....

  5. 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...

  6. Sequential Inverse Problems Bayesian Principles and the Logistic Map Example

    Science.gov (United States)

    Duan, Lian; Farmer, Chris L.; Moroz, Irene M.

    2010-09-01

    Bayesian statistics provides a general framework for solving inverse problems, but is not without interpretation and implementation problems. This paper discusses difficulties arising from the fact that forward models are always in error to some extent. Using a simple example based on the one-dimensional logistic map, we argue that, when implementation problems are minimal, the Bayesian framework is quite adequate. In this paper the Bayesian Filter is shown to be able to recover excellent state estimates in the perfect model scenario (PMS) and to distinguish the PMS from the imperfect model scenario (IMS). Through a quantitative comparison of the way in which the observations are assimilated in both the PMS and the IMS scenarios, we suggest that one can, sometimes, measure the degree of imperfection.

  7. A Bayesian framework for cosmic string searches in CMB maps

    Energy Technology Data Exchange (ETDEWEB)

    Ciuca, Razvan; Hernández, Oscar F., E-mail: razvan.ciuca@mail.mcgill.ca, E-mail: oscarh@physics.mcgill.ca [Department of Physics, McGill University, 3600 rue University, Montréal, QC, H3A 2T8 (Canada)

    2017-08-01

    There exists various proposals to detect cosmic strings from Cosmic Microwave Background (CMB) or 21 cm temperature maps. Current proposals do not aim to find the location of strings on sky maps, all of these approaches can be thought of as a statistic on a sky map. We propose a Bayesian interpretation of cosmic string detection and within that framework, we derive a connection between estimates of cosmic string locations and cosmic string tension G μ. We use this Bayesian framework to develop a machine learning framework for detecting strings from sky maps and outline how to implement this framework with neural networks. The neural network we trained was able to detect and locate cosmic strings on noiseless CMB temperature map down to a string tension of G μ=5 ×10{sup −9} and when analyzing a CMB temperature map that does not contain strings, the neural network gives a 0.95 probability that G μ≤2.3×10{sup −9}.

  8. MAP estimators and their consistency in Bayesian nonparametric inverse problems

    KAUST Repository

    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.

  9. MAP estimators and their consistency in Bayesian nonparametric inverse problems

    International Nuclear Information System (INIS)

    Dashti, M; Law, K J H; Stuart, A M; Voss, J

    2013-01-01

    We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map G 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 μ 0 . We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μ y . 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 G(u) 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. (paper)

  10. 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...

  11. Empirical Bayesian Geographical Mapping of Occupational Accidents among Iranian Workers.

    Science.gov (United States)

    Vahabi, Nasim; Kazemnejad, Anoshirvan; Datta, Somnath

    2017-05-01

    Work-related accidents are believed to be a serious preventable cause of mortality and disability worldwide. This study aimed to provide Bayesian geographical maps of occupational injury rates among workers insured by the Iranian Social Security Organization. The participants included all insured workers in the Iranian Social Security Organization database in 2012. One of the applications of the Bayesian approach called the Poisson-Gamma model was applied to estimate the relative risk of occupational accidents. Data analysis and mapping were performed using R 3.0.3, Open-Bugs 3.2.3 rev 1012 and ArcMap9.3. The majority of all 21,484 investigated occupational injury victims were male (98.3%) including 16,443 (76.5%) single workers aged 20 - 29 years. The accidents were more frequent in basic metal, electric, and non-electric machining jobs. About 0.4% (96) of work-related accidents led to death, 2.2% (457) led to disability (partial and total), 4.6% (980) led to fixed compensation, and 92.8% (19,951) of the injured victims recovered completely. The geographical maps of estimated relative risk of occupational accidents were also provided. The results showed that the highest estimations pertained to provinces which were mostly located along mountain chains, some of which are categorized as deprived provinces in Iran. The study revealed the need for further investigation of the role of economic and climatic factors in high risk areas. The application of geographical mapping together with statistical approaches can provide more accurate tools for policy makers to make better decisions in order to prevent and reduce the risks and adverse outcomes of work-related accidents.

  12. Inferring the most probable maps of underground utilities using Bayesian mapping model

    Science.gov (United States)

    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.

  13. 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...

  14. 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

    Motivation: The evolution of protein sequences is constrained by complex interactions between amino acid residues. Because harmful substitutions may be compensated for by other substitutions at neighboring sites, residues can coevolve. We describe a Bayesian phylogenetic approach to the detection...

  15. GENERALIZED DOUBLE PARETO SHRINKAGE.

    Science.gov (United States)

    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.

  16. Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information.

    NARCIS (Netherlands)

    Brus, D.J.; Bogaert, P.; Heuvelink, G.B.M.

    2008-01-01

    Bayesian Maximum Entropy was used to estimate the probabilities of occurrence of soil categories in the Netherlands, and to simulate realizations from the associated multi-point pdf. Besides the hard observations (H) of the categories at 8369 locations, the soil map of the Netherlands 1:50 000 was

  17. On Bayesian shared component disease mapping and ecological regression with errors in covariates.

    Science.gov (United States)

    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.

  18. Transport maps and dimension reduction for Bayesian computation

    KAUST Repository

    Marzouk, Youssef

    2015-01-01

    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

  19. Transport maps and dimension reduction for Bayesian computation

    KAUST Repository

    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

  20. Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network

    Science.gov (United States)

    Mukashema, A.; Veldkamp, A.; Vrieling, A.

    2014-12-01

    African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2 = 0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.

  1. MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

    Science.gov (United States)

    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.

  2. Methods for measuring shrinkage

    OpenAIRE

    Chapman, Paul; Templar, Simon

    2006-01-01

    This paper presents findings from research amongst European grocery retailers into their methods for measuring shrinkage. The findings indicate that: there is no dominant method for valuing or stating shrinkage; shrinkage in the supply chain is frequently overlooked; data is essential in pinpointing where and when loss occurs and that many retailers collect data at the stock-keeping unit (SKU) level and do so every 6 months. These findings reveal that it is difficult to benc...

  3. REMOVING BIASES IN RESOLVED STELLAR MASS MAPS OF GALAXY DISKS THROUGH SUCCESSIVE BAYESIAN MARGINALIZATION

    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.

  4. An automated land-use mapping comparison of the Bayesian maximum likelihood and linear discriminant analysis algorithms

    Science.gov (United States)

    Tom, C. H.; Miller, L. D.

    1984-01-01

    The Bayesian maximum likelihood parametric classifier has been tested against the data-based formulation designated 'linear discrimination analysis', using the 'GLIKE' decision and "CLASSIFY' classification algorithms in the Landsat Mapping System. Identical supervised training sets, USGS land use/land cover classes, and various combinations of Landsat image and ancilliary geodata variables, were used to compare the algorithms' thematic mapping accuracy on a single-date summer subscene, with a cellularized USGS land use map of the same time frame furnishing the ground truth reference. CLASSIFY, which accepts a priori class probabilities, is found to be more accurate than GLIKE, which assumes equal class occurrences, for all three mapping variable sets and both levels of detail. These results may be generalized to direct accuracy, time, cost, and flexibility advantages of linear discriminant analysis over Bayesian methods.

  5. 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.

  6. System Analysis by Mapping a Fault-tree into a Bayesian-network

    Science.gov (United States)

    Sheng, B.; Deng, C.; Wang, Y. H.; Tang, L. H.

    2018-05-01

    In view of the limitations of fault tree analysis in reliability assessment, Bayesian Network (BN) has been studied as an alternative technology. After a brief introduction to the method for mapping a Fault Tree (FT) into an equivalent BN, equations used to calculate the structure importance degree, the probability importance degree and the critical importance degree are presented. Furthermore, the correctness of these equations is proved mathematically. Combining with an aircraft landing gear’s FT, an equivalent BN is developed and analysed. The results show that richer and more accurate information have been achieved through the BN method than the FT, which demonstrates that the BN is a superior technique in both reliability assessment and fault diagnosis.

  7. Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping.

    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.

  8. Bayesian mapping of HIV infection among women of reproductive age in Rwanda.

    Directory of Open Access Journals (Sweden)

    François Niragire

    Full Text Available HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.

  9. Bayesian mapping of HIV infection among women of reproductive age in Rwanda.

    Science.gov (United States)

    Niragire, François; Achia, Thomas N O; Lyambabaje, Alexandre; Ntaganira, Joseph

    2015-01-01

    HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.

  10. A Bayesian and Physics-Based Ground Motion Parameters Map Generation System

    Science.gov (United States)

    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

  11. Implementation of bayesian model averaging on the weather data forecasting applications utilizing open weather map

    Science.gov (United States)

    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.

  12. Landslide Susceptibility Mapping of Tegucigalpa, Honduras Using Artificial Neural Network, Bayesian Network and Decision Trees

    Science.gov (United States)

    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

  13. Shrinkage Reducing Admixture for Concrete

    OpenAIRE

    ECT Team, Purdue

    2007-01-01

    Concrete shrinkage cracking is a common problem in all types of concrete structures, especially for structures and environments where the cracks are prevalent and the repercussions are most severe. A liquid shrinkage reducing admixture for concrete, developed by GRACE Construction Products and ARCO Chemical Company, that reduces significantly the shrinkage during concrete drying and potentially reduces overall cracking over time.

  14. 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.

  15. The Bayesian Covariance Lasso.

    Science.gov (United States)

    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.

  16. AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

    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.

  17. AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

    Science.gov (United States)

    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.

  18. Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist

    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.

  19. 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

  20. Evaluating Spatial Variability in Sediment and Phosphorus Concentration-Discharge Relationships Using Bayesian Inference and Self-Organizing Maps

    Science.gov (United States)

    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.

  1. Spatiotemporal analysis and mapping of oral cancer risk in changhua county (taiwan): an application of generalized bayesian maximum entropy method.

    Science.gov (United States)

    Yu, Hwa-Lung; Chiang, Chi-Ting; Lin, Shu-De; Chang, Tsun-Kuo

    2010-02-01

    Incidence rate of oral cancer in Changhua County is the highest among the 23 counties of Taiwan during 2001. However, in health data analysis, crude or adjusted incidence rates of a rare event (e.g., cancer) for small populations often exhibit high variances and are, thus, less reliable. We proposed a generalized Bayesian Maximum Entropy (GBME) analysis of spatiotemporal disease mapping under conditions of considerable data uncertainty. GBME was used to study the oral cancer population incidence in Changhua County (Taiwan). Methodologically, GBME is based on an epistematics principles framework and generates spatiotemporal estimates of oral cancer incidence rates. In a way, it accounts for the multi-sourced uncertainty of rates, including small population effects, and the composite space-time dependence of rare events in terms of an extended Poisson-based semivariogram. The results showed that GBME analysis alleviates the noises of oral cancer data from population size effect. Comparing to the raw incidence data, the maps of GBME-estimated results can identify high risk oral cancer regions in Changhua County, where the prevalence of betel quid chewing and cigarette smoking is relatively higher than the rest of the areas. GBME method is a valuable tool for spatiotemporal disease mapping under conditions of uncertainty. 2010 Elsevier Inc. All rights reserved.

  2. DAFNE: A Matlab toolbox for Bayesian multi-source remote sensing and ancillary data fusion, with application to flood mapping

    Science.gov (United States)

    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.

  3. Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

    Science.gov (United States)

    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.

  4. Thermal Shrinkage for Shoulder Instability

    OpenAIRE

    Toth, Alison P.; Warren, Russell F.; Petrigliano, Frank A.; Doward, David A.; Cordasco, Frank A.; Altchek, David W.; O’Brien, Stephen J.

    2010-01-01

    Thermal capsular shrinkage was popular for the treatment of shoulder instability, despite a paucity of outcomes data in the literature defining the indications for this procedure or supporting its long-term efficacy. The purpose of this study was to perform a clinical evaluation of radiofrequency thermal capsular shrinkage for the treatment of shoulder instability, with a minimum 2-year follow-up. From 1999 to 2001, 101 consecutive patients with mild to moderate shoulder instability underwent...

  5. Bayesian feature weighting for unsupervised learning, with application to object recognition

    OpenAIRE

    Carbonetto , Peter; De Freitas , Nando; Gustafson , Paul; Thompson , Natalie

    2003-01-01

    International audience; We present a method for variable selection/weighting in an unsupervised learning context using Bayesian shrinkage. The basis for the model parameters and cluster assignments can be computed simultaneous using an efficient EM algorithm. Applying our Bayesian shrinkage model to a complex problem in object recognition (Duygulu, Barnard, de Freitas and Forsyth 2002), our experiments yied good results.

  6. Mapping and prediction of schistosomiasis in Nigeria using compiled survey data and Bayesian geospatial modelling

    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...

  7. 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...

  8. Mapping brucellosis increases relative to elk density using hierarchical Bayesian models

    Science.gov (United States)

    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.

  9. 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.

  10. Mapas de taxas epidemiológicas: uma abordagem Bayesiana Maps of epidemiological rates: a Bayesian approach

    Directory of Open Access Journals (Sweden)

    Renato Martins Assunção

    1998-10-01

    Full Text Available Neste artigo, apresentamos métodos estatísticos desenvolvidos recentemente para a análise de mapas de taxas de morbidade quando as unidades geográficas possuem pequenas populações de risco. Eles adotam a abordagem Bayesiana e utilizam métodos computacionais intensivos para estimação do risco de cada área. O objetivo dos métodos é separar a variabilidade das taxas devida às diferenças entre as regiões do risco subjacente daquela devida à pura flutuação aleatória. As estimativas de risco possuem um erro quadrático médio total menor que as estimativas usuais. Aplicamos esses novos métodos para estimar o risco de mortalidade infantil nos municípios de Minas Gerais em 1994.This article presents statistical methods recently developed for the analysis of maps of disease rates when the geographic units have small populations at risk. They adopt the Bayesian approach and use intensive computational methods for estimating risk in each area. The objective of the methods is to separate the variability of rates due to differences between regions from the background risk due to pure random fluctuation. Risk estimates have a total mean quadratic error smaller than usual estimates. We apply these new methods to estimate infant mortality risk in the municipalities of the State of Minas Gerais in 1994.

  11. Thermal shrinkage for shoulder instability.

    Science.gov (United States)

    Toth, Alison P; Warren, Russell F; Petrigliano, Frank A; Doward, David A; Cordasco, Frank A; Altchek, David W; O'Brien, Stephen J

    2011-07-01

    Thermal capsular shrinkage was popular for the treatment of shoulder instability, despite a paucity of outcomes data in the literature defining the indications for this procedure or supporting its long-term efficacy. The purpose of this study was to perform a clinical evaluation of radiofrequency thermal capsular shrinkage for the treatment of shoulder instability, with a minimum 2-year follow-up. From 1999 to 2001, 101 consecutive patients with mild to moderate shoulder instability underwent shoulder stabilization surgery with thermal capsular shrinkage using a monopolar radiofrequency device. Follow-up included a subjective outcome questionnaire, discussion of pain, instability, and activity level. Mean follow-up was 3.3 years (range 2.0-4.7 years). The thermal capsular shrinkage procedure failed due to instability and/or pain in 31% of shoulders at a mean time of 39 months. In patients with unidirectional anterior instability and those with concomitant labral repair, the procedure proved effective. Patients with multidirectional instability had moderate success. In contrast, four of five patients with isolated posterior instability failed. Thermal capsular shrinkage has been advocated for the treatment of shoulder instability, particularly mild to moderate capsular laxity. The ease of the procedure makes it attractive. However, our retrospective review revealed an overall failure rate of 31% in 80 patients with 2-year minimum follow-up. This mid- to long-term cohort study adds to the literature lacking support for thermal capsulorrhaphy in general, particularly posterior instability. The online version of this article (doi:10.1007/s11420-010-9187-7) contains supplementary material, which is available to authorized users.

  12. 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.

  13. 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.

  14. A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

    Science.gov (United States)

    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.

  15. 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

  16. Mitigation strategies for autogenous shrinkage cracking

    DEFF Research Database (Denmark)

    Bentz, Dale P.; Jensen, Ole Mejlhede

    2004-01-01

    As the use of high-performance concrete has increased, problems with early-age cracking have become prominent. The reduction in water-to-cement ratio, the incorporation of silica fume, and the increase in binder content of high-performance concretes all contribute to this problem. In this paper......, the fundamental parameters contributing to the autogenous shrinkage and resultant early-age cracking of concrete are presented. Basic characteristics of the cement paste that contribute to or control the autogenous shrinkage response include the surface tension of the pore solution, the geometry of the pore...... of early-age cracking due to autogenous shrinkage. Mitigation strategies discussed in this paper include: the addition of shrinkage-reducing admixtures more commonly used to control drying shrinkage, control of the cement particle size distribution, modification of the mineralogical composition...

  17. Bayesian analysis in plant pathology.

    Science.gov (United States)

    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.

  18. Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: an empirical analysis converting SF-12 into EQ-5D utility index in a national US sample.

    Science.gov (United States)

    Le, Quang A; Doctor, Jason N

    2011-05-01

    As quality-adjusted life years have become the standard metric in health economic evaluations, mapping health-profile or disease-specific measures onto preference-based measures to obtain quality-adjusted life years has become a solution when health utilities are not directly available. However, current mapping methods are limited due to their predictive validity, reliability, and/or other methodological issues. We employ probability theory together with a graphical model, called a Bayesian network, to convert health-profile measures into preference-based measures and to compare the results to those estimated with current mapping methods. A sample of 19,678 adults who completed both the 12-item Short Form Health Survey (SF-12v2) and EuroQoL 5D (EQ-5D) questionnaires from the 2003 Medical Expenditure Panel Survey was split into training and validation sets. Bayesian networks were constructed to explore the probabilistic relationships between each EQ-5D domain and 12 items of the SF-12v2. The EQ-5D utility scores were estimated on the basis of the predicted probability of each response level of the 5 EQ-5D domains obtained from the Bayesian inference process using the following methods: Monte Carlo simulation, expected utility, and most-likely probability. Results were then compared with current mapping methods including multinomial logistic regression, ordinary least squares, and censored least absolute deviations. The Bayesian networks consistently outperformed other mapping models in the overall sample (mean absolute error=0.077, mean square error=0.013, and R overall=0.802), in different age groups, number of chronic conditions, and ranges of the EQ-5D index. Bayesian networks provide a new robust and natural approach to map health status responses into health utility measures for health economic evaluations.

  19. A novel image fusion algorithm based on 2D scale-mixing complex wavelet transform and Bayesian MAP estimation for multimodal medical images

    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.

  20. Bayesian LASSO, scale space and decision making in association genetics.

    Science.gov (United States)

    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.

  1. Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills.

    Science.gov (United States)

    Achilles, Elisabeth I S; Weiss, Peter H; Fink, Gereon R; Binder, Ellen; Price, Cathy J; Hope, Thomas M H

    2017-11-01

    Past attempts to identify the neural substrates of hand and finger imitation skills in the left hemisphere of the brain have yielded inconsistent results. Here, we analyse those associations in a large sample of 257 left hemisphere stroke patients. By introducing novel Bayesian methods, we characterise lesion symptom associations at three levels: the voxel-level, the single-region level (using anatomically defined regions), and the region-pair level. The results are inconsistent across those three levels and we argue that each level of analysis makes assumptions which constrain the results it can produce. Regardless of the inconsistencies across levels, and contrary to past studies which implicated differential neural substrates for hand and finger imitation, we find no consistent voxels or regions, where damage affects one imitation skill and not the other, at any of the three analysis levels. Our novel Bayesian approach indicates that any apparent differences appear to be driven by an increased sensitivity of hand imitation skills to lesions that also impair finger imitation. In our analyses, the results of the highest level of analysis (region-pairs) emphasise a role of the primary somatosensory and motor cortices, and the occipital lobe in imitation. We argue that this emphasis supports an account of both imitation tasks based on direct sensor-motor connections, which throws doubt on past accounts which imply the need for an intermediate (e.g. body-part-coding) system of representation. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  2. Disease Mapping and Regression with Count Data in the Presence of Overdispersion and Spatial Autocorrelation: A Bayesian Model Averaging Approach

    Science.gov (United States)

    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

  3. 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.

  4. Volumetric polymerization shrinkage of contemporary composite resins

    OpenAIRE

    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 ...

  5. Bayesian nonparametric areal wombling for small-scale maps with an application to urinary bladder cancer data from Connecticut.

    Science.gov (United States)

    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.

  6. Risk mapping of clonorchiasis in the People's Republic of China: A systematic review and Bayesian geostatistical analysis.

    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

  7. Bayesian Simultaneous Estimation for Means in k Sample Problems

    OpenAIRE

    Imai, Ryo; Kubokawa, Tatsuya; Ghosh, Malay

    2017-01-01

    This paper is concerned with the simultaneous estimation of k population means when one suspects that the k means are nearly equal. As an alternative to the preliminary test estimator based on the test statistics for testing hypothesis of equal means, we derive Bayesian and minimax estimators which shrink individual sample means toward a pooled mean estimator given under the hypothesis. Interestingly, it is shown that both the preliminary test estimator and the Bayesian minimax shrinkage esti...

  8. Polymerization shrinkage kinetics and shrinkage-stress in dental resin-composites.

    Science.gov (United States)

    Al Sunbul, Hanan; Silikas, Nick; Watts, David C

    2016-08-01

    To investigate a set of resin-composites and the effect of their composition on polymerization shrinkage strain and strain kinetics, shrinkage stress and the apparent elastic modulus. Eighteen commercially available resin-composites were investigated. Three specimens (n=3) were made per material and light-cured with an LED unit (1200mW/cm(2)) for 20s. The bonded-disk method was used to measure the shrinkage strain and Bioman shrinkage stress instrument was used to measure shrinkage stress. The shrinkage strain kinetics at 23°C was monitored for 60min. Maximum strain and stress was evaluated at 60min. The shrinkage strain rate was calculated using numerical differentiation. The shrinkage strain values ranged from 1.83 (0.09) % for Tetric Evoceram (TEC) to 4.68 (0.04) % for Beautifil flow plus (BFP). The shrinkage strain rate ranged from 0.11 (0.01%s(-1)) for Gaenial posterior (GA-P) to 0.59 (0.07) %s(-1) for BFP. Shrinkage stress values ranged from 3.94 (0.40)MPa for TET to 10.45 (0.41)MPa for BFP. The apparent elastic modulus ranged from 153.56 (18.7)MPa for Ever X posterior (EVX) to 277.34 (25.5) MPa for Grandio SO heavy flow (GSO). The nature of the monomer system determines the amount of the bulk contraction that occurs during polymerization and the resultant stress. Higher values of shrinkage strain and stress were demonstrated by the investigated flowable materials. The bulk-fill materials showed comparable result when compared to the traditional resin-composites. Copyright © 2016 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

  9. Bayesian biostatistics

    CERN Document Server

    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

  10. 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...

  11. 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)

  12. 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).

  13. Bayesian image reconstruction for improving detection performance of muon tomography.

    Science.gov (United States)

    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.

  14. Bayesian Utilitarianism

    OpenAIRE

    ZHOU, Lin

    1996-01-01

    In this paper I consider social choices under uncertainty. I prove that any social choice rule that satisfies independence of irrelevant alternatives, translation invariance, and weak anonymity is consistent with ex post Bayesian utilitarianism

  15. 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)

  16. 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)

  17. 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.

  18. 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

  19. 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 ...

  20. 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

  1. Shrinkage Approach for Gene Expression Data Analysis

    Czech Academy of Sciences Publication Activity Database

    Haman, Jiří; Valenta, Zdeněk; Kalina, Jan

    2013-01-01

    Roč. 1, č. 1 (2013), s. 65-65 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : shrinkage estimation * covariance matrix * high dimensional data * gene expression Subject RIV: IN - Informatics, Computer Science

  2. Drying shrinkage problems in high PI subgrade soils.

    Science.gov (United States)

    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...

  3. 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...... 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....

  4. The shrinkage of hardening cement paste and mortar

    NARCIS (Netherlands)

    Haas, de G.D.; Kreijger, P.C.; Niël, E.M.M.G.; Slagter, J.C.; Stein, H.N.; Theissing, E.M.; Wallendael, van M.

    1975-01-01

    This paper is an abstract from the report of the commission B10: "The influence of the shrinkage of cement on the shrink-age of concrete", of the Netherlands Committee for Concrete Research. Measurements of pulse velocity, volume shrinkage and heat of hydration on hardening portland cement support

  5. Effect of Dolomite as Expansive Agent and Shrinkage Reducing Admixture in Self-Compacting Shrinkage – Compensating Concrete

    OpenAIRE

    Qosai Sahib Radi Marshdi; Ahlam Hamid Jasim; Haider Abass Obeed

    2018-01-01

    The principle of using expansive agents has been recommended to manufacture shrinkage compensating concrete provided that an adequate wet curing is carried out. On the other hand, shrinkage-reducing admixture (SRA) in the concrete mixes, has been more recently suggested to reduce the risk of cracking in concrete structures caused by drying shrinkage. This paper is devoted to the study of the influence of complex modifier in the form of superplasticizer, shrinkage reducing admixture and e...

  6. Shrinkage measurement for holographic recording materials

    Science.gov (United States)

    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).

  7. Shrinkage deformation of cement foam concrete

    Science.gov (United States)

    Kudyakov, A. I.; Steshenko, A. B.

    2015-01-01

    The article presents the results of research of dispersion-reinforced cement foam concrete with chrysotile asbestos fibers. The goal was to study the patterns of influence of chrysotile asbestos fibers on drying shrinkage deformation of cement foam concrete of natural hardening. The chrysotile asbestos fiber contains cylindrical fiber shaped particles with a diameter of 0.55 micron to 8 microns, which are composed of nanostructures of the same form with diameters up to 55 nm and length up to 22 microns. Taking into account the wall thickness, effective reinforcement can be achieved only by microtube foam materials, the so- called carbon nanotubes, the dimensions of which are of power less that the wall pore diameter. The presence of not reinforced foam concrete pores with perforated walls causes a decrease in its strength, decreases the mechanical properties of the investigated material and increases its shrinkage. The microstructure investigation results have shown that introduction of chrysotile asbestos fibers in an amount of 2 % by weight of cement provides the finely porous foam concrete structure with more uniform size closed pores, which are uniformly distributed over the volume. This reduces the shrinkage deformation of foam concrete by 50%.

  8. Reducing Shrinkage in Canned and Frozen Mushrooms

    OpenAIRE

    Gormley, T. R. (Thomas Ronan); Walshe, P.E.

    1982-01-01

    The process involving a preliminary soaking of the mushrooms in water for 20 min followed by a chill storage period followed by a further water soak for 2 hr, and known as the 3S process, gave a considerable reduction in total shrinkage in both brown and white strain canned mushrooms compared with the control samples. Water uptake by the mushrooms in the 3S process was greatest when the soaking water temperature was between 20 and 30°C and had a pH of 8. Citric acid in the blanch water enhanc...

  9. Creep and shrinkage of Mo(Ni)

    International Nuclear Information System (INIS)

    Kaysser, W.A.; Hofmann-Amtenbrink, M.; Petzow, G.

    1984-01-01

    To avoid some of the errors inherent in a quantitative interpretation of shrinkage of powder compacts as Mo-Ni, other experiments were looked for, where the influence of Ni on the material transport properties of Mo could be measured semi-quantitatively during heating up to temperature and subsequent isothermal annealing. The bending of thin Mo foils under small loads was found to be an experimental arrangement, where variations in stress, in Ni-concentration and in intrinsic material properties could be realized. The results of these creep experiments will be compared in a qualitative sense with sintering experiments in Mo-Ni done under similar conditions as the creep experiments

  10. Bayesian programming

    CERN Document Server

    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

  11. Distinct spontaneous shrinkage of a sporadic vestibular schwannoma

    DEFF Research Database (Denmark)

    Huang, Xiaowen; Cayé-Thomasen, Per; Stangerup, Sven-Eric

    2013-01-01

    on "shrinkage" or "negative growth" or "regression" or "involution" of the tumor were selected, and the contents on the rate, extent and mechanism of spontaneous tumor shrinkage were extracted and reviewed. The reported rate of spontaneous shrinkage of vestibular schwannoma is 5-10% of patients managed......We present a case with outspoken spontaneous vestibular schwannoma shrinkage and review the related literature. The patient was initially diagnosed with a left-sided, intrameatal vestibular schwannoma, which subsequently grew into the cerebello-pontine angle (CPA), followed by total shrinkage...... of the CPA component without any intervention over a 12-year observation period. The literature on spontaneous tumor shrinkage was retrieved by searching the subject terms "vestibular schwannoma, conservative management" in PubMed/MEDLINE database, without a time limit. Of the published data, the articles...

  12. Ultrasonic assessment of shrinkage type discontinuities

    International Nuclear Information System (INIS)

    Hubber, John

    2010-01-01

    This investigation into ultrasonic internal discontinuities is intended to demonstrate typical examples of internal 'shrinkage' type discontinuities and its connection with the casting suitability, integrity and reliability in service. This type of discontinuity can be misinterpreted by ultrasonic technicians and can lead to the rejection of castings unnecessarily, due to the mis-characterization of fine shrinkage - discrete porosity. The samples for this investigation were taken from thirty ton heavy section ductile iron mill flange castings, manufactured by Graham Campbell Ferrum International. The sampled area was of discontinuities that were recorded for sizing on an area due to loss of back wall echo, but had acceptable reflectivity. A comparative sample was taken adjacent to the area of discrete porosity. The discontinuities found by this investigation are of a 'spongy' type, gaseous in appearance and are surrounded by acoustically sound material. All discontinuities discussed in this paper are centrally located in the through thickness of the casting. The porous nature of this type of discontinuity consisting of approximately 80-90% metal has its own residual strength, as indicated by the proof stress results which reveal a residual strength of up to 50-60% of that of the unaffected area of the casting. The affected areas are elliptical in shape and vary in density and through thickness throughout.

  13. 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

  14. Creep and shrinkage of concrete according to Eurocode 2

    Directory of Open Access Journals (Sweden)

    Milićević Ivan M.

    2017-01-01

    Full Text Available This paper presents the procedure for calculation of creep coefficient and shrinkage strain according to Eurocode 2 (SRPS EN 1992-1-1:2004. The calculated values of final creep coefficient and shrinkage strain, for the usual design conditions, are given in Annexes. The influence of key parameters on final creep coefficient and shrinkage strain is analyzed and the comparison between their final values calculated according to Eurocode 2 and BAB 87 is presented.

  15. Silorane- and high filled-based"low-shrinkage" resin composites: shrinkage, flexural strength and modulus

    Directory of Open Access Journals (Sweden)

    Cesar Augusto Galvão Arrais

    2013-04-01

    Full Text Available This study compared the volumetric shrinkage (VS, flexural strength (FS and flexural modulus (FM properties of the low-shrinkage resin composite Aelite LS (Bisco to those of Filtek LS (3M ESPE and two regular dimethacrylate-based resin composites, the microfilled Heliomolar (Ivoclar Vivadent and the microhybrid Aelite Universal (Bisco. The composites (n = 5 were placed on the Teflon pedestal of a video-imaging device, and VS was recorded every minute for 5 min after 40 s of light exposure. For the FS and FM tests, resin discs (0.6 mm in thickness and 6.0 mm in diameter were obtained (n = 12 and submitted to a piston-ring biaxial test in a universal testing machine. VS, FS, and FM data were submitted to two-way repeated measures and one-way ANOVA, respectively, followed by Tukey's post-hoc test (a = 5%. Filtek LS showed lower VS than did Aelite LS, which in turn showed lower shrinkage than did the other composites. Aelite Universal and Filtek LS exhibited higher FS than did Heliomolar and Aelite LS, both of which exhibited the highest FM. No significant difference in FM was noted between Filtek LS and Aelite Universal, while Heliomolar exhibited the lowest values. Aelite LS was not as effective as Filtek LS regarding shrinkage, although both low-shrinkage composites showed lower VS than did the other composites. Only Filtek LS exhibited FS and FM comparable to those of the regular microhybrid dimethacrylate-based resin composite.

  16. Further Evaluation of Covariate Analysis using Empirical Bayes Estimates in Population Pharmacokinetics: the Perception of Shrinkage and Likelihood Ratio Test.

    Science.gov (United States)

    Xu, Xu Steven; Yuan, Min; Yang, Haitao; Feng, Yan; Xu, Jinfeng; Pinheiro, Jose

    2017-01-01

    Covariate analysis based on population pharmacokinetics (PPK) is used to identify clinically relevant factors. The likelihood ratio test (LRT) based on nonlinear mixed effect model fits is currently recommended for covariate identification, whereas individual empirical Bayesian estimates (EBEs) are considered unreliable due to the presence of shrinkage. The objectives of this research were to investigate the type I error for LRT and EBE approaches, to confirm the similarity of power between the LRT and EBE approaches from a previous report and to explore the influence of shrinkage on LRT and EBE inferences. Using an oral one-compartment PK model with a single covariate impacting on clearance, we conducted a wide range of simulations according to a two-way factorial design. The results revealed that the EBE-based regression not only provided almost identical power for detecting a covariate effect, but also controlled the false positive rate better than the LRT approach. Shrinkage of EBEs is likely not the root cause for decrease in power or inflated false positive rate although the size of the covariate effect tends to be underestimated at high shrinkage. In summary, contrary to the current recommendations, EBEs may be a better choice for statistical tests in PPK covariate analysis compared to LRT. We proposed a three-step covariate modeling approach for population PK analysis to utilize the advantages of EBEs while overcoming their shortcomings, which allows not only markedly reducing the run time for population PK analysis, but also providing more accurate covariate tests.

  17. Bayesian Graphical Models

    DEFF Research Database (Denmark)

    Jensen, Finn Verner; Nielsen, Thomas Dyhre

    2016-01-01

    Mathematically, a Bayesian graphical model is a compact representation of the joint probability distribution for a set of variables. The most frequently used type of Bayesian graphical models are Bayesian networks. The structural part of a Bayesian graphical model is a graph consisting of nodes...

  18. Plastic shrinkage of mortars with shrinkage reducing admixture and lightweight aggregates studied by neutron tomography

    Energy Technology Data Exchange (ETDEWEB)

    Wyrzykowski, Mateusz, E-mail: mateusz.wyrzykowski@empa.ch [Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); Lodz University of Technology, Department of Building Physics and Building Materials, Lodz (Poland); Trtik, Pavel [Paul Scherrer Institute, Laboratory for Neutron Scattering and Imaging, Villigen (Switzerland); Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); Münch, Beat [Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); Weiss, Jason [Purdue University, School of Civil Engineering, West Lafayette (United States); Vontobel, Peter [Paul Scherrer Institute, Laboratory for Neutron Scattering and Imaging, Villigen (Switzerland); Lura, Pietro [Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); ETH Zurich, Institute for Building Materials (IfB), Zurich (Switzerland)

    2015-07-15

    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.

  19. Plastic shrinkage of mortars with shrinkage reducing admixture and lightweight aggregates studied by neutron tomography

    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

  20. PLASTIC SHRINKAGE CONTROLLING EFFECT BY POLYPROPYLENE SHORT FIBER WITH HYDROPHILY

    Science.gov (United States)

    Hosoda, Akira; Sadatsuki, Yoshitomo; Oshima, Akihiro; Ishii, Akina; Tsubaki, Tatsuya

    The aim of this research is to clarify the mechanism of controlling plastic shrinkage crack by adding small amout of synthetic short fiber, and to propose optimum polypropylene short fiber to control plastic shrinkage crack. In this research, the effect of the hydrophily of polypropylene fiber was investigated in the amount of plastic shrinkage of mortar, total area of plastic shrinkage crack, and bond properties between fiber and mortar. The plastic shrinkage test of morar was conducted under high temperature, low relative humidity, and constant wind velocity. When polypropylene fiber had hydrophily, the amount of plastic shrinkage of mortar was restrained, which was because cement paste in morar was captured by hydrophilic fiber and then bleeding of mortar was restrained. With hydrophily, plastic shrinkage of mortar was restrained and bridging effect was improved due to better bond, which led to remarkable reduction of plastic shrinkage crack. Based on experimental results, the way of developing optimum polypropylene short fiber for actual construction was proposed. The fiber should have large hydrophily and small diameter, and should be used in as small amount as possible in order not to disturb workability of concrete.

  1. 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)

  2. Shrinkage Degree in $L_{2}$ -Rescale Boosting for Regression.

    Science.gov (United States)

    Xu, Lin; Lin, Shaobo; Wang, Yao; Xu, Zongben

    2017-08-01

    L 2 -rescale boosting ( L 2 -RBoosting) is a variant of L 2 -Boosting, which can essentially improve the generalization performance of L 2 -Boosting. The key feature of L 2 -RBoosting lies in introducing a shrinkage degree to rescale the ensemble estimate in each iteration. Thus, the shrinkage degree determines the performance of L 2 -RBoosting. The aim of this paper is to develop a concrete analysis concerning how to determine the shrinkage degree in L 2 -RBoosting. We propose two feasible ways to select the shrinkage degree. The first one is to parameterize the shrinkage degree and the other one is to develop a data-driven approach. After rigorously analyzing the importance of the shrinkage degree in L 2 -RBoosting, we compare the pros and cons of the proposed methods. We find that although these approaches can reach the same learning rates, the structure of the final estimator of the parameterized approach is better, which sometimes yields a better generalization capability when the number of sample is finite. With this, we recommend to parameterize the shrinkage degree of L 2 -RBoosting. We also present an adaptive parameter-selection strategy for shrinkage degree and verify its feasibility through both theoretical analysis and numerical verification. The obtained results enhance the understanding of L 2 -RBoosting and give guidance on how to use it for regression tasks.

  3. Drying Shrinkage Microcracking in Cement-based Materials

    NARCIS (Netherlands)

    Bisschop, J.; Van Mier, J.G.M.

    2002-01-01

    In this paper the nature of drying shrinkage microcracking in a variety of model cementbased materials, as well as in more practical types of concrete is described. The model mixtures were studied to elucidate the mechanisms of drying shrinkage microcracking and the factors that influence these

  4. Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage.

    Science.gov (United States)

    Mejia, Amanda F; Nebel, Mary Beth; Barber, Anita D; Choe, Ann S; Pekar, James J; Caffo, Brian S; Lindquist, Martin A

    2018-05-15

    Reliability of subject-level resting-state functional connectivity (FC) is determined in part by the statistical techniques employed in its estimation. Methods that pool information across subjects to inform estimation of subject-level effects (e.g., Bayesian approaches) have been shown to enhance reliability of subject-level FC. However, fully Bayesian approaches are computationally demanding, while empirical Bayesian approaches typically rely on using repeated measures to estimate the variance components in the model. Here, we avoid the need for repeated measures by proposing a novel measurement error model for FC describing the different sources of variance and error, which we use to perform empirical Bayes shrinkage of subject-level FC towards the group average. In addition, since the traditional intra-class correlation coefficient (ICC) is inappropriate for biased estimates, we propose a new reliability measure denoted the mean squared error intra-class correlation coefficient (ICC MSE ) to properly assess the reliability of the resulting (biased) estimates. We apply the proposed techniques to test-retest resting-state fMRI data on 461 subjects from the Human Connectome Project to estimate connectivity between 100 regions identified through independent components analysis (ICA). We consider both correlation and partial correlation as the measure of FC and assess the benefit of shrinkage for each measure, as well as the effects of scan duration. We find that shrinkage estimates of subject-level FC exhibit substantially greater reliability than traditional estimates across various scan durations, even for the most reliable connections and regardless of connectivity measure. Additionally, we find partial correlation reliability to be highly sensitive to the choice of penalty term, and to be generally worse than that of full correlations except for certain connections and a narrow range of penalty values. This suggests that the penalty needs to be chosen carefully

  5. Reduction of the Early Autogenous Shrinkage of High Strength Concrete

    Directory of Open Access Journals (Sweden)

    Drago Saje

    2015-01-01

    Full Text Available The results of a laboratory investigation on the early autogenous shrinkage of high strength concrete, and the possibilities of its reduction, are presented. Such concrete demonstrates significant autogenous shrinkage, which should, however, be limited in the early stages of its development in order to prevent the occurrence of cracks and/or drop in the load-carrying capacity of concrete structures. The following possibilities for reducing autogenous shrinkage were investigated: the use of low-heat cement, a shrinkage-reducing admixture, steel fibres, premoistened polypropylene fibres, and presoaked lightweight aggregate. In the case of the use of presoaked natural lightweight aggregate, with a fraction from 2 to 4 mm, the early autogenous shrinkage of one-day-old high strength concrete decreased by about 90%, with no change to the concrete's compressive strength in comparison with that of the reference concrete.

  6. Introduction to Bayesian statistics

    CERN Document Server

    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...

  7. Bayesian artificial intelligence

    CERN Document Server

    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

  8. Bayesian artificial intelligence

    CERN Document Server

    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.

  9. 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)

  10. BAYESIAN FORECASTS COMBINATION TO IMPROVE THE ROMANIAN INFLATION PREDICTIONS BASED ON ECONOMETRIC MODELS

    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.

  11. 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

  12. Bayesian Group Bridge for Bi-level Variable Selection.

    Science.gov (United States)

    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.

  13. Bayesian emulation for optimization in multi-step portfolio decisions

    OpenAIRE

    Irie, Kaoru; West, Mike

    2016-01-01

    We discuss the Bayesian emulation approach to computational solution of multi-step portfolio studies in financial time series. "Bayesian emulation for decisions" involves mapping the technical structure of a decision analysis problem to that of Bayesian inference in a purely synthetic "emulating" statistical model. This provides access to standard posterior analytic, simulation and optimization methods that yield indirect solutions of the decision problem. We develop this in time series portf...

  14. Bayesian Mediation Analysis

    OpenAIRE

    Yuan, Ying; MacKinnon, David P.

    2009-01-01

    This article proposes Bayesian analysis of mediation effects. Compared to 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 mediation analysis, inference is straightforward and exact, which makes it appealing for studies with small samples. Third, the Bayesian approach is conceptua...

  15. Creep and Shrinkage of High Strength Concretes: an Experimental Analysis

    Directory of Open Access Journals (Sweden)

    Berenice Martins Toralles carbonari

    2002-01-01

    Full Text Available The creep and shrinkage behaviour of high strength silica fume concretes is significantly different from that of conventional concretes. In order to represent the proper time-dependent response of the material in structural analysis and design, these aspects should be adequately quantified. This paper discusses an experimental setup that is able to determine the creep and shrinkage of concrete from the time of placing. It also compares different gages that can be used for measuring the strains. The method is applied to five different concretes in the laboratory under controlled environmental conditions. The phenomena that are quantified can be classified as basic shrinkage, drying shrinkage, basic creep and drying creep. The relative importance of these mechanisms in high strength concrete will also be presented.

  16. Comparison of shrinkage related properties of various patch repair materials

    Science.gov (United States)

    Kristiawan, S. A.; Fitrianto, R. S.

    2017-02-01

    A patch repair material has been developed in the form of unsaturated polyester resin (UPR)-mortar. The performance and durability of this material are governed by its compatibility with the concrete being repaired. One of the compatibility issue that should be tackled is the dimensional compatibility as a result of differential shrinkage between the repair material and the concrete substrate. This research aims to evaluate such shrinkage related properties of UPR-mortar and to compare with those of other patch repair materials. The investigation includes the following aspects: free shrinkage, resistance to delamination and cracking. The results indicate that UPR-mortar poses a lower free shrinkage, lower risk of both delamination and cracking tendency in comparison to other repair materials.

  17. Influence of gelatinous fibers on the shrinkage of silver maple

    Science.gov (United States)

    Donals G. Arganbright; Dwight W. Bensend; Floyd G. Manwiller

    1970-01-01

    The degree of lean was found to have a significant influence on the logitudinal and transverse shrinkage of three soft maple trees. This may be accounted for by differences in the cell wall layer thickness and fibril angle.

  18. Shrinkage and durability study of bridge deck concrete.

    Science.gov (United States)

    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 ...

  19. Bayesian benefits with JASP

    NARCIS (Netherlands)

    Marsman, M.; Wagenmakers, E.-J.

    2017-01-01

    We illustrate the Bayesian approach to data analysis using the newly developed statistical software program JASP. With JASP, researchers are able to take advantage of the benefits that the Bayesian framework has to offer in terms of parameter estimation and hypothesis testing. The Bayesian

  20. 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

  1. Shrinkage Module of Soil Samples with Different Cement Content

    Directory of Open Access Journals (Sweden)

    Mohannad Sabry

    2017-12-01

    Full Text Available The differences in soil's body mass during shrinkage over time have changes in soil physical properties which provide an important reason to check the design of underground foundations in expansive soils. In this paper, a state-of-art of the soil heat stress-strain relationship prediction methods is checked using soil engineering laboratory experiments and Matlab R2013b numerical modelling. The shrinkage of soils with different cement content of (0%, 2%, 4%, 6% and 8% with the same water content of 20 percent in room temperature for 24 hours, are critically reviewed in terms of their predictive shrinkage along with their strengths and flexural behaviour. The review highlights the prediction methods present to determine the effect of heat stress on the shrinkage of soil samples with different cement content after classifying the soils into clay, silt and sand depending on their particle size using sieve and hydrometer experiments. The results of the soil engineering laboratory experiments showed that as the cement content increases, the shrinkage of soil decreases as a result of increased elasticity in soil. The numerical analysis using finite element method in Matlab R2013b shows that as the cement content increases the displacement in the soil sample decreases and that the soil sample with 8% cement content has more resistance to shrinkage and less displacement than the soil with 6% cement, which has less resistance to heat stresses and more displacement.

  2. Variation of Shrinkage Strain within the Depth of Concrete Beams

    Directory of Open Access Journals (Sweden)

    Jong-Hyun Jeong

    2015-11-01

    Full Text Available The variation of shrinkage strain within beam depth was examined through four series of time-dependent laboratory experiments on unreinforced concrete beam specimens. Two types of beam specimens, horizontally cast and vertically cast, were tested; shrinkage variation was observed in the horizontally cast specimens. This indicated that the shrinkage variation within the beam depth was due to water bleeding and tamping during the placement of the fresh concrete. Shrinkage strains were measured within the beam depth by two types of strain gages, surface-attached and embedded. The shrinkage strain distribution within the beam depth showed a consistent tendency for the two types of gages. The test beams were cut into four sections after completion of the test, and the cutting planes were divided into four equal sub-areas to measure the aggregate concentration for each sub-area of the cutting plane. The aggregate concentration increased towards the bottom of the beam. The shrinkage strain distribution was estimated by Hobbs’ equation, which accounts for the change of aggregate volume concentration.

  3. Volume change of limestone and its effects on drying shrinkage of concrete

    OpenAIRE

    YAGI, Shogo; AQUINO, Carlos; INOUE, Masumi; OKAMOTO, Takahisa

    2010-01-01

    Recently, the cracks of concrete by drying shrinkage become one of the problems in the construction industry in Japan. The drying shrinkage decreases when the concrete is produced with limestone aggregate. However, it is not clear why the drying shrinkage is decreased. The purpose of this study is to clarify the relation between the drying shrinkage of concrete and the limestone aggregate. In this study, the experiments about the strength, elasticity and drying shrinkage of concrete and the p...

  4. Time-Dependent Behavior of Shrinkage Strain for Early Age Concrete Affected by Temperature Variation

    OpenAIRE

    Qin, Yu; Yi, Zhijian; Wang, Weina; Wang, Di

    2017-01-01

    Shrinkage has been proven to be an important property of early age concrete. The shrinkage strain leads to inherent engineering problems, such as cracking and loss of prestress. Atmospheric temperature is an important factor in shrinkage strain. However, current research does not provide much attention to the effect of atmospheric temperature on shrinkage of early age concrete. In this paper, a laboratory study was undertaken to present the time-dependent shrinkage of early age concrete under...

  5. Geosynthetic clay liners shrinkage under simulated daily thermal cycles.

    Science.gov (United States)

    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.

  6. 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.

  7. 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...

  8. Bayesian estimation of sensitivity and specificity of a commercial serum/milk ELISA against the Mycobacterium avium subsp. Paratuberculosis (MAP) antibody response for each lactation stage in Greek dairy sheep.

    Science.gov (United States)

    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.

  9. Understanding Computational Bayesian Statistics

    CERN Document Server

    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

  10. Bayesian statistics an introduction

    CERN Document Server

    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

  11. Self-compacting fine-grained concretes with compensated shrinkage

    Directory of Open Access Journals (Sweden)

    Alimov Lev

    2017-01-01

    Full Text Available This paper substantiates the efficiency of application of fine-grained concrete for erection of cast-in-place concrete and reinforced concrete structures of different purpose. On the basis of analysis of experimental research results it was established that the introduction of microfillers with expansion effect to composite binder allows not only improving the rheological properties of fine-grained concrete, but also decreasing of value of shrinkage strain and improving of concrete crack resistance and durability. The analysis of the results of industrial use of fine-grained concretes with compensated shrinkage is given.

  12. 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...

  13. Void shrinkage in stainless steel during high energy electron irradiation

    International Nuclear Information System (INIS)

    Singh, B.N.; Foreman, A.J.E.

    1976-03-01

    During irradiation of thin foils of an austenitic stainless steel in a high voltage electron microscope, steadily growing voids have been observed to suddenly shrink and disappear at the irradiation temperature of 650 0 Cthe phenomenon has been observed in specimens both with and withoutimplanted helium. Possible mechanisms for void shrinkage during irradiation are considered. It is suggested that the dislocation-pipe-diffusion of vacancies from or of self-interstitial atoms to the voids can explain the shrinkage behaviour of voids observed during our experiments. (author)

  14. Bayesian Mediation Analysis

    Science.gov (United States)

    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…

  15. The Bayesian Score Statistic

    NARCIS (Netherlands)

    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

  16. Bayesian Probability Theory

    Science.gov (United States)

    von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

    2014-06-01

    Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

  17. Measuring method for heat-shrinkage of fuel pellet

    International Nuclear Information System (INIS)

    Komono, Akira; Ishizaki, Jin; Inaki, Kiyohiro.

    1997-01-01

    The present invention concerns a method of determining an amount of heat-shrinkage of UR 2 pellets containing gadolinium oxide (Gd 2 O 2 ) based on the difference of the density thereof before and after heating. In a heat shrinkage test of UO 2 pellets containing from 1.0 to 15.0% by weight of gadolinium oxide, the amount of heat-shrinkage is measured under the condition of heat-retaining temperature: from 1700 to 1750degC, temperature elevation time and lowering time: from 90 to 120mins, heat-retaining time: 24hours, inert gas atmosphere, gas pressure: 0.35kg/cm 2 and gas dew point: from -55 to 40degC without changing O/M. This invention has a feature in the use of the inert gas and the elevation of the dew point of the gas. Then, oxygen dissociation phenomenon from crystal lattices of the fuel pellets is suppressed, and normal densification value is shown. Then, fuel pellets of good quality with less fluctuation of the heat-shrinkage can be obtained. (N.H.)

  18. Fast generation of computer-generated holograms using wavelet shrinkage.

    Science.gov (United States)

    Shimobaba, Tomoyoshi; Ito, Tomoyoshi

    2017-01-09

    Computer-generated holograms (CGHs) are generated by superimposing complex amplitudes emitted from a number of object points. However, this superposition process remains very time-consuming even when using the latest computers. We propose a fast calculation algorithm for CGHs that uses a wavelet shrinkage method, eliminating small wavelet coefficient values to express approximated complex amplitudes using only a few representative wavelet coefficients.

  19. Effect of processing conditions on shrinkage in injection moulding

    NARCIS (Netherlands)

    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

  20. Accurate characterisation of post moulding shrinkage of polymer parts

    DEFF Research Database (Denmark)

    Neves, L. C.; De Chiffre, L.; González-Madruga, D.

    2015-01-01

    The work deals with experimental determination of the shrinkage of polymer parts after injection moulding. A fixture for length measurements on 8 parts at the same time was designed and manufactured in Invar, mounted with 8 electronic gauges, and provided with 3 temperature sensors. The fixture w...

  1. Drying and Radial Shrinkage Characteristics and Changes in Color ...

    African Journals Online (AJOL)

    nahimana

    2011-08-12

    Aug 12, 2011 ... A pre-test experiment was carried out following the. Thompson ... energy saving potential and the ability to control drying temperature and air humidity. ..... structural collapse by shrinkage, case hardening, etc. From the slopes of .... Thus, the Nahimana et al. model is proposed as a new model predicting with ...

  2. 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

  3. 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 ...

  4. Characterisation of tissue shrinkage during microwave thermal ablation.

    Science.gov (United States)

    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.

  5. 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

  6. Effects of Shrinkage Reducing Agent and Expansive Admixture on the Volume Deformation of Ultrahigh Performance Concrete

    OpenAIRE

    Anshuang, Su; Ling, Qin; Shoujie, Zhang; Jiayang, Zhang; Zhaoyu, Li

    2017-01-01

    This paper investigated the influences of shrinkage reducing agent and expansive admixture on autogenous and drying shrinkage of ultrahigh performance concrete (UHPC) containing antifoaming admixture. The shrinkage reducing agent was used at dosage of 0.5%, 1%, and 2% and the expansive admixture was used at dosage of 2% to 4% by mass of cementitious material. The results show that the air content of UHPC increases with the higher addition of shrinkage reducing agent and expansive admixtures. ...

  7. Bayesian computation with R

    CERN Document Server

    Albert, Jim

    2009-01-01

    There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry. Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The earl

  8. Bayesian data analysis for newcomers.

    Science.gov (United States)

    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.

  9. Hydration of mineral shrinkage-compensating admixture for concrete : an experimental and numerical study

    NARCIS (Netherlands)

    Chen, Wei; Brouwers, H.J.H.

    2012-01-01

    The use of shrinkage-compensating admixture in concrete has been proven to be an effective way to mitigate the shrinkage of concrete. The hydration of a shrinkage-compensating admixture in cement paste and concrete is investigated in this paper with numerical simulation and experimental study. An

  10. Bayesian methods for data analysis

    CERN Document Server

    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

  11. 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...

  12. 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...

  13. Bayesian psychometric scaling

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; van den Berg, Stéphanie Martine; Veldkamp, Bernard P.; Irwing, P.; Booth, T.; Hughes, D.

    2015-01-01

    In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item

  14. 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.

  15. Bayesian Networks An Introduction

    CERN Document Server

    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

  16. A Bayesian encourages dropout

    OpenAIRE

    Maeda, Shin-ichi

    2014-01-01

    Dropout is one of the key techniques to prevent the learning from overfitting. It is explained that dropout works as a kind of modified L2 regularization. Here, we shed light on the dropout from Bayesian standpoint. Bayesian interpretation enables us to optimize the dropout rate, which is beneficial for learning of weight parameters and prediction after learning. The experiment result also encourages the optimization of the dropout.

  17. 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.

  18. Non-linear Bayesian update of PCE coefficients

    KAUST Repository

    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).

  19. Non-linear Bayesian update of PCE coefficients

    KAUST Repository

    Litvinenko, Alexander; Matthies, Hermann G.; Pojonk, Oliver; Rosic, Bojana V.; Zander, Elmar

    2014-01-01

    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).

  20. Bayesian component separation: The Planck experience

    Science.gov (United States)

    Wehus, Ingunn Kathrine; Eriksen, Hans Kristian

    2018-05-01

    Bayesian component separation techniques have played a central role in the data reduction process of Planck. The most important strength of this approach is its global nature, in which a parametric and physical model is fitted to the data. Such physical modeling allows the user to constrain very general data models, and jointly probe cosmological, astrophysical and instrumental parameters. This approach also supports statistically robust goodness-of-fit tests in terms of data-minus-model residual maps, which are essential for identifying residual systematic effects in the data. The main challenges are high code complexity and computational cost. Whether or not these costs are justified for a given experiment depends on its final uncertainty budget. We therefore predict that the importance of Bayesian component separation techniques is likely to increase with time for intensity mapping experiments, similar to what has happened in the CMB field, as observational techniques mature, and their overall sensitivity improves.

  1. Basics of Bayesian methods.

    Science.gov (United States)

    Ghosh, Sujit K

    2010-01-01

    Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information available to a researcher. Prior knowledge arising from scientific background, expert judgment, or previously collected data is used to build a prior distribution which is then combined with current data via the likelihood function to characterize the current state of knowledge using the so-called posterior distribution. Bayesian methods allow the use of models of complex physical phenomena that were previously too difficult to estimate (e.g., using asymptotic approximations). Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models based on hierarchical conditional distributions that can be estimated even with limited amounts of data. Furthermore, advances in numerical integration methods, particularly those based on Monte Carlo methods, have made it possible to compute the optimal Bayes estimators. However, there is a reasonably wide gap between the background of the empirically trained scientists and the full weight of Bayesian statistical inference. Hence, one of the goals of this chapter is to bridge the gap by offering elementary to advanced concepts that emphasize linkages between standard approaches and full probability modeling via Bayesian methods.

  2. 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.

  3. 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

  4. PREDIKSI SHRINKAGE UNTUK MENGHINDARI CACAT PRODUK PADA PLASTIC INJECTION

    Directory of Open Access Journals (Sweden)

    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.

  5. The Shrinkage Model And Expert System Of Plastic Lens Formation

    Science.gov (United States)

    Chang, Rong-Seng

    1988-06-01

    Shrinkage causes both the appearance & dimension defects of the injected plastic lens. We have built up a model of state equations with the help of finite element analysis program to estimate the volume change (shrinkage and swelling) under the combinations of injection variables such as pressure and temperature etc., then the personal computer expert system has been build up to make that knowledge conveniently available to the user in the model design, process planning, process operation and some other work. The domain knowledge is represented by a R-graph (Relationship-graph) model which states the relationships of variables & equations. This model could be compare with other models in the expert system. If the user has better model to solve the shrinkage problem, the program will evaluate it automatically and a learning file will be trigger by the expert system to teach the user to update their knowledge base and modify the old model by this better model. The Rubin's model and Gilmore's model have been input to the expert system. The conflict has been solved both from the user and the deeper knowledge base. A cube prism and the convex lens examples have been shown in this paper. This program is written by MULISP language in IBM PC-AT. The natural language provides English Explaination of know why and know how and the automatic English translation for the equation rules and the production rules.

  6. Experimental Analysis on Shrinkage and Swelling in Ordinary Concrete

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. Evaluation of shrinkage and cracking in concrete of ring test by acoustic emission method

    Science.gov (United States)

    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.

  9. Influence of length-to-diameter ratio on shrinkage of basalt fiber concrete

    Science.gov (United States)

    Ruijie, MA; Yang, Jiansen; Liu, Yuan; Zheng, Xiaojun

    2017-09-01

    In order to study the shrinkage performance of basalt concrete, using the shrinkage rate as index, the work not only studied the influence of different length-to-diameter ratio (LDR) on plastic shrinkage and drying shrinkage of basalt fiber concrete, but also analyzed the action mechanism. The results show that when the fiber content is 0.1%, the LDR of 800 and 1200 take better effects on reducing plastic shrinkage, however the fiber content is 0.3%, that of LDR 600 is better. To improve drying shrinkage, the fiber of LDR 800 takes best effect. In the concrete structure, the adding basalt fibers form a uniform and chaotic supporting system, optimize the pore and the void structure of concrete, make the material further compacted, reduce the water loss, so as to decrease the shrinkage of concrete effectively.

  10. Bayesian networks with examples in R

    CERN Document Server

    Scutari, Marco

    2014-01-01

    Introduction. The Discrete Case: Multinomial Bayesian Networks. The Continuous Case: Gaussian Bayesian Networks. More Complex Cases. Theory and Algorithms for Bayesian Networks. Real-World Applications of Bayesian Networks. Appendices. Bibliography.

  11. Bayesian methods in reliability

    Science.gov (United States)

    Sander, P.; Badoux, R.

    1991-11-01

    The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.

  12. Polymerization shrinkage stress of composite resins and resin cements – What do we need to know?

    Directory of Open Access Journals (Sweden)

    Carlos José SOARES

    2017-08-01

    Full Text Available Abstract 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.

  13. Polymerization shrinkage stress of composite resins and resin cements - What do we need to know?

    Science.gov (United States)

    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.

  14. Bayesian policy reuse

    CSIR Research Space (South Africa)

    Rosman, Benjamin

    2016-02-01

    Full Text Available Keywords Policy Reuse · Reinforcement Learning · Online Learning · Online Bandits · Transfer Learning · Bayesian Optimisation · Bayesian Decision Theory. 1 Introduction As robots and software agents are becoming more ubiquitous in many applications.... The agent has access to a library of policies (pi1, pi2 and pi3), and has previously experienced a set of task instances (τ1, τ2, τ3, τ4), as well as samples of the utilities of the library policies on these instances (the black dots indicate the means...

  15. Exploiting tumor shrinkage through temporal optimization of radiotherapy

    International Nuclear Information System (INIS)

    Unkelbach, Jan; Craft, David; Hong, Theodore; Papp, Dávid; Wolfgang, John; Bortfeld, Thomas; Ramakrishnan, Jagdish; Salari, Ehsan

    2014-01-01

    In multi-stage radiotherapy, a patient is treated in several stages separated by weeks or months. This regimen has been motivated mostly by radiobiological considerations, but also provides an approach to reduce normal tissue dose by exploiting tumor shrinkage. The paper considers the optimal design of multi-stage treatments, motivated by the clinical management of large liver tumors for which normal liver dose constraints prohibit the administration of an ablative radiation dose in a single treatment. We introduce a dynamic tumor model that incorporates three factors: radiation induced cell kill, tumor shrinkage, and tumor cell repopulation. The design of multi-stage radiotherapy is formulated as a mathematical optimization problem in which the total dose to the normal tissue is minimized, subject to delivering the prescribed dose to the tumor. Based on the model, we gain insight into the optimal administration of radiation over time, i.e. the optimal treatment gaps and dose levels. We analyze treatments consisting of two stages in detail. The analysis confirms the intuition that the second stage should be delivered just before the tumor size reaches a minimum and repopulation overcompensates shrinking. Furthermore, it was found that, for a large range of model parameters, approximately one-third of the dose should be delivered in the first stage. The projected benefit of multi-stage treatments in terms of normal tissue sparing depends on model assumptions. However, the model predicts large dose reductions by more than a factor of 2 for plausible model parameters. The analysis of the tumor model suggests that substantial reduction in normal tissue dose can be achieved by exploiting tumor shrinkage via an optimal design of multi-stage treatments. This suggests taking a fresh look at multi-stage radiotherapy for selected disease sites where substantial tumor regression translates into reduced target volumes. (paper)

  16. Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

    KAUST Repository

    Desmal, Abdulla; Bagci, Hakan

    2015-01-01

    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.

  17. Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

    KAUST Repository

    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.

  18. Bayesian methods for hackers probabilistic programming and Bayesian inference

    CERN Document Server

    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...

  19. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    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

  20. Bayesian Dark Knowledge

    NARCIS (Netherlands)

    Korattikara, A.; Rathod, V.; Murphy, K.; Welling, M.; Cortes, C.; Lawrence, N.D.; Lee, D.D.; Sugiyama, M.; Garnett, R.

    2015-01-01

    We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities p(y|x, D), e.g., for applications involving bandits or active learning. One simple

  1. Bayesian Geostatistical Design

    DEFF Research Database (Denmark)

    Diggle, Peter; Lophaven, Søren Nymand

    2006-01-01

    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...

  2. Bayesian statistical inference

    Directory of Open Access Journals (Sweden)

    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.

  3. Bayesian grid matching

    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 r...

  4. 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...

  5. Bayesian Exponential Smoothing.

    OpenAIRE

    Forbes, C.S.; Snyder, R.D.; Shami, R.S.

    2000-01-01

    In this paper, a Bayesian version of the exponential smoothing method of forecasting is proposed. The approach is based on a state space model containing only a single source of error for each time interval. This model allows us to improve current practices surrounding exponential smoothing by providing both point predictions and measures of the uncertainty surrounding them.

  6. Investigation of Shrinkage Defect in Castings by Quantitative Ishikawa Diagram

    Directory of Open Access Journals (Sweden)

    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.

  7. Design changes of device to investigation of alloys linear contraction and shrinkage stresses

    Directory of Open Access Journals (Sweden)

    J. Mutwil

    2009-07-01

    Full Text Available Some design changes in device elaborated by author to examination of linear contraction and shrinkage stresses progress of metals and alloys during– and after solidification have been described. The introduced changes have been focused on design of closing of shrinkage test rod mould. The introduced changes have been allowed to simplify a mounting procedure of thermocouples measuring a temperature of the shrinkage rod casting (in 6 points. Exemplary investigation results of linear contraction and shrinkage stresses development in Al-Si13.5% alloy have been presented.

  8. Topology optimization of reinforced concrete structures considering control of shrinkage and strength failure

    DEFF Research Database (Denmark)

    Luo, Yangjun; Wang, Michael Yu; Zhou, Mingdong

    2015-01-01

    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......-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 ensure the structural safety under the combined action of external loads and shrinkage....

  9. Bayesian optimization for materials science

    CERN Document Server

    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...

  10. The effect of fibers on the loss of water by evaporation and shrinkage of concrete

    Directory of Open Access Journals (Sweden)

    N. M. P. Pillar

    Full Text Available Shrinkage is one of the least desirable attributes in concrete. Large areas of exposed concrete surfaces , such as in shotcrete tunnel linings, where it is practically impossible to make a moist cure, are highly susceptible to plastic shrinkage at early ages. The autogenous and drying shrinkage can lead to states of greater than threshold strength, causing fracture, mechanical damage and lack of durability of concrete structures. The addition of fibers can greatly reduce plastic shrinkage, but has limited effect in mitigating autogenous and drying shrinkage. To evaluate the performance of polypropylene and steel fibers to understand their effect on shrinkage of concrete, a study was carried out to relate the loss of water from the paste and the shrinkage during the first 28 days of age, and compare it with a control mix without fiber. The loss of water was obtained by the weight loss of the specimens at different ages, since the only component that could contribute for the loss of weight was the water lost by the paste of the concrete. And the paste itself is the only source of shrinkage. Uniaxial compressive tests from very early ages enabled the determination of time when plastic shrinkage ended. It was observed that the control concrete mix lost three times more water and developed plastic and drying shrinkage 60 % higher than the fiber reinforced concrete mixes. It was possible to demonstrate that the reduced loss of water caused by the incorporation of fibers is related to the mitigation of plastic shrinkage. It was observed that the fibers are effective to restrain the movement of water through the cement paste in the plastic state, however such effect is limited after concrete starts the hardening state.

  11. 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)

  12. Probability and Bayesian statistics

    CERN Document Server

    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...

  13. Bayesian community detection

    DEFF Research Database (Denmark)

    Mørup, Morten; Schmidt, Mikkel N

    2012-01-01

    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....

  14. Preparation of Shrinkage Compensating Concrete with HCSA Expansive Agent

    Science.gov (United States)

    Li, Changcheng; Jia, Fujia

    2017-10-01

    Shrinkage compensating concrete (SCC) has become one of the best effective methods of preventing and reducing concrete cracking. SCC is prepared by HCSA high performance expansive agent for concrete which restrained expansion rate is optimized by 0.057%. Slump, compressive strength, restrained expansion rate and cracking resistance test were carried out on SCC. The results show that the initial slump of fresh SCC was about 220mm-230mm, while slump after 2 hours was 180mm-200mm. The restrained expansion rate of SCC increased with the mixing amount of expansive agent. After cured in water for 14 days, the restrained expansion rate of C35 and C40 SCC were 0.020%-0.032%. With the dosage of expansive agent increasing, restrained expansion rate of SCC increased, maximum compressive stress and cracking stress improved, cracking temperature fell, thus cracking resistance got effectively improvement.

  15. 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

  16. Subjective Bayesian Beliefs

    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 experimenta...... 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....

  17. Bayesian Hypothesis Testing

    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 τ2 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 H0.

  18. Introduction to Bayesian statistics

    CERN Document Server

    Koch, Karl-Rudolf

    2007-01-01

    This book presents Bayes' theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters. It does so in a simple manner that is easy to comprehend. The book compares traditional and Bayesian methods with the rules of probability presented in a logical way allowing an intuitive understanding of random variables and their probability distributions to be formed.

  19. Creep and shrinkage effects on integral abutment bridges

    Science.gov (United States)

    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

  20. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Bayesian theory and applications

    CERN Document Server

    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...

  2. A break-even analysis of RFID technology for inventory sensitive to shrinkage

    NARCIS (Netherlands)

    Kok, de A.G.; Donselaar, van K.H.; Woensel, van T.

    2008-01-01

    By embedding RFID tags onto their products, both manufacturers and retailers try to control for shrinkage (e.g. due to theft). Current inventory control systems do not take into account the disappearing inventory due to this shrinkage. As a response, corrective actions are made by performing costly

  3. Study of Drying Shrinkage Cracking by Lattice Gas Automaton and Environmental Scanning Electron Microscope

    NARCIS (Netherlands)

    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

  4. Development and Performance Assessment of the High-Performance Shrinkage Reducing Agent for Concrete

    Directory of Open Access Journals (Sweden)

    Hyung Sub Han

    2016-01-01

    Full Text Available To develop a high-performance shrinkage reducing agent, this study investigated several shrinkage reducing materials and supplements for those materials. Fluidity and air content were satisfactory for the various shrinkage reducing materials. The decrease in viscosity was the lowest for glycol-based materials. The decrease in drying shrinkage was most prominent for mixtures containing glycol-based materials. In particular, mixtures containing G2 achieved a 40% decrease in the amount of drying shrinkage. Most shrinkage reducing materials had weaker level of compressive strength than that of the plain mixture. When 3% triethanolamine was used for early strength improvement, the strength was enhanced by 158% compared to that of the plain mixture on day 1; enhancement values were 135% on day 7 and 113% on day 28. To assess the performance of the developed high-performance shrinkage reducing agent and to determine the optimal amount, 2.0% shrinkage reducing agent was set as 40% of the value of the plain mixture. While the effect was more prominent at higher amounts, to prevent deterioration of the compressive strength and the other physical properties, the recommended amount is less than 2.0%.

  5. Autogenous and drying shrinkage of sodium carbonate activated slag altered by limestone powder incorporation

    NARCIS (Netherlands)

    Yuan, B.; Yu, Q.L.; Dainese, E.; Brouwers, H.J.H.

    2017-01-01

    This paper aims to study the shrinkage mechanism of sodium carbonate activated slag containing limestone powder (LP). The workability, pore structure, reaction kinetics and strength development were characterized. The results show that the autogenous shrinkage increases when the dosage of LP is low

  6. 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

    . The shrinkage of the composite was calculated from density measurements using Archimedes method. The rate of the phase transformation in resin was measured by determining the volume fraction of monoclinic zirconia (vm). The composite had a vm of 0.5 after 8 h of water storage. The overall shrinkage...

  7. Can superabsorbent polymers mitigate shrinkage in cementitious materials blended with supplementary cementitious materials?

    DEFF Research Database (Denmark)

    Snoeck, Didier; Jensen, Ole Mejlhede; De Belie, Nele

    2016-01-01

    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...... to induce internal curing and mitigation of self-desiccation. Their purposefulness has been demonstrated in Portland cement pastes with and without silica fume. Nowadays, fly ash and blast-furnace slag containing binders are also frequently used in the construction industry. The results on autogenous...... 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...

  8. Creep and shrinkage analysis for concrete spent fuel dry storage module

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, D. [Atomic Energy of Canada Limited, Chalk River, Ontario (Canada)], E-mail: zhangd@aecl.ca

    2009-07-01

    CANDU reactors are designed in Canada and are built and operated worldwide to produce electricity economically with no emission of green house gases. This paper presents creep and shrinkage analysis for a concrete spent fuel dry storage module of a CANDU nuclear power plant. Creep and shrinkage analysis was performed using a method outlined in American Concrete Institute (ACI) code, and then the creep and shrinkage strains were analyzed in a finite element model to obtain the structural behavior of the concrete module. This demonstrated that the creep and shrinkage analysis for concrete spent fuel dry storage is reasonable. AECL's spent fuel dry storage module is adequate to resist the time-dependent effects due to creep and shrinkage of concrete. (author)

  9. Creep and shrinkage analysis for concrete spent fuel dry storage module

    International Nuclear Information System (INIS)

    Zhang, D.

    2009-01-01

    CANDU reactors are designed in Canada and are built and operated worldwide to produce electricity economically with no emission of green house gases. This paper presents creep and shrinkage analysis for a concrete spent fuel dry storage module of a CANDU nuclear power plant. Creep and shrinkage analysis was performed using a method outlined in American Concrete Institute (ACI) code, and then the creep and shrinkage strains were analyzed in a finite element model to obtain the structural behavior of the concrete module. This demonstrated that the creep and shrinkage analysis for concrete spent fuel dry storage is reasonable. AECL's spent fuel dry storage module is adequate to resist the time-dependent effects due to creep and shrinkage of concrete. (author)

  10. Aerosol particle shrinkage event phenomenology in a South European suburban area during 2009-2015

    Science.gov (United States)

    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

  11. Effect of temperature and humidity on post-gel shrinkage, cusp deformation, bond strength and shrinkage stress - Construction of a chamber to simulate the oral environment.

    Science.gov (United States)

    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

  12. Evaluation of polymerization shrinkage, polymerization shrinkage stress, wear resistance, and compressive strength of a silorane-based composite: A finite element analysis study

    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.

  13. Bayesian nonparametric data analysis

    CERN Document Server

    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.

  14. Applied Bayesian modelling

    CERN Document Server

    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

  15. Influence of shrinkage porosity on fatigue performance of iron castings and life estimation method

    Directory of Open Access Journals (Sweden)

    Wei Liu

    2016-01-01

    Full Text Available Shrinkage porosity exists more or less in heavy castings, and it plays an important role in the fatigue behavior of cast materials. In this study, fatigue tests were carried out on the QT400-18 cast iron specimens containing random degrees of shrinkage porosity defect. Experimental results showed that the order of magnitude of life scattered from 103 to 106 cycles when the shrinkage percentage ranged from 0.67% to 5.91%. SEM analyses were carried out on the shrinkage porosity region. The inter-granular discontinuous, micro cracks and inclusions interfered with the fatigue sliding or hindering process. The slip in shrinkage porosity region was not as orderly as the ordinary continuous medium. The shrinkage porosity area on fracture surface (SPAFS and alternating stress intensity factor (ASIF were applied to evaluate the tendency of residual life distribution; their relationship was fitted by negative exponent functions. Based on the intermediate variable of ASIF, a fatigue life prediction model of nodular cast iron containing shrinkage porosity defects was established. The modeling prediction was in agreement with the experimental results.

  16. Investigations of linear contraction and shrinkage stresses development in hypereutectic al-si binary alloys

    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.

  17. Effect of the key mixture parameters on shrinkage of reactive powder concrete.

    Science.gov (United States)

    Ahmad, Shamsad; Zubair, Ahmed; Maslehuddin, Mohammed

    2014-01-01

    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 3(3) 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.

  18. 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.

  19. 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...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....

  20. Searching Algorithm Using Bayesian Updates

    Science.gov (United States)

    Caudle, Kyle

    2010-01-01

    In late October 1967, the USS Scorpion was lost at sea, somewhere between the Azores and Norfolk Virginia. Dr. Craven of the U.S. Navy's Special Projects Division is credited with using Bayesian Search Theory to locate the submarine. Bayesian Search Theory is a straightforward and interesting application of Bayes' theorem which involves searching…

  1. Bayesian Data Analysis (lecture 2)

    CERN Multimedia

    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.

  2. Bayesian Data Analysis (lecture 1)

    CERN Multimedia

    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.

  3. Bayesian dynamic mediation analysis.

    Science.gov (United States)

    Huang, Jing; Yuan, Ying

    2017-12-01

    Most existing methods for mediation analysis assume that mediation is a stationary, time-invariant process, which overlooks the inherently dynamic nature of many human psychological processes and behavioral activities. In this article, we consider mediation as a dynamic process that continuously changes over time. We propose Bayesian multilevel time-varying coefficient models to describe and estimate such dynamic mediation effects. By taking the nonparametric penalized spline approach, the proposed method is flexible and able to accommodate any shape of the relationship between time and mediation effects. Simulation studies show that the proposed method works well and faithfully reflects the true nature of the mediation process. By modeling mediation effect nonparametrically as a continuous function of time, our method provides a valuable tool to help researchers obtain a more complete understanding of the dynamic nature of the mediation process underlying psychological and behavioral phenomena. We also briefly discuss an alternative approach of using dynamic autoregressive mediation model to estimate the dynamic mediation effect. The computer code is provided to implement the proposed Bayesian dynamic mediation analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. 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.

  5. The iterative shrinkage method for impulsive noise reduction from images

    International Nuclear Information System (INIS)

    Beygi, Sajjad; Kafashan, Mohammadmehdi; Bahrami, Hamid Reza; Mugler, Dale H

    2012-01-01

    In this paper, we present a novel scheme to compensate impulsive noise from images using the sparse shrinkage method. In this scheme, we assume the remaining noise after using a simple median filtering in place of corrupted pixels, found by boundary discriminative noise detection method, to be Gaussian additive noise. This assumption will later be verified by the means of simulation. Knowing that the pure image in the discrete wavelet transform (DWT) domain is a sparse vector, we define an optimization problem to minimize the l 0 -norm of the estimated image vector from the noisy one in the DWT domain. l 0 -norm makes the optimization problem a combinatorial optimization problem which is NP-hard to solve. To come up with a solution for our optimization problem, we convert the l 0 -norm problem to a continuous optimization problem which is then solved to find the estimated image with reduced noise. In the simulation and discussion part, the performance of our proposed method in reducing impulsive noise is compared to that of existing methods in the literature. We show that our proposed algorithm generally performs better in terms of both subjective and objective evaluations and is less complex. (paper)

  6. Bayesian inference with ecological applications

    CERN Document Server

    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...

  7. 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.

  8. Bayesian analysis of heterogeneous treatment effects for patient-centered outcomes research.

    Science.gov (United States)

    Henderson, Nicholas C; Louis, Thomas A; Wang, Chenguang; Varadhan, Ravi

    2016-01-01

    Evaluation of heterogeneity of treatment effect (HTE) is an essential aspect of personalized medicine and patient-centered outcomes research. Our goal in this article is to promote the use of Bayesian methods for subgroup analysis and to lower the barriers to their implementation by describing the ways in which the companion software beanz can facilitate these types of analyses. To advance this goal, we describe several key Bayesian models for investigating HTE and outline the ways in which they are well-suited to address many of the commonly cited challenges in the study of HTE. Topics highlighted include shrinkage estimation, model choice, sensitivity analysis, and posterior predictive checking. A case study is presented in which we demonstrate the use of the methods discussed.

  9. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

    Directory of Open Access Journals (Sweden)

    Lewei Duan

    2013-01-01

    Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

  10. Effects of Shrinkage Reducing Agent and Expansive Additive on Mortar Properties

    OpenAIRE

    Treesuwan, Sarapon; Maleesee, Komsan

    2017-01-01

    This research is to study the effect of mortar mixed with shrinkage reducing agent (polyoxyalkylene alkyl ether type), expansive additive (CaO type), and fly ash (hereinafter “SRA,” “EX,” and “FA,” resp.). Moreover, steam curing was studied to improve the properties of mortar. The plastic shrinkage test was conducted by using the strain gauge embedded at 0.5 cm from the surface according to the ASTM C1579-06 standard within early age followed by the total shrinkage test and compressive streng...

  11. 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

  12. How to practise Bayesian statistics outside the Bayesian church: What philosophy for Bayesian statistical modelling?

    NARCIS (Netherlands)

    Borsboom, D.; Haig, B.D.

    2013-01-01

    Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science

  13. The influence of superabsorbent polymers on the autogenous shrinkage properties of cement pastes with supplementary cementitious materials

    DEFF Research Database (Denmark)

    Snoeck, D.; Jensen, Ole Mejlhede; De Belie, N.

    2015-01-01

    Fly ash and blast-furnace slag containing binders are frequently used in the construction industry and it is important to know the extent of autogenous shrinkage and its (ideal) mitigation by superabsorbent polymers in these systems as a function of their age. In this paper, the autogenous...... 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...

  14. Bayesian Monte Carlo method

    International Nuclear Information System (INIS)

    Rajabalinejad, M.

    2010-01-01

    To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.

  15. Bayesian nonparametric hierarchical modeling.

    Science.gov (United States)

    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.

  16. Swelling/shrinkage of compacted and natural clayey soils

    International Nuclear Information System (INIS)

    Nowamooz, H.

    2007-12-01

    This thesis presents an experimental study performed on compacted loose and natural dense expansive soils using osmotic odometers. Several successive cycles were applied under three different low constant vertical net stresses. The loose soil presents a significant shrinkage accumulation while the dense one produces the swelling accumulation during the suction cycles. The suction cycles induced an equilibrium stage which indicates an elastic behaviour of the samples. At the end of suction cycles, a loading/unloading test was performed at the constant suctions for both materials. The mechanical parameters, i.e. the virgin compression index lambda(s), the apparent pre-consolidation stress p0(s) and the elastic compression index values lambda are completely dependent on the followed stress paths. The whole experimental results made it possible to define the yielding surfaces: suction limit between micro and macrostructure (Lm/M), loading collapse (LC) and saturation curve (SCS). The suction limit (Lm/M) depends completely to the soil fabrics and to the diameter separating the micro- and macrostructure. The pre-consolidation stress variation with suction is represented by the LC surface. The compression curves at different imposed suctions converge towards the saturated state for the high applied vertical stresses. We consider the saturation pressure (Psat) as the necessary pressure to reach the saturated state for an imposed suction. The higher the suction, the higher the saturation pressure. The yielding surface representing this pressure as a function of suction is called the saturation curve (SCS). Generally we can state that the suction cycles unified the LC and SC surfaces and increased the (Lm/M) up to a higher value. (author)

  17. Report D : self-consolidating concrete (SCC) for infrastructure elements - creep, shrinkage and abrasion resistance.

    Science.gov (United States)

    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...

  18. Shrinkage-thresholding enhanced born iterative method for solving 2D inverse electromagnetic scattering problem

    KAUST Repository

    Desmal, Abdulla; Bagci, Hakan

    2014-01-01

    A numerical framework that incorporates recently developed iterative shrinkage thresholding (IST) algorithms within the Born iterative method (BIM) is proposed for solving the two-dimensional inverse electromagnetic scattering problem. IST

  19. The evolution of shrinkage strain of pet-mortar composite eco ...

    African Journals Online (AJOL)

    ... resulting from the cement hydration and are governed by various physical and ... of PET volumetric additive amounts for cement substituting and for the behavior ... Keywords: Composite Eco-materials; Cement substitution; Shrinkage strain; ...

  20. A case study of shrinkage-in place leaching of low grade uranium ore deposit

    International Nuclear Information System (INIS)

    Ding Dexin; Zhou Guohe

    1998-09-01

    A case study of shrinkage-in place leaching of low grade uranium ore deposit is dealt with. A test block was selected, and the shrinkage mining method was employed to construct the in place heap for leaching. Blast parameters and operations were carefully tried in order to make sure that the fragment size composition was adequate for leaching. A leaching system was planned and the corresponding leaching parameters were tried, too. The results show that the shrinkage method and the parameters for blasting and leaching are all adequate for the in-situ leaching of the blasted ore. This shrinkage-in place leaching system combines the mining and metallurgy processes into one and produces a lot of profits and could be applicable to many low grade uranium ore deposits which are so hard and compact that they have to be fragmented before being leached

  1. Estimation of the profile of cross-machine shrinkage of paper

    International Nuclear Information System (INIS)

    I'Anson, S J; Sampson, W W; Constantino, R P A; Hoole, S M

    2008-01-01

    In common with many other materials, paper tends to shrink as it dries. Although every attempt is made to restrain paper, some shrinkage occurs on all paper machines in the direction perpendicular to that of manufacture and this shrinkage is always much higher at the edges of the machine than in the centre. Measurement of the profile of this cross-machine shrinkage is possible using the fast Fourier transform to locate and measure periodic elements imprinted by the filtration fabrics used during the formation of the paper web. This paper describes a new method which allows the geometrical relationships within the fabric to be used along with dimensional changes to estimate shrinkage. The method has the advantages over previous methods of more tolerant sampling protocols, operator independent analysis and improved accuracy

  2. Drying shrinkage problems in high-plastic clay soils in Oklahoma.

    Science.gov (United States)

    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...

  3. Sudden shrinkage of free rectus abdominis musculocutaneous flap 15 years after maxilla reconstruction

    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.

  4. Influence of fly ash, slag cement and specimen curing on shrinkage of bridge deck concrete.

    Science.gov (United States)

    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...

  5. Prediction of shrinkage cracking age of concrete with and without expansive additive

    Directory of Open Access Journals (Sweden)

    Dung Tien Nguyen

    2010-10-01

    Full Text Available The aim of this research is to propose a model for predicting cracking age of concrete due to restrained shrinkage. Thisstudy focuses on analyzing shrinkage and expansion mechanisms in the expansive concrete to formulate a model that can beemployed to predict whether shrinkage cracking occurs or not. In case of conventional (non-expansive concrete, this modelcan be applied by neglecting the early expansion due to expansive additive. Parameters considered in this model are restrainedexpansion, free shrinkage, cracking strain that can be experimentally measured by experiment and tensile creep which isderived by back calculation. The model was verified by test results of expansive concrete mixtures as well as normal concretemixtures both with and without fly ash.

  6. Development of high shrinkage polyethylene terephthalate (PET) shape memory polymer tendons for concrete crack closure

    Science.gov (United States)

    Teall, Oliver; Pilegis, Martins; Sweeney, John; Gough, Tim; Thompson, Glen; Jefferson, Anthony; Lark, Robert; Gardner, Diane

    2017-04-01

    The shrinkage force exerted by restrained shape memory polymers (SMPs) can potentially be used to close cracks in structural concrete. This paper describes the physical processing and experimental work undertaken to develop high shrinkage die-drawn polyethylene terephthalate (PET) SMP tendons for use within a crack closure system. The extrusion and die-drawing procedure used to manufacture a series of PET tendon samples is described. The results from a set of restrained shrinkage tests, undertaken at differing activation temperatures, are also presented along with the mechanical properties of the most promising samples. The stress developed within the tendons is found to be related to the activation temperature, the cross-sectional area and to the draw rate used during manufacture. Comparisons with commercially-available PET strip samples used in previous research are made, demonstrating an increase in restrained shrinkage stress by a factor of two for manufactured PET filament samples.

  7. Numerical Simulation on Open Wellbore Shrinkage and Casing Equivalent Stress in Bedded Salt Rock Stratum

    Directory of Open Access Journals (Sweden)

    Jianjun Liu

    2013-01-01

    Full Text Available Most salt rock has interbed of mudstone in China. Owing to the enormous difference of mechanical properties between the mudstone interbed and salt rock, the stress-strain and creep behaviors of salt rock are significantly influenced by neighboring mudstone interbed. In order to identify the rules of wellbore shrinkage and casings equivalent stress in bedded salt rock stratum, three-dimensional finite difference models were established. The effects of thickness and elasticity modulus of mudstone interbed on the open wellbore shrinkage and equivalent stress of casing after cementing operation were studied, respectively. The results indicate that the shrinkage of open wellbore and equivalent stress of casings decreases with the increase of mudstone interbed thickness. The increasing of elasticity modulus will reduce the shrinkage of open wellbore and casing equivalent stress. Research results can provide the scientific basis for the design of mud density and casing strength.

  8. 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.

  9. Characteristics of low polymerization shrinkage flowable resin composites in newly-developed cavity base materials for bulk filling technique.

    Science.gov (United States)

    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.

  10. Book review: Bayesian analysis for population ecology

    Science.gov (United States)

    Link, William A.

    2011-01-01

    Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)

  11. 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....

  12. Shrinkage stress in concrete under dry-wet cycles: an example with concrete column

    Science.gov (United States)

    Gao, Yuan; Zhang, Jun; Luosun, Yiming

    2014-02-01

    This paper focuses on the simulation of shrinkage stress in concrete structures under dry-wet environments. In the modeling, an integrative model for autogenous and drying shrinkage predictions of concrete under dry-wet cycles is introduced first. Second, a model taking both cement hydration and moisture diffusion into account synchronously is used to calculate the distribution of interior humidity in concrete. Using the above two models, the distributions of shrinkage strain and stress in concrete columns made by normal and high strength concrete respectively under dry-wet cycles are calculated. The model results show that shrinkage gradient along the radial direction of the column from the center to outer surface increases with age as the outer circumference suffers to dry. The maximum and minimum shrinkage occur at the outer surface and the center of the column, respectively, under drying condition. As wetting starts, the shrinkage strain decreases with increase of interior humidity. The closer to the wetting face, the higher the humidity and the lower the shrinkage strain, as well as the lower the shrinkage stress. As results of the dry-wet cycles acting on the outer circumference of the column, cyclic stress status is developed within the area close to the outer surface of the column. The depth of the influencing zone of dry-wet cyclic action is influenced by concrete strength and dry-wet regime. For low strength concrete, relatively deeper influencing zone is expected compared with that of high strength concrete. The models are verified by concrete-steel composite ring tests and a good agreement between model and test results is found.

  13. Bayesian analogy with relational transformations.

    Science.gov (United States)

    Lu, Hongjing; Chen, Dawn; Holyoak, Keith J

    2012-07-01

    How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. Copyright 2012 APA, all rights reserved.

  14. The effect of mucosal cuff shrinkage around dental implants during healing abutment replacement.

    Science.gov (United States)

    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.

  15. Effect of shrinkage porosity on mechanical properties of ferritic ductile iron

    Directory of Open Access Journals (Sweden)

    Wang Zehua

    2013-05-01

    Full Text Available Casting defects could largely affect the mechanical properties of casting products. A number of test pieces made of ductile iron (EN-GJS-400-18-LT with different levels of shrinkage porosity were prepared and then tensile and fatigue tests were performed to investigate the impact of shrinkage porosity on their mechanical properties. The results showed that the tensile strength decreases linearly with increasing of the shrinkage porosity. The tensile elongation decreases sharply with the increase of the shrinkage porosity mainly due to the non-uniform plastic deformation. The fatigue life also dramatically declines with increasing of the porosity and follows a power law relationship with the area percentage of porosity. The existence of the shrinkage porosity made the fatigue fracture complex. The shrinkage pores, especially those close to the surface usually became the crack initiation sites. For test pieces with less porosity, the fatigue fracture was clearly composed of crack initiation, propagation, and overloading. While for samples with high level of porosity, multiple crack initiation sites were observed.

  16. Digital image analysis of radial shrinkage of fresh spruce (Picea abies L.) wood.

    Science.gov (United States)

    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.

  17. Current trends in Bayesian methodology with applications

    CERN Document Server

    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

  18. Bayesian image restoration, using configurations

    OpenAIRE

    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...

  19. 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...

  20. Minimum mean square error estimation and approximation of the Bayesian update

    KAUST Repository

    Litvinenko, Alexander; Matthies, Hermann G.; Zander, Elmar

    2015-01-01

    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.

  1. Minimum mean square error estimation and approximation of the Bayesian update

    KAUST Repository

    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.

  2. Image-based modeling of tumor shrinkage in head and neck radiation therapy1

    Science.gov (United States)

    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. PMID:20527569

  3. 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.

  4. Image-based modeling of tumor shrinkage in head and neck radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Chao Ming; Xie Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing Lei [Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 and Department of Radiation Oncology, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Little Rock, Arkansas 72205-1799 (United States); Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 (United States); Department of Radiation Oncology, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Little Rock, Arkansas 72205-1799 (United States); Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 (United States)

    2010-05-15

    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.

  5. Water storage change estimation from in situ shrinkage measurements of clay soils

    Directory of Open Access Journals (Sweden)

    B. te Brake

    2013-05-01

    Full Text Available The objective of this study is to assess the applicability of clay soil elevation change measurements to estimate soil water storage changes, using a simplified approach. We measured moisture contents in aggregates by EC-5 sensors, and in multiple aggregate and inter-aggregate spaces (bulk soil by CS616 sensors. In a long dry period, the assumption of constant isotropic shrinkage proved invalid and a soil moisture dependant geometry factor was applied. The relative overestimation made by assuming constant isotropic shrinkage in the linear (basic shrinkage phase was 26.4% (17.5 mm for the actively shrinking layer between 0 and 60 cm. Aggregate-scale water storage and volume change revealed a linear relation for layers ≥ 30 cm depth. The range of basic shrinkage in the bulk soil was limited by delayed drying of deep soil layers, and maximum water loss in the structural shrinkage phase was 40% of total water loss in the 0–60 cm layer, and over 60% in deeper layers. In the dry period, fitted slopes of the ΔV–ΔW relationship ranged from 0.41 to 0.56 (EC-5 and 0.42 to 0.55 (CS616. Under a dynamic drying and wetting regime, slopes ranged from 0.21 to 0.38 (EC-5 and 0.22 to 0.36 (CS616. Alternating shrinkage and incomplete swelling resulted in limited volume change relative to water storage change. The slope of the ΔV–ΔW relationship depended on the drying regime, measurement scale and combined effect of different soil layers. Therefore, solely relying on surface level elevation changes to infer soil water storage changes will lead to large underestimations. Recent and future developments might provide a basis for application of shrinkage relations to field situations, but in situ observations will be required to do so.

  6. Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Peng, E-mail: peng@ices.utexas.edu [The Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 East 24th Street, Stop C0200, Austin, TX 78712-1229 (United States); Schwab, Christoph, E-mail: christoph.schwab@sam.math.ethz.ch [Seminar für Angewandte Mathematik, Eidgenössische Technische Hochschule, Römistrasse 101, CH-8092 Zürich (Switzerland)

    2016-07-01

    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

  7. Complexity analysis of accelerated MCMC methods for Bayesian inversion

    International Nuclear Information System (INIS)

    Hoang, Viet Ha; Schwab, Christoph; Stuart, Andrew M

    2013-01-01

    The Bayesian approach to inverse problems, in which the posterior probability distribution on an unknown field is sampled for the purposes of computing posterior expectations of quantities of interest, is starting to become computationally feasible for partial differential equation (PDE) inverse problems. Balancing the sources of error arising from finite-dimensional approximation of the unknown field, the PDE forward solution map and the sampling of the probability space under the posterior distribution are essential for the design of efficient computational Bayesian methods for PDE inverse problems. We study Bayesian inversion for a model elliptic PDE with an unknown diffusion coefficient. We provide complexity analyses of several Markov chain Monte Carlo (MCMC) methods for the efficient numerical evaluation of expectations under the Bayesian posterior distribution, given data δ. Particular attention is given to bounds on the overall work required to achieve a prescribed error level ε. Specifically, we first bound the computational complexity of ‘plain’ MCMC, based on combining MCMC sampling with linear complexity multi-level solvers for elliptic PDE. Our (new) work versus accuracy bounds show that the complexity of this approach can be quite prohibitive. Two strategies for reducing the computational complexity are then proposed and analyzed: first, a sparse, parametric and deterministic generalized polynomial chaos (gpc) ‘surrogate’ representation of the forward response map of the PDE over the entire parameter space, and, second, a novel multi-level Markov chain Monte Carlo strategy which utilizes sampling from a multi-level discretization of the posterior and the forward PDE. For both of these strategies, we derive asymptotic bounds on work versus accuracy, and hence asymptotic bounds on the computational complexity of the algorithms. In particular, we provide sufficient conditions on the regularity of the unknown coefficients of the PDE and on the

  8. Neoadjuvant androgen deprivation and prostate gland shrinkage during conformal radiotherapy

    International Nuclear Information System (INIS)

    Sanguineti, Giuseppe; Marcenaro, Michela; Franzone, Paola; Foppiano, Franca; Vitale, Vito

    2003-01-01

    =0.03). At tmtCT, on average, patients undergoing 3DCRT within 3 months from AD start showed an increase of the amount of rectum receiving 40-75 Gy compared to plCT values. At 40 Gy (V40) the mean difference between tmtCT and plCT was +7.5%. In the other two groups, average variations of V40-70 were within ±2% of plCT values. However, these differences are not significant. Conclusion: For patients who undergo plCT and 3DCRT shortly after AD start, prostate gland shrinkage may be substantial. In some of these patients, this might lead to an unexpected increase of the percentage of rectal wall exposed to intermediate doses

  9. 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

  10. BAYESIAN INFERENCE OF CMB GRAVITATIONAL LENSING

    Energy Technology Data Exchange (ETDEWEB)

    Anderes, Ethan [Department of Statistics, University of California, Davis, CA 95616 (United States); Wandelt, Benjamin D.; Lavaux, Guilhem [Sorbonne Universités, UPMC Univ Paris 06 and CNRS, UMR7095, Institut d’Astrophysique de Paris, F-75014, Paris (France)

    2015-08-01

    The Planck satellite, along with several ground-based telescopes, has mapped the cosmic microwave background (CMB) at sufficient resolution and signal-to-noise so as to allow a detection of the subtle distortions due to the gravitational influence of the intervening matter distribution. A natural modeling approach is to write a Bayesian hierarchical model for the lensed CMB in terms of the unlensed CMB and the lensing potential. So far there has been no feasible algorithm for inferring the posterior distribution of the lensing potential from the lensed CMB map. We propose a solution that allows efficient Markov Chain Monte Carlo sampling from the joint posterior of the lensing potential and the unlensed CMB map using the Hamiltonian Monte Carlo technique. The main conceptual step in the solution is a re-parameterization of CMB lensing in terms of the lensed CMB and the “inverse lensing” potential. We demonstrate a fast implementation on simulated data, including noise and a sky cut, that uses a further acceleration based on a very mild approximation of the inverse lensing potential. We find that the resulting Markov Chain has short correlation lengths and excellent convergence properties, making it promising for applications to high-resolution CMB data sets in the future.

  11. Effects of Prepolymerized Particle Size and Polymerization Kinetics on Volumetric Shrinkage of Dental Modeling Resins

    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.

  12. Drying Shrinkage of Mortar Incorporating High Volume Oil Palm Biomass Waste

    Science.gov (United States)

    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.

  13. Shrinkage Characteristics of Experimental Polymer Containing Composites under Controlled Light Curing Modes

    Directory of Open Access Journals (Sweden)

    Alain Pefferkorn

    2012-01-01

    Full Text Available The adsorption of polymethylmethacrylate polymer of different molecular weight at the aerosil/ethyleneglycol- or 1,3 butanediol-dimethacrylate interfaces was determined to provide microstructured networks. Their structural characteristics were determined to be controlled by the amount of polymer initially supplied to the system. The sediment (the settled phase characteristics, determined as a function of the polymer concentration and the rate of the polymerization shrinkage determined for composite resins, obtained by extrusion of the sediment after centrifugation, were found to be correlated. The specific role of the adsorbed polymer was found to be differently perturbed with the supplementary supply of dimethacrylate based monomer additives. Particularly, the bisphenol A dimethacrylate that generated crystals within the sediment was found to impede the shrinkage along the crystal lateral faces and strongly limit the shrinkage along its basal faces. Addition of ethyleneglycol- or polyethylene-glycoldimethacrylate monomers was determined to modify the sedimentation characteristics of the aerosil suspension and the shrinkage properties of the composites. Finally, the effects of stepwise light curing methods with prolonged lighting-off periods were investigated and found to modify the development and the final values of the composite shrinkage.

  14. Drying Shrinkage Behaviour of Fibre Reinforced Concrete Incorporating Polyvinyl Alcohol Fibres and Fly Ash

    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.

  15. Shrinkage modeling of concrete reinforced by palm fibres in hot dry environments

    Science.gov (United States)

    Akchiche, Hamida; Kriker, Abdelouahed

    2017-02-01

    The cement materials, such as concrete and conventional mortar present very little resistance to traction and cracking, these hydraulic materials which induces large withdrawals on materials and cracks in structures. The hot dry environments such as: the Saharan regions of Algeria, Indeed, concrete structures in these regions are very fragile, and present high shrinkage. Strengthening of these materials by fibers can provide technical solutions for improving the mechanical performance. The aim of this study is firstly, to reduce the shrinkage of conventional concrete with its reinforcement with date palm fibers. In fact, Algeria has an extraordinary resources in natural fibers (from Palm, Abaca, Hemp) but without valorization in practical areas, especially in building materials. Secondly, to model the shrinkage behavior of concrete was reinforced by date palm fibers. In the literature, several models for still fiber concrete were founded but few are offers for natural fiber concretes. To do so, a still fiber concretes model of YOUNG - CHERN was used. According to the results, a reduction of shrinkage with reinforcement by date palm fibers was showed. A good ability of molding of shrinkage of date palm reinforced concrete with YOUNG - CHERN Modified model was obtained. In fact, a good correlation between experimental data and the model data was recorded.

  16. Effect of steel fibers on plastic shrinkage cracking of normal and high strength concretes

    Directory of Open Access Journals (Sweden)

    Özgür Eren

    2010-06-01

    Full Text Available Naturally concrete shrinks when it is subjected to a drying environment. If this shrinkage is restrained, tensile stresses develop and concrete may crack. Plastic shrinkage cracks are especially harmful on slabs. One of the methods to reduce the adverse effects of shrinkage cracking of concrete is by reinforcing concrete with short randomly distributed fibers. The main objective of this study was to investigate the effect of fiber volume and aspect ratio of hooked steel fibers on plastic shrinkage cracking behavior together with some other properties of concrete. In this research two different compressive strength levels namely 56 and 73 MPa were studied. Concretes were produced by adding steel fibers of 3 different volumes of 3 different aspect ratios. From this research study, it is observed that steel fibers can significantly reduce plastic shrinkage cracking behavior of concretes. On the other hand, it was observed that these steel fibers can adversely affect some other properties of concrete during fresh and hardened states.

  17. Modified creep and shrinkage prediction model B3 for serviceability limit state analysis of composite slabs

    Science.gov (United States)

    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.

  18. 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.

  19. A generalized DEMATEL theory with a shrinkage coefficient for an indirect relation matrix

    Directory of Open Access Journals (Sweden)

    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.

  20. Restrained Shrinkage Cracking of Fiber-Reinforced High-Strength Concrete

    Directory of Open Access Journals (Sweden)

    Ashkan Saradar

    2018-02-01

    Full Text Available Concrete shrinkage and volume reduction happens due to the loss of moisture, which eventually results in cracks and more concrete deformation. In this study, the effect of polypropylene (PP, steel, glass, basalt, and polyolefin fibers on compressive and flexural strength, drying shrinkage, and cracking potential, using the ring test at early ages of high-strength concrete mixtures, was investigated. The restrained shrinkage test was performed on concrete ring specimens according to the ASTM C1581 standard. The crack width and age of restrained shrinkage cracking were the main parameters studied in this research. The results indicated that the addition of fiber increases the compressive strength by 16%, 20%, and 3% at the age of 3, 7, and 28 days, respectively, and increases the flexural toughness index up to 7.7 times. Steel and glass fibers had a better performance in flexural strength, but relatively poor action in the velocity reduction and cracking time of the restrained shrinkage. Additionally, cracks in all concrete ring specimens except for the polypropylene-containing mixture, was developed to a full depth crack. The mixture with polypropylene fiber indicated a reduction in crack width up to 62% and an increasing age cracking up to 84%.

  1. Bayesian networks improve causal environmental ...

    Science.gov (United States)

    Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

  2. Bayesian Latent Class Analysis Tutorial.

    Science.gov (United States)

    Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca

    2018-01-01

    This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.

  3. Kernel Bayesian ART and ARTMAP.

    Science.gov (United States)

    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.

  4. Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

    Science.gov (United States)

    Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

    2016-05-01

    elicitation methodology is developed and applied to the real-world test case in order to provide a road map for the use of fuzzy Bayesian inference in groundwater modeling applications.

  5. Conjugation of diisocyanate side chains to dimethacrylate reduces polymerization shrinkage and increases the hardness of composite 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.

  6. An Experimental Study on Shrinkage Strains of Normal-and High-Strength Concrete-Filled Frp Tubes

    Science.gov (United States)

    Vincent, Thomas; Ozbakkaloglu, Togay

    2017-09-01

    It is now well established that concrete-filled fiber reinforced polymer (FRP) tubes (CFFTs) are an attractive construction technique for new columns, however studies examining concrete shrinkage in CFFTs remain limited. Concrete shrinkage may pose a concern for CFFTs, as in these members the curing of concrete takes place inside the FRP tube. This paper reports the findings from an experimental study on concrete shrinkage strain measurements for CFFTs manufactured with normal- and high-strength concrete (NSC and HSC). A total of 6 aramid FRP (AFRP)-confined concrete specimens with circular cross-sections were manufactured, with 3 specimens each manufactured using NSC and HSC. The specimens were instrumented with surface and embedded strain gauges to monitor shrinkage development of exposed concrete and concrete sealed inside the CFFTs, respectively. All specimens were cylinders with a 152 mm diameter and 305 mm height, and their unconfined concrete strengths were 44.8 or 83.2 MPa. Analysis of the shrinkage measurements from concrete sealed inside the CFFTs revealed that embedment depth and concrete compressive strength only had minor influences on recorded shrinkage strains. However, an analysis of shrinkage measurements from the exposed concrete surface revealed that higher amounts of shrinkage can occur in HSC. Finally, it was observed that shrinkage strains are significantly higher for concrete exposed at the surface compared to concrete sealed inside the CFFTs.

  7. Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space

    DEFF Research Database (Denmark)

    Østby, Ivar; Øyehaug, Leiv; Einevoll, Gaute T

    2009-01-01

    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 astr......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...... 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...

  8. Mathematical model for creep and thermal shrinkage of concrete at high temperature

    International Nuclear Information System (INIS)

    Bazant, Z.P.

    1983-01-01

    Based on the existing limited test data, it is possible to set up an approximate constitutive model for creep and shrinkage at temperatures above 100 0 C, up to about 400 0 C. The model presented here describes the effect of various constant temperatures on the creep rate and the rate of aging, similar effects of the specific water content, the creep increase caused by simultaneous changes in moisture content, the thermal volume changes as well as the volume changes caused by changes in moisture content (drying shrinkage or thermal shrinkage), and the effect of pore pressure produced by heating. Generalizations to time-variable stresses and multiaxial stresses are also given. The model should allow more realistic analysis of reactor vessels and containments for accident situations, of concrete structures subjected to fire, of vessels for coal gasification or liquefaction, etc. (orig.)

  9. 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

  10. 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

    Fundamental studies of the early-age desiccation of cement-based materials with and without a shrinkage-reducing admixture (SRA) have been performed. Studies have been conducted under both sealed and drying conditions. Physical measurements include mass loss, surface tension, X-ray absorption to ...... to low w/c ratio concretes undergoing self-desiccation, in addition to their normal usage to reduce drying shrinkage.......Fundamental studies of the early-age desiccation of cement-based materials with and without a shrinkage-reducing admixture (SRA) have been performed. Studies have been conducted under both sealed and drying conditions. Physical measurements include mass loss, surface tension, X-ray absorption...

  11. Numerical simulation of early-age shrinkage effects on RC member deflections and cracking development

    Directory of Open Access Journals (Sweden)

    P. Bernardi

    2016-07-01

    Full Text Available Shrinkage effects on short-term behavior of reinforced concrete elements are often neglected both in design code provisions and in numerical simulations. However, it is known that their influence on serviceability performance can be significant, especially in case of lightly-reinforced beams. As a matter of fact, the restraint provided by the reinforcement on concrete determines a reduction of the cracking load of the structural element, as well as an increase of its deflection. This paper deals with the modeling of early-age shrinkage effects in the field of smeared crack approaches. To this aim, an existing non-linear constitutive relation for cracked reinforced concrete elements is extended herein to include early-age concrete shrinkage. Careful verifications of the model are carried out by comparing numerical results with significant experimental data reported in technical literature, providing a good agreement both in terms of global and local behavior.

  12. Ultra low-K shrinkage behavior when under electron beam in a scanning electron microscope

    Energy Technology Data Exchange (ETDEWEB)

    Lorut, F.; Imbert, G. [ST Microelectronics, 850 rue Jean Monnet, 38926 Crolles Cedex (France); Roggero, A. [Centre National d' Etudes Spatiales, 18 Avenue Edouard Belin, 31400 Toulouse (France)

    2013-08-28

    In this paper, we investigate the tendency of porous low-K dielectrics (also named Ultra Low-K, ULK) behavior to shrink when exposed to the electron beam of a scanning electron microscope. Various experimental electron beam conditions have been used for irradiating ULK thin films, and the resulting shrinkage has been measured through use of an atomic force microscope tool. We report the shrinkage to be a fast, cumulative, and dose dependent effect. Correlation of the shrinkage with incident electron beam energy loss has also been evidenced. The chemical modification of the ULK films within the interaction volume has been demonstrated, with a densification of the layer and a loss of carbon and hydrogen elements being observed.

  13. Shrinkage Analysis on Thick Plate Part using Response Surface Methodology (RSM

    Directory of Open Access Journals (Sweden)

    Isafiq M.

    2016-01-01

    Full Text Available The work reported herein is about an analysis on the quality (shrinkage on a thick plate part using Response Surface Methodology (RSM. Previous researches showed that the most influential factor affecting the shrinkage on moulded parts are mould and melt temperature. Autodesk Moldflow Insight software was used for the analysis, while specifications of Nessei NEX 1000 injection moulding machine and P20 mould material were incorporated in this study on top of Acrylonitrile Butadiene Styrene (ABS as a moulded thermoplastic material. Mould temperature, melt temperature, packing pressure and packing time were selected as variable parameters. The results show that the shrinkage have improved 42.48% and 14.41% in parallel and normal directions respectively after the optimisation process.

  14. Interactive Instruction in Bayesian Inference

    DEFF Research Database (Denmark)

    Khan, Azam; Breslav, Simon; Hornbæk, Kasper

    2018-01-01

    An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These pri......An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction....... These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pretraining. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions...... that an instructional approach to improving human performance in Bayesian inference is a promising direction....

  15. Probability biases as Bayesian inference

    Directory of Open Access Journals (Sweden)

    Andre; C. R. Martins

    2006-11-01

    Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.

  16. Bayesian analysis of CCDM models

    Science.gov (United States)

    Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.

    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 = 3αH0 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.

  17. 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.

  18. Learning Bayesian networks for discrete data

    KAUST Repository

    Liang, Faming; Zhang, Jian

    2009-01-01

    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

  19. Bayesian Network Induction via Local Neighborhoods

    National Research Council Canada - National Science Library

    Margaritis, Dimitris

    1999-01-01

    .... We present an efficient algorithm for learning Bayesian networks from data. Our approach constructs Bayesian networks by first identifying each node's Markov blankets, then connecting nodes in a consistent way...

  20. Can a significance test be genuinely Bayesian?

    OpenAIRE

    Pereira, Carlos A. de B.; Stern, Julio Michael; Wechsler, Sergio

    2008-01-01

    The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.

  1. Bayesian modeling using WinBUGS

    CERN Document Server

    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 ...

  2. Polymerization Behavior and Mechanical Properties of High-Viscosity Bulk Fill and Low Shrinkage Resin Composites.

    Science.gov (United States)

    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

  3. Strength, shrinkage, erodibility and capillary flow characteristics of cement-treated recycled pavement materials

    Directory of Open Access Journals (Sweden)

    William Fedrigo

    2017-09-01

    Full Text Available Full-depth recycling with portland cement (FDR-PC has been widely used for pavement rehabilitation; however, doubts remain regarding factors affecting some properties of the recycled material. Aiming on quantifying the effects of those factors on the strength, drying shrinkage, erodibility, capillary rise and absorption of cement-treated mixtures (CTM of reclaimed asphalt pavement (RAP and graded crushed stone, tests were conducted considering different RAP contents, cement contents, compaction efforts and curing times. Cement addition increased the mixtures strength and reduced their erodibility and capillary flow characteristics, but increased shrinkage. Low cement contents resulted in acceptable strength for CTM, but in high capillary rise and absorption, not being suitable if the layer is exposed to long periods of water soaking. Higher compaction effort led to similar effects as cement addition, counterbalancing low cement contents usage and reducing costs and shrinkage cracking risk. Strength and shrinkage showed higher growth rates at early stages, and then precautions should be taken in order to avoid moisture loss. Increasing RAP content decreased strength; though, RAP effect on the other properties was statistically non-significant, indicating a similar behaviour as CTM without RAP. Considering the studied properties, the mixture with most satisfactory behaviour for field applications was identified. The results highlighted strength is not the only property to be considered when designing FDR-PC mixtures; although presenting acceptable strength, some mixtures may fail due to shrinkage cracking or erosion, when exposed to water content variations. Keywords: Full-depth recycling with cement, Strength, Drying shrinkage, Erodibility, Capillary rise, Absorption

  4. Diversity shrinkage: Cross-validating pareto-optimal weights to enhance diversity via hiring practices.

    Science.gov (United States)

    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).

  5. Regional Brain Shrinkage over Two Years: Individual Differences and Effects of Pro-Inflammatory Genetic Polymorphisms

    Science.gov (United States)

    Persson, N.; Ghisletta, P.; Dahle, C.L.; Bender, A.R.; Yang, Y.; Yuan, P.; Daugherty, A.M.; Raz, N.

    2014-01-01

    We examined regional changes in brain volume in healthy adults (N = 167, age 19-79 years at baseline; N = 90 at follow-up) over approximately two years. With latent change score models, we evaluated mean change and individual differences in rates of change in 10 anatomically-defined and manually-traced regions of interest (ROIs): lateral prefrontal cortex (LPFC), orbital frontal cortex (OF), prefrontal white matter (PFw), hippocampus (HC), parahippocampal gyrus (PhG), caudate nucleus (Cd), putamen (Pt), insula (In), cerebellar hemispheres (CbH), and primary visual cortex (VC). Significant mean shrinkage was observed in the HC, CbH, In, OF, and the PhG, and individual differences in change were noted in all regions, except the OF. Pro-inflammatory genetic variants mediated shrinkage in PhG and CbH. Carriers of two T alleles of interleukin-1β (IL-1βC-511T, rs16944) and a T allele of methylenetetrahydrofolate reductase (MTHFRC677T, rs1801133) polymorphisms showed increased PhG shrinkage. No effects of a pro-inflammatory polymorphism for C-reactive protein (CRP-286C>A>T, rs3091244) or apolipoprotein (APOE) ε4 allele were noted. These results replicate the pattern of brain shrinkage observed in previous studies, with a notable exception of the LPFC thus casting doubt on the unique importance of prefrontal cortex in aging. Larger baseline volumes of CbH and In were associated with increased shrinkage, in conflict with the brain reserve hypothesis. Contrary to previous reports, we observed no significant linear effects of age and hypertension on regional brain shrinkage. Our findings warrant further investigation of the effects of neuroinflammation on structural brain change throughout the lifespan. PMID:25264227

  6. Inference in hybrid Bayesian networks

    International Nuclear Information System (INIS)

    Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio

    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 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 (the so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability.

  7. 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....

  8. Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method

    KAUST Repository

    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.

  9. Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method

    KAUST Repository

    Desmal, Abdulla; Bagci, Hakan

    2014-01-01

    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.

  10. OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE.

    Science.gov (United States)

    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.

  11. 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

    shrinkage, has been marketed. Objective. To investigate whether reduced polymerization shrinkage improves the marginal adaptation of composite restorations. Material and methods. A total of 156 scanning electron microscopy (SEM) pictures (78 baseline, 78 follow-up) of the occlusal part of Class II......-casts of the restorations were used for SEM pictures at x 16 magnification. Pictures from baseline and follow-up (398 days, SD 29 days) were randomized and the examiner was blinded to the material and the age of the restoration. Stereologic measurements were used to calculate the length and the width of the marginal...

  12. 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....

  13. 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.

  14. Bayesian networks and food security - An introduction

    NARCIS (Netherlands)

    Stein, A.

    2004-01-01

    This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision

  15. Plug & Play object oriented Bayesian networks

    DEFF Research Database (Denmark)

    Bangsø, Olav; Flores, J.; Jensen, Finn Verner

    2003-01-01

    been shown to be quite suitable for dynamic domains as well. However, processing object oriented Bayesian networks in practice does not take advantage of their modular structure. Normally the object oriented Bayesian network is transformed into a Bayesian network and, inference is performed...... dynamic domains. The communication needed between instances is achieved by means of a fill-in propagation scheme....

  16. A Bayesian framework for risk perception

    NARCIS (Netherlands)

    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

  17. 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.

  18. Bayesian NL interpretation and learning

    NARCIS (Netherlands)

    Zeevat, H.

    2011-01-01

    Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language

  19. Bayesian image restoration, using configurations

    DEFF Research Database (Denmark)

    Thorarinsdottir, Thordis

    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...

  20. Bayesian image restoration, using configurations

    DEFF Research Database (Denmark)

    Thorarinsdottir, Thordis Linda

    2006-01-01

    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...

  1. Differentiated Bayesian Conjoint Choice Designs

    NARCIS (Netherlands)

    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

  2. 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...

  3. Bayesian Sampling using Condition Indicators

    DEFF Research Database (Denmark)

    Faber, Michael H.; Sørensen, John Dalsgaard

    2002-01-01

    of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...

  4. 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 dimensi...

  5. Bayesian estimates of linkage disequilibrium

    Directory of Open Access Journals (Sweden)

    Abad-Grau María M

    2007-06-01

    Full Text Available Abstract Background The maximum likelihood estimator of D' – a standard measure of linkage disequilibrium – is biased toward disequilibrium, and the bias is particularly evident in small samples and rare haplotypes. Results This paper proposes a Bayesian estimation of D' to address this problem. The reduction of the bias is achieved by using a prior distribution on the pair-wise associations between single nucleotide polymorphisms (SNPs that increases the likelihood of equilibrium with increasing physical distances between pairs of SNPs. We show how to compute the Bayesian estimate using a stochastic estimation based on MCMC methods, and also propose a numerical approximation to the Bayesian estimates that can be used to estimate patterns of LD in large datasets of SNPs. Conclusion Our Bayesian estimator of D' corrects the bias toward disequilibrium that affects the maximum likelihood estimator. A consequence of this feature is a more objective view about the extent of linkage disequilibrium in the human genome, and a more realistic number of tagging SNPs to fully exploit the power of genome wide association studies.

  6. 3-D contextual Bayesian classifiers

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...

  7. 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

  8. 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)

  9. Use of rice husk ash for mitigating the autogenous shrinkage of cement pastes at low water cement ratio

    NARCIS (Netherlands)

    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

  10. Study of SEM preparation artefacts with correlative microscopy: Cell shrinkage of adherent cells by HMDS-drying.

    Science.gov (United States)

    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.

  11. Bayesian analysis of rare events

    Energy Technology Data Exchange (ETDEWEB)

    Straub, Daniel, E-mail: straub@tum.de; 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.

  12. Effectiveness of Fiber Reinforcement on the Mechanical Properties and Shrinkage Cracking of Recycled Fine Aggregate Concrete

    Science.gov (United States)

    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

  13. Significance of Shrinkage Induced Clamping Pressure in Fiber-Matrix Bonding in Cementitious Composite Materials

    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...

  14. 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...

  15. The Influence of Water Sorption of Dental Light-Cured Composites on Shrinkage Stress

    Directory of Open Access Journals (Sweden)

    Kinga Bociong

    2017-09-01

    Full Text Available The contraction stress generated during the photopolymerization of resin dental composites is the major disadvantage. The water sorption in the oral environment should counteract the contraction stress. The purpose was to evaluate the influence of the water sorption of composite materials on polymerization shrinkage stress generated at the restoration-tooth interface. The following materials were tested: Filtek Ultimate, Gradia Direct LoFlo, Heliomolar Flow, Tetric EvoCeram, Tetric EvoCeram Bulk Fill, Tetric EvoFlow, Tetric EvoFlow Bulk Fill, X-tra Base, Venus BulkFil, and Ceram.X One. The shrinkage stress was measured immediately after curing and after: 0.5 h, 24 h, 72 h, 96 h, 168 h, 240 h, 336 h, 504 h, 672 h, and 1344 h by means of photoelastic study. Moreover, water sorption and solubility were evaluated. Material samples were weighted on scale in time intervals to measure the water absorbency and the dynamic of this process. The tested materials during polymerization generated shrinkage stresses ranging from 6.3 MPa to 12.5 MPa. Upon water conditioning (56 days, the decrease in shrinkage strain (not less than 48% was observed. The decrease in value stress in time is material-dependent.

  16. Fabrication and characterization of self-folding thermoplastic sheets using unbalanced thermal shrinkage.

    Science.gov (United States)

    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.

  17. Effects of Shrinkage Reducing Agent and Expansive Additive on Mortar Properties

    Directory of Open Access Journals (Sweden)

    Sarapon Treesuwan

    2017-01-01

    Full Text Available This research is to study the effect of mortar mixed with shrinkage reducing agent (polyoxyalkylene alkyl ether type, expansive additive (CaO type, and fly ash (hereinafter “SRA,” “EX,” and “FA,” resp.. Moreover, steam curing was studied to improve the properties of mortar. The plastic shrinkage test was conducted by using the strain gauge embedded at 0.5 cm from the surface according to the ASTM C1579-06 standard within early age followed by the total shrinkage test and compressive strength test. The test results showed that mixing both the EX and SRA increases the plastic enlargement of the mortar during the early age more than using either the EX or SRA solely. The steam curing helps to reduce the plastic shrinkage when the mortar is added with the FA and SRA while adding the EX increases the enlargement compared to the normal curing. When the EX, SRA, and FA are all added to the mortar mixing, great attention should be paid due to the increase of greater enlargement. For the compressive strength view, the steam curing increases the compressive strength in all types of mixture. The steam curing significantly helps increasing the compressive strength of mortar with combination of EX, SRA, and FA. Nevertheless, the XRD and SEM tests explain such enlargement accordingly.

  18. Specimen Shrinkage and Its Influence on Margin Assessment in Breast Cancer

    Directory of Open Access Journals (Sweden)

    Badrul H. Yeap

    2007-07-01

    Conclusion: Breast specimens undergo shrinkage after histological fixation, losing more than a third of their original closest free margin, whilst the tumour itself does not shrink substantially. This phenomenon has vital implications in the accuracy of margin analysis and consequent decisions on further management, including re-operation and the institution of adjuvant radiotherapy.

  19. 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.

  20. Measurement with corrugated tubes of early-age autogenous shrinkage of cement-based material

    DEFF Research Database (Denmark)

    Tian, Qian; Jensen, Ole Mejlhede

    2009-01-01

    The use of a special corrugated mould enables transformation of volume strain into horizontal, linear strain measurement in the fluid stage. This allows continuous measurement of the autogenous shrinkage of cement-based materials since casting, and also effectively eliminates unwanted influence...

  1. Ultra high performance concrete made with rice husk ash for reduced autogenous shrinkage

    NARCIS (Netherlands)

    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

  2. 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.)

  3. A modelling study of drying shrinkage damage in concrete repair systems

    NARCIS (Netherlands)

    Lukovic, M.; Savija, B.; Schlangen, E.; Ye, G.; van Breugel, K.

    2014-01-01

    Differential shrinkage between repair material and concrete substrate is considered to be the main cause of premature failure of repair systems (Martinola, Sadouki et al. 2001, Beushausen and Alexander 2007). Magnitude of induced stresses depends on many factors, for example the amount of restraint,

  4. A 3D Lattice Modelling Study of Drying Shrinkage Damage in Concrete Repair Systems

    NARCIS (Netherlands)

    Lukovic, M.; Savija, B.; Schlangen, H.E.J.G.; Ye, G.; van Breugel, K.

    2016-01-01

    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,

  5. 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.)

  6. Porous stainless steel hollow fibers with shrinkage-controlled small radial dimensions

    NARCIS (Netherlands)

    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

  7. Combined Use of Shrinkage Reducing Admixture and CaO in Cement Based Materials

    Science.gov (United States)

    Tittarelli, Francesca; Giosuè, Chiara; Monosi, Saveria

    2017-10-01

    The combined addition of a Shrinkage-Reducing Admixture (SRA) with a CaO-based expansive agent (CaO) has been found to have a synergistic effect to improve the dimensional stability of cement based materials. In this work, aimed to further investigate the effect, mortar and self-compacting concrete specimens were prepared either without admixtures, as reference, or with SRA alone and/or CaO. Their performance was compared in terms of compressive strength and free shrinkage measurements. Results showed that the synergistic effect in reducing shrinkage is confirmed in the specimens manufactured with SRA and CaO. In order to clarify this phenomenon, the effect of SRA on the hydration of CaO as well as cement was evaluated through different techniques. The obtained results show that SRA induces a finer microstructure of the CaO hydration products and a retarding effect on the microstructure development of cement based materials. A more deformable mortar or concrete, due to the delay in microstructure development by SRA, coupled with a finer microstructure of CaO hydration products could allow higher early expansion, which might contribute in contrasting better the successive drying shrinkage.

  8. Evaluation of the polymerization shrinkage of experimental flowable composite resins through optical coherence tomography

    Science.gov (United States)

    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.

  9. Urban shrinkage in Germany and the USA: a comparison of transformation patterns and local strategies.

    Science.gov (United States)

    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.

  10. 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...

  11. 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...

  12. 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

  13. ISTA-Net: Iterative Shrinkage-Thresholding Algorithm Inspired Deep Network for Image Compressive Sensing

    KAUST Repository

    Zhang, Jian; Ghanem, Bernard

    2017-01-01

    and the performance/speed of network-based ones. We propose a novel structured deep network, dubbed ISTA-Net, which is inspired by the Iterative Shrinkage-Thresholding Algorithm (ISTA) for optimizing a general $l_1$ norm CS reconstruction model. ISTA-Net essentially

  14. Polymerization stresses in low-shrinkage dental resin composites measured by crack analysis.

    Science.gov (United States)

    Yamamoto, Takatsugu; Kubota, Yu; Momoi, Yasuko; Ferracane, Jack L

    2012-09-01

    The objective of this study was to compare several dental restoratives currently advertised as low-shrinkage composites (Clearfil Majesty Posterior, Kalore, Reflexions XLS Dentin and Venus Diamond) with a microfill composite (Heliomolar) in terms of polymerization stress, polymerization shrinkage and elastic modulus. Cracks were made at several distances from the edge of a precision cavity in a soda-lime glass disk. The composites were placed into the cavity and lengths of the cracks were measured before and after light curing. Polymerization stresses generated in the glass at 2 and 10 min after the irradiation were calculated from the crack lengths and K(c) of the glass. Polymerization shrinkage and elastic modulus of the composites also were measured at 2 and 10 min after irradiation using a video-imaging device and a nanoindenter, respectively. The data were statistically analyzed by ANOVAs and Tukey's test (pelastic moduli of Clearfil Majesty Posterior and Reflexions XLS Dentin were greatest at 2 and 10 min, respectively. Among the four low-shrinkage composites, two demonstrated significantly reduced polymerization stress compared to Heliomolar, which has previously been shown in in vitro tests to generate low curing stress. Copyright © 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

  15. 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.

  16. Effectiveness of Fiber Reinforcement on the Mechanical Properties and Shrinkage Cracking of Recycled Fine Aggregate Concrete.

    Science.gov (United States)

    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.

  17. Direct voxel-based comparisons between grey matter shrinkage and glucose hypometabolism in chronic alcoholism.

    Science.gov (United States)

    Ritz, Ludivine; Segobin, Shailendra; Lannuzel, Coralie; Boudehent, Céline; Vabret, François; Eustache, Francis; Beaunieux, Hélène; Pitel, Anne L

    2016-09-01

    Alcoholism is associated with widespread brain structural abnormalities affecting mainly the frontocerebellar and the Papez's circuits. Brain glucose metabolism has received limited attention, and few studies used regions of interest approach and showed reduced global brain metabolism predominantly in the frontal and parietal lobes. Even though these studies have examined the relationship between grey matter shrinkage and hypometabolism, none has performed a direct voxel-by-voxel comparison between the degrees of structural and metabolic abnormalities. Seventeen alcoholic patients and 16 control subjects underwent both structural magnetic resonance imaging and (18)F-2-fluoro-deoxy-glucose-positron emission tomography examinations. Structural abnormalities and hypometabolism were examined in alcoholic patients compared with control subjects using two-sample t-tests. Then, these two patterns of brain damage were directly compared with a paired t-test. Compared to controls, alcoholic patients had grey matter shrinkage and hypometabolism in the fronto-cerebellar circuit and several nodes of Papez's circuit. The direct comparison revealed greater shrinkage than hypometabolism in the cerebellum, cingulate cortex, thalamus and hippocampus and parahippocampal gyrus. Conversely, hypometabolism was more severe than shrinkage in the dorsolateral, premotor and parietal cortices. The distinct profiles of abnormalities found within the Papez's circuit, the fronto-cerebellar circuit and the parietal gyrus in chronic alcoholism suggest the involvement of different pathological mechanisms. © The Author(s) 2015.

  18. Analysis of the shrinkage at the thick plate part using response surface methodology

    Science.gov (United States)

    Hatta, N. M.; Azlan, M. Z.; Shayfull, Z.; Roselina, S.; Nasir, S. M.

    2017-09-01

    Injection moulding is well known for its manufacturing process especially in producing plastic products. To measure the final product quality, there are lots of precautions to be taken into such as parameters setting at the initial stage of the process. Sometimes, if these parameters were set up wrongly, defects may be occurred and one of the well-known defects in the injection moulding process is a shrinkage. To overcome this problem, a maximisation at the precaution stage by making an optimal adjustment on the parameter setting need to be done and this paper focuses on analysing the shrinkage by optimising the parameter at thick plate part with the help of Response Surface Methodology (RSM) and ANOVA analysis. From the previous study, the outstanding parameter gained from the optimisation method in minimising the shrinkage at the moulded part was packing pressure. Therefore, with the reference from the previous literature, packing pressure was selected as the parameter setting for this study with other three parameters which are melt temperature, cooling time and mould temperature. The analysis of the process was obtained from the simulation by Autodesk Moldflow Insight (AMI) software and the material used for moulded part was Acrylonitrile Butadiene Styrene (ABS). The analysis and result were obtained and it found that the shrinkage can be minimised and the significant parameters were found as packing pressure, mould temperature and melt temperature.

  19. Experimental evaluation and simulation of volumetric shrinkage and warpage on polymeric composite reinforced with short natural fibers

    Science.gov (United States)

    Santos, Jonnathan D.; Fajardo, Jorge I.; Cuji, Alvaro R.; García, Jaime A.; Garzón, Luis E.; López, Luis M.

    2015-09-01

    A polymeric natural fiber-reinforced composite is developed by extrusion and injection molding process. The shrinkage and warpage of high-density polyethylene reinforced with short natural fibers of Guadua angustifolia Kunth are analyzed by experimental measurements and computer simulations. Autodesk Moldflow® and Solid Works® are employed to simulate both volumetric shrinkage and warpage of injected parts at different configurations: 0 wt.%, 20 wt.%, 30 wt.% and 40 wt.% reinforcing on shrinkage and warpage behavior of polymer composite. Become evident the restrictive effect of reinforcing on the volumetric shrinkage and warpage of injected parts. The results indicate that volumetric shrinkage of natural composite is reduced up to 58% with fiber increasing, whereas the warpage shows a reduction form 79% to 86% with major fiber content. These results suggest that it is a highly beneficial use of natural fibers to improve the assembly properties of polymeric natural fiber-reinforced composites.

  20. Predicting shrinkage and warpage in injection molding: Towards automatized mold design

    Science.gov (United States)

    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.

  1. Porcine intestinal mast cells. Evaluation of different fixatives for histochemical staining techniques considering tissue shrinkage

    Directory of Open Access Journals (Sweden)

    J. Rieger

    2013-07-01

    Full Text Available Staining of mast cells (MCs, including porcine ones, is critically dependent upon the fixation and staining technique. In the pig, mucosal and submucosal MCs do not stain or stain only faintly after formalin fixation. Some fixation methods are particularly recommended for MC staining, for example the fixation with Carnoy or lead salts. Zinc salt fixation (ZSF has been reported to work excellently for the preservation of fixation-sensitive antigens. The aim of this study was to establish a reliable histological method for counting of MCs in the porcine intestinum. For this purpose, different tissue fixation and staining methods that also allow potential subsequent immunohistochemical investigations were evaluated in the porcine mucosa, as well as submucosa of small and large intestine. Tissues were fixed in Carnoy, lead acetate, lead nitrate, Zamboni and ZSF and stained subsequently with either polychromatic methylene blue, alcian blue or toluidine blue. For the first time our study reveals that ZSF, a heavy metal fixative, preserves metachromatic staining of porcine MCs. Zamboni fixation was not suitable for histochemical visualization of MCs in the pig intestine. All other tested fixatives were suitable. Alcian blue and toluidine blue co-stained intestinal goblet cells which made a prima facie identification of MCs difficult. The polychromatic methylene blue proved to be the optimal staining. In order to compare MC counting results of the different fixation methods, tissue shrinkage was taken into account. As even the same fixation caused shrinkage-differences between tissue from small and large intestine, different factors for each single fixation and intestinal localization had to be calculated. Tissue shrinkage varied between 19% and 57%, the highest tissue shrinkage was found after fixation with ZSF in the large intestine, the lowest one in the small intestine after lead acetate fixation. Our study emphasizes that MC counting results from

  2. Reoxygenation of hypoxic cells by tumor shrinkage during irradiation. A computer simulation

    International Nuclear Information System (INIS)

    Kocher, M.; Treuer, H.

    1995-01-01

    A 3-dimensional computer simulation was developed in order to estimate the impact of tumor shrinkage on reoxygenation of chronic hypoxic tumor cells during a full course of fractionated irradiation. The growth of a small tumor situated in a vascularized stroma with 350 capillary cross-sections/mm 3 which were displaced by the growing tumor was simulated. Tumors contained 10 4 cells when irradiation started, intrinsic radiosensitivity was set to either low (α=0.3 Gy -1 , β=0.03 Gy -2 ) or high (α=0.4 Gy -1 , β=0.04 Gy -2 ) values. Oxygen enhancement ratio was 3.0, potential tumor doubling time T pot =1, 2 or 5 days. A simulated fractionated radiotherapy was carried out with daily fractions of 2.0 Gy, total dose 50 to 70 Gy. The presence or absence of factors preventing tumor cord shrinkage was also included. During the growth phase, all tumors developed a necrotic core with a hypoxic cell fraction of 25% under these conditions. During irradiation, the slower growing tumors (T pot =2 to 5 days) showed complete reoxygenation of the hypoxic cells after 30 to 40 Gy independent from radiosensitivity, undisturbed tumor shrinkage provided. If shrinkage was prevented, the hypoxic fraction rose to 100% after 30 to 50 Gy. Local tumor control, defined as the destruction of all clonogenic and hypoxic tumor cells increased by 20 to 100% due to reoxygenation and 50 Gy were enough in order to sterilize the tumors in these cases. In the fast growing tumors (T pot =1 day), reoxygenation was only observed in the case of high radiosensitivity and undisturbed tumor shrinkage. In these tumors reoxygenation increased the control rates by up to 60%. (orig./MG) [de

  3. DH and ESPI laser interferometry applied to the restoration shrinkage assessment

    International Nuclear Information System (INIS)

    Campos, L.M.P.; Parra, D.F.; Vasconcelos, M.R.; Vaz, M.; Monteiro, J.

    2014-01-01

    In dental restoration postoperative marginal leakage is commonly associated to polymerization shrinkage effects. In consequence the longevity and quality of restorative treatment depends on the shrinkage mechanisms of the composite filling during the polymerization. In this work the development of new techniques for evaluation of those effects under light-induced polymerization of dental nano composite fillings is reported. The composite resins activated by visible light, initiate the polymerization process by absorbing light in wavelengths at about 470 nm. The techniques employed in the contraction assessment were digital holography (DH) and Electronic Speckle Pattern Interferometry (ESPI) based on laser interferometry. A satisfactory resolution was achieved in the non-contact displacement field measurements on small objects concerning the experimental dental samples. According to a specific clinical protocol, natural teeth were used (human mandibular premolars). A class I cavity was drilled and restored with nano composite material, according to Black principles. The polymerization was monitored by DH and ESPI in real time during the cure reaction of the restoration. The total displacement reported for the material in relation of the tooth wall was 3.7 μm (natural tooth). The technique showed the entire tooth surface (wall) deforming during polymerization shrinkage. - Highlights: • Both of holographic techniques were able to measure the polymerization shrinkage. • The entire tooth surface was deformed during the polymerization shrinkage. • The group with greater percentage of filler showed the lowest value of deformation. • The values of displacement ranged from 0.9 to 3.4 μm

  4. Design and evaluation of high-volume fly ash (HVFA) concrete mixes, report D : creep, shrinkage, and abrasion resistance of HVFA concrete.

    Science.gov (United States)

    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...

  5. Bayesian estimation methods in metrology

    International Nuclear Information System (INIS)

    Cox, M.G.; Forbes, A.B.; Harris, P.M.

    2004-01-01

    In metrology -- the science of measurement -- a measurement result must be accompanied by a statement of its associated uncertainty. The degree of validity of a measurement result is determined by the validity of the uncertainty statement. In recognition of the importance of uncertainty evaluation, the International Standardization Organization in 1995 published the Guide to the Expression of Uncertainty in Measurement and the Guide has been widely adopted. The validity of uncertainty statements is tested in interlaboratory comparisons in which an artefact is measured by a number of laboratories and their measurement results compared. Since the introduction of the Mutual Recognition Arrangement, key comparisons are being undertaken to determine the degree of equivalence of laboratories for particular measurement tasks. In this paper, we discuss the possible development of the Guide to reflect Bayesian approaches and the evaluation of key comparison data using Bayesian estimation methods

  6. 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.

  7. 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.

  8. 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.

  9. Space Shuttle RTOS Bayesian Network

    Science.gov (United States)

    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

  10. 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....

  11. 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

  12. A thermal active restrained shrinkage ring test to study the early age concrete behaviour of massive structures

    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.

  13. Effects of molecular structure of the resins on the volumetric shrinkage and the mechanical strength of dental restorative composites.

    Science.gov (United States)

    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.

  14. Variational Bayesian Learning for Wavelet Independent Component Analysis

    Science.gov (United States)

    Roussos, E.; Roberts, S.; Daubechies, I.

    2005-11-01

    In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.

  15. Maximum entropy perception-action space: a Bayesian model of eye movement selection

    OpenAIRE

    Colas , Francis; Bessière , Pierre; Girard , Benoît

    2010-01-01

    International audience; In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps...

  16. 12th Brazilian Meeting on Bayesian Statistics

    CERN Document Server

    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...

  17. Evaluation of shrinkage polymerization and temperature of different acrylic resins used to splinting transfer copings in indirect impression technique

    Science.gov (United States)

    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.

  18. Probabilistic risk assessment framework for structural systems under multiple hazards using Bayesian statistics

    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.

  19. Probabilistic risk assessment framework for structural systems under multiple hazards using Bayesian statistics

    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.

  20. Bayesian Lagrangian Data Assimilation and Drifter Deployment Strategies

    Science.gov (United States)

    Dutt, A.; Lermusiaux, P. F. J.

    2017-12-01

    Ocean currents transport a variety of natural (e.g. water masses, phytoplankton, zooplankton, sediments, etc.) and man-made materials and other objects (e.g. pollutants, floating debris, search and rescue, etc.). Lagrangian Coherent Structures (LCSs) or the most influential/persistent material lines in a flow, provide a robust approach to characterize such Lagrangian transports and organize classic trajectories. Using the flow-map stochastic advection and a dynamically-orthogonal decomposition, we develop uncertainty prediction schemes for both Eulerian and Lagrangian variables. We then extend our Bayesian Gaussian Mixture Model (GMM)-DO filter to a joint Eulerian-Lagrangian Bayesian data assimilation scheme. The resulting nonlinear filter allows the simultaneous non-Gaussian estimation of Eulerian variables (e.g. velocity, temperature, salinity, etc.) and Lagrangian variables (e.g. drifter/float positions, trajectories, LCSs, etc.). Its results are showcased using a double-gyre flow with a random frequency, a stochastic flow past a cylinder, and realistic ocean examples. We further show how our Bayesian mutual information and adaptive sampling equations provide a rigorous efficient methodology to plan optimal drifter deployment strategies and predict the optimal times, locations, and types of measurements to be collected.

  1. A Bayesian model for binary Markov chains

    Directory of Open Access Journals (Sweden)

    Belkheir Essebbar

    2004-02-01

    Full Text Available This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.

  2. 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....... The study has been carried out for typical commercial polystyrene and polypropylene grades. The relationship between mold surface topography and linear shrinkage has been investigated with an experimental two-cavity mold producing simple rectangular parts with the nominal dimensions 1 x 25 x 50 mm (see...... figure 1). The cavities have different surface topographies on one side, but are otherwise identical (see discussion of other contribution factors)....

  3. SHRINKAGE REDUCTION AND CRACK PREVENTION OF ALKALI-ACTIVATED PHOSPHOROUS SLAG CEMENT

    Directory of Open Access Journals (Sweden)

    Yanan Wang

    2016-05-01

    Full Text Available The effects of fly ash, calcium oxide and polypropylene fiber on the physical and mechanical properties, shrinkage and cracking behaviors of alkali-activated phosphorous slag cement (AA-PS-C were studied. The results show that replacing 10-15% phosphorous slag by fly ash and adding calcium oxide as an expansive agent reduce the shrinkage of AA-PS-C. Fly ash will increase the flexural strength, although the compressive strength will be slightly decreased, while the calcium oxide expansive agent coated with aluminum stearate will slightly shorten the setting time and reduce the strength. Adding polypropylene fiber can greatly increase the crack-resistance of AA-PS-C.

  4. 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).

  5. Autogenous shrinkage in high-performance cement paste: An evaluation of basic mechanisms

    DEFF Research Database (Denmark)

    Lura, Pietro; Jensen, Ole Mejlhede; van Breugel, Klaas

    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...... 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....

  6. Modelling of shrinkage cavity defects during the wheel and belt casting process

    International Nuclear Information System (INIS)

    Dablement, S; Mortensen, D; Fjaer, H; Lee, M; Grandfield, J; Savage, G; Nguyen, V

    2012-01-01

    Properzi continuous casting is a wheel and belt casting process used for producing aluminium wire rod which is essential to the making of electrical cables and over head lines. One of the main concerns of Properzi process users is to ensure good quality of the final product and to avoid cast defects especially the presence of shrinkage cavity. Numerical models developed with the Alsim software, which allows an automatic calculation of gap dependent heat transfer coefficients at the metal-mould interface due to thermal deformation, are used in order to get a better understanding on the shrinkage cavity formation. Models show the effect of process parameters on the cavity defect development and provide initial guidance for users in order to avoid this kind of casting defect.

  7. 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...... cell function. The present study demonstrates that oxygenated RBCs in all major groups of reptiles exhibit no or a very reduced RVI upon ~ 25% calculated hyperosmotic shrinkage. Thus, RBCs from the snakes Crotalus durissus and Python regius, the turtle Trachemys scripta and the alligator Alligator...... 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...

  8. 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

  9. 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.

  10. The origin of early age expansions induced in cementitious materials containing shrinkage reducing admixtures

    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.

  11. Shrinkage Simulation of Holographic Grating Using Diffusion Model in PQ-PMMA Photopolymer

    Directory of Open Access Journals (Sweden)

    Wei Zepeng

    2015-01-01

    Full Text Available An extended model based on nonlocal polymerization-driven diffusion model is derived by introducing shrinkage process for describing photopolymerized dynamics in PQ-PMMA photopolymer. The kinetic parameters, polymerization rate and diffusion rate are experimentally determined to provide quantitative simulation. The numerical results show that the fringes at edge of grating are firstly shifted and consequently, it leads to a contrast reduction of holograms. Finally, theoretical results are experimentally checked by temporal evolution of diffraction efficiency, and the shrinkage coefficient 0.5% is approximately achieved under incident intensity 25.3mw/cm2. This work can enhance the applicability of diffusion model and contribute to the reasonable description of the grating formation in the photopolymer.

  12. Fissure formation in coke. 2: Effect of heating rate, shrinkage and coke strength

    Energy Technology Data Exchange (ETDEWEB)

    D.R. Jenkins; M.R. Mahoney [CSIRO, North Ryde, NSW (Australia). Mathematical and Information Sciences

    2010-07-15

    We investigate the effects of the heating rate, coke shrinkage and coke breakage strength upon the fissure pattern developed in a coke oven charge during carbonisation. This is done principally using a mechanistic model of the formation of fissures, which considers them to be an array of equally spaced fissures, whose depth follows a 'period doubling' pattern based upon the time history of the fissures. The model results are compared with pilot scale coke oven experiments. The results show that the effect of heating rate on the fissure pattern is different to the effect of coke shrinkage, while the effect of coke breakage strength on the pattern is less pronounced. The results can be seen in both the shape and size of resulting coke lumps after stabilisation. The approach gives the opportunity to consider means of controlling the carbonisation process in order to tune the size of the coke lumps produced. 7 refs., 18 figs., 4 tabs.

  13. 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...... accelerated in fibroblasts overexpressing Rac. Conversely, the activation of the extracellular signal-regulated kinase (Erk1/2) was initially significantly decreased. Subsequent to activation of p38, p53 was activated through serine-15 phosphorylation, and active p53 was translocated from the cytosol......: cellular shrinkage activates Rac, with activation of p38, followed by phosphorylation and nuclear translocation of p53, resulting in permeability increases and caspase-3 activation....

  14. 3rd Bayesian Young Statisticians Meeting

    CERN Document Server

    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).

  15. Application of combined shrinkage stoping and pillarless sublevel caving mining method to a uranium deposit

    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)

  16. 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

  17. In-Situ Observation of Sintering Shrinkage of UO2 Compacts Derived from Different Powder Routes

    International Nuclear Information System (INIS)

    Rhee, Young Woo; Oh, Jang Soo; Kim, Dong Joo; Kim, Keon Sik; Kim, Jong Hun; Yang, Jae Ho; Koo, Yang Hyun

    2015-01-01

    In-situ observations on the shrinkage of green pellets with precisely controlled dimensions were carefully conducted by using TOM during H2 atmosphere sintering. The shrinkage retardation in IDR-UO 2 might be attributed to the larger primary particle size of IDRUO 2 than those of ADU- and AUC- UO 2 powders. It would be important to understand the different sintering characteristics of UO 2 powders according to the powder routes, when it comes to designing a new sintering process or choosing a sintering additive for new fuel pellet like PCI (Pellet Cladding Interaction) remedy pellet. In this paper, we have investigated the initial and intermediate sintering shrinkage of UO 2 from different powder routes by in-situ observation of green samples during H2 atmosphere sintering. Effect of powder characteristics of three different UO 2 powders on the initial and intermediate sintering were closely reviewed including crystal structure, powder size, specific surface area, primary crystal size, and O/U ratio

  18. Non-uniform shrinkage of multiple-walled carbon nanotubes under in situ electron beam irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Li, Lunxiong [South China Normal University, Brain Science Institute, Guangzhou (China); Xiamen University, China-Australia Joint Laboratory for Functional Nanomaterials and Physics Department, Xiamen (China); Su, Jiangbin [Xiamen University, China-Australia Joint Laboratory for Functional Nanomaterials and Physics Department, Xiamen (China); Chang Zhou University, School of Mathematics and Physics, Changzhou (China); Zhu, Xianfang [Xiamen University, China-Australia Joint Laboratory for Functional Nanomaterials and Physics Department, Xiamen (China)

    2016-10-15

    Instability of multiple-walled carbon nanotubes (MWCNTs) was investigated by in situ transmission electron microscopy at room temperature. Specially, the non-uniform shrinkage of tubes was found: The pristine MWCNT shrank preferentially in its axial direction from the most curved free cap end of the tube, but the shrinkage of the tube diameter was offset by the axial shrinkage: For the complex MWCNT, the two inner MWCNTs also preferentially axially shrank from their most curved cap ends and separated from each other. However, for the effect of the radial pressure from the out walls which enveloped the two inner tubes and the tube amorphization, the two inner tubes were extruded to come close to each other and finally touched again. The new ''evaporation'' and ''diffusion'' mechanisms of carbon atoms as driven by the nano-curvature of CNT and the electron beam-induced athermal activation were suggested to explain the above phenomena. (orig.)

  19. Statistical mechanics provides novel insights into microtubule stability and mechanism of shrinkage.

    Directory of Open Access Journals (Sweden)

    Ishutesh Jain

    2015-02-01

    Full Text Available Microtubules are nano-machines that grow and shrink stochastically, making use of the coupling between chemical kinetics and mechanics of its constituent protofilaments (PFs. We investigate the stability and shrinkage of microtubules taking into account inter-protofilament interactions and bending interactions of intrinsically curved PFs. Computing the free energy as a function of PF tip position, we show that the competition between curvature energy, inter-PF interaction energy and entropy leads to a rich landscape with a series of minima that repeat over a length-scale determined by the intrinsic curvature. Computing Langevin dynamics of the tip through the landscape and accounting for depolymerization, we calculate the average unzippering and shrinkage velocities of GDP protofilaments and compare them with the experimentally known results. Our analysis predicts that the strength of the inter-PF interaction (E(s(m has to be comparable to the strength of the curvature energy (E(b(m such that E(s(m - E(b(m ≈ 1kBT, and questions the prevalent notion that unzippering results from the domination of bending energy of curved GDP PFs. Our work demonstrates how the shape of the free energy landscape is crucial in explaining the mechanism of MT shrinkage where the unzippered PFs will fluctuate in a set of partially peeled off states and subunit dissociation will reduce the length.

  20. Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection

    Science.gov (United States)

    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.

  1. Reduction of cracking and shrinkage in compressed clay beams during dying

    International Nuclear Information System (INIS)

    Lakho, N.A.; Zardari, M.A.; Memon, N.A.

    2016-01-01

    Uncontrolled evaporation of moisture from compressed clay beams can cause surface cracks, resulting in reduction of strength. This paper presents various treatments applied to clay beams during the process of casting, compacting and drying in order to curtail the possibility of cracking and to decrease percentage of drying shrinkage. Following treatments were applied to the beams during casting and drying: (i) a steel plate and double layer of plastic sheet was provided between the beam and the plank, (ii) the beam was enveloped with a propylene fabric sheet during casting and (iii) beams were covered with plastic sheet during drying. Using these treatments, the clay beams were cast and compacted at various intensities of compaction. The results show that the drying shrinkage was reduced to minimum and the cracks were curtailed. The rate of drying shrinkage was decreased depending upon the level of compaction. Thus at the higher degree of compaction, more density of clay beams was achieved, which resulted in higher degree of compressive strength in baked and unbaked state. (author)

  2. Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data

    KAUST Repository

    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.

  3. Thoracoscopic CO laser coagulation shrinkage of blebs in treatment of spontaneous pneumothorax

    Science.gov (United States)

    Sensaki, Koji; Arai, Tsunenori; Kikuchi, Keiichi; Takagi, Keigo; Tanaka, Susumu; Kikuchi, Makoto

    1992-06-01

    Spontaneous pneumothorax is a common disease in young people. Operative intervention has been done in most of the recurrent cases. Recently thoracoscopic treatment has been tested as a less invasive treatment modarity. We adopted carbon monoxide (CO) laser for thoracoscopic treatment of recurrent spontaneous pneumothorax. CO laser (wavelength; 5.4 micrometers ) could be delivered by chalcogenide glass (As - S) covered with a teflon sheath and ZnSe fiber tip. The sterilized flexible bronchoscope was inserted through the thoracoscopic outer sheath under local anesthesia. Shrinkage of blebs was obtained by non-contact method of CO laser irradiation. Laser power at the tip was 2.5 - 5 W and irradiation duration was 0.5 s each. Excellent shrinkage of bleb and bulla could be obtained by CO laser without perforation complication. Advantages of CO laser as a thoracoscopic treatment were: (1) capability of fiber delivery (flexible thoracoscopy was easy to operate and clear to visualize the blebs which were frequently found at the apical portion of the lung, and (2) shallow extinction length (good shrinkage of blebs, low risk of perforation, and thin layer of carbonization). In conclusion, our new technique of thoracoscopic CO laser irradiation was found to be a safe and effective treatment of spontaneous pneumothorax.

  4. 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.

  5. Hydro-mechanical coupling in non-saturated medium with phase change. Application to desiccation shrinkage

    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

  6. 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)

  7. Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data

    KAUST Repository

    Dong, Kai; Pang, Herbert; Tong, Tiejun; Genton, Marc G.

    2015-01-01

    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.

  8. Sparsity-based shrinkage approach for practicability improvement of H-LBP-based edge extraction

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Chenyi [School of Physics, Northeast Normal University, Changchun 130024 (China); Qiao, Shuang, E-mail: qiaos810@nenu.edu.cn [School of Physics, Northeast Normal University, Changchun 130024 (China); Sun, Jianing, E-mail: sunjn118@nenu.edu.cn [School of Mathematics and Statistics, Northeast Normal University, Changchun 130024 (China); Zhao, Ruikun; Wu, Wei [Jilin Cancer Hospital, Changchun 130021 (China)

    2016-07-21

    The local binary pattern with H function (H-LBP) technique enables fast and efficient edge extraction in digital radiography. In this paper, we reformulate the model of H-LBP and propose a novel sparsity-based shrinkage approach, in which the threshold can be adapted to the data sparsity. Using this model, we upgrade fast H-LBP framework and apply it to real digital radiography. The experiments show that the method improved using the new shrinkage approach can avoid elaborately artificial modulation of parameters and possess greater robustness in edge extraction compared with the other current methods without increasing processing time. - Highlights: • An novel sparsity-based shrinkage approach for edge extraction on digital radiography is proposed. • The threshold of SS-LBP can be adaptive to the data sparsity. • SS-LBP is the development of AH-LBP and H-LBP. • Without boosting processing time and losing processing efficiency, SS-LBP can avoid elaborately artificial modulation of parameters provides. • SS-LBP has more robust performance in edge extraction compared with the existing methods.

  9. Application of Artificial Neural Network to Predict Colour Change, Shrinkage and Texture of Osmotically Dehydrated Pumpkin

    Science.gov (United States)

    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.

  10. Evaluation of linear polymerization shrinkage, flexural strength and modulus of elasticity of dental composites

    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.

  11. Shrinkage Porosity Criterion and Its Application to A 5.5 Ton Steel Ingot

    Directory of Open Access Journals (Sweden)

    Zhang C.

    2016-06-01

    Full Text Available In order to predict the distribution of shrinkage porosity in steel ingot efficiently and accurately, a criterion R√L and a method to obtain its threshold value were proposed. The criterion R√L was derived based on the solidification characteristics of steel ingot and pressure gradient in the mushy zone, in which the physical properties, the thermal parameters, the structure of the mushy zone and the secondary dendrite arm spacing were all taken into consideration. The threshold value of the criterion R√L was obtained with combination of numerical simulation of ingot solidification and total solidification shrinkage rate. Prediction of the shrinkage porosity in a 5.5 ton ingot of 2Cr13 steel with criterion R√L>0.21 m · °C1/2 · s−3/2 agreed well with the results of experimental sectioning. Based on this criterion, optimization of the ingot was carried out by decreasing the height-to-diameter ratio and increasing the taper, which successfully eliminated the centreline porosity and further proved the applicability of this criterion.

  12. Mechanical properties and polymerization shrinkage of composite resins light-cured using two different lasers.

    Science.gov (United States)

    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.

  13. Bayesian Analysis of the Cosmic Microwave Background

    Science.gov (United States)

    Jewell, Jeffrey

    2007-01-01

    There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background! Experiments designed to map the microwave sky are returning a flood of data (time streams of instrument response as a beam is swept over the sky) at several different frequencies (from 30 to 900 GHz), all with different resolutions and noise properties. The resulting analysis challenge is to estimate, and quantify our uncertainty in, the spatial power spectrum of the cosmic microwave background given the complexities of "missing data", foreground emission, and complicated instrumental noise. Bayesian formulation of this problem allows consistent treatment of many complexities including complicated instrumental noise and foregrounds, and can be numerically implemented with Gibbs sampling. Gibbs sampling has now been validated as an efficient, statistically exact, and practically useful method for low-resolution (as demonstrated on WMAP 1 and 3 year temperature and polarization data). Continuing development for Planck - the goal is to exploit the unique capabilities of Gibbs sampling to directly propagate uncertainties in both foreground and instrument models to total uncertainty in cosmological parameters.

  14. Bayesian data assimilation in shape registration

    KAUST Repository

    Cotter, C J

    2013-03-28

    In this paper we apply a Bayesian framework to the problem of geodesic curve matching. Given a template curve, the geodesic equations provide a mapping from initial conditions for the conjugate momentum onto topologically equivalent shapes. Here, we aim to recover the well-defined posterior distribution on the initial momentum which gives rise to observed points on the target curve; this is achieved by explicitly including a reparameterization in the formulation. Appropriate priors are chosen for the functions which together determine this field and the positions of the observation points, the initial momentum p0 and the reparameterization vector field ν, informed by regularity results about the forward model. Having done this, we illustrate how maximum likelihood estimators can be used to find regions of high posterior density, but also how we can apply recently developed Markov chain Monte Carlo methods on function spaces to characterize the whole of the posterior density. These illustrative examples also include scenarios where the posterior distribution is multimodal and irregular, leading us to the conclusion that knowledge of a state of global maximal posterior density does not always give us the whole picture, and full posterior sampling can give better quantification of likely states and the overall uncertainty inherent in the problem. © 2013 IOP Publishing Ltd.

  15. Mapping out Map Libraries

    Directory of Open Access Journals (Sweden)

    Ferjan Ormeling

    2008-09-01

    Full Text Available Discussing the requirements for map data quality, map users and their library/archives environment, the paper focuses on the metadata the user would need for a correct and efficient interpretation of the map data. For such a correct interpretation, knowledge of the rules and guidelines according to which the topographers/cartographers work (such as the kind of data categories to be collected, and the degree to which these rules and guidelines were indeed followed are essential. This is not only valid for the old maps stored in our libraries and archives, but perhaps even more so for the new digital files as the format in which we now have to access our geospatial data. As this would be too much to ask from map librarians/curators, some sort of web 2.0 environment is sought where comments about data quality, completeness and up-to-dateness from knowledgeable map users regarding the specific maps or map series studied can be collected and tagged to scanned versions of these maps on the web. In order not to be subject to the same disadvantages as Wikipedia, where the ‘communis opinio’ rather than scholarship, seems to be decisive, some checking by map curators of this tagged map use information would still be needed. Cooperation between map curators and the International Cartographic Association ( ICA map and spatial data use commission to this end is suggested.

  16. Bayesian Methods and Universal Darwinism

    Science.gov (United States)

    Campbell, John

    2009-12-01

    Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.

  17. Effect of cyclic loading on microleakage of silorane based composite compared with low shrinkage methacrylate-based composites

    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 .

  18. Development of concrete mix proportions for minimizing/eliminating shrinkage cracks in slabs and high performance grouts : final report.

    Science.gov (United States)

    2017-02-01

    The two focus areas of this research address longstanding problems of (1) cracking of concrete slabs due to creep and shrinkage and (2) high performance compositions for grouting and joining precast concrete structural elements. Cracking of bridge de...

  19. Temperature dependence of autogenous shrinkage of silica fume cement pastes with a very low water–binder ratio

    Energy Technology Data Exchange (ETDEWEB)

    Maruyama, I., E-mail: ippei@dali.nuac.nagoya-u.ac.jp [Graduate School of Environmental Studies, Nagoya University, ES Building, No. 539, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); Teramoto, A. [Graduate School of Environmental Studies, Nagoya University, Faculty of Engineering, ES Building, No. 546, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan)

    2013-08-15

    Ultra-high-strength concrete with a large unit cement content undergoes considerable temperature increase inside members due to hydration heat, leading to a higher risk of internal cracking. Hence, the temperature dependence of autogenous shrinkage of cement pastes made with silica fume premixed cement with a water–binder ratio of 0.15 was studied extensively. Development of autogenous shrinkage showed different behaviors before and after the inflection point, and dependence on the temperature after mixing and subsequent temperature histories. The difference in autogenous shrinkage behavior poses problems for winter construction because autogenous shrinkage may increase with decrease in temperature after mixing before the inflection point and with increase in temperature inside concrete members with large cross sections.

  20. Temperature dependence of autogenous shrinkage of silica fume cement pastes with a very low water–binder ratio

    International Nuclear Information System (INIS)

    Maruyama, I.; Teramoto, A.

    2013-01-01

    Ultra-high-strength concrete with a large unit cement content undergoes considerable temperature increase inside members due to hydration heat, leading to a higher risk of internal cracking. Hence, the temperature dependence of autogenous shrinkage of cement pastes made with silica fume premixed cement with a water–binder ratio of 0.15 was studied extensively. Development of autogenous shrinkage showed different behaviors before and after the inflection point, and dependence on the temperature after mixing and subsequent temperature histories. The difference in autogenous shrinkage behavior poses problems for winter construction because autogenous shrinkage may increase with decrease in temperature after mixing before the inflection point and with increase in temperature inside concrete members with large cross sections

  1. Bayesian flood forecasting methods: A review

    Science.gov (United States)

    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

  2. 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....

  3. 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....

  4. Numeracy, frequency, and Bayesian reasoning

    Directory of Open Access Journals (Sweden)

    Gretchen B. Chapman

    2009-02-01

    Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.

  5. The correlation between aldehyde dehydrogenase-1A1 level and tumor shrinkage after preoperative chemoradiation in locally advanced rectal cancer

    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.

  6. Investigation on Failures of Composite Beam and Substrate Concrete due to Drying Shrinkage Property of Repair Materials

    Science.gov (United States)

    Pattnaik, Rashmi Ranjan

    2017-06-01

    A Finite Element Analysis (FEA) and an experimental study was conducted on composite beam of repair material and substrate concrete to investigate the failures of the composite beam due to drying shrinkage property of the repair materials. In FEA, the stress distribution in the composite beam due to two concentrate load and shrinkage of repair materials were investigated in addition to the deflected shape of the composite beam. The stress distributions and load deflection shapes of the finite element model were investigated to aid in analysis of the experimental findings. In the experimental findings, the mechanical properties such as compressive strength, split tensile strength, flexural strength, and load-deflection curves were studied in addition to slant shear bond strength, drying shrinkage and failure patterns of the composite beam specimens. Flexure test was conducted to simulate tensile stress at the interface between the repair material and substrate concrete. The results of FEA were used to analyze the experimental results. It was observed that the repair materials with low drying shrinkage are showing compatible failure in the flexure test of the composite beam and deform adequately in the load deflection curves. Also, the flexural strength of the composite beam with low drying shrinkage repair materials showed higher flexural strength as compared to the composite beams with higher drying shrinkage value of the repair materials even though the strength of those materials were more.

  7. Four-Phase Dendritic Model for the Prediction of Macrosegregation, Shrinkage Cavity, and Porosity in a 55-Ton Ingot

    Science.gov (United States)

    Ge, Honghao; Ren, Fengli; Li, Jun; Han, Xiujun; Xia, Mingxu; Li, Jianguo

    2017-03-01

    A four-phase dendritic model was developed to predict the macrosegregation, shrinkage cavity, and porosity during solidification. In this four-phase dendritic model, some important factors, including dendritic structure for equiaxed crystals, melt convection, crystals sedimentation, nucleation, growth, and shrinkage of solidified phases, were taken into consideration. Furthermore, in this four-phase dendritic model, a modified shrinkage criterion was established to predict shrinkage porosity (microporosity) of a 55-ton industrial Fe-3.3 wt pct C ingot. The predicted macrosegregation pattern and shrinkage cavity shape are in a good agreement with experimental results. The shrinkage cavity has a significant effect on the formation of positive segregation in hot top region, which generally forms during the last stage of ingot casting. The dendritic equiaxed grains also play an important role on the formation of A-segregation. A three-dimensional laminar structure of A-segregation in industrial ingot was, for the first time, predicted by using a 3D case simulation.

  8. Sparse Bayesian Information Filters for Localization and Mapping

    Science.gov (United States)

    2008-02-01

    Jacob, and Kristian for the many interesting discussions that we have had. It was great to work with David in preparing and operating the AUVs for the two...Wiley & Sons, Inc., New York, NY, 1994. [43] D. Fox, W. Burgard, S. Thrun, and A. Cremers . Position estimation for mobile robots in dynamic

  9. Bayesian multi-QTL mapping for growth curve parameters

    DEFF Research Database (Denmark)

    Heuven, Henri C M; Janss, Luc L G

    2010-01-01

    % for ASYM and SCAL while the heritability for XMID was approximately 24%. The genome wide scan revealed four QTLs affecting ASYM, one QTL affecting XMID and four QTLs affecting SCAL. The size of the QTL differed. QTL with a larger effect could be more precisely located compared to QTL with small effect....... The locations of the QTLs for separate parameters were very close in some cases and probably caused the genetic correlation observed between ASYM and XMID and SCAL respectively. None of the QTL appeared on chromosome five. Conclusions Repeated observations on individuals were affected by at least nine QTLs....... For most QTL a precise location could be determined. The QTL for the inflection point (XMID) was difficult to pinpoint and might actually exist of two closely linked QTL on chromosome one....

  10. MAP estimators and their consistency in Bayesian nonparametric inverse problems

    KAUST Repository

    Dashti, M.; Law, K. J H; Stuart, A. M.; Voss, J.

    2013-01-01

    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.

  11. Bayesian mapping QTL for fruit and growth phenological traits in ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-01-19

    livestock in tropical and ... Moreover, both the grain and the immature pods of lablab are a lesser human food source in Africa (Smartt, ... Using four different populations of soybean,. Wang et al. (2004) identified four QTLs for ...

  12. Modelling of JET diagnostics using Bayesian Graphical Models

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, J. [IPP Greifswald, Greifswald (Germany); Ford, O. [Imperial College, London (United Kingdom); McDonald, D.; Hole, M.; Nessi, G. von; Meakins, A.; Brix, M.; Thomsen, H.; Werner, A.; Sirinelli, A.

    2011-07-01

    The mapping between physics parameters (such as densities, currents, flows, temperatures etc) defining the plasma 'state' under a given model and the raw observations of each plasma diagnostic will 1) depend on the particular physics model used, 2) is inherently probabilistic, from uncertainties on both observations and instrumental aspects of the mapping, such as calibrations, instrument functions etc. A flexible and principled way of modelling such interconnected probabilistic systems is through so called Bayesian graphical models. Being an amalgam between graph theory and probability theory, Bayesian graphical models can simulate the complex interconnections between physics models and diagnostic observations from multiple heterogeneous diagnostic systems, making it relatively easy to optimally combine the observations from multiple diagnostics for joint inference on parameters of the underlying physics model, which in itself can be represented as part of the graph. At JET about 10 diagnostic systems have to date been modelled in this way, and has lead to a number of new results, including: the reconstruction of the flux surface topology and q-profiles without any specific equilibrium assumption, using information from a number of different diagnostic systems; profile inversions taking into account the uncertainties in the flux surface positions and a substantial increase in accuracy of JET electron density and temperature profiles, including improved pedestal resolution, through the joint analysis of three diagnostic systems. It is believed that the Bayesian graph approach could potentially be utilised for very large sets of diagnostics, providing a generic data analysis framework for nuclear fusion experiments, that would be able to optimally utilize the information from multiple diagnostics simultaneously, and where the explicit graph representation of the connections to underlying physics models could be used for sophisticated model testing. This

  13. Bayesian analysis of magnetic island dynamics

    International Nuclear Information System (INIS)

    Preuss, R.; Maraschek, M.; Zohm, H.; Dose, V.

    2003-01-01

    We examine a first order differential equation with respect to time used to describe magnetic islands in magnetically confined plasmas. The free parameters of this equation are obtained by employing Bayesian probability theory. Additionally, a typical Bayesian change point is solved in the process of obtaining the data

  14. 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 learned...

  15. Using Bayesian Networks to Improve Knowledge Assessment

    Science.gov (United States)

    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…

  16. Using Bayesian belief networks in adaptive management.

    Science.gov (United States)

    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...

  17. Bayesian Decision Theoretical Framework for Clustering

    Science.gov (United States)

    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…

  18. Robust Bayesian detection of unmodelled bursts

    International Nuclear Information System (INIS)

    Searle, Antony C; Sutton, Patrick J; Tinto, Massimo; Woan, Graham

    2008-01-01

    We develop a Bayesian treatment of the problem of detecting unmodelled gravitational wave bursts using the new global network of interferometric detectors. We also compare this Bayesian treatment with existing coherent methods, and demonstrate that the existing methods make implicit assumptions on the distribution of signals that make them sub-optimal for realistic signal populations

  19. Bayesian models: A statistical primer for ecologists

    Science.gov (United States)

    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

  20. Particle identification in ALICE: a Bayesian approach

    NARCIS (Netherlands)

    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.

    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

  1. Advances in Bayesian Modeling in Educational Research

    Science.gov (United States)

    Levy, Roy

    2016-01-01

    In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…

  2. 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...

  3. 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...

  4. BELM: Bayesian extreme learning machine.

    Science.gov (United States)

    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.

  5. BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.

    Science.gov (United States)

    Khakabimamaghani, Sahand; Ester, Martin

    2016-01-01

    The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.

  6. Bayesian Nonparametric Longitudinal Data Analysis.

    Science.gov (United States)

    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.

  7. 2nd Bayesian Young Statisticians Meeting

    CERN Document Server

    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 ...

  8. Bayesian natural language semantics and pragmatics

    CERN Document Server

    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.

  9. Unavailability of the residual system heat removal of Angra 1 by Bayesian networks considering dependent failures

    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)

  10. Unavailability of the residual system heat removal of Angra 1 by Bayesian networks considering dependent failures

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Many R.S.; Melo, Paulo F.F.F. e, E-mail: mgomes@con.ufrj.br, E-mail: frutuoso@nuclear.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Programa de Pos-Graduacao em Engenharia Nuclear

    2015-07-01

    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)

  11. TH-E-BRF-01: Exploiting Tumor Shrinkage in Split-Course Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Unkelbach, J; Craft, D; Hong, T; Papp, D; Wolfgang, J; Bortfeld, T [Massachusetts General Hospital, Boston, MA (United States); Ramakrishnan, J [University of Wisconsin, Madison, Wisconsin (United States); Salari, E [Wichita State University, Wichita, KS (United States)

    2014-06-15

    Purpose: In split-course radiotherapy, a patient is treated in several stages separated by weeks or months. This regimen has been motivated by radiobiological considerations. However, using modern image-guidance, it also provides an approach to reduce normal tissue dose by exploiting tumor shrinkage. In this work, we consider the optimal design of split-course treatments, motivated by the clinical management of large liver tumors for which normal liver dose constraints prohibit the administration of an ablative radiation dose in a single treatment. Methods: We introduce a dynamic tumor model that incorporates three factors: radiation induced cell kill, tumor shrinkage, and tumor cell repopulation. The design of splitcourse radiotherapy is formulated as a mathematical optimization problem in which the total dose to the liver is minimized, subject to delivering the prescribed dose to the tumor. Based on the model, we gain insight into the optimal administration of radiation over time, i.e. the optimal treatment gaps and dose levels. Results: We analyze treatments consisting of two stages in detail. The analysis confirms the intuition that the second stage should be delivered just before the tumor size reaches a minimum and repopulation overcompensates shrinking. Furthermore, it was found that, for a large range of model parameters, approximately one third of the dose should be delivered in the first stage. The projected benefit of split-course treatments in terms of liver sparing depends on model assumptions. However, the model predicts large liver dose reductions by more than a factor of two for plausible model parameters. Conclusion: The analysis of the tumor model suggests that substantial reduction in normal tissue dose can be achieved by exploiting tumor shrinkage via an optimal design of multi-stage treatments. This suggests taking a fresh look at split-course radiotherapy for selected disease sites where substantial tumor regression translates into reduced

  12. TH-E-BRF-01: Exploiting Tumor Shrinkage in Split-Course Radiotherapy

    International Nuclear Information System (INIS)

    Unkelbach, J; Craft, D; Hong, T; Papp, D; Wolfgang, J; Bortfeld, T; Ramakrishnan, J; Salari, E

    2014-01-01

    Purpose: In split-course radiotherapy, a patient is treated in several stages separated by weeks or months. This regimen has been motivated by radiobiological considerations. However, using modern image-guidance, it also provides an approach to reduce normal tissue dose by exploiting tumor shrinkage. In this work, we consider the optimal design of split-course treatments, motivated by the clinical management of large liver tumors for which normal liver dose constraints prohibit the administration of an ablative radiation dose in a single treatment. Methods: We introduce a dynamic tumor model that incorporates three factors: radiation induced cell kill, tumor shrinkage, and tumor cell repopulation. The design of splitcourse radiotherapy is formulated as a mathematical optimization problem in which the total dose to the liver is minimized, subject to delivering the prescribed dose to the tumor. Based on the model, we gain insight into the optimal administration of radiation over time, i.e. the optimal treatment gaps and dose levels. Results: We analyze treatments consisting of two stages in detail. The analysis confirms the intuition that the second stage should be delivered just before the tumor size reaches a minimum and repopulation overcompensates shrinking. Furthermore, it was found that, for a large range of model parameters, approximately one third of the dose should be delivered in the first stage. The projected benefit of split-course treatments in terms of liver sparing depends on model assumptions. However, the model predicts large liver dose reductions by more than a factor of two for plausible model parameters. Conclusion: The analysis of the tumor model suggests that substantial reduction in normal tissue dose can be achieved by exploiting tumor shrinkage via an optimal design of multi-stage treatments. This suggests taking a fresh look at split-course radiotherapy for selected disease sites where substantial tumor regression translates into reduced

  13. Shrinkage stress compensation in composite-restored teeth: relaxation or hygroscopic expansion?

    Science.gov (United States)

    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.

  14. Risk-based design of process systems using discrete-time Bayesian networks

    International Nuclear Information System (INIS)

    Khakzad, Nima; Khan, Faisal; Amyotte, Paul

    2013-01-01

    Temporal Bayesian networks have gained popularity as a robust technique to model dynamic systems in which the components' sequential dependency, as well as their functional dependency, cannot be ignored. In this regard, discrete-time Bayesian networks have been proposed as a viable alternative to solve dynamic fault trees without resort to Markov chains. This approach overcomes the drawbacks of Markov chains such as the state-space explosion and the error-prone conversion procedure from dynamic fault tree. It also benefits from the inherent advantages of Bayesian networks such as probability updating. However, effective mapping of the dynamic gates of dynamic fault trees into Bayesian networks while avoiding the consequent huge multi-dimensional probability tables has always been a matter of concern. In this paper, a new general formalism has been developed to model two important elements of dynamic fault tree, i.e., cold spare gate and sequential enforcing gate, with any arbitrary probability distribution functions. Also, an innovative Neutral Dependency algorithm has been introduced to model dynamic gates such as priority-AND gate, thus reducing the dimension of conditional probability tables by an order of magnitude. The second part of the paper is devoted to the application of discrete-time Bayesian networks in the risk assessment and safety analysis of complex process systems. It has been shown how dynamic techniques can effectively be applied for optimal allocation of safety systems to obtain maximum risk reduction.

  15. C-O-H-S magmatic fluid system in shrinkage bubbles of melt inclusions

    Science.gov (United States)

    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

  16. 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.

  17. 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...... selective and integrative roles, and thus cannot be easily extended to complex environments. We suggest that the resource bottleneck stems from the computational intractability of exact perceptual inference in complex settings, and that attention reflects an evolved mechanism for approximate inference which...... can be shaped to refine the local accuracy of perception. We show that this approach extends the simple picture of attention as prior, so as to provide a unified and computationally driven account of both selective and integrative attentional phenomena....

  18. 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.

  19. Nonparametric Bayesian inference in biostatistics

    CERN Document Server

    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...

  20. 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

  1. Bayesian estimation in homodyne interferometry

    International Nuclear Information System (INIS)

    Olivares, Stefano; Paris, Matteo G A

    2009-01-01

    We address phase-shift estimation by means of squeezed vacuum probe and homodyne detection. We analyse Bayesian estimator, which is known to asymptotically saturate the classical Cramer-Rao bound to the variance, and discuss convergence looking at the a posteriori distribution as the number of measurements increases. We also suggest two feasible adaptive methods, acting on the squeezing parameter and/or the homodyne local oscillator phase, which allow us to optimize homodyne detection and approach the ultimate bound to precision imposed by the quantum Cramer-Rao theorem. The performances of our two-step methods are investigated by means of Monte Carlo simulated experiments with a small number of homodyne data, thus giving a quantitative meaning to the notion of asymptotic optimality.

  2. Bayesian Kernel Mixtures for Counts.

    Science.gov (United States)

    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.

  3. Bayesian networks in educational assessment

    CERN Document Server

    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 ...

  4. 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 ...

  5. Bayesian models a statistical primer for ecologists

    CERN Document Server

    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

  6. Bayesian inversion of refraction seismic traveltime data

    Science.gov (United States)

    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

  7. Evaluation of shrinkage temperature of bovine pericardium tissue for bioprosthetic heart valve application by differential scanning calorimetry and freeze-drying microscopy

    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.

  8. A Mesoscopic Simulation for the Early-Age Shrinkage Cracking Process of High Performance Concrete in Bridge Engineering

    Directory of Open Access Journals (Sweden)

    Guodong Li

    2017-01-01

    Full Text Available On a mesoscopic level, high performance concrete (HPC was assumed to be a heterogeneous composite material consisting of aggregates, mortar, and pores. The concrete mesoscopic structure model had been established based on CT image reconstruction. By combining this model with continuum mechanics, damage mechanics, and fracture mechanics, a relatively complete system for concrete mesoscopic mechanics analysis was established to simulate the process of early-age shrinkage cracking in HPC. This process was based on the dispersion crack model. The results indicated that the interface between the aggregate and mortar was the crack point caused by shrinkage cracks in HPC. The locations of early-age shrinkage cracks in HPC were associated with the spacing and the size of the aggregate particle. However, the shrinkage deformation size of the mortar was related to the scope of concrete cracking and was independent of the crack position. Whereas lower water to cement ratios can improve the early strength of concrete, this ratio cannot control early-age shrinkage cracks in HPC.

  9. Durability and Shrinkage Characteristics of Self-Compacting Concretes Containing Recycled Coarse and/or Fine Aggregates

    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.

  10. Conjugation of diisocyanate side chains to dimethacrylate reduces polymerization shrinkage and increases the hardness of composite resins.

    Science.gov (United States)

    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.

  11. 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.

  12. 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.

  13. Influence of inert fillers on shrinkage cracking of meta-kaolin geo-polymers

    International Nuclear Information System (INIS)

    Kuenzel, C.; Boccaccini, A.R.

    2012-01-01

    Geo-polymers contain a network of tetrahedral coordinated aluminate and silicate, and are potential materials to immobilize/encapsulate nuclear wastes. They can exhibit shrinkage cracking when water is removed by drying, and in order to use geo-polymers for waste encapsulation this effect needs to be investigated and controlled. In this study, six different fillers were mixed with meta-kaolin and sodium silicate solution at high pH to form geo-polymers, and the influence of filler addition on mechanical properties has been determined. The fillers used were Fe 2 O 3 , Al 2 O 3 , CaCO 3 , sand, glass and rubber and these do not react during geo-polymerisation reactions. Geo-polymers were prepared containing 30 weight percent of filler. The mechanical properties of the geo-polymers were influenced by the type of filler, with low density fillers increasing mortar viscosity. Geo-polymer samples containing fine filler particles exhibited shrinkage cracking on drying. This was not observed when coarser particles were added and these samples also had significantly improved mechanical properties. (authors)

  14. 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

  15. THE INFLUENCE OF SHRINKAGE AND MOISTURE DIFFUSION ON IDEALIZED TOOTH STRUCTURE INVOLVING DEBONDING DAMAGE

    Institute of Scientific and Technical Information of China (English)

    FanJianping; TangChak-Yin

    2005-01-01

    This study highlights the joint effect of early polymerization shrinkage and longtermmoisture diffusion on the behavior of the restoration-tooth structure. The interphase debonding between particle and polymer resin in dental composite is taken into account by introducing the damage variable. The idealized model is designed and constructed for representing the restorationtooth structure, which consists of enamel, dentin, composite and interphase, each considered as homogenous material. The simulation is carried out using the general-purpose finite element software package, ABAQUS incorporated with a user subroutine for definition of damaged material behavior. The influence of Young's moduli of composite and interphase on stress and displacement is discussed. The compensating effect of water sorption on the polymerization shrinkage is examined with and without involving damage evolution. A comparison is made between the influence of hyper-, equi- and hypo-water sorption. Interfacial failure in the specific regions as well as cuspal movement has been predicated. The damage evolving in dental composite reduces the rigidity of composite, thus in turn reducing consequent stress and increasing consequent displacement. The development of stresses at the restoration-tooth interface can have a detrimental effect on the longevity of a restoration.

  16. Influence of vertical holes on creep and shrinkage of railway prestressed concrete sleepers

    Science.gov (United States)

    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.

  17. Assessment and prediction of drying shrinkage cracking in bonded mortar overlays

    Energy Technology Data Exchange (ETDEWEB)

    Beushausen, Hans, E-mail: hans.beushausen@uct.ac.za; Chilwesa, Masuzyo

    2013-11-15

    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.

  18. Recycling of rubble from building demolition for low-shrinkage concretes.

    Science.gov (United States)

    Corinaldesi, Valeria; Moriconi, Giacomo

    2010-04-01

    In this project concrete mixtures were prepared that were characterized by low ductility due to desiccation by using debris from building demolition, which after a suitable treatment was used as aggregate for partial replacement of natural aggregates. The recycled aggregate used came from a recycling plant, in which rubble from building demolition was selected, crushed, cleaned, sieved, and graded. Such aggregates are known to be more porous as indicated by the Saturated Surface Dry (SSD) moisture content. The recycled concrete used as aggregates were added to the concrete mixture in order to study their influence on the fresh and hardened concrete properties. They were added either after water pre-soaking or in dry condition, in order to evaluate the influence of moisture in aggregates on the performance of concrete containing recycled aggregate. In particular, the effect of internal curing, due to the use of such aggregates, was studied. Concrete behavior due to desiccation under dehydration was studied by means of both drying shrinkage test and German angle test, through which shrinkage under the restrained condition of early age concrete can be evaluated. Copyright 2009 Elsevier Ltd. All rights reserved.

  19. 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.

  20. Fabrication of Polydimethylsiloxane Microlenses Utilizing Hydrogel Shrinkage and a Single Molding Step

    Directory of Open Access Journals (Sweden)

    Bader Aldalali

    2014-05-01

    Full Text Available We report on polydimethlysiloxane (PDMS microlenses and microlens arrays on flat and curved substrates fabricated via a relatively simple process combining liquid-phase photopolymerization and a single molding step. The mold for the formation of the PDMS lenses is fabricated by photopolymerizing a polyacrylamide (PAAm pre-hydrogel. The shrinkage of PAAm after its polymerization forms concave lenses. The lenses are then transferred to PDMS by a single step molding to form PDMS microlens array on a flat substrate. The PAAm concave lenses are also transferred to PDMS and another flexible polymer, Solaris, to realize artificial compound eyes. The resultant microlenses and microlens arrays possess good uniformity and optical properties. The focal length of the lenses is inversely proportional to the shrinkage time. The microlens mold can also be rehydrated to change the focal length of the ultimate PDMS microlenses. The spherical aberration is 2.85 μm and the surface roughness is on the order of 204 nm. The microlenses can resolve 10.10 line pairs per mm (lp/mm and have an f-number range between f/2.9 and f/56.5. For the compound eye, the field of view is 113°.

  1. Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies

    KAUST Repository

    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.

  2. Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies

    KAUST Repository

    Chen, Yi-Hau; Chatterjee, Nilanjan; Carroll, Raymond J.

    2009-01-01

    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.

  3. Study on the shrinkage behavior and conductivity of silver microwires during electrostatic field assisted sintering

    Science.gov (United States)

    Shangguan, Lei; Ma, Liuhong; Li, Mengke; Peng, Wei; Zhong, Yinghui; Su, Yufeng; Duan, Zhiyong

    2018-05-01

    An electrostatic field was applied to sintering Ag microwires to achieve a more compact structure and better conductivity. The shrinkage behavior of Ag microwires shows anisotropy, since bigger particle sizes, less micropores and smoother surfaces were observed in the direction of the electrostatic field in comparsion with the direction perpendicular to the electrostatic field, and the shrinkage rate of Ag microwires in the direction of electrostatic field improves about 2.4% with the electrostatic field intensity of 800 V cm‑1. The electrostatic field assisted sintering model of Ag microwires is proposed according to thermal diffuse dynamics analysis and experimental research. Moreover, the grain size of Ag microwres sintered with electrostatic field increases with the electrostatic field intensity and reaches 113 nm when the electrostatic field intensity is 800 V cm‑1, and the resistivity decreases to 2.07  ×  10‑8 Ω m as well. This method may overcome the restriction of metal wires which fabricated by the pseudoplastic metal nanoparticle fluid and be used as interconnects in nanoimprint lithography.

  4. 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.

  5. 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

  6. 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

  7. Bayesian adaptive methods for clinical trials

    National Research Council Canada - National Science Library

    Berry, Scott M

    2011-01-01

    .... One is that Bayesian approaches implemented with the majority of their informative content coming from the current data, and not any external prior informa- tion, typically have good frequentist properties (e.g...

  8. 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

  9. Structure-based bayesian sparse reconstruction

    KAUST Repository

    Quadeer, Ahmed Abdul; Al-Naffouri, Tareq Y.

    2012-01-01

    Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical

  10. 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++

  11. Learning Bayesian networks for discrete data

    KAUST Repository

    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.

  12. An Intuitive Dashboard for Bayesian Network Inference

    Science.gov (United States)

    Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.

    2014-03-01

    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++.

  13. Bayesian optimization for computationally extensive probability distributions.

    Science.gov (United States)

    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.

  14. Correct Bayesian and frequentist intervals are similar

    International Nuclear Information System (INIS)

    Atwood, C.L.

    1986-01-01

    This paper argues that Bayesians and frequentists will normally reach numerically similar conclusions, when dealing with vague data or sparse data. It is shown that both statistical methodologies can deal reasonably with vague data. With sparse data, in many important practical cases Bayesian interval estimates and frequentist confidence intervals are approximately equal, although with discrete data the frequentist intervals are somewhat longer. This is not to say that the two methodologies are equally easy to use: The construction of a frequentist confidence interval may require new theoretical development. Bayesians methods typically require numerical integration, perhaps over many variables. Also, Bayesian can easily fall into the trap of over-optimism about their amount of prior knowledge. But in cases where both intervals are found correctly, the two intervals are usually not very different. (orig.)

  15. 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

  16. 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.

  17. Quantum Bayesian networks with application to games displaying Parrondo's paradox

    Science.gov (United States)

    Pejic, Michael

    Bayesian networks and their accompanying graphical models are widely used for prediction and analysis across many disciplines. We will reformulate these in terms of linear maps. This reformulation will suggest a natural extension, which we will show is equivalent to standard textbook quantum mechanics. Therefore, this extension will be termed quantum. However, the term quantum should not be taken to imply this extension is necessarily only of utility in situations traditionally thought of as in the domain of quantum mechanics. In principle, it may be employed in any modelling situation, say forecasting the weather or the stock market---it is up to experiment to determine if this extension is useful in practice. Even restricting to the domain of quantum mechanics, with this new formulation the advantages of Bayesian networks can be maintained for models incorporating quantum and mixed classical-quantum behavior. The use of these will be illustrated by various basic examples. Parrondo's paradox refers to the situation where two, multi-round games with a fixed winning criteria, both with probability greater than one-half for one player to win, are combined. Using a possibly biased coin to determine the rule to employ for each round, paradoxically, the previously losing player now wins the combined game with probabilitygreater than one-half. Using the extended Bayesian networks, we will formulate and analyze classical observed, classical hidden, and quantum versions of a game that displays this paradox, finding bounds for the discrepancy from naive expectations for the occurrence of the paradox. A quantum paradox inspired by Parrondo's paradox will also be analyzed. We will prove a bound for the discrepancy from naive expectations for this paradox as well. Games involving quantum walks that achieve this bound will be presented.

  18. Smartphone technologies and Bayesian networks to assess shorebird habitat selection

    Science.gov (United States)

    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

  19. Predicting coastal cliff erosion using a Bayesian probabilistic model

    Science.gov (United States)

    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.

  20. 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