Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model

Directory of Open Access Journals (Sweden)

Changming Liu

2018-01-01

Full Text Available Acoustic emission (AE technique is a common approach to identify the damage of the refractories; however, there is a complex problem since there are as many as fifteen involved parameters, which calls for effective data processing and classification algorithms to reduce the level of complexity. In this paper, experiments involving three-point bending tests of refractories were conducted and AE signals were collected. A new data processing method of merging the similar parameters in the description of the damage and reducing the dimension was developed. By means of the principle component analysis (PCA for dimension reduction, the fifteen related parameters can be reduced to two parameters. The parameters were the linear combinations of the fifteen original parameters and taken as the indexes for damage classification. Based on the proposed approach, the Gaussian mixture model was integrated with the Bayesian information criterion to group the AE signals into two damage categories, which accounted for 99% of all damage. Electronic microscope scanning of the refractories verified the two types of damage.

Disentangling the developmental and neurobehavioural effects of perinatal exposure to a chemical mixture found in blood of Arctic populations: differential toxicity of mixture components

Energy Technology Data Exchange (ETDEWEB)

Bowers, W.; Nakai, J.; Yagminas, A.; Chu, I.; Moir, D. [Health Canada (Canada)

2004-09-15

The current study was designed to evaluate the neurobehavioral effects of perinatal exposure to a chemical mixture that is based on relative concentrations of persistent organic pollutants found in the blood of Canadian Arctic populations and contains 14 PCB congeners, 12 organochlorine pesticides and methyl mercury. This study compared the effects of the complete mixture with the effects of three major components of the mixture (the PCB component, the organochlorine pesticide component, and the methyl mercury component). By examining a range of neurobehavioural functions over development we also determine if specific neurobehavioural disturbances produced by the mixture can be attributed to components of the mixture and if neurobehavioural effects produced by components of the mixture are altered by concurrent exposure to other components in the mixture. Ninety-two nulliparious female Sprague-Dawley rats served as subjects.

Conversion of cresols and naphthalene in the hydroprocessing of three-component model mixtures simulating fast pyrolysis tars

Energy Technology Data Exchange (ETDEWEB)

Wandas, R.; Surygala, J.; Sliwka, E. [Technical University of Wroclaw, Wroclaw (Poland). Inst. of Chemistry and Technology of Petroleum and Coal

1996-05-01

The hydroconversion of o-, m- and p-cresols in three-component model mixtures with naphthalene and n-hexadecane was investigated over a CoMo/Al{sub 2}O{sub 3} catalyst at 360{degree}C, a hydrogen pressure of 7 MPa and a reaction time of 60 min. The results were compared with those obtained for cresols and naphthalene as single model compounds. A lower efficiency of cresol hydrodeoxygenation as well as naphthalene hydrogenation in the mixtures was found than in the conversion of the single compounds. Conversion mechanisms of cresols in the mixtures with naphthalene are considerably more complex than for individual components. Beside typical catalytic reactions, they include radical reactions in which tetralin, formed by naphthalene hydrogenation, participates as a labile-hydrogen source. The cresol reaction products in such systems include phenol, xylenols, xylenes and dimethycyclohexanes, i.e. compounds essentially absent in hydroconversion of cresols as single substances. Under the experimental conditions, the hydrodeoxygenation efficiency of the cresol isomers decreases in the sequence: para {gt} metal {gt} ortho. 22 refs., 3 figs., 3 tabs.

Mixture of Regression Models with Single-Index

OpenAIRE

Xiang, Sijia; Yao, Weixin

2016-01-01

In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However, unlike existing semiparametric mixture regression models, the new pro- posed model can easily incorporate multivariate predictors into the nonparametric components. Backfitting estimates and the corresponding algorithms have been proposed for...

Maximum likelihood estimation of finite mixture model for economic data

Science.gov (United States)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-06-01

Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.

Improved predictive model for n-decane kinetics across species, as a component of hydrocarbon mixtures.

Science.gov (United States)

Merrill, E A; Gearhart, J M; Sterner, T R; Robinson, P J

2008-07-01

n-Decane is considered a major component of various fuels and industrial solvents. These hydrocarbon products are complex mixtures of hundreds of components, including straight-chain alkanes, branched chain alkanes, cycloalkanes, diaromatics, and naphthalenes. Human exposures to the jet fuel, JP-8, or to industrial solvents in vapor, aerosol, and liquid forms all have the potential to produce health effects, including immune suppression and/or neurological deficits. A physiologically based pharmacokinetic (PBPK) model has previously been developed for n-decane, in which partition coefficients (PC), fitted to 4-h exposure kinetic data, were used in preference to measured values. The greatest discrepancy between fitted and measured values was for fat, where PC values were changed from 250-328 (measured) to 25 (fitted). Such a large change in a critical parameter, without any physiological basis, greatly impedes the model's extrapolative abilities, as well as its applicability for assessing the interactions of n-decane or similar alkanes with other compounds in a mixture model. Due to these limitations, the model was revised. Our approach emphasized the use of experimentally determined PCs because many tissues had not approached steady-state concentrations by the end of the 4-h exposures. Diffusion limitation was used to describe n-decane kinetics for the brain, perirenal fat, skin, and liver. Flow limitation was used to describe the remaining rapidly and slowly perfused tissues. As expected from the high lipophilicity of this semivolatile compound (log K(ow) = 5.25), sensitivity analyses showed that parameters describing fat uptake were next to blood:air partitioning and pulmonary ventilation as critical in determining overall systemic circulation and uptake in other tissues. In our revised model, partitioning into fat took multiple days to reach steady state, which differed considerably from the previous model that assumed steady-state conditions in fat at 4 h post

A Comprehensive Mixture of Tobacco Smoke Components Retards Orthodontic Tooth Movement via the Inhibition of Osteoclastogenesis in a Rat Model

Directory of Open Access Journals (Sweden)

Maya Nagaie

2014-10-01

Full Text Available Tobacco smoke is a complex mixture of numerous components. Nevertheless, most experiments have examined the effects of individual chemicals in tobacco smoke. The comprehensive effects of components on tooth movement and bone resorption remain unexplored. Here, we have shown that a comprehensive mixture of tobacco smoke components (TSCs attenuated bone resorption through osteoclastogenesis inhibition, thereby retarding experimental tooth movement in a rat model. An elastic power chain (PC inserted between the first and second maxillary molars robustly yielded experimental tooth movement within 10 days. TSC administration effectively retarded tooth movement since day 4. Histological evaluation disclosed that tooth movement induced bone resorption at two sites: in the bone marrow and the peripheral bone near the root. TSC administration significantly reduced the number of tartrate-resistant acid phosphatase (TRAP-positive osteoclastic cells in the bone marrow cavity of the PC-treated dentition. An in vitro study indicated that the inhibitory effects of TSCs on osteoclastogenesis seemed directed more toward preosteoclasts than osteoblasts. These results indicate that the comprehensive mixture of TSCs might be a useful tool for detailed verification of the adverse effects of tobacco smoke, possibly contributing to the development of reliable treatments in various fields associated with bone resorption.

Partitioning detectability components in populations subject to within-season temporary emigration using binomial mixture models.

Science.gov (United States)

O'Donnell, Katherine M; Thompson, Frank R; Semlitsch, Raymond D

2015-01-01

Detectability of individual animals is highly variable and nearly always binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model's potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3-5 surveys each spring and fall 2010-2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability.

Modelling of an homogeneous equilibrium mixture model

International Nuclear Information System (INIS)

Bernard-Champmartin, A.; Poujade, O.; Mathiaud, J.; Mathiaud, J.; Ghidaglia, J.M.

2014-01-01

We present here a model for two phase flows which is simpler than the 6-equations models (with two densities, two velocities, two temperatures) but more accurate than the standard mixture models with 4 equations (with two densities, one velocity and one temperature). We are interested in the case when the two-phases have been interacting long enough for the drag force to be small but still not negligible. The so-called Homogeneous Equilibrium Mixture Model (HEM) that we present is dealing with both mixture and relative quantities, allowing in particular to follow both a mixture velocity and a relative velocity. This relative velocity is not tracked by a conservation law but by a closure law (drift relation), whose expression is related to the drag force terms of the two-phase flow. After the derivation of the model, a stability analysis and numerical experiments are presented. (authors)

Estimation of value at risk and conditional value at risk using normal mixture distributions model

Science.gov (United States)

Kamaruzzaman, Zetty Ain; Isa, Zaidi

2013-04-01

Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

Isolation of EPR spectra and estimation of spin-states in two-component mixtures of paramagnets.

Science.gov (United States)

Chabbra, Sonia; Smith, David M; Bode, Bela E

2018-04-26

The presence of multiple paramagnetic species can lead to overlapping electron paramagnetic resonance (EPR) signals. This complication can be a critical obstacle for the use of EPR to unravel mechanisms and aid the understanding of earth abundant metal catalysis. Furthermore, redox or spin-crossover processes can result in the simultaneous presence of metal centres in different oxidation or spin states. In this contribution, pulse EPR experiments on model systems containing discrete mixtures of Cr(i) and Cr(iii) or Cu(ii) and Mn(ii) complexes demonstrate the feasibility of the separation of the EPR spectra of these species by inversion recovery filters and the identification of the relevant spin states by transient nutation experiments. We demonstrate the isolation of component spectra and identification of spin states in a mixture of catalyst precursors. The usefulness of the approach is emphasised by monitoring the fate of the chromium species upon activation of an industrially used precatalyst system.

Gravel-Sand-Clay Mixture Model for Predictions of Permeability and Velocity of Unconsolidated Sediments

Science.gov (United States)

Konishi, C.

2014-12-01

Gravel-sand-clay mixture model is proposed particularly for unconsolidated sediments to predict permeability and velocity from volume fractions of the three components (i.e. gravel, sand, and clay). A well-known sand-clay mixture model or bimodal mixture model treats clay contents as volume fraction of the small particle and the rest of the volume is considered as that of the large particle. This simple approach has been commonly accepted and has validated by many studies before. However, a collection of laboratory measurements of permeability and grain size distribution for unconsolidated samples show an impact of presence of another large particle; i.e. only a few percent of gravel particles increases the permeability of the sample significantly. This observation cannot be explained by the bimodal mixture model and it suggests the necessity of considering the gravel-sand-clay mixture model. In the proposed model, I consider the three volume fractions of each component instead of using only the clay contents. Sand becomes either larger or smaller particles in the three component mixture model, whereas it is always the large particle in the bimodal mixture model. The total porosity of the two cases, one is the case that the sand is smaller particle and the other is the case that the sand is larger particle, can be modeled independently from sand volume fraction by the same fashion in the bimodal model. However, the two cases can co-exist in one sample; thus, the total porosity of the mixed sample is calculated by weighted average of the two cases by the volume fractions of gravel and clay. The effective porosity is distinguished from the total porosity assuming that the porosity associated with clay is zero effective porosity. In addition, effective grain size can be computed from the volume fractions and representative grain sizes for each component. Using the effective porosity and the effective grain size, the permeability is predicted by Kozeny-Carman equation

Generation of two-dimensional binary mixtures in complex plasmas

Science.gov (United States)

Wieben, Frank; Block, Dietmar

2016-10-01

Complex plasmas are an excellent model system for strong coupling phenomena. Under certain conditions the dust particles immersed into the plasma form crystals which can be analyzed in terms of structure and dynamics. Previous experiments focussed mostly on monodisperse particle systems whereas dusty plasmas in nature and technology are polydisperse. Thus, a first and important step towards experiments in polydisperse systems are binary mixtures. Recent experiments on binary mixtures under microgravity conditions observed a phase separation of particle species with different radii even for small size disparities. This contradicts several numerical studies of 2D binary mixtures. Therefore, dedicated experiments are required to gain more insight into the physics of polydisperse systems. In this contribution first ground based experiments on two-dimensional binary mixtures are presented. Particular attention is paid to the requirements for the generation of such systems which involve the consideration of the temporal evolution of the particle properties. Furthermore, the structure of these two-component crystals is analyzed and compared to simulations. This work was supported by the Deutsche Forschungsgemeinschaft DFG in the framework of the SFB TR24 Greifswald Kiel, Project A3b.

The separation of solid and liquid components of mixtures

International Nuclear Information System (INIS)

Hunter, W.M.

1980-01-01

An improved method of separating solid and liquid components of mixtures is described which is particularly suited for use in automated radioimmunoassay systems in the analysis of bound and free fractions. A second liquid, having a density intermediate between those of the solid and liquid components, is delivered to the solid/ liquid mixture to form a discrete layer below the mixture and the solid separates into this lower liquid layer assisted by centrifugal force. The second liquid of intermediate density is an aqueous solution of a highly hydrophilic and electrically non-polar solute, such as an aqueous sucrose solution. Further liquids of intermediate density and progressively higher density may be delivered to form further discrete layers below the initial layer of the second dense liquid. After separation of the solid and liquid components of the mixture, the supernatant liquid component of the original mixture is removed in a controlled and non-turbulent manner. The method is illustrated in radioimmunoassays for platelet β-thromboglobulin and human follicle stimulating hormone. (U.K.)

Generalization of two-phase model with topology microstructure of mixture to Lagrange-Euler methodology

International Nuclear Information System (INIS)

Vladimir V Chudanov; Alexei A Leonov

2005-01-01

Full text of publication follows: One of the mathematical models (hyperbolic type) for describing evolution of compressible two-phase mixtures was offered in [1] to deal with the following applications: interfaces between compressible materials; shock waves in multiphase mixtures; evolution of homogeneous two-phase flows; cavitation in liquids. The basic difficulties of this model was connected to discretization of the non-conservative equation terms. As result, the class of problems concerned with passage of shock waves through fields with a discontinuing profile of a volume fraction was not described by means of this model. A class of schemes that are able to converge to the correct solution of such problems was received in [2] due to a deeper analysis of two-phase model. The technique offered in [2] was implemented on a Eulerian grid via the Godunov scheme. In present paper the additional analysis of two-phase model in view of microstructure of an mixture topology is carried out in Lagrange mass coordinates. As result, the equations averaged over the set of all possible realizations for two-phase mixture are received. The numerical solution is carried out with use of PPM method [3] in two steps: at first - the equations averaged over mass variable are solved; on the second - the solution, found on the previous step, is re-mapped to a fixed Eulerian grid. Such approach allows to expand the proposed technique on two-dimensional (three-dimensional) case, as in the Lagrange variables the Euler equations system is split on two (three) identical subsystems, each of which describes evolution of considered medium in the given direction. The accuracy and robustness of the described procedure are demonstrated on a sequence of the numerical problems. References: (1). R. Saurel, R. Abgrall, A multiphase Godunov method for compressible multi-fluid and multiphase flows, J. Comput. Phys. 150 (1999) 425-467; (2). R. Saurel, R. Abgrall, Discrete equations for physical and

Partitioning detectability components in populations subject to within-season temporary emigration using binomial mixture models.

Directory of Open Access Journals (Sweden)

Katherine M O'Donnell

Full Text Available Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model's potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3-5 surveys each spring and fall 2010-2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling, while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling. By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and

The Umov effect in application to an optically thin two-component cloud of cosmic dust

Science.gov (United States)

Zubko, Evgenij; Videen, Gorden; Zubko, Nataliya; Shkuratov, Yuriy

2018-04-01

The Umov effect is an inverse correlation between linear polarization of the sunlight scattered by an object and its geometric albedo. The Umov effect has been observed in particulate surfaces, such as planetary regoliths, and recently it also was found in single-scattering small dust particles. Using numerical modeling, we study the Umov effect in a two-component mixture of small irregularly shaped particles. Such a complex chemical composition is suggested in cometary comae and other types of optically thin clouds of cosmic dust. We find that the two-component mixtures of small particles also reveal the Umov effect regardless of the chemical composition of their end-member components. The interrelation between log(Pmax) and log(A) in a two-component mixture of small irregularly shaped particles appears either in a straight linear form or in a slightly curved form. This curvature tends to decrease while the index n in a power-law size distribution r-n grows; at n > 2.5, the log(Pmax)-log(A) diagrams are almost straight linear in appearance. The curvature also noticeably decreases with the packing density of constituent material in irregularly shaped particles forming the mixture. That such a relation exists suggest the Umov effect may also be observed in more complex mixtures.

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of

How Many Separable Sources? Model Selection In Independent Components Analysis

Science.gov (United States)

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Optimal designs for linear mixture models

NARCIS (Netherlands)

Mendieta, E.J.; Linssen, H.N.; Doornbos, R.

1975-01-01

In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this

Analysis of water hammer in two-component two-phase flows

International Nuclear Information System (INIS)

Warde, H.; Marzouk, E.; Ibrahim, S.

1989-01-01

The water hammer phenomena caused by a sudden valve closure in air-water two-phase flows must be clarified for the safety analysis of LOCA in reactors and further for the safety of boilers, chemical plants, pipe transport of fluids such as petroleum and natural gas. In the present work water hammer phenomena caused by sudden valve closure in two-component two-phase flows are investigated theoretically and experimentally. The phenomena are more complicated than in single phase-flows due to the fact of the presence of compressible component. Basic partial differential equations based on a one-dimensional homogeneous flow model are solved by the method of characteristic. The analysis is extended to include friction in a two-phase mixture depending on the local flow pattern. The profiles of the pressure transients, the propagation velocity of pressure waves and the effect of valve closure on the transient pressure are found. Different two-phase flow pattern and frictional pressure drop correlations were used including Baker, Chesholm and Beggs and Bril correlations. The effect of the flow pattern on the characteristic of wave propagation is discussed primarily to indicate the effect of void fraction on the velocity of wave propagation and on the attenuation of pressure waves. Transient pressure in the mixture were recorded at different air void fractions, rates of uniform valve closure and liquid flow velocities with the aid of pressure transducers, transient wave form recorders interfaced with an on-line pc computer. The results are compared with computation, and good agreement was obtained within experimental accuracy

mixtools: An R Package for Analyzing Mixture Models

Directory of Open Access Journals (Sweden)

Tatiana Benaglia

2009-10-01

Full Text Available The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of different mixture-of-regression contexts, in multinomial mixtures such as those arising from discretizing continuous multivariate data, in nonparametric situations where the multivariate component densities are completely unspecified, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecified densities. Many of the algorithms of the mixtools package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for finite mixture models.

Itinerant Ferromagnetism in a Polarized Two-Component Fermi Gas

DEFF Research Database (Denmark)

Massignan, Pietro; Yu, Zhenhua; Bruun, Georg

2013-01-01

We analyze when a repulsively interacting two-component Fermi gas becomes thermodynamically unstable against phase separation. We focus on the strongly polarized limit, where the free energy of the homogeneous mixture can be calculated accurately in terms of well-defined quasiparticles, the repul......We analyze when a repulsively interacting two-component Fermi gas becomes thermodynamically unstable against phase separation. We focus on the strongly polarized limit, where the free energy of the homogeneous mixture can be calculated accurately in terms of well-defined quasiparticles...

Evaluation of solution stability for two-component polydisperse systems by small-angle scattering

Science.gov (United States)

Kryukova, A. E.; Konarev, P. V.; Volkov, V. V.

2017-12-01

The article is devoted to the modelling of small-angle scattering data using the program MIXTURE designed for the study of polydisperse multicomponent mixtures. In this work we present the results of solution stability studies for theoretical small-angle scattering data sets from two-component models. It was demonstrated that the addition of the noise to the data influences the stability range of the restored structural parameters. The recommendations for the optimal minimization schemes that permit to restore the volume size distributions for polydisperse systems are suggested.

A study of finite mixture model: Bayesian approach on financial time series data

Science.gov (United States)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-07-01

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

The two-component spin-fermion model for high-Tc cuprates: its applications in neutron scattering and ARPES experiments

International Nuclear Information System (INIS)

Bang, Yunkyu

2012-01-01

Motivated by neutron scattering experiments in high-T c cuprates, we propose the two-component spin-fermion model as a minimal phenomenological model, which has both local spins and itinerant fermions as independent degrees of freedom (d.o.f.). Our calculations of the dynamic spin correlation function provide a successful description of the puzzling neutron experiment data and show that: (i) the upward dispersion branch of magnetic excitations is mostly due to local spin excitations; (ii) the downward dispersion branch is from collective particle-hole excitations of fermions; and (iii) the resonance mode is a mixture of both d.o.f. Using the same model with the same set of parameters, we calculated the renormalized quasiparticle (q.p.) dispersion and successfully reproduced one of the key features of the angle-resolved photoemission spectroscopy (ARPES) experiments, namely the high-energy kink structure in the fermion q.p. dispersion, thus supporting the two-component spin-fermion phenomenology. (paper)

Bayesian estimation of mixtures with dynamic transitions and known component parameters

Czech Academy of Sciences Publication Activity Database

Nagy, I.; Suzdaleva, Evgenia; Kárný, Miroslav

2011-01-01

Roč. 47, č. 4 (2011), s. 572-594 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA TA ČR TA01030123; GA ČR GA102/08/0567 Grant - others:Skoda Auto(CZ) ENS/2009/UTIA Institutional research plan: CEZ:AV0Z10750506 Keywords : mixture model * Bayesian estimation * approximation * clustering * classification Subject RIV: BC - Control Systems Theory Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/nagy-bayesian estimation of mixtures with dynamic transitions and known component parameters.pdf

A further component analysis for illicit drugs mixtures with THz-TDS

Science.gov (United States)

Xiong, Wei; Shen, Jingling; He, Ting; Pan, Rui

2009-07-01

A new method for quantitative analysis of mixtures of illicit drugs with THz time domain spectroscopy was proposed and verified experimentally. In traditional method we need fingerprints of all the pure chemical components. In practical as only the objective components in a mixture and their absorption features are known, it is necessary and important to present a more practical technique for the detection and identification. Our new method of quantitatively inspect of the mixtures of illicit drugs is developed by using derivative spectrum. In this method, the ratio of objective components in a mixture can be obtained on the assumption that all objective components in the mixture and their absorption features are known but the unknown components are not needed. Then methamphetamine and flour, a illicit drug and a common adulterant, were selected for our experiment. The experimental result verified the effectiveness of the method, which suggested that it could be an effective method for quantitative identification of illicit drugs. This THz spectroscopy technique is great significant in the real-world applications of illicit drugs quantitative analysis. It could be an effective method in the field of security and pharmaceuticals inspection.

Uniform phases in fluids of hard isosceles triangles: One-component fluid and binary mixtures

Science.gov (United States)

Martínez-Ratón, Yuri; Díaz-De Armas, Ariel; Velasco, Enrique

2018-05-01

We formulate the scaled particle theory for a general mixture of hard isosceles triangles and calculate different phase diagrams for the one-component fluid and for certain binary mixtures. The fluid of hard triangles exhibits a complex phase behavior: (i) the presence of a triatic phase with sixfold symmetry, (ii) the isotropic-uniaxial nematic transition is of first order for certain ranges of aspect ratios, and (iii) the one-component system exhibits nematic-nematic transitions ending in critical points. We found the triatic phase to be stable not only for equilateral triangles but also for triangles of similar aspect ratios. We focus the study of binary mixtures on the case of symmetric mixtures: equal particle areas with aspect ratios (κi) symmetric with respect to the equilateral one, κ1κ2=3 . For these mixtures we found, aside from first-order isotropic-nematic and nematic-nematic transitions (the latter ending in a critical point): (i) a region of triatic phase stability even for mixtures made of particles that do not form this phase at the one-component limit, and (ii) the presence of a Landau point at which two triatic-nematic first-order transitions and a nematic-nematic demixing transition coalesce. This phase behavior is analogous to that of a symmetric three-dimensional mixture of rods and plates.

A three-region model for tracking a two-phase mixture water level in the micro-simulator

International Nuclear Information System (INIS)

Seok, Ho

1994-02-01

A simplified one-dimensional three-region model is developed to predict two-phase mixture and subcooled levels in vertical and horizontal channels during the loss of coolant accidents and to satisfy the requirement of the capability of real-time computation in the micro-simulator. The present model treats a physical component as one node which is divided into three sub-regions by thermal-hydraulic conditions: subcooled region, mixture region, and steam dome region. The bubble rise model and the drift-flux model concept are used to account for the mass and energy transfer between the mixture region and the steam dome region. The conservation equations of mass, energy, and momentum are derived based on the two-fluid model. Especially, the volumes of the subcooled region and the mixture region are adopted as principal unknowns and incorporated in the governing equations. The area change at the junction is modeled in the momentum equation. The non-linear difference equations of mass, energy, and momentum for the three regions are numerically solved by the Implicit Coulant Eulerian (ICE) method similar to that used in advanced safety codes such as TRAC and RELAP5. The proposed model is tested through the comparison of its simulation results with the experimental data of Edwards and O' Brien pipe blodwdown test, GE small vessel blowdown tests, Marviken tests, and 336-rod bundle test in order to confirm its capability of fast calculation but reasonable accuracy. The computation time by RELAP5/MOD3 is up to around 50 times longer than that by the proposed model when the Marviken tests are simulated. The predictions with Bertodanoi's correlation for the drift velocity in the blowdown tests and with the correlation of Ishii et. al. in the 336-rod bundle test are in best agreement with the test data, respectively. A WS-based real-time simulator for two-loop pressurized water reactor plants, also, is developed for classroom training in support of full-support simulator, on

Construction of a 21-Component Layered Mixture Experiment Design

International Nuclear Information System (INIS)

Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley

2004-01-01

This paper describes the solution to a unique and challenging mixture experiment design problem involving: (1) 19 and 21 components for two different parts of the design, (2) many single-component and multi-component constraints, (3) augmentation of existing data, (4) a layered design developed in stages, and (5) a no-candidate-point optimal design approach. The problem involved studying the liquidus temperature of spinel crystals as a function of nuclear waste glass composition. The statistical objective was to develop an experimental design by augmenting existing glasses with new nonradioactive and radioactive glasses chosen to cover the designated nonradioactive and radioactive experimental regions. The existing 144 glasses were expressed as 19-component nonradioactive compositions and then augmented with 40 new nonradioactive glasses. These included 8 glasses on the outer layer of the region, 27 glasses on an inner layer, 2 replicate glasses at the centroid, and one replicate each of three existing glasses. Then, the 144 + 40 = 184 glasses were expressed as 21-component radioactive compositions and augmented with 5 radioactive glasses. A D-optimal design algorithm was used to select the new outer layer, inner layer, and radioactive glasses. Several statistical software packages can generate D-optimal experimental designs, but nearly all require a set of candidate points (e.g., vertices) from which to select design points. The large number of components (19 or 21) and many constraints made it impossible to generate the huge number of vertices and other typical candidate points. JMP(R) was used to select design points without candidate points. JMP uses a coordinate-exchange algorithm modified for mixture experiments, which is discussed in the paper

A Two-Stage Layered Mixture Experiment Design for a Nuclear Waste Glass Application-Part 2

International Nuclear Information System (INIS)

Cooley, Scott K.; Piepel, Gregory F.; Gan, Hao; Kot, Wing; Pegg, Ian L.

2003-01-01

Part 1 (Cooley and Piepel, 2003a) describes the first stage of a two-stage experimental design to support property-composition modeling for high-level waste (HLW) glass to be produced at the Hanford Site in Washington state. Each stage used a layered design having an outer layer, an inner layer, a center point, and some replicates. However, the design variables and constraints defining the layers of the experimental glass composition region (EGCR) were defined differently for the second stage than for the first. The first-stage initial design involved 15 components, all treated as mixture variables. The second-stage augmentation design involved 19 components, with 14 treated as mixture variables and 5 treated as non-mixture variables. For each second-stage layer, vertices were generated and optimal design software was used to select alternative subsets of vertices for the design and calculate design optimality measures. A model containing 29 partial quadratic mixture terms plus 5 linear terms for the non-mixture variables was the basis for the optimal design calculations. Predicted property values were plotted for the alternative subsets of second-stage vertices and the first-stage design points. Based on the optimality measures and the predicted property distributions, a ''best'' subset of vertices was selected for each layer of the second-stage to augment the first-stage design

Evaluation of the H-point standard additions method (HPSAM) and the generalized H-point standard additions method (GHPSAM) for the UV-analysis of two-component mixtures.

Science.gov (United States)

Hund, E; Massart, D L; Smeyers-Verbeke, J

1999-10-01

The H-point standard additions method (HPSAM) and two versions of the generalized H-point standard additions method (GHPSAM) are evaluated for the UV-analysis of two-component mixtures. Synthetic mixtures of anhydrous caffeine and phenazone as well as of atovaquone and proguanil hydrochloride were used. Furthermore, the method was applied to pharmaceutical formulations that contain these compounds as active drug substances. This paper shows both the difficulties that are related to the methods and the conditions by which acceptable results can be obtained.

A minimal model for two-component dark matter

International Nuclear Information System (INIS)

Esch, Sonja; Klasen, Michael; Yaguna, Carlos E.

2014-01-01

We propose and study a new minimal model for two-component dark matter. The model contains only three additional fields, one fermion and two scalars, all singlets under the Standard Model gauge group. Two of these fields, one fermion and one scalar, are odd under a Z_2 symmetry that renders them simultaneously stable. Thus, both particles contribute to the observed dark matter density. This model resembles the union of the singlet scalar and the singlet fermionic models but it contains some new features of its own. We analyze in some detail its dark matter phenomenology. Regarding the relic density, the main novelty is the possible annihilation of one dark matter particle into the other, which can affect the predicted relic density in a significant way. Regarding dark matter detection, we identify a new contribution that can lead either to an enhancement or to a suppression of the spin-independent cross section for the scalar dark matter particle. Finally, we define a set of five benchmarks models compatible with all present bounds and examine their direct detection prospects at planned experiments. A generic feature of this model is that both particles give rise to observable signals in 1-ton direct detection experiments. In fact, such experiments will be able to probe even a subdominant dark matter component at the percent level.

Quantification of Multiple Components of Complex Aluminum-Based Adjuvant Mixtures by Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Modeling.

Science.gov (United States)

Dowling, Quinton M; Kramer, Ryan M

2017-01-01

Fourier transform infrared (FTIR) spectroscopy is widely used in the pharmaceutical industry for process monitoring, compositional quantification, and characterization of critical quality attributes in complex mixtures. Advantages over other spectroscopic measurements include ease of sample preparation, quantification of multiple components from a single measurement, and the ability to quantify optically opaque samples. This method describes the use of a multivariate model for quantifying a TLR4 agonist (GLA) adsorbed onto aluminum oxyhydroxide (Alhydrogel ® ) using FTIR spectroscopy that may be adapted to quantify other complex aluminum based adjuvant mixtures.

Analysis of Minor Component Segregation in Ternary Powder Mixtures

Directory of Open Access Journals (Sweden)

Asachi Maryam

2017-01-01

Full Text Available In many powder handling operations, inhomogeneity in powder mixtures caused by segregation could have significant adverse impact on the quality as well as economics of the production. Segregation of a minor component of a highly active substance could have serious deleterious effects, an example is the segregation of enzyme granules in detergent powders. In this study, the effects of particle properties and bulk cohesion on the segregation tendency of minor component are analysed. The minor component is made sticky while not adversely affecting the flowability of samples. The segregation extent is evaluated using image processing of the photographic records taken from the front face of the heap after the pouring process. The optimum average sieve cut size of components for which segregation could be reduced is reported. It is also shown that the extent of segregation is significantly reduced by applying a thin layer of liquid to the surfaces of minor component, promoting an ordered mixture.

Algorithms and programs of dynamic mixture estimation unified approach to different types of components

CERN Document Server

Nagy, Ivan

2017-01-01

This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.

A two-component dark matter model with real singlet scalars ...

Indian Academy of Sciences (India)

2016-01-05

Jan 5, 2016 ... We propose a two-component dark matter (DM) model, each component of which is a real singlet scalar, to explain results from both direct and indirect detection experiments. We put the constraints on the model parameters from theoretical bounds, PLANCK relic density results and direct DM experiments.

The R Package bgmm : Mixture Modeling with Uncertain Knowledge

Directory of Open Access Journals (Sweden)

Przemys law Biecek

2012-04-01

Full Text Available Classical supervised learning enjoys the luxury of accessing the true known labels for the observations in a modeled dataset. Real life, however, poses an abundance of problems, where the labels are only partially defined, i.e., are uncertain and given only for a subsetof observations. Such partial labels can occur regardless of the knowledge source. For example, an experimental assessment of labels may have limited capacity and is prone to measurement errors. Also expert knowledge is often restricted to a specialized area and is thus unlikely to provide trustworthy labels for all observations in the dataset. Partially supervised mixture modeling is able to process such sparse and imprecise input. Here, we present an R package calledbgmm, which implements two partially supervised mixture modeling methods: soft-label and belief-based modeling. For completeness, we equipped the package also with the functionality of unsupervised, semi- and fully supervised mixture modeling. On real data we present the usage of bgmm for basic model-fitting in all modeling variants. The package can be applied also to selection of the best-fitting from a set of models with different component numbers or constraints on their structures. This functionality is presented on an artificial dataset, which can be simulated in bgmm from a distribution defined by a given model.

Construction of a 21-Component Layered Mixture Experiment Design Using a New Mixture Coordinate-Exchange Algorithm

International Nuclear Information System (INIS)

Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley

2005-01-01

This paper describes the solution to a unique and challenging mixture experiment design problem involving: (1) 19 and 21 components for two different parts of the design, (2) many single-component and multi-component constraints, (3) augmentation of existing data, (4) a layered design developed in stages, and (5) a no-candidate-point optimal design approach. The problem involved studying the liquidus temperature of spinel crystals as a function of nuclear waste glass composition. The statistical objective was to develop an experimental design by augmenting existing glasses with new nonradioactive and radioactive glasses chosen to cover the designated nonradioactive and radioactive experimental regions. The existing 144 glasses were expressed as 19-component nonradioactive compositions and then augmented with 40 new nonradioactive glasses. These included 8 glasses on the outer layer of the region, 27 glasses on an inner layer, 2 replicate glasses at the centroid, and one replicate each of three existing glasses. Then, the 144 + 40 = 184 glasses were expressed as 21-component radioactive compositions, and augmented with 5 radioactive glasses. A D-optimal design algorithm was used to select the new outer layer, inner layer, and radioactive glasses. Several statistical software packages can generate D-optimal experimental designs, but nearly all of them require a set of candidate points (e.g., vertices) from which to select design points. The large number of components (19 or 21) and many constraints made it impossible to generate the huge number of vertices and other typical candidate points. JMP was used to select design points without candidate points. JMP uses a coordinate-exchange algorithm modified for mixture experiments, which is discussed and illustrated in the paper

Merging Mixture Components for Cell Population Identification in Flow Cytometry

Directory of Open Access Journals (Sweden)

Greg Finak

2009-01-01

Full Text Available We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated flow cytometry data distributions. Our framework allows the automated selection of the number of distinct cell subpopulations and we are able to identify cases where the algorithm fails, thus making it suitable for application in a high throughput FCM analysis pipeline. Furthermore, we demonstrate a method for summarizing complex merged cell subpopulations in a simple manner that integrates with the existing flowClust framework and enables downstream data analysis. We demonstrate the performance of our framework on simulated and real FCM data. The software is available in the flowMerge package through the Bioconductor project.

Combinatorial bounds on the α-divergence of univariate mixture models

KAUST Repository

Nielsen, Frank

2017-06-20

We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified empirically through simulated Gaussian mixture models. The presented methodology generalizes to other divergence families relying on Hellinger-type integrals.

Modeling adsorption of binary and ternary mixtures on microporous media

DEFF Research Database (Denmark)

Monsalvo, Matias Alfonso; Shapiro, Alexander

2007-01-01

it possible using the same equation of state to describe the thermodynamic properties of the segregated and the bulk phases. For comparison, we also used the ideal adsorbed solution theory (IAST) to describe adsorption equilibria. The main advantage of these two models is their capabilities to predict......The goal of this work is to analyze the adsorption of binary and ternary mixtures on the basis of the multicomponent potential theory of adsorption (MPTA). In the MPTA, the adsorbate is considered as a segregated mixture in the external potential field emitted by the solid adsorbent. This makes...... multicomponent adsorption equilibria on the basis of single-component adsorption data. We compare the MPTA and IAST models to a large set of experimental data, obtaining reasonable good agreement with experimental data and high degree of predictability. Some limitations of both models are also discussed....

Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

OpenAIRE

Hiroyuki Kasahara; Katsumi Shimotsu

2006-01-01

In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution.

Science.gov (United States)

Lo, Kenneth; Gottardo, Raphael

2012-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components.

Novel two-tiered approach of ecological risk assessment for pesticide mixtures based on joint effects.

Science.gov (United States)

Tian, Dayong; Mao, Haichen; Lv, Huichao; Zheng, Yong; Peng, Conghu; Hou, Shaogang

2018-02-01

Ecological risk assessments for mixtures have attracted considerable attention. In this study, 38 pesticides in the real environment were taken as objects and their toxicities to different organisms from three trophic levels were employed to assess the ecological risk of the mixture. The first tier assessment was based on the CA effect and the obtained sum of risk quotients (SRQ species-CA ) were 3.06-9.22. The second tier assessment was based on non-CA effects and the calculated SRQ species-TU are 5.37-9.29 using joint effects (TU sum ) as modified coefficients, which is higher than SRQ species-CA and indicates that ignoring joint effects might run the risk of underestimating the actual impact of pesticide mixtures. Due to the influences of synergistic and antagonistic effects, risk contribution of components to mixture risks based on non-CA effects are different from those based on the CA effect. Moreover, it was found that the top 8 dominating components explained 95.5%-99.8% of mixture risks in this study. The dominating components are similar in the two tiers for a given species. Accordingly, a novel two-tiered approach was proposed to assess the ecological risks of mixtures based on joint effects. This study provides new insights for ecological risk assessments with the consideration of joint effects of components in the pesticide mixtures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling the effect of mixture components on permeation through skin.

Science.gov (United States)

Ghafourian, T; Samaras, E G; Brooks, J D; Riviere, J E

2010-10-15

A vehicle influences the concentration of penetrant within the membrane, affecting its diffusivity in the skin and rate of transport. Despite the huge amount of effort made for the understanding and modelling of the skin absorption of chemicals, a reliable estimation of the skin penetration potential from formulations remains a challenging objective. In this investigation, quantitative structure-activity relationship (QSAR) was employed to relate the skin permeation of compounds to the chemical properties of the mixture ingredients and the molecular structures of the penetrants. The skin permeability dataset consisted of permeability coefficients of 12 different penetrants each blended in 24 different solvent mixtures measured from finite-dose diffusion cell studies using porcine skin. Stepwise regression analysis resulted in a QSAR employing two penetrant descriptors and one solvent property. The penetrant descriptors were octanol/water partition coefficient, logP and the ninth order path molecular connectivity index, and the solvent property was the difference between boiling and melting points. The negative relationship between skin permeability coefficient and logP was attributed to the fact that most of the drugs in this particular dataset are extremely lipophilic in comparison with the compounds in the common skin permeability datasets used in QSAR. The findings show that compounds formulated in vehicles with small boiling and melting point gaps will be expected to have higher permeation through skin. The QSAR was validated internally, using a leave-many-out procedure, giving a mean absolute error of 0.396. The chemical space of the dataset was compared with that of the known skin permeability datasets and gaps were identified for future skin permeability measurements. Copyright 2010 Elsevier B.V. All rights reserved.

Thermodynamic parameters for mixtures of quartz under shock wave loading in views of the equilibrium model

International Nuclear Information System (INIS)

Maevskii, K. K.; Kinelovskii, S. A.

2015-01-01

The numerical results of modeling of shock wave loading of mixtures with the SiO 2 component are presented. The TEC (thermodynamic equilibrium component) model is employed to describe the behavior of solid and porous multicomponent mixtures and alloys under shock wave loading. State equations of a Mie–Grüneisen type are used to describe the behavior of condensed phases, taking into account the temperature dependence of the Grüneisen coefficient, gas in pores is one of the components of the environment. The model is based on the assumption that all components of the mixture under shock-wave loading are in thermodynamic equilibrium. The calculation results are compared with the experimental data derived by various authors. The behavior of the mixture containing components with a phase transition under high dynamic loads is described

Measurement and modelling of hydrogen bonding in 1-alkanol plus n-alkane binary mixtures

DEFF Research Database (Denmark)

von Solms, Nicolas; Jensen, Lars; Kofod, Jonas L.

2007-01-01

Two equations of state (simplified PC-SAFT and CPA) are used to predict the monomer fraction of 1-alkanols in binary mixtures with n-alkanes. It is found that the choice of parameters and association schemes significantly affects the ability of a model to predict hydrogen bonding in mixtures, eve...... studies, which is clarified in the present work. New hydrogen bonding data based on infrared spectroscopy are reported for seven binary mixtures of alcohols and alkanes. (C) 2007 Elsevier B.V. All rights reserved....... though pure-component liquid densities and vapour pressures are predicted equally accurately for the associating compound. As was the case in the study of pure components, there exists some confusion in the literature about the correct interpretation and comparison of experimental data and theoretical...

Operation of the multigap resistive plate chamber using a gas mixture free of flammable components

CERN Document Server

Akindinov, A; Antonioli, P; Arcelli, S; Basile, M; Cara Romeo, G; Cifarelli, Luisa; Cindolo, F; De Caro, A; De Pasquale, S; Di Bartolomeo, A; Fusco-Girard, M; Golovine, V; Guida, M; Hatzifotiadou, D; Kaidalov, A B; Kim, D H; Kim, D W; Kisselev, S M; Laurenti, G; Lee, K; Lee, S C; Lioublev, E; Luvisetto, M L; Margotti, A; Martemyanov, A N; Nania, R; Noferini, F; Otiougova, P; Pesci, A; Pinazza, O; Polozov, P A; Scapparone, E; Scioli, G; Sellitto, S B; Semeria, F; Smirnitsky, A V; Tchoumakov, M M; Usenko, E; Valenti, G; Voloshin, K G; Williams, M C S; Zagreev, B V; Zampolli, C; Zichichi, A

2004-01-01

We have investigated the operation of the multigap resistive plate chamber (MRPC) for the ALICE-TOF system with a gas mixture free of flammable components. Two different gas mixtures, with and without iso-C//4H//1//0 have been used to measure the performance of the MRPC. The efficiency, time resolution, total charge, and the fast to total charge ratio have been found to be comparable.

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

Science.gov (United States)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Enantiomer-specific analysis of multi-component mixtures by correlated electron imaging-ion mass spectrometry

NARCIS (Netherlands)

Rafiee Fanood, M.M.; Ram, N.B.; Lehmann, C.S.; Powis, I.; Janssen, M.H.M.

2015-01-01

Simultaneous, enantiomer-specific identification of chiral molecules in multi-component mixtures is extremely challenging. Many established techniques for single-component analysis fail to provide selectivity in multi-component mixtures and lack sensitivity for dilute samples. Here we show how

Bayesian mixture models for source separation in MEG

International Nuclear Information System (INIS)

Calvetti, Daniela; Homa, Laura; Somersalo, Erkki

2011-01-01

This paper discusses the problem of imaging electromagnetic brain activity from measurements of the induced magnetic field outside the head. This imaging modality, magnetoencephalography (MEG), is known to be severely ill posed, and in order to obtain useful estimates for the activity map, complementary information needs to be used to regularize the problem. In this paper, a particular emphasis is on finding non-superficial focal sources that induce a magnetic field that may be confused with noise due to external sources and with distributed brain noise. The data are assumed to come from a mixture of a focal source and a spatially distributed possibly virtual source; hence, to differentiate between those two components, the problem is solved within a Bayesian framework, with a mixture model prior encoding the information that different sources may be concurrently active. The mixture model prior combines one density that favors strongly focal sources and another that favors spatially distributed sources, interpreted as clutter in the source estimation. Furthermore, to address the challenge of localizing deep focal sources, a novel depth sounding algorithm is suggested, and it is shown with simulated data that the method is able to distinguish between a signal arising from a deep focal source and a clutter signal. (paper)

Mixture-mixture design for the fingerprint optimization of chromatographic mobile phases and extraction solutions for Camellia sinensis.

Science.gov (United States)

Borges, Cleber N; Bruns, Roy E; Almeida, Aline A; Scarminio, Ieda S

2007-07-09

A composite simplex centroid-simplex centroid mixture design is proposed for simultaneously optimizing two mixture systems. The complementary model is formed by multiplying special cubic models for the two systems. The design was applied to the simultaneous optimization of both mobile phase chromatographic mixtures and extraction mixtures for the Camellia sinensis Chinese tea plant. The extraction mixtures investigated contained varying proportions of ethyl acetate, ethanol and dichloromethane while the mobile phase was made up of varying proportions of methanol, acetonitrile and a methanol-acetonitrile-water (MAW) 15%:15%:70% mixture. The experiments were block randomized corresponding to a split-plot error structure to minimize laboratory work and reduce environmental impact. Coefficients of an initial saturated model were obtained using Scheffe-type equations. A cumulative probability graph was used to determine an approximate reduced model. The split-plot error structure was then introduced into the reduced model by applying generalized least square equations with variance components calculated using the restricted maximum likelihood approach. A model was developed to calculate the number of peaks observed with the chromatographic detector at 210 nm. A 20-term model contained essentially all the statistical information of the initial model and had a root mean square calibration error of 1.38. The model was used to predict the number of peaks eluted in chromatograms obtained from extraction solutions that correspond to axial points of the simplex centroid design. The significant model coefficients are interpreted in terms of interacting linear, quadratic and cubic effects of the mobile phase and extraction solution components.

Fluorescence lifetime selectivity in excitation-emission matrices for qualitative analysis of a two-component system

International Nuclear Information System (INIS)

Millican, D.W.; McGown, L.B.

1989-01-01

Steady-state fluorescence excitation-emission matrices (EEMs), and phase-resolved EEMs (PREEMs) collected at modulation frequencies of 6, 18, and 30 MHz, were used for qualitative analysis of mixtures of benzo[k]fluoranthene (τ = 8 ns) and benzo[b]fluoranthene (τ = 29 ns) in ethanol. The EEMs of the individual components were extracted from mixture EEMs by means of wavelength component vector-gram (WCV) analysis. Phase resolution was found to be superior to steady-state measurements for extraction of the component spectra, for mixtures in which the intensity contributions from the two components are unequal

Application of the Electronic Nose Technique to Differentiation between Model Mixtures with COPD Markers

Directory of Open Access Journals (Sweden)

Jacek Namieśnik

2013-04-01

Full Text Available The paper presents the potential of an electronic nose technique in the field of fast diagnostics of patients suspected of Chronic Obstructive Pulmonary Disease (COPD. The investigations were performed using a simple electronic nose prototype equipped with a set of six semiconductor sensors manufactured by FIGARO Co. They were aimed at verification of a possibility of differentiation between model reference mixtures with potential COPD markers (N,N-dimethylformamide and N,N-dimethylacetamide. These mixtures contained volatile organic compounds (VOCs such as acetone, isoprene, carbon disulphide, propan-2-ol, formamide, benzene, toluene, acetonitrile, acetic acid, dimethyl ether, dimethyl sulphide, acrolein, furan, propanol and pyridine, recognized as the components of exhaled air. The model reference mixtures were prepared at three concentration levels—10 ppb, 25 ppb, 50 ppb v/v—of each component, except for the COPD markers. Concentration of the COPD markers in the mixtures was from 0 ppb to 100 ppb v/v. Interpretation of the obtained data employed principal component analysis (PCA. The investigations revealed the usefulness of the electronic device only in the case when the concentration of the COPD markers was twice as high as the concentration of the remaining components of the mixture and for a limited number of basic mixture components.

Shear viscosity of liquid mixtures: Mass dependence

International Nuclear Information System (INIS)

Kaushal, Rohan; Tankeshwar, K.

2002-06-01

Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model. (author)

Shear viscosity of liquid mixtures Mass dependence

CERN Document Server

Kaushal, R

2002-01-01

Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model.

Molecular Orientation in Two Component Vapor-Deposited Glasses: Effect of Substrate Temperature and Molecular Shape

Science.gov (United States)

Powell, Charles; Jiang, Jing; Walters, Diane; Ediger, Mark

Vapor-deposited glasses are widely investigated for use in organic electronics including the emitting layers of OLED devices. These materials, while macroscopically homogenous, have anisotropic packing and molecular orientation. By controlling this orientation, outcoupling efficiency can be increased by aligning the transition dipole moment of the light-emitting molecules parallel to the substrate. Light-emitting molecules are typically dispersed in a host matrix, as such, it is imperative to understand molecular orientation in two-component systems. In this study we examine two-component vapor-deposited films and the orientations of the constituent molecules using spectroscopic ellipsometry, UV-vis and IR spectroscopy. The role of temperature, composition and molecular shape as it effects molecular orientation is examined for mixtures of DSA-Ph in Alq3 and in TPD. Deposition temperature relative to the glass transition temperature of the two-component mixture is the primary controlling factor for molecular orientation. In mixtures of DSA-Ph in Alq3, the linear DSA-Ph has a horizontal orientation at low temperatures and slight vertical orientation maximized at 0.96Tg,mixture, analogous to one-component films.

Effect of the addition of mixture of plant components on the mechanical properties of wheat bread

Science.gov (United States)

Wójcik, Monika; Dziki, Dariusz; Biernacka, Beata; Różyło, Renata; Miś, Antoni; Hassoon, Waleed H.

2017-10-01

Instrumental methods of measuring the mechanical properties of bread can be used to determine changes in the properties of it during storage, as well as to determine the effect of various additives on the bread texture. The aim of this study was to investigate the effect of the mixture of plant components on the physical properties of wheat bread. In particular, the mechanical properties of the crumb and crust were studied. A sensory evaluation of the end product was also performed. The mixture of plant components included: carob fiber, milled grain red quinoa and black oat (1:2:2) - added at 0, 5, 10, 15, 20, 25 % - into wheat flour. The results showed that the increase of the addition of the proposed additive significantly increased the water absorption of flour mixtures. Moreover, the use of the mixture of plant components above 5% resulted in the increase of bread volume and decrease of crumb density. Furthermore, the addition of the mixture of plant components significantly affected the mechanical properties of bread crumb. The hardness of crumb also decreased as a result of the mixture of plant components addition. The highest cohesiveness was obtained for bread with 10% of additive and the lowest for bread with 25% of mixture of plant components. Most importantly, the enrichment of wheat flour with the mixture of plant components significantly reduced the crust failure force and crust failure work. The results of sensory evaluation showed that the addition of the mixture of plant components of up to 10% had little effect on bread quality.

Finite mixture model: A maximum likelihood estimation approach on time series data

Science.gov (United States)

Yen, Phoong Seuk; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad

2014-09-01

Recently, statistician emphasized on the fitting of finite mixture model by using maximum likelihood estimation as it provides asymptotic properties. In addition, it shows consistency properties as the sample sizes increases to infinity. This illustrated that maximum likelihood estimation is an unbiased estimator. Moreover, the estimate parameters obtained from the application of maximum likelihood estimation have smallest variance as compared to others statistical method as the sample sizes increases. Thus, maximum likelihood estimation is adopted in this paper to fit the two-component mixture model in order to explore the relationship between rubber price and exchange rate for Malaysia, Thailand, Philippines and Indonesia. Results described that there is a negative effect among rubber price and exchange rate for all selected countries.

Two-component thermosensitive hydrogels : Phase separation affecting rheological behavior

NARCIS (Netherlands)

Abbadessa, Anna; Landín, Mariana; Oude Blenke, Erik; Hennink, Wim E.; Vermonden, Tina

2017-01-01

Extracellular matrices are mainly composed of a mixture of different biopolymers and therefore the use of two or more building blocks for the development of tissue-mimicking hydrogels is nowadays an attractive strategy in tissue-engineering. Multi-component hydrogel systems may undergo phase

Stability equation and two-component Eigenmode for domain walls in scalar potential model

International Nuclear Information System (INIS)

Dias, G.S.; Graca, E.L.; Rodrigues, R. de Lima

2002-08-01

Supersymmetric quantum mechanics involving a two-component representation and two-component eigenfunctions is applied to obtain the stability equation associated to a potential model formulated in terms of two coupled real scalar fields. We investigate the question of stability by introducing an operator technique for the Bogomol'nyi-Prasad-Sommerfield (BPS) and non-BPS states on two domain walls in a scalar potential model with minimal N 1-supersymmetry. (author)

Application of some geometrical and empirical models to excess molar volume for the multi-component mixtures at T = 298.15 K

International Nuclear Information System (INIS)

Iloukhani, H.; Khanlarzadeh, K.

2012-01-01

Highlights: ► Excess molar volume of quartenary mixtures of 1-chlorobutane, 2-chlorobutane, butylamine, and butylacetate was determined. ► The experimental data were correlated by some empirical and semi empirical models. ► A comparison with PFP theory has been successfully applied from binary data. - Abstract: Densities of the quaternary mixture consisting of {1-chlorobutane (1) + 2-chlorobutane (2) + butylamine (3) + butylacetate (4)} and related ternary mixtures of {1-chlorobutane (1) + 2-chlorobutane (2) + butylamine (3)}, {1-chlorobutane (1) + 2-chlorobutane (2) + butylacetate (4)}, {2-chlorobutane (2) + butylamine (3) + butylacetate (4)}, and binary systems of {1-chlorobutane (1) + 2-chlorobutane (2)}, {2-chlorobutane (2) + butylamine (3)}, were measured over the whole range of composition at T = 298.15 K and ambient pressure. Excess molar volumes, V m E , for the mixtures were derived and correlated as a function of mole fraction by using the Redlich–Kister and the Cibulka equations for binary and ternary mixtures, respectively. From the experimental data, partial molar volumes, V m,i and excess partial molar volumes, V m,i E were also calculated for binary systems. The experimental results of the constituted binary mixtures have been used to test the applicability of the Prigogine–Flory–Paterson (PFP) theory. A number of geometrical and empirical equations were also used to verify their ability to predict ternary and quaternary properties from their lower order mixtures. The experimental data were used to evaluate the nature and type of intermolecular interactions in multi-component mixtures.

Detailed finite element method modeling of evaporating multi-component droplets

Energy Technology Data Exchange (ETDEWEB)

Diddens, Christian, E-mail: C.Diddens@tue.nl

2017-07-01

The evaporation of sessile multi-component droplets is modeled with an axisymmetic finite element method. The model comprises the coupled processes of mixture evaporation, multi-component flow with composition-dependent fluid properties and thermal effects. Based on representative examples of water–glycerol and water–ethanol droplets, regular and chaotic examples of solutal Marangoni flows are discussed. Furthermore, the relevance of the substrate thickness for the evaporative cooling of volatile binary mixture droplets is pointed out. It is shown how the evaporation of the more volatile component can drastically decrease the interface temperature, so that ambient vapor of the less volatile component condenses on the droplet. Finally, results of this model are compared with corresponding results of a lubrication theory model, showing that the application of lubrication theory can cause considerable errors even for moderate contact angles of 40°. - Graphical abstract:.

Improvement of a Mixture Experiment Model Relating the Component Proportions to the Size of Nanonized Itraconazole Particles in Extemporary Suspensions

Energy Technology Data Exchange (ETDEWEB)

Pattarino, Franco; Piepel, Gregory F.; Rinaldi, Maurizio

2018-05-01

The Foglio Bonda et al. (2016) (henceforth FB) paper discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (the response variable of interest). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). After publication of the FB paper, the second author of this corrigendum (not an author of the original paper) contacted the corresponding author to point out some errors as well as insufficient explanations in parts of the paper. This corrigendum was prepared to address these issues. The authors of the original paper apologize for any inconveniences to readers.

A Two-Stage Layered Mixture Experiment Design for a Nuclear Waste Glass Application-Part 1

International Nuclear Information System (INIS)

Cooley, Scott K.; Piepel, Gregory F.; Gan, Hao; Kot, Wing; Pegg, Ian L.

2003-01-01

A layered experimental design involving mixture variables was generated to support developing property-composition models for high-level waste (HLW) glasses. The design was generated in two stages, each having unique characteristics. Each stage used a layered design having an outer layer, an inner layer, a center point, and some replicates. The layers were defined by single- and multi-variable constraints. The first stage involved 15 glass components treated as mixture variables. For each layer, vertices were generated and optimal design software was used to select alternative subsets of vertices and calculate design optimality measures. Two partial quadratic mixture models, containing 25 terms for the outer layer and 30 terms for the inner layer, were the basis for the optimal design calculations. Distributions of predicted glass property values were plotted and evaluated for the alternative subsets of vertices. Based on the optimality measures and the predicted property distributions, a ''best'' subset of vertices was selected for each layer to form a layered design for the first stage. The design for the second stage was selected to augment the first-stage design. The discussion of the second-stage design begins in this Part 1 and is continued in Part 2 (Cooley and Piepel, 2003b)

CO2 Removal from Multi-component Gas Mixtures Utilizing Spiral-Wound Asymmetric Membranes

International Nuclear Information System (INIS)

Said, W.B.; Fahmy, M.F.M.; Gad, F.K.; EI-Aleem, G.A.

2004-01-01

A systematic procedure and a computer program have been developed for simulating the performance of a spiral-wound gas permeate for the CO 2 removal from natural gas and other hydrocarbon streams. The simulation program is based on the approximate multi-component model derived by Qi and Henson(l), in addition to the membrane parameters achieved from the binary simulation program(2) (permeability and selectivity). Applying the multi-component program on the same data used by Qi and Henson to evaluate the deviation of the approximate model from the basic transport model, showing results more accurate than those of the approximate model, and are very close to those of the basic transport model, while requiring significantly less than 1 % of the computation time. The program was successfully applied on the data of Salam gas plant membrane unit at Khalda Petroleum Company, Egypt, for the separation of CO 2 from hydrocarbons in an eight-component mixture to estimate the stage cut, residue, and permeate compositions, and gave results matched with the actual Gas Chromatography Analysis measured by the lab

Flow boiling heat transfer coefficients at cryogenic temperatures for multi-component refrigerant mixtures of nitrogen-hydrocarbons

Science.gov (United States)

Ardhapurkar, P. M.; Sridharan, Arunkumar; Atrey, M. D.

2014-01-01

The recuperative heat exchanger governs the overall performance of the mixed refrigerant Joule-Thomson cryocooler. In these heat exchangers, the non-azeotropic refrigerant mixture of nitrogen-hydrocarbons undergoes boiling and condensation simultaneously at cryogenic temperature. Hence, the design of such heat exchanger is crucial. However, due to lack of empirical correlations to predict two-phase heat transfer coefficients of multi-component mixtures at low temperature, the design of such heat exchanger is difficult.

Structural properties of dendrimer-colloid mixtures

International Nuclear Information System (INIS)

Lenz, Dominic A; Blaak, Ronald; Likos, Christos N

2012-01-01

We consider binary mixtures of colloidal particles and amphiphilic dendrimers of the second generation by means of Monte Carlo simulations. By using the effective interactions between monomer-resolved dendrimers and colloids, we compare the results of simulations of mixtures stemming from a full monomer-resolved description with the effective two-component description at different densities, composition ratios, colloid diameters and interaction strengths. Additionally, we map the two-component system onto an effective one-component model for the colloids in the presence of the dendrimers. Simulations based on the resulting depletion potentials allow us to extend the comparison to yet another level of coarse graining and to examine under which conditions this two-step approach is valid. In addition, a preliminary outlook into the phase behavior of this system is given. (paper)

Beyond GLMs: a generative mixture modeling approach to neural system identification.

Directory of Open Access Journals (Sweden)

Lucas Theis

Full Text Available Generalized linear models (GLMs represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships to be discovered. Alternative approaches exist that make only very weak assumptions but scale poorly to high-dimensional stimulus spaces. Here we seek an approach which can gracefully interpolate between the two extremes. We extend two frequently used special cases of the GLM-a linear and a quadratic model-by assuming that the spike-triggered and non-spike-triggered distributions can be adequately represented using Gaussian mixtures. Because we derive the model from a generative perspective, its components are easy to interpret as they correspond to, for example, the spike-triggered distribution and the interspike interval distribution. The model is able to capture complex dependencies on high-dimensional stimuli with far fewer parameters than other approaches such as histogram-based methods. The added flexibility comes at the cost of a non-concave log-likelihood. We show that in practice this does not have to be an issue and the mixture-based model is able to outperform generalized linear and quadratic models.

Multidimensional profiling of components in complex mixtures of natural products for metabolic analysis, proof of concept: application to Quillaja saponins.

Science.gov (United States)

Bankefors, Johan; Nord, Lars I; Kenne, Lennart

2010-02-01

A method for separation and detection of major and minor components in complex mixtures has been developed, utilising two-dimensional high-performance liquid chromatography (2D-HPLC) combined with electrospray ionisation ion-trap multiple-stage mass spectrometry (ESI-ITMS(n)). Chromatographic conditions were matched with mass spectrometric detection to maximise the number of components that could be separated. The described procedure has proven useful to discern several hundreds of saponin components when applied to Quillaja saponaria Molina bark extracts. The discrimination of each saponin component relies on the fact that three coordinates (x, y, z) for each component can be derived from the retention time of the two chromatographic steps (x, y) and the m/z-values from the multiple-stage mass spectrometry (z(n), n=1, 2, ...). Thus an improved graphical representation was obtained by combining retention times from the two-stage separation with +MS(1) (z(1)) and the additional structural information from the second mass stage +MS(2) (z(2), z(3)) corresponding to the main fragment ions. By this approach three-dimensional plots can be made that reveal both the chromatographic and structural properties of a specific mixture which can be useful in fingerprinting of complex mixtures. 2009 Elsevier B.V. All rights reserved.

Two-Microphone Separation of Speech Mixtures

DEFF Research Database (Denmark)

Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan

2008-01-01

combined, independent component analysis (ICA) and binary time–frequency (T–F) masking. By estimating binary masks from the outputs of an ICA algorithm, it is possible in an iterative way to extract basis speech signals from a convolutive mixture. The basis signals are afterwards improved by grouping...

XeCl Excimer Laser with Three- and Four-Component Mixture of Active Gases

International Nuclear Information System (INIS)

Iwanejko, L.; Pokora, L.

1998-01-01

Selected results of investigations of a XeCl excimer laser employing a new type (four-component)of mixture of gases, He-Kr:Xe-HCl, are presented. The mixture includes, instead of Xe, a mixture of not-separated Kr and Xe gases, much less expensive than pure xenon. A comparison of durations and energies of pulses generated in the XeCl excimer laser using three- or four-component gaseous active medium (He-Xe-HCl or He-Kr:Xe-HCl) is made. The investigations have been carried out with the use of a laser system with UV preionization and self sustained pumping discharge. (author)

Finite mixture model applied in the analysis of a turbulent bistable flow on two parallel circular cylinders

Energy Technology Data Exchange (ETDEWEB)

Paula, A.V. de, E-mail: vagtinski@mecanica.ufrgs.br [PROMEC – Programa de Pós Graduação em Engenharia Mecânica, UFRGS – Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil); Möller, S.V., E-mail: svmoller@ufrgs.br [PROMEC – Programa de Pós Graduação em Engenharia Mecânica, UFRGS – Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil)

2013-11-15

This paper presents a study of the bistable phenomenon which occurs in the turbulent flow impinging on circular cylinders placed side-by-side. Time series of axial and transversal velocity obtained with the constant temperature hot wire anemometry technique in an aerodynamic channel are used as input data in a finite mixture model, to classify the observed data according to a family of probability density functions. Wavelet transforms are applied to analyze the unsteady turbulent signals. Results of flow visualization show that the flow is predominantly two-dimensional. A double-well energy model is suggested to describe the behavior of the bistable phenomenon in this case. -- Highlights: ► Bistable flow on two parallel cylinders is studied with hot wire anemometry as a first step for the application on the analysis to tube bank flow. ► The method of maximum likelihood estimation is applied to hot wire experimental series to classify the data according to PDF functions in a mixture model approach. ► Results show no evident correlation between the changes of flow modes with time. ► An energy model suggests the presence of more than two flow modes.

[Study of Determination of Oil Mixture Components Content Based on Quasi-Monte Carlo Method].

Science.gov (United States)

Wang, Yu-tian; Xu, Jing; Liu, Xiao-fei; Chen, Meng-han; Wang, Shi-tao

2015-05-01

Gasoline, kerosene, diesel is processed by crude oil with different distillation range. The boiling range of gasoline is 35 ~205 °C. The boiling range of kerosene is 140~250 °C. And the boiling range of diesel is 180~370 °C. At the same time, the carbon chain length of differentmineral oil is different. The carbon chain-length of gasoline is within the scope of C7 to C11. The carbon chain length of kerosene is within the scope of C12 to C15. And the carbon chain length of diesel is within the scope of C15 to C18. The recognition and quantitative measurement of three kinds of mineral oil is based on different fluorescence spectrum formed in their different carbon number distribution characteristics. Mineral oil pollution occurs frequently, so monitoring mineral oil content in the ocean is very important. A new method of components content determination of spectra overlapping mineral oil mixture is proposed, with calculation of characteristic peak power integrationof three-dimensional fluorescence spectrum by using Quasi-Monte Carlo Method, combined with optimal algorithm solving optimum number of characteristic peak and range of integral region, solving nonlinear equations by using BFGS(a rank to two update method named after its inventor surname first letter, Boyden, Fletcher, Goldfarb and Shanno) method. Peak power accumulation of determined points in selected area is sensitive to small changes of fluorescence spectral line, so the measurement of small changes of component content is sensitive. At the same time, compared with the single point measurement, measurement sensitivity is improved by the decrease influence of random error due to the selection of points. Three-dimensional fluorescence spectra and fluorescence contour spectra of single mineral oil and the mixture are measured by taking kerosene, diesel and gasoline as research objects, with a single mineral oil regarded whole, not considered each mineral oil components. Six characteristic peaks are

Anisotropic properties of phase separation in two-component dipolar Bose-Einstein condensates

Science.gov (United States)

Wang, Wei; Li, Jinbin

2018-03-01

Using Crank-Nicolson method, we calculate ground state wave functions of two-component dipolar Bose-Einstein condensates (BECs) and show that, due to dipole-dipole interaction (DDI), the condensate mixture displays anisotropic phase separation. The effects of DDI, inter-component s-wave scattering, strength of trap potential and particle numbers on the density profiles are investigated. Three types of two-component profiles are present, first cigar, along z-axis and concentric torus, second pancake (or blood cell), in xy-plane, and two non-uniform ellipsoid, separated by the pancake and third two dumbbell shapes.

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

Science.gov (United States)

Baek, Jangsun; Son, Young Sook; McLachlan, Geoffrey J

2007-02-15

We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions; (4) the

Revealing the equivalence of two clonal survival models by principal component analysis

International Nuclear Information System (INIS)

Lachet, Bernard; Dufour, Jacques

1976-01-01

The principal component analysis of 21 chlorella cell survival curves, adjusted by one-hit and two-hit target models, lead to quite similar projections on the principal plan: the homologous parameters of these models are linearly correlated; the reason for the statistical equivalence of these two models, in the present state of experimental inaccuracy, is revealed [fr

Combinatorial bounds on the α-divergence of univariate mixture models

KAUST Repository

Nielsen, Frank; Sun, Ke

2017-01-01

We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified

A two-component dark matter model with real singlet scalars ...

Indian Academy of Sciences (India)

Theoretical framework. In the present work, the dark matter candidate has two components S and S′ both of ... The scalar sector potential (for Higgs and two real singlet scalars) in this framework can then be written .... In this work we obtain the allowed values of model parameters (δ2, δ′2, MS and M′S) using three direct ...

A Dirichlet process mixture of generalized Dirichlet distributions for proportional data modeling.

Science.gov (United States)

Bouguila, Nizar; Ziou, Djemel

2010-01-01

In this paper, we propose a clustering algorithm based on both Dirichlet processes and generalized Dirichlet distribution which has been shown to be very flexible for proportional data modeling. Our approach can be viewed as an extension of the finite generalized Dirichlet mixture model to the infinite case. The extension is based on nonparametric Bayesian analysis. This clustering algorithm does not require the specification of the number of mixture components to be given in advance and estimates it in a principled manner. Our approach is Bayesian and relies on the estimation of the posterior distribution of clusterings using Gibbs sampler. Through some applications involving real-data classification and image databases categorization using visual words, we show that clustering via infinite mixture models offers a more powerful and robust performance than classic finite mixtures.

Phase Equilibrium Calculations for Multi-Component Polar Fluid Mixtures with tPC-PSAFT

DEFF Research Database (Denmark)

Karakatsani, Eirini; Economou, Ioannis

2007-01-01

The truncated Perturbed-Chain Polar Statistical Associating Fluid Theory (tPC-PSAFT) is applied to a number of different mixtures, including binary, ternary and quaternary mixtures of components that differ substantially in terms of intermolecular interactions and molecular size. In contrast to m...

A turbulence model in mixtures. First part: Statistical description of mixture

International Nuclear Information System (INIS)

Besnard, D.

1987-03-01

Classical theory of mixtures gives a model for molecular mixtures. This kind of model is based on a small gradient approximation for concentration, temperature, and pression. We present here a mixture model, allowing for large gradients in the flow. We also show that, with a local balance assumption between material diffusion and flow gradients evolution, we obtain a model similar to those mentioned above [fr

Data Requirements and Modeling for Gas Hydrate-Related Mixtures and a Comparison of Two Association Models

DEFF Research Database (Denmark)

Liang, Xiaodong; Aloupis, Georgios; Kontogeorgis, Georgios M.

2017-01-01

the performance of the CPA and sPC-SAFT EOS for modeling the fluid-phase equilibria of gas hydrate-related systems and will try to explore how the models can help in suggesting experimental measurements. These systems contain water, hydrocarbon (alkane or aromatic), and either methanol or monoethylene glycol...... parameter sets have been chosen for the sPC-SAFT EOS for a fair comparison. The comparisons are made for pure fluid properties, vapor liquid-equilibria, and liquid liquid equilibria of binary and ternary mixtures as well as vapor liquid liquid equilibria of quaternary mixtures. The results show, from...

Modeling of the flame propagation in coal-dust- methane air mixture in an enclosed sphere volume

International Nuclear Information System (INIS)

Krainov, A Yu; Moiseeva, K M

2016-01-01

The results of the numerical simulation of the flame front propagation in coal-dust- methane-air mixture in an enclosed volume with the ignition source in the center of the volume are presented. The mathematical model is based on a dual-velocity two-phase model of the reacting gas-dispersion medium. The system of equations includes the mass-conversation equation, the impulse-conversation equation, the total energy-conversation equation of the gas and particles taking into account the thermal conductivity and chemical reactions in the gas and on the particle surface, mass-conversation equation of the mixture gas components considering the diffusion and the burn-out and the particle burn-out equation. The influence of the coal particle mass on the pressure in the volume after the mixture burn out and on the burn-out time has been investigated. It has been shown that the burning rate of the coal-dust methane air mixtures depends on the coal particle size. (paper)

Structure-reactivity modeling using mixture-based representation of chemical reactions.

Science.gov (United States)

Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

2017-09-01

We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

Prevalence Incidence Mixture Models

Science.gov (United States)

The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

MODELING THERMAL DUST EMISSION WITH TWO COMPONENTS: APPLICATION TO THE PLANCK HIGH FREQUENCY INSTRUMENT MAPS

International Nuclear Information System (INIS)

Meisner, Aaron M.; Finkbeiner, Douglas P.

2015-01-01

We apply the Finkbeiner et al. two-component thermal dust emission model to the Planck High Frequency Instrument maps. This parameterization of the far-infrared dust spectrum as the sum of two modified blackbodies (MBBs) serves as an important alternative to the commonly adopted single-MBB dust emission model. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. based on FIRAS and DIRBE. We also derive full-sky 6.'1 resolution maps of dust optical depth and temperature by fitting the two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100 μm data. Because our two-component model matches the dust spectrum near its peak, accounts for the spectrum's flattening at millimeter wavelengths, and specifies dust temperature at 6.'1 FWHM, our model provides reliable, high-resolution thermal dust emission foreground predictions from 100 to 3000 GHz. We find that, in diffuse sky regions, our two-component 100-217 GHz predictions are on average accurate to within 2.2%, while extrapolating the Planck Collaboration et al. single-MBB model systematically underpredicts emission by 18.8% at 100 GHz, 12.6% at 143 GHz, and 7.9% at 217 GHz. We calibrate our two-component optical depth to reddening, and compare with reddening estimates based on stellar spectra. We find the dominant systematic problems in our temperature/reddening maps to be zodiacal light on large angular scales and the cosmic infrared background anisotropy on small angular scales

Bayesian Plackett-Luce Mixture Models for Partially Ranked Data.

Science.gov (United States)

Mollica, Cristina; Tardella, Luca

2017-06-01

The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a specific population. The Plackett-Luce model is one of the most popular and frequently applied parametric distributions to analyze rankings of a finite set of items. The present work introduces a Bayesian finite mixture of Plackett-Luce models to account for unobserved sample heterogeneity of partially ranked data. We describe an efficient way to incorporate the latent group structure in the data augmentation approach and the derivation of existing maximum likelihood procedures as special instances of the proposed Bayesian method. Inference can be conducted with the combination of the Expectation-Maximization algorithm for maximum a posteriori estimation and the Gibbs sampling iterative procedure. We additionally investigate several Bayesian criteria for selecting the optimal mixture configuration and describe diagnostic tools for assessing the fitness of ranking distributions conditionally and unconditionally on the number of ranked items. The utility of the novel Bayesian parametric Plackett-Luce mixture for characterizing sample heterogeneity is illustrated with several applications to simulated and real preference ranked data. We compare our method with the frequentist approach and a Bayesian nonparametric mixture model both assuming the Plackett-Luce model as a mixture component. Our analysis on real datasets reveals the importance of an accurate diagnostic check for an appropriate in-depth understanding of the heterogenous nature of the partial ranking data.

Thermodiffusion in Multicomponent Mixtures Thermodynamic, Algebraic, and Neuro-Computing Models

CERN Document Server

Srinivasan, Seshasai

2013-01-01

Thermodiffusion in Multicomponent Mixtures presents the computational approaches that are employed in the study of thermodiffusion in various types of mixtures, namely, hydrocarbons, polymers, water-alcohol, molten metals, and so forth. We present a detailed formalism of these methods that are based on non-equilibrium thermodynamics or algebraic correlations or principles of the artificial neural network. The book will serve as single complete reference to understand the theoretical derivations of thermodiffusion models and its application to different types of multi-component mixtures. An exhaustive discussion of these is used to give a complete perspective of the principles and the key factors that govern the thermodiffusion process.

Diffusion coefficients in 4-component mixture expressed explicitly in terms of binary diffusion coefficients and mole fractions

International Nuclear Information System (INIS)

Furuta, Hiroshi; Yamamoto, Ichiro

1996-01-01

Diffusion coefficients in 4-component mixture D ij (4) were expressed explicitly in terms of binary diffusion coefficients and mole fractions by solving a ratio of determinants defined by Hirschfelder et al. The explicit expressions of D ij (4) were divided into two terms, a term due to the i-j pairs of attention and a term common to all the pairs out of the 4 components. The two terms of D ij (4) had extended structures similar to corresponding those of D ij (3) respectively. (author)

Two-component scattering model and the electron density spectrum

Science.gov (United States)

Zhou, A. Z.; Tan, J. Y.; Esamdin, A.; Wu, X. J.

2010-02-01

In this paper, we discuss a rigorous treatment of the refractive scintillation caused by a two-component interstellar scattering medium and a Kolmogorov form of density spectrum. It is assumed that the interstellar scattering medium is composed of a thin-screen interstellar medium (ISM) and an extended interstellar medium. We consider the case that the scattering of the thin screen concentrates in a thin layer represented by a δ function distribution and that the scattering density of the extended irregular medium satisfies the Gaussian distribution. We investigate and develop equations for the flux density structure function corresponding to this two-component ISM geometry in the scattering density distribution and compare our result with the observations. We conclude that the refractive scintillation caused by this two-component ISM scattering gives a more satisfactory explanation for the observed flux density variation than does the single extended medium model. The level of refractive scintillation is strongly sensitive to the distribution of scattering material along the line of sight (LOS). The theoretical modulation indices are comparatively less sensitive to the scattering strength of the thin-screen medium, but they critically depend on the distance from the observer to the thin screen. The logarithmic slope of the structure function is sensitive to the scattering strength of the thin-screen medium, but is relatively insensitive to the thin-screen location. Therefore, the proposed model can be applied to interpret the structure functions of flux density observed in pulsar PSR B2111 + 46 and PSR B0136 + 57. The result suggests that the medium consists of a discontinuous distribution of plasma turbulence embedded in the interstellar medium. Thus our work provides some insight into the distribution of the scattering along the LOS to the pulsar PSR B2111 + 46 and PSR B0136 + 57.

METHODS OF ANALYSIS AND CLASSIFICATION OF THE COMPONENTS OF GRAIN MIXTURES BASED ON MEASURING THE REFLECTION AND TRANSMISSION SPECTRA

Directory of Open Access Journals (Sweden)

Artem O. Donskikh*

2017-10-01

Full Text Available The paper considers methods of classification of grain mixture components based on spectral analysis in visible and near-infrared wavelength ranges using various measurement approaches - reflection, transmission and combined spectrum methods. It also describes the experimental measuring units used and suggests the prototype of a multispectral grain mixture analyzer. The results of the spectral measurement were processed using neural network based classification algorithms. The probabilities of incorrect recognition for various numbers of spectral parts and combinations of spectral methods were estimated. The paper demonstrates that combined usage of two spectral analysis methods leads to higher classification accuracy and allows for reducing the number of the analyzed spectral parts. A detailed description of the proposed measurement device for high-performance real-time multispectral analysis of the components of grain mixtures is given.

Scattering and radiative properties of semi-external versus external mixtures of different aerosol types

International Nuclear Information System (INIS)

Mishchenko, Michael I.; Liu Li; Travis, Larry D.; Lacis, Andrew A.

2004-01-01

The superposition T-matrix method is used to compute the scattering of unpolarized light by semi-external aerosol mixtures in the form of polydisperse, randomly oriented two-particle clusters with touching components. The results are compared with those for composition-equivalent external aerosol mixtures, in which the components are widely separated and scatter light in isolation from each other. It is concluded that aggregation is likely to have a relatively weak effect on scattering and radiative properties of two-component tropospheric aerosols and can be replaced by the much simpler external-mixture model in remote sensing studies and atmospheric radiation balance computations

Methodology for predicting oily mixture properties in the mathematical modeling of molecular distillation

Directory of Open Access Journals (Sweden)

M. F. Gayol

2017-06-01

Full Text Available A methodology for predicting the thermodynamic and transport properties of a multi-component oily mixture, in which the different mixture components are grouped into a small number of pseudo components is shown. This prediction of properties is used in the mathematical modeling of molecular distillation, which consists of a system of differential equations in partial derivatives, according to the principles of the Transport Phenomena and is solved by an implicit finite difference method using a computer code. The mathematical model was validated with experimental data, specifically the molecular distillation of a deodorizer distillate (DD of sunflower oil. The results obtained were satisfactory, with errors less than 10% with respect to the experimental data in a temperature range in which it is possible to apply the proposed method.

Methodology for predicting oily mixture properties in the mathematical modeling of molecular distillation

International Nuclear Information System (INIS)

Gayol, M.F.; Pramparo, M.C.; Miró Erdmann, S.M.

2017-01-01

A methodology for predicting the thermodynamic and transport properties of a multi-component oily mixture, in which the different mixture components are grouped into a small number of pseudo components is shown. This prediction of properties is used in the mathematical modeling of molecular distillation, which consists of a system of differential equations in partial derivatives, according to the principles of the Transport Phenomena and is solved by an implicit finite difference method using a computer code. The mathematical model was validated with experimental data, specifically the molecular distillation of a deodorizer distillate (DD) of sunflower oil. The results obtained were satisfactory, with errors less than 10% with respect to the experimental data in a temperature range in which it is possible to apply the proposed method. [es

Kinetic behavior of Fe(o,o-EDDHA)-humic substance mixtures in several soil components and in calcareous soils.

Science.gov (United States)

Cerdán, Mar; Alcañiz, Sara; Juárez, Margarita; Jordá, Juana D; Bermúdez, Dolores

2007-10-31

Ferric ethylenediamine- N, N'-bis-(o-hydroxyphenylacetic)acid chelate (Fe(o, o-EDDHA)) is one of the most effective Fe fertilizers in calcareous soils. However, humic substances are occasionally combined with iron chelates in drip irrigation systems in order to lower costs. The reactivity of iron chelate-humic substance mixtures in several soil components and in calcareous soils was investigated through interaction tests, and their behavior was compared to the application of iron chelates and humic substances separately. Two commercial humic substances and two Fe(o, o-EDDHA) chelates (one synthesized in the laboratory and one commercial) were used to prepare iron chelate-humic substance mixtures at 50% (w/w). Various soil components (calcium carbonate, gibbsite, amorphous iron oxide, hematite, tenorite, zincite, amorphous Mn oxide, and peat) and three calcareous soils were shaken for 15 days with the mixtures and with iron chelate and humic substance solutions. The kinetic behavior of Fe(o, o-EDDHA) and Fe non-(o,o-EDDHA) (Fe bonded to (o,p-EDDHA) and other polycondensated ligands) and of the different nutrients solubilized after the interaction assay was determined. The results showed that the mixtures did not significantly reduce the retention of Fe(o, o-EDDHA) and Fe non-(o,o-EDDHA) in the soil components and the calcareous soils compared to the iron chelate solutions, but they did produce changes in the retention rate. Moreover, the competition between humic substances and synthetic chelating agents for complexing metal cations limited the effectiveness of the mixtures to mobilize nutrients from the substrates. The presence of Fe(o, p-EDDHA) and other byproducts in the commercial iron chelate had an important effect on the evolution of Fe(o, o-EDDHA) and the nutrient solubilization process.

Modelling of phase equilibria for associating mixtures using an equation of state

International Nuclear Information System (INIS)

Ferreira, Olga; Brignole, Esteban A.; Macedo, Eugenia A.

2004-01-01

In the present work, the group contribution with association equation of state (GCA-EoS) is extended to represent phase equilibria in mixtures containing acids, esters, and ketones, with water, alcohols, and any number of inert components. Association effects are represented by a group-contribution approach. Self- and cross-association between the associating groups present in these mixtures are considered. The GCA-EoS model is compared to the group-contribution method MHV2, which does not take into account explicitly association effects. The results obtained with the GCA-EoS model are, in general, more accurate when compared to the ones achieved by the MHV2 equation with less number of parameters. Model predictions are presented for binary self- and cross-associating mixtures

Use of Mixture Designs to Investigate Contribution of Minor Sex Pheromone Components to Trap Catch of the Carpenterworm Moth, Chilecomadia valdiviana.

Science.gov (United States)

Lapointe, Stephen L; Barros-Parada, Wilson; Fuentes-Contreras, Eduardo; Herrera, Heidy; Kinsho, Takeshi; Miyake, Yuki; Niedz, Randall P; Bergmann, Jan

2017-12-01

Field experiments were carried out to study responses of male moths of the carpenterworm, Chilecomadia valdiviana (Lepidoptera: Cossidae), a pest of tree and fruit crops in Chile, to five compounds previously identified from the pheromone glands of females. Previously, attraction of males to the major component, (7Z,10Z)-7,10-hexadecadienal, was clearly demonstrated while the role of the minor components was uncertain due to the use of an experimental design that left large portions of the design space unexplored. We used mixture designs to study the potential contributions to trap catch of the four minor pheromone components produced by C. valdiviana. After systematically exploring the design space described by the five pheromone components, we concluded that the major pheromone component alone is responsible for attraction of male moths in this species. The need for appropriate experimental designs to address the problem of assessing responses to mixtures of semiochemicals in chemical ecology is described. We present an analysis of mixture designs and response surface modeling and an explanation of why this approach is superior to commonly used, but statistically inappropriate, designs.

VISCOSITY OF BINARY NON-ELECTROLYTE LIQUID MIXTURES: PREDICTION AND CORRELATION

Directory of Open Access Journals (Sweden)

Mirjana Lj. Kijevčanin

2008-11-01

Full Text Available The viscosity of 31 binary liquid mixtures containing diverse groups of organic compounds, determined at atmospheric pressure: alcohols, alkanes (cyclo and aliphatic, esters, aromatics, ketones etc., were calculated using two different approaches, correlative (with Teja-Rice and McAllister models and predictive by group contribution models (UNIFAC-VISCO, ASOG-VISCO and Grunberg-Nissan. The obtained results were analysed in terms of the applied approach and model, the structure of the investigated mixtures, the nature of components of the mixtures and the influence of alkyl chain length of the alcohol molecule.

On the nonequilibrium segregation state of a two-phase mixture in a porous column

DEFF Research Database (Denmark)

Shapiro, Alexander; Stenby, Erling Halfdan

1996-01-01

The problem of segregation of a two-phase multicomponent mixture under the action of thermal gradient, gravity and capillary forces is studied with respect to component distribution in a thick oil-gas-condensate reservoir. Governing equations are derived on the basis of nonequilibrium...

Stochastic radiative transfer model for mixture of discontinuous vegetation canopies

International Nuclear Information System (INIS)

Shabanov, Nikolay V.; Huang, D.; Knjazikhin, Y.; Dickinson, R.E.; Myneni, Ranga B.

2007-01-01

Modeling of the radiation regime of a mixture of vegetation species is a fundamental problem of the Earth's land remote sensing and climate applications. The major existing approaches, including the linear mixture model and the turbid medium (TM) mixture radiative transfer model, provide only an approximate solution to this problem. In this study, we developed the stochastic mixture radiative transfer (SMRT) model, a mathematically exact tool to evaluate radiation regime in a natural canopy with spatially varying optical properties, that is, canopy, which exhibits a structured mixture of vegetation species and gaps. The model solves for the radiation quantities, direct input to the remote sensing/climate applications: mean radiation fluxes over whole mixture and over individual species. The canopy structure is parameterized in the SMRT model in terms of two stochastic moments: the probability of finding species and the conditional pair-correlation of species. The second moment is responsible for the 3D radiation effects, namely, radiation streaming through gaps without interaction with vegetation and variation of the radiation fluxes between different species. We performed analytical and numerical analysis of the radiation effects, simulated with the SMRT model for the three cases of canopy structure: (a) non-ordered mixture of species and gaps (TM); (b) ordered mixture of species without gaps; and (c) ordered mixture of species with gaps. The analysis indicates that the variation of radiation fluxes between different species is proportional to the variation of species optical properties (leaf albedo, density of foliage, etc.) Gaps introduce significant disturbance to the radiation regime in the canopy as their optical properties constitute major contrast to those of any vegetation species. The SMRT model resolves deficiencies of the major existing mixture models: ignorance of species radiation coupling via multiple scattering of photons (the linear mixture model

On modeling of structured multiphase mixtures

International Nuclear Information System (INIS)

Dobran, F.

1987-01-01

The usual modeling of multiphase mixtures involves a set of conservation and balance equations of mass, momentum, energy and entropy (the basic set) constructed by an averaging procedure or postulated. The averaged models are constructed by averaging, over space or time segments, the local macroscopic field equations of each phase, whereas the postulated models are usually motivated by the single phase multicomponent mixture models. In both situations, the resulting equations yield superimposed continua models and are closed by the constitutive equations which place restrictions on the possible material response during the motion and phase change. In modeling the structured multiphase mixtures, the modeling of intrinsic motion of grains or particles is accomplished by adjoining to the basic set of field equations the additional balance equations, thereby placing restrictions on the motion of phases only within the imposed extrinsic and intrinsic sources. The use of the additional balance equations has been primarily advocated in the postulatory theories of multiphase mixtures and are usually derived through very special assumptions of the material deformation. Nevertheless, the resulting mixture models can predict a wide variety of complex phenomena such as the Mohr-Coulomb yield criterion in granular media, Rayleigh bubble equation, wave dispersion and dilatancy. Fundamental to the construction of structured models of multiphase mixtures are the problems pertaining to the existence and number of additional balance equations to model the structural characteristics of a mixture. Utilizing a volume averaging procedure it is possible not only to derive the basic set of field equation discussed above, but also a very general set of additional balance equations for modeling of structural properties of the mixture

Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

Directory of Open Access Journals (Sweden)

Ghosh Debashis

2004-12-01

Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

New methods for the characterization of pyrocarbon; The two component model of pyrocarbon

Energy Technology Data Exchange (ETDEWEB)

Luhleich, H.; Sutterlin, L.; Hoven, H.; Nickel, H.

1972-04-19

In the first part, new experiments to clarify the origin of different pyrocarbon components are described. Three new methods (plasma-oxidation, wet-oxidation, ultrasonic method) are presented to expose the carbon black like component in the pyrocarbon deposited in fluidized beds. In the second part, a two component model of pyrocarbon is proposed and illustrated by examples.

Bayesian Analysis of two Censored Shifted Gompertz Mixture Distributions using Informative and Noninformative Priors

Directory of Open Access Journals (Sweden)

Tabassum Naz Sindhu

2017-03-01

Full Text Available This study deals with Bayesian analysis of shifted Gompertz mixture model under type-I censored samples assuming both informative and noninformative priors. We have discussed the Bayesian estimation of parameters of shifted Gompertz mixture model under the uniform, and gamma priors assuming three loss functions. Further, some properties of the model with some graphs of the mixture density are discussed. These properties include Bayes estimators, posterior risks and reliability function under simulation scheme. Bayes estimates are obtained considering two cases: (a when the shape parameter is known and (b when all parameters are unknown. We analyzed some simulated sets in order to investigate the effect of prior belief, loss functions, and performance of the proposed set of estimators of the mixture model parameters.

A mixture model-based approach to the clustering of microarray expression data.

Science.gov (United States)

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

Viscous Growth in Spinodal Decomposition of the Two-component Lennard-Jones Model in Two Dimensions

DEFF Research Database (Denmark)

Laradji, M.; Toxvaerd, S.; Mouritsen, Ole G.

1997-01-01

The dynamics of phase separation of a two-component Lennard-Jones model in three dimensions is investigated by means of large scale molecular dynamics simulation. A systematic study over a wide range of quench temperatures within the coexistence region shows that the binary system reaches...

Modelling time course gene expression data with finite mixtures of linear additive models.

Science.gov (United States)

Grün, Bettina; Scharl, Theresa; Leisch, Friedrich

2012-01-15

A model class of finite mixtures of linear additive models is presented. The component-specific parameters in the regression models are estimated using regularized likelihood methods. The advantages of the regularization are that (i) the pre-specified maximum degrees of freedom for the splines is less crucial than for unregularized estimation and that (ii) for each component individually a suitable degree of freedom is selected in an automatic way. The performance is evaluated in a simulation study with artificial data as well as on a yeast cell cycle dataset of gene expression levels over time. The latest release version of the R package flexmix is available from CRAN (http://cran.r-project.org/).

Correlation inequalities for two-component hypercubic φ4 models. Pt. 2

International Nuclear Information System (INIS)

Soria, J.L.; Instituto Tecnologico de Tijuana

1990-01-01

We continue the program started in the first paper (J. Stat. Phys. 52 (1988) 711-726). We find new and already known correlation inequalities for a family of two-component hypercubic φ 4 models, using techniques of rotated correlation inequalities and random walk representation. (orig.)

Modeling the evaporation of sessile multi-component droplets

NARCIS (Netherlands)

Diddens, C.; Kuerten, Johannes G.M.; van der Geld, C.W.M.; Wijshoff, H.M.A.

2017-01-01

We extended a mathematical model for the drying of sessile droplets, based on the lubrication approximation, to binary mixture droplets. This extension is relevant for e.g. inkjet printing applications, where ink consisting of several components are used. The extension involves the generalization of

Characterization of the pharmacokinetics of gasoline using PBPK modeling with a complex mixtures chemical lumping approach.

Science.gov (United States)

Dennison, James E; Andersen, Melvin E; Yang, Raymond S H

2003-09-01

Gasoline consists of a few toxicologically significant components and a large number of other hydrocarbons in a complex mixture. By using an integrated, physiologically based pharmacokinetic (PBPK) modeling and lumping approach, we have developed a method for characterizing the pharmacokinetics (PKs) of gasoline in rats. The PBPK model tracks selected target components (benzene, toluene, ethylbenzene, o-xylene [BTEX], and n-hexane) and a lumped chemical group representing all nontarget components, with competitive metabolic inhibition between all target compounds and the lumped chemical. PK data was acquired by performing gas uptake PK studies with male F344 rats in a closed chamber. Chamber air samples were analyzed every 10-20 min by gas chromatography/flame ionization detection and all nontarget chemicals were co-integrated. A four-compartment PBPK model with metabolic interactions was constructed using the BTEX, n-hexane, and lumped chemical data. Target chemical kinetic parameters were refined by studies with either the single chemical alone or with all five chemicals together. o-Xylene, at high concentrations, decreased alveolar ventilation, consistent with respiratory irritation. A six-chemical interaction model with the lumped chemical group was used to estimate lumped chemical partitioning and metabolic parameters for a winter blend of gasoline with methyl t-butyl ether and a summer blend without any oxygenate. Computer simulation results from this model matched well with experimental data from single chemical, five-chemical mixture, and the two blends of gasoline. The PBPK model analysis indicated that metabolism of individual components was inhibited up to 27% during the 6-h gas uptake experiments of gasoline exposures.

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

Science.gov (United States)

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

Ignition of alkane-rich FACE gasoline fuels and their surrogate mixtures

KAUST Repository

Sarathy, Mani

2015-01-01

Petroleum derived gasoline is the most used transportation fuel for light-duty vehicles. In order to better understand gasoline combustion, this study investigated the ignition propensity of two alkane-rich FACE (Fuels for Advanced Combustion Engines) gasoline test fuels and their corresponding PRF (primary reference fuel) blend in fundamental combustion experiments. Shock tube ignition delay times were measured in two separate facilities at pressures of 10, 20, and 40 bar, temperatures from 715 to 1500 K, and two equivalence ratios. Rapid compression machine ignition delay times were measured for fuel/air mixtures at pressures of 20 and 40 bar, temperatures from 632 to 745 K, and two equivalence ratios. Detailed hydrocarbon analysis was also performed on the FACE gasoline fuels, and the results were used to formulate multi-component gasoline surrogate mixtures. Detailed chemical kinetic modeling results are presented herein to provide insights into the relevance of utilizing PRF and multi-component surrogate mixtures to reproduce the ignition behavior of the alkane-rich FACE gasoline fuels. The two FACE gasoline fuels and their corresponding PRF mixture displayed similar ignition behavior at intermediate and high temperatures, but differences were observed at low temperatures. These trends were mimicked by corresponding surrogate mixture models, except for the amount of heat release in the first stage of a two-stage ignition events, when observed. © 2014 The Combustion Institute.

Model-based experimental design for assessing effects of mixtures of chemicals

Energy Technology Data Exchange (ETDEWEB)

Baas, Jan, E-mail: jan.baas@falw.vu.n [Vrije Universiteit of Amsterdam, Dept of Theoretical Biology, De Boelelaan 1085, 1081 HV Amsterdam (Netherlands); Stefanowicz, Anna M., E-mail: anna.stefanowicz@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Klimek, Beata, E-mail: beata.klimek@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Laskowski, Ryszard, E-mail: ryszard.laskowski@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Kooijman, Sebastiaan A.L.M., E-mail: bas@bio.vu.n [Vrije Universiteit of Amsterdam, Dept of Theoretical Biology, De Boelelaan 1085, 1081 HV Amsterdam (Netherlands)

2010-01-15

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms. - We show a mechanistic approach to assess effects of mixtures in low concentrations.

Model-based experimental design for assessing effects of mixtures of chemicals

International Nuclear Information System (INIS)

Baas, Jan; Stefanowicz, Anna M.; Klimek, Beata; Laskowski, Ryszard; Kooijman, Sebastiaan A.L.M.

2010-01-01

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms. - We show a mechanistic approach to assess effects of mixtures in low concentrations.

Prediction of two-phase mixture density using artificial neural networks

International Nuclear Information System (INIS)

Lombardi, C.; Mazzola, A.

1997-01-01

In nuclear power plants, the density of boiling mixtures has a significant relevance due to its influence on the neutronic balance, the power distribution and the reactor dynamics. Since the determination of the two-phase mixture density on a purely analytical basis is in fact impractical in many situations of interest, heuristic relationships have been developed based on the parameters describing the two-phase system. However, the best or even a good structure for the correlation cannot be determined in advance, also considering that it is usually desired to represent the experimental data with the most compact equation. A possible alternative to empirical correlations is the use of artificial neural networks, which allow one to model complex systems without requiring the explicit formulation of the relationships existing among the variables. In this work, the neural network methodology was applied to predict the density data of two-phase mixtures up-flowing in adiabatic channels under different experimental conditions. The trained network predicts the density data with a root-mean-square error of 5.33%, being ∼ 93% of the data points predicted within 10%. When compared with those of two conventional well-proven correlations, i.e. the Zuber-Findlay and the CISE correlations, the neural network performances are significantly better. In spite of the good accuracy of the neural network predictions, the 'black-box' characteristic of the neural model does not allow an easy physical interpretation of the knowledge integrated in the network weights. Therefore, the neural network methodology has the advantage of not requiring a formal correlation structure and of giving very accurate results, but at the expense of a loss of model transparency. (author)

The phase behavior of a hard sphere chain model of a binary n-alkane mixture

International Nuclear Information System (INIS)

Malanoski, A. P.; Monson, P. A.

2000-01-01

Monte Carlo computer simulations have been used to study the solid and fluid phase properties as well as phase equilibrium in a flexible, united atom, hard sphere chain model of n-heptane/n-octane mixtures. We describe a methodology for calculating the chemical potentials for the components in the mixture based on a technique used previously for atomic mixtures. The mixture was found to conform accurately to ideal solution behavior in the fluid phase. However, much greater nonidealities were seen in the solid phase. Phase equilibrium calculations indicate a phase diagram with solid-fluid phase equilibrium and a eutectic point. The components are only miscible in the solid phase for dilute solutions of the shorter chains in the longer chains. (c) 2000 American Institute of Physics

New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables

NARCIS (Netherlands)

A. Ruseckaite (Aiste)

2017-01-01

markdownabstractThis thesis discusses new mixture(-amount) models, choice models and the optimal design of experiments. Two chapters of the thesis relate to the so-called mixture, which is a product or service whose ingredients’ proportions sum to one. The thesis begins by introducing mixture

A Note on the Use of Mixture Models for Individual Prediction.

Science.gov (United States)

Cole, Veronica T; Bauer, Daniel J

Mixture models capture heterogeneity in data by decomposing the population into latent subgroups, each of which is governed by its own subgroup-specific set of parameters. Despite the flexibility and widespread use of these models, most applications have focused solely on making inferences for whole or sub-populations, rather than individual cases. The current article presents a general framework for computing marginal and conditional predicted values for individuals using mixture model results. These predicted values can be used to characterize covariate effects, examine the fit of the model for specific individuals, or forecast future observations from previous ones. Two empirical examples are provided to demonstrate the usefulness of individual predicted values in applications of mixture models. The first example examines the relative timing of initiation of substance use using a multiple event process survival mixture model whereas the second example evaluates changes in depressive symptoms over adolescence using a growth mixture model.

Consistency of the MLE under mixture models

OpenAIRE

Chen, Jiahua

2016-01-01

The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many researchers ignore the precise conditions required on the mixture model. An incorrect claim of consistency can lead to false conclusions even if the mixture model under investigation seems well behaved. Under a finite normal mixture model, for instance, the consis...

A general mixture model and its application to coastal sandbar migration simulation

Science.gov (United States)

Liang, Lixin; Yu, Xiping

2017-04-01

A mixture model for general description of sediment laden flows is developed and then applied to coastal sandbar migration simulation. Firstly the mixture model is derived based on the Eulerian-Eulerian approach of the complete two-phase flow theory. The basic equations of the model include the mass and momentum conservation equations for the water-sediment mixture and the continuity equation for sediment concentration. The turbulent motion of the mixture is formulated for the fluid and the particles respectively. A modified k-ɛ model is used to describe the fluid turbulence while an algebraic model is adopted for the particles. A general formulation for the relative velocity between the two phases in sediment laden flows, which is derived by manipulating the momentum equations of the enhanced two-phase flow model, is incorporated into the mixture model. A finite difference method based on SMAC scheme is utilized for numerical solutions. The model is validated by suspended sediment motion in steady open channel flows, both in equilibrium and non-equilibrium state, and in oscillatory flows as well. The computed sediment concentrations, horizontal velocity and turbulence kinetic energy of the mixture are all shown to be in good agreement with experimental data. The mixture model is then applied to the study of sediment suspension and sandbar migration in surf zones under a vertical 2D framework. The VOF method for the description of water-air free surface and topography reaction model is coupled. The bed load transport rate and suspended load entrainment rate are all decided by the sea bed shear stress, which is obtained from the boundary layer resolved mixture model. The simulation results indicated that, under small amplitude regular waves, erosion occurred on the sandbar slope against the wave propagation direction, while deposition dominated on the slope towards wave propagation, indicating an onshore migration tendency. The computation results also shows that

Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using Neural Networks.

Science.gov (United States)

Ajmani, Subhash; Rogers, Stephen C; Barley, Mark H; Burgess, Andrew N; Livingstone, David J

2010-09-17

In our earlier work, we have demonstrated that it is possible to characterize binary mixtures using single component descriptors by applying various mixing rules. We also showed that these methods were successful in building predictive QSPR models to study various mixture properties of interest. Here in, we developed a QSPR model of an excess thermodynamic property of binary mixtures i.e. excess molar volume (V(E) ). In the present study, we use a set of mixture descriptors which we earlier designed to specifically account for intermolecular interactions between the components of a mixture and applied successfully to the prediction of infinite-dilution activity coefficients using neural networks (part 1 of this series). We obtain a significant QSPR model for the prediction of excess molar volume (V(E) ) using consensus neural networks and five mixture descriptors. We find that hydrogen bond and thermodynamic descriptors are the most important in determining excess molar volume (V(E) ), which is in line with the theory of intermolecular forces governing excess mixture properties. The results also suggest that the mixture descriptors utilized herein may be sufficient to model a wide variety of properties of binary and possibly even more complex mixtures. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Kinematics of two-phase mixture level motion in BWR pressure vessels

International Nuclear Information System (INIS)

Wulff, W.; Cheng, H.S.; Mallen, A.N.; Stritar, A.

1985-01-01

A model is presented for predicting two-phase mixture level elevations in BWR systems. The model accounts for the particular geometry and conditions in a BWR system during Small-Break Loss of Coolant Accidents. The model presented here is particularly suitable for efficient, high-speed simulations on small minicomputers. The model has been implemented and tested. Results are shown from BWR ATWS simulations

Discrete kink dynamics in hydrogen-bonded chains: The two-component model

DEFF Research Database (Denmark)

Karpan, V.M.; Zolotaryuk, Yaroslav; Christiansen, Peter Leth

2004-01-01

We study discrete topological solitary waves (kinks and antikinks) in two nonlinear diatomic chain models that describe the collective dynamics of proton transfers in one-dimensional hydrogen-bonded networks. The essential ingredients of the models are (i) a realistic (anharmonic) ion-proton inte......We study discrete topological solitary waves (kinks and antikinks) in two nonlinear diatomic chain models that describe the collective dynamics of proton transfers in one-dimensional hydrogen-bonded networks. The essential ingredients of the models are (i) a realistic (anharmonic) ion...... chain subject to a substrate with two optical bands), both providing a bistability of the hydrogen-bonded proton. Exact two-component (kink and antikink) discrete solutions for these models are found numerically. We compare the soliton solutions and their properties in both the one- (when the heavy ions...... principal differences, like a significant difference in the stability switchings behavior for the kinks and the antikinks. Water-filled carbon nanotubes are briefly discussed as possible realistic systems, where topological discrete (anti)kink states might exist....

Probabilistic mixture-based image modelling

Czech Academy of Sciences Publication Activity Database

Haindl, Michal; Havlíček, Vojtěch; Grim, Jiří

2011-01-01

Roč. 47, č. 3 (2011), s. 482-500 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:CESNET(CZ) 387/2010; GA MŠk(CZ) 2C06019; GA ČR(CZ) GA103/11/0335 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF texture modelling * discrete distribution mixtures * Bernoulli mixture * Gaussian mixture * multi-spectral texture modelling Subject RIV: BD - Theory of Information Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/RO/haindl-0360244.pdf

A Bayesian Approach to Model Selection in Hierarchical Mixtures-of-Experts Architectures.

Science.gov (United States)

Tanner, Martin A.; Peng, Fengchun; Jacobs, Robert A.

1997-03-01

There does not exist a statistical model that shows good performance on all tasks. Consequently, the model selection problem is unavoidable; investigators must decide which model is best at summarizing the data for each task of interest. This article presents an approach to the model selection problem in hierarchical mixtures-of-experts architectures. These architectures combine aspects of generalized linear models with those of finite mixture models in order to perform tasks via a recursive "divide-and-conquer" strategy. Markov chain Monte Carlo methodology is used to estimate the distribution of the architectures' parameters. One part of our approach to model selection attempts to estimate the worth of each component of an architecture so that relatively unused components can be pruned from the architecture's structure. A second part of this approach uses a Bayesian hypothesis testing procedure in order to differentiate inputs that carry useful information from nuisance inputs. Simulation results suggest that the approach presented here adheres to the dictum of Occam's razor; simple architectures that are adequate for summarizing the data are favored over more complex structures. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

Mathematical Model for Multicomponent Adsorption Equilibria Using Only Pure Component Data

DEFF Research Database (Denmark)

Marcussen, Lis

2000-01-01

A mathematical model for nonideal adsorption equilibria in multicomponent mixtures is developed. It is applied with good results for pure substances and for prediction of strongly nonideal multicomponent equilibria using only pure component data. The model accounts for adsorbent...

Competitive adsorption of a two-component gas on a deformable adsorbent

International Nuclear Information System (INIS)

Usenko, A S

2014-01-01

We investigate the competitive adsorption of a two-component gas on the surface of an adsorbent whose adsorption properties vary due to the adsorbent deformation. The essential difference of adsorption isotherms for a deformable adsorbent both from the classical Langmuir adsorption isotherms of a two-component gas and from the adsorption isotherms of a one-component gas is obtained, taking into account variations in the adsorption properties of the adsorbent in adsorption. We establish bistability and tristability of the system caused by variations in adsorption properties of the adsorbent in competitive adsorption of gas particles on it. We derive conditions under which adsorption isotherms of a binary gas mixture have two stable asymptotes. It is shown that the specific features of the behavior of the system under study can be described in terms of a potential of the known explicit form. (paper)

Investigation of low-latitude hydrogen emission in terms of a two-component interstellar gas model

International Nuclear Information System (INIS)

Baker, P.L.; Burton, W.B.

1975-01-01

The high-resolution 21-cm hydrogen line observations at low galactic latitude of Burton and Verschuur have been analyzed to determine the large-scale distribution of galactic hydrogen. The distribution parameters are found by model fitting. Optical depth affects have been computed using a two-component gas model. Analysis shows that a multiphase description of the medium is essential to the interpretation of low-latitude emission observations. Where possible, the number of free parameters in the gas model has been reduced. Calculations were performed for a one-component, uniform spin temperature, gas model in order to show the systematic departures between this model and the data caused by the incorrect treatment of the optical depth effect. In the two-component gas, radiative transfer is treated by a Monte Carlo calculation since the opacity of the gas arises in a randomly distributed, cold, optically thick, low velocity-dispersion, cloud medium. The emission arises in both the cloud medium and a smoothly distributed, optically thin, high velocity-dispersion, intercloud medium. The synthetic profiles computed from the two-component model reproduce both the large-scale trends of the observed emission profiles and the magnitude of the small-scale emission irregularities. The analysis permits the determination of values for []he thickness of the galactic disk between half density points, the total observed neutral hydrogen mass of the Galaxy, and the central number density of the intercloud atoms. In addition, the analysis is sensitive to the size of clouds contributing to the observations. Computations also show that synthetic emission profiles based on the two-component model display both the zero-velocity and high-velocity ridges, indicative of optical thinness on a large scale, in spite of the presence of optically thick gas

A numerical study of blood flow using mixture theory

OpenAIRE

Wu, Wei-Tao; Aubry, Nadine; Massoudi, Mehrdad; Kim, Jeongho; Antaki, James F.

2014-01-01

In this paper, we consider the two dimensional flow of blood in a rectangular microfluidic channel. We use Mixture Theory to treat this problem as a two-component system: One component is the red blood cells (RBCs) modeled as a generalized Reiner–Rivlin type fluid, which considers the effects of volume fraction (hematocrit) and influence of shear rate upon viscosity. The other component, plasma, is assumed to behave as a linear viscous fluid. A CFD solver based on OpenFOAM® was developed and ...

New models for predicting thermophysical properties of ionic liquid mixtures.

Science.gov (United States)

Huang, Ying; Zhang, Xiangping; Zhao, Yongsheng; Zeng, Shaojuan; Dong, Haifeng; Zhang, Suojiang

2015-10-28

Potential applications of ILs require the knowledge of the physicochemical properties of ionic liquid (IL) mixtures. In this work, a series of semi-empirical models were developed to predict the density, surface tension, heat capacity and thermal conductivity of IL mixtures. Each semi-empirical model only contains one new characteristic parameter, which can be determined using one experimental data point. In addition, as another effective tool, artificial neural network (ANN) models were also established. The two kinds of models were verified by a total of 2304 experimental data points for binary mixtures of ILs and molecular compounds. The overall average absolute deviations (AARDs) of both the semi-empirical and ANN models are less than 2%. Compared to previously reported models, these new semi-empirical models require fewer adjustable parameters and can be applied in a wider range of applications.

Semiparametric accelerated failure time cure rate mixture models with competing risks.

Science.gov (United States)

Choi, Sangbum; Zhu, Liang; Huang, Xuelin

2018-01-15

Modern medical treatments have substantially improved survival rates for many chronic diseases and have generated considerable interest in developing cure fraction models for survival data with a non-ignorable cured proportion. Statistical analysis of such data may be further complicated by competing risks that involve multiple types of endpoints. Regression analysis of competing risks is typically undertaken via a proportional hazards model adapted on cause-specific hazard or subdistribution hazard. In this article, we propose an alternative approach that treats competing events as distinct outcomes in a mixture. We consider semiparametric accelerated failure time models for the cause-conditional survival function that are combined through a multinomial logistic model within the cure-mixture modeling framework. The cure-mixture approach to competing risks provides a means to determine the overall effect of a treatment and insights into how this treatment modifies the components of the mixture in the presence of a cure fraction. The regression and nonparametric parameters are estimated by a nonparametric kernel-based maximum likelihood estimation method. Variance estimation is achieved through resampling methods for the kernel-smoothed likelihood function. Simulation studies show that the procedures work well in practical settings. Application to a sarcoma study demonstrates the use of the proposed method for competing risk data with a cure fraction. Copyright © 2017 John Wiley & Sons, Ltd.

Thermodynamically consistent modeling and simulation of multi-component two-phase flow model with partial miscibility

KAUST Repository

Kou, Jisheng; Sun, Shuyu

2016-01-01

A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is a latest

Two component WIMP-FImP dark matter model with singlet fermion, scalar and pseudo scalar

Energy Technology Data Exchange (ETDEWEB)

Dutta Banik, Amit; Pandey, Madhurima; Majumdar, Debasish [Saha Institute of Nuclear Physics, HBNI, Astroparticle Physics and Cosmology Division, Kolkata (India); Biswas, Anirban [Harish Chandra Research Institute, Allahabad (India)

2017-10-15

We explore a two component dark matter model with a fermion and a scalar. In this scenario the Standard Model (SM) is extended by a fermion, a scalar and an additional pseudo scalar. The fermionic component is assumed to have a global U(1){sub DM} and interacts with the pseudo scalar via Yukawa interaction while a Z{sub 2} symmetry is imposed on the other component - the scalar. These ensure the stability of both dark matter components. Although the Lagrangian of the present model is CP conserving, the CP symmetry breaks spontaneously when the pseudo scalar acquires a vacuum expectation value (VEV). The scalar component of the dark matter in the present model also develops a VEV on spontaneous breaking of the Z{sub 2} symmetry. Thus the various interactions of the dark sector and the SM sector occur through the mixing of the SM like Higgs boson, the pseudo scalar Higgs like boson and the singlet scalar boson. We show that the observed gamma ray excess from the Galactic Centre as well as the 3.55 keV X-ray line from Perseus, Andromeda etc. can be simultaneously explained in the present two component dark matter model and the dark matter self interaction is found to be an order of magnitude smaller than the upper limit estimated from the observational results. (orig.)

Mixture Modeling: Applications in Educational Psychology

Science.gov (United States)

Harring, Jeffrey R.; Hodis, Flaviu A.

2016-01-01

Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are…

Modeling of non-additive mixture properties using the Online CHEmical database and Modeling environment (OCHEM

Directory of Open Access Journals (Sweden)

Oprisiu Ioana

2013-01-01

Full Text Available Abstract The Online Chemical Modeling Environment (OCHEM, http://ochem.eu is a web-based platform that provides tools for automation of typical steps necessary to create a predictive QSAR/QSPR model. The platform consists of two major subsystems: a database of experimental measurements and a modeling framework. So far, OCHEM has been limited to the processing of individual compounds. In this work, we extended OCHEM with a new ability to store and model properties of binary non-additive mixtures. The developed system is publicly accessible, meaning that any user on the Web can store new data for binary mixtures and develop models to predict their non-additive properties. The database already contains almost 10,000 data points for the density, bubble point, and azeotropic behavior of binary mixtures. For these data, we developed models for both qualitative (azeotrope/zeotrope and quantitative endpoints (density and bubble points using different learning methods and specially developed descriptors for mixtures. The prediction performance of the models was similar to or more accurate than results reported in previous studies. Thus, we have developed and made publicly available a powerful system for modeling mixtures of chemical compounds on the Web.

Direct Importance Estimation with Gaussian Mixture Models

Science.gov (United States)

Yamada, Makoto; Sugiyama, Masashi

The ratio of two probability densities is called the importance and its estimation has gathered a great deal of attention these days since the importance can be used for various data processing purposes. In this paper, we propose a new importance estimation method using Gaussian mixture models (GMMs). Our method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an expectation-maximization procedure, so the proposed method — which we call the Gaussian mixture KLIEP (GM-KLIEP) — is expected to work well when the true importance function has high correlation. Through experiments, we show the validity of the proposed approach.

Reliability analysis of nuclear component cooling water system using semi-Markov process model

International Nuclear Information System (INIS)

Veeramany, Arun; Pandey, Mahesh D.

2011-01-01

Research highlights: → Semi-Markov process (SMP) model is used to evaluate system failure probability of the nuclear component cooling water (NCCW) system. → SMP is used because it can solve reliability block diagram with a mixture of redundant repairable and non-repairable components. → The primary objective is to demonstrate that SMP can consider Weibull failure time distribution for components while a Markov model cannot → Result: the variability in component failure time is directly proportional to the NCCW system failure probability. → The result can be utilized as an initiating event probability in probabilistic safety assessment projects. - Abstract: A reliability analysis of nuclear component cooling water (NCCW) system is carried out. Semi-Markov process model is used in the analysis because it has potential to solve a reliability block diagram with a mixture of repairable and non-repairable components. With Markov models it is only possible to assume an exponential profile for component failure times. An advantage of the proposed model is the ability to assume Weibull distribution for the failure time of components. In an attempt to reduce the number of states in the model, it is shown that usage of poly-Weibull distribution arises. The objective of the paper is to determine system failure probability under these assumptions. Monte Carlo simulation is used to validate the model result. This result can be utilized as an initiating event probability in probabilistic safety assessment projects.

Generalized renewal process for repairable systems based on finite Weibull mixture

International Nuclear Information System (INIS)

Veber, B.; Nagode, M.; Fajdiga, M.

2008-01-01

Repairable systems can be brought to one of possible states following a repair. These states are: 'as good as new', 'as bad as old' and 'better than old but worse than new'. The probabilistic models traditionally used to estimate the expected number of failures account for the first two states, but they do not properly apply to the last one, which is more realistic in practice. In this paper, a probabilistic model that is applicable to all of the three after-repair states, called generalized renewal process (GRP), is applied. Simplistically, GRP addresses the repair assumption by introducing the concept of virtual age into the stochastic point processes to enable them to represent the full spectrum of repair assumptions. The shape of measured or design life distributions of systems can vary considerably, and therefore frequently cannot be approximated by simple distribution functions. The scope of the paper is to prove that a finite Weibull mixture, with positive component weights only, can be used as underlying distribution of the time to first failure (TTFF) of the GRP model, on condition that the unknown parameters can be estimated. To support the main idea, three examples are presented. In order to estimate the unknown parameters of the GRP model with m-fold Weibull mixture, the EM algorithm is applied. The GRP model with m mixture components distributions is compared to the standard GRP model based on two-parameter Weibull distribution by calculating the expected number of failures. It can be concluded that the suggested GRP model with Weibull mixture with an arbitrary but finite number of components is suitable for predicting failures based on the past performance of the system

Personal Exposure to Mixtures of Volatile Organic Compounds: Modeling and Further Analysis of the RIOPA Data

Science.gov (United States)

Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong

2015-01-01

semi-parametric Dirichlet process mixture (DPM) of normal distributions for three individual VOCs (chloroform, 1,4-DCB, and styrene). Goodness of fit for these full distribution models was also evaluated using simulated data. Specific Aim 2 Mixtures in the RIOPA VOC data set were identified using positive matrix factorization (PMF) and by toxicologic mode of action. Dependency structures of a mixture’s components were examined using mixture fractions and were modeled using copulas, which address correlations of multiple components across their entire distributions. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) were evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks were calculated for mixtures, and results from copulas and multivariate lognormal models were compared with risks based on RIOPA observations. Specific Aim 3 Exposure determinants were identified using stepwise regressions and linear mixed-effects models (LMMs). RESULTS Specific Aim 1 Extreme value exposures in RIOPA typically were best fitted by three-parameter generalized extreme value (GEV) distributions, and sometimes by the two-parameter Gumbel distribution. In contrast, lognormal distributions significantly underestimated both the level and likelihood of extreme values. Among the VOCs measured in RIOPA, 1,4-dichlorobenzene (1,4-DCB) was associated with the greatest cancer risks; for example, for the highest 10% of measurements of 1,4-DCB, all individuals had risk levels above 10−4, and 13% of all participants had risk levels above 10−2. Of the full-distribution models, the finite mixture of normal distributions with two to four clusters and the DPM of normal distributions had superior performance in comparison with the lognormal models. DPM distributions provided slightly better fit than the finite mixture distributions; the advantages of the DPM model were avoiding certain convergence issues associated

Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA data.

Science.gov (United States)

Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong

2014-06-01

-parametric Dirichlet process mixture (DPM) of normal distributions for three individual VOCs (chloroform, 1,4-DCB, and styrene). Goodness of fit for these full distribution models was also evaluated using simulated data. Specific Aim 2. Mixtures in the RIOPA VOC data set were identified using positive matrix factorization (PMF) and by toxicologic mode of action. Dependency structures of a mixture's components were examined using mixture fractions and were modeled using copulas, which address correlations of multiple components across their entire distributions. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) were evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks were calculated for mixtures, and results from copulas and multivariate lognormal models were compared with risks based on RIOPA observations. Specific Aim 3. Exposure determinants were identified using stepwise regressions and linear mixed-effects models (LMMs). Specific Aim 1. Extreme value exposures in RIOPA typically were best fitted by three-parameter generalized extreme value (GEV) distributions, and sometimes by the two-parameter Gumbel distribution. In contrast, lognormal distributions significantly underestimated both the level and likelihood of extreme values. Among the VOCs measured in RIOPA, 1,4-dichlorobenzene (1,4-DCB) was associated with the greatest cancer risks; for example, for the highest 10% of measurements of 1,4-DCB, all individuals had risk levels above 10(-4), and 13% of all participants had risk levels above 10(-2). Of the full-distribution models, the finite mixture of normal distributions with two to four clusters and the DPM of normal distributions had superior performance in comparison with the lognormal models. DPM distributions provided slightly better fit than the finite mixture distributions; the advantages of the DPM model were avoiding certain convergence issues associated with the finite mixture

Correlation inequalities for two-component hypercubic /varreverse arrowphi/4 models

International Nuclear Information System (INIS)

Soria, J.L.

1988-01-01

A collection of new and already known correlation inequalities is found for a family of two-component hypercubic /varreverse arrowphi/ 4 models, using techniques of duplicated variables, rotated correlation inequalities, and random walk representation. Among the interesting new inequalities are: rotated very special Dunlop-Newman inequality 2 ; /varreverse arrowphi//sub 1z/ 2 + /varreverse arrowphi//sub 2z/ 2 ≥ 0, rotated Griffiths I inequality 2 - /varreverse arrowphi//sub 2z/ 2 > ≥ 0, and anti-Lebowitz inequality u 4 1111 ≥ 0

Exploring a minimal two-component p53 model

International Nuclear Information System (INIS)

Sun, Tingzhe; Zhu, Feng; Shen, Pingping; Yuan, Ruoshi; Xu, Wei

2010-01-01

The tumor suppressor p53 coordinates many attributes of cellular processes via interlocked feedback loops. To understand the biological implications of feedback loops in a p53 system, a two-component model which encompasses essential feedback loops was constructed and further explored. Diverse bifurcation properties, such as bistability and oscillation, emerge by manipulating the feedback strength. The p53-mediated MDM2 induction dictates the bifurcation patterns. We first identified irradiation dichotomy in p53 models and further proposed that bistability and oscillation can behave in a coordinated manner. Further sensitivity analysis revealed that p53 basal production and MDM2-mediated p53 degradation, which are central to cellular control, are most sensitive processes. Also, we identified that the much more significant variations in amplitude of p53 pulses observed in experiments can be derived from overall amplitude parameter sensitivity. The combined approach with bifurcation analysis, stochastic simulation and sampling-based sensitivity analysis not only gives crucial insights into the dynamics of the p53 system, but also creates a fertile ground for understanding the regulatory patterns of other biological networks

Scaling and crossover in a fermion-boson mixture

International Nuclear Information System (INIS)

Singh, K.K.

1987-01-01

Thermodynamic behaviour of a mixture of weakly interacting fermions and bosons is investigated in (4 - ε) dimensions by the renormalization group method with a view to study scaling and crossover properties of the system in the tricritical region. Conventional tricritical scaling, first found to breakdown for a classical infinite-component model, is seen to do so more spectacularly in the case of the mixture. Whereas in the infinite-component model, conventional scaling holds in the ordered and disordered phases separately (i.e. with different tricritical exponents), no such thing is possible in either of the phases of the mixture. The breakdown of scaling in the mixture is associated with the dimensionless strength v 6 of the 6-point interaction in the effective Hamiltonian which causes the parameters of the renormalized Hamiltonian to depend on two combinations of scaling fields rather than one. The strength v 6 is a quantum mechanical parameter being proportional in 3 dimensions to (b 3 /λ T 4 K F ) where λ T , K F and b denote, respectively, the boson thermal wavelength, the Fermi momentum of the fermion component and the scattering length associated with the fermion-boson interaction. The square root of this quantity agrees with the non-universality parameter which was found to characterize tricritical amplitude ratios in 3 dimensions in an earlier work. (author). 19 refs, 8 figs

On-line component ratio measurement of oil/gas/water mixtures using an admittance sensor

Energy Technology Data Exchange (ETDEWEB)

Andersen, J A

1984-01-01

The operator of a production platform is primarily interested in which types of fluids a well is producing and how quickly these different components are being produced. The component ratio and production rate of a well vary during the life of a field. To optimize production, measurement of each well's output is thus desirable. Current designs for subsea production systems lack means of continuously measuring three-component flows. A new method of component ratio measurement is described. The fraction of oil, gas and water flowing between two insulated electrode plates is determined by measuring both the electrical conductance and suseptance across the sensor. A preliminary evaluation of the new measurement system has been performed using a process oil/ water/air mixture. The method is not limited to small pipe diameters. The only possible limitation is that for low velocities in very large pipe diameters an in-line mixer may be required. Advantages of this new system are that real-time measurement of void fraction and water content is possible if a non-intrusive rugged sensor is used, and there are no range limitations, as each component may be measured for any given concentration. 4 references.

Theory of synergistic effects: Hill-type response surfaces as 'null-interaction' models for mixtures.

Science.gov (United States)

Schindler, Michael

2017-08-02

The classification of effects caused by mixtures of agents as synergistic, antagonistic or additive depends critically on the reference model of 'null interaction'. Two main approaches are currently in use, the Additive Dose (ADM) or concentration addition (CA) and the Multiplicative Survival (MSM) or independent action (IA) models. We compare several response surface models to a newly developed Hill response surface, obtained by solving a logistic partial differential equation (PDE). Assuming that a mixture of chemicals with individual Hill-type dose-response curves can be described by an n-dimensional logistic function, Hill's differential equation for pure agents is replaced by a PDE for mixtures whose solution provides Hill surfaces as 'null-interaction' models and relies neither on Bliss independence or Loewe additivity nor uses Chou's unified general theory. An n-dimensional logistic PDE decribing the Hill-type response of n-component mixtures is solved. Appropriate boundary conditions ensure the correct asymptotic behaviour. Mathematica 11 (Wolfram, Mathematica Version 11.0, 2016) is used for the mathematics and graphics presented in this article. The Hill response surface ansatz can be applied to mixtures of compounds with arbitrary Hill parameters. Restrictions which are required when deriving analytical expressions for response surfaces from other principles, are unnecessary. Many approaches based on Loewe additivity turn out be special cases of the Hill approach whose increased flexibility permits a better description of 'null-effect' responses. Missing sham-compliance of Bliss IA, known as Colby's model in agrochemistry, leads to incompatibility with the Hill surface ansatz. Examples of binary and ternary mixtures illustrate the differences between the approaches. For Hill-slopes close to one and doses below the half-maximum effect doses MSM (Colby, Bliss, Finney, Abbott) predicts synergistic effects where the Hill model indicates 'null

Dynamic mean field theory for lattice gas models of fluid mixtures confined in mesoporous materials.

Science.gov (United States)

Edison, J R; Monson, P A

2013-11-12

We present the extension of dynamic mean field theory (DMFT) for fluids in porous materials (Monson, P. A. J. Chem. Phys. 2008, 128, 084701) to the case of mixtures. The theory can be used to describe the relaxation processes in the approach to equilibrium or metastable equilibrium states for fluids in pores after a change in the bulk pressure or composition. It is especially useful for studying systems where there are capillary condensation or evaporation transitions. Nucleation processes associated with these transitions are emergent features of the theory and can be visualized via the time dependence of the density distribution and composition distribution in the system. For mixtures an important component of the dynamics is relaxation of the composition distribution in the system, especially in the neighborhood of vapor-liquid interfaces. We consider two different types of mixtures, modeling hydrocarbon adsorption in carbon-like slit pores. We first present results on bulk phase equilibria of the mixtures and then the equilibrium (stable/metastable) behavior of these mixtures in a finite slit pore and an inkbottle pore. We then use DMFT to describe the evolution of the density and composition in the pore in the approach to equilibrium after changing the state of the bulk fluid via composition or pressure changes.

Robust non-rigid point set registration using student's-t mixture model.

Directory of Open Access Journals (Sweden)

Zhiyong Zhou

Full Text Available The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat one point set as Student's-t mixture model centroids. Then, we fit the Student's-t mixture model centroids to the other point set which is treated as data. Finally, we get the closed-form solutions of registration parameters, leading to a computationally efficient registration algorithm. The proposed algorithm is especially effective for addressing the non-rigid point set registration problem when significant amounts of noise and outliers are present. Moreover, less registration parameters have to be set manually for our algorithm compared to the popular coherent points drift (CPD algorithm. We have compared our algorithm with other state-of-the-art registration algorithms on both 2D and 3D data with noise and outliers, where our non-rigid registration algorithm showed accurate results and outperformed the other algorithms.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

Science.gov (United States)

Kou, Jisheng; Sun, Shuyu

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng

2016-05-10

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

PCA: Principal Component Analysis for spectra modeling

Science.gov (United States)

Hurley, Peter D.; Oliver, Seb; Farrah, Duncan; Wang, Lingyu; Efstathiou, Andreas

2012-07-01

The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components. This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.

Theory and simulations for hard-disk models of binary mixtures of molecules with internal degrees of freedom

DEFF Research Database (Denmark)

Fraser, Diane P.; Zuckermann, Martin J.; Mouritsen, Ole G.

1991-01-01

A two-dimensional Monte Carlo simulation method based on the NpT ensemble and the Voronoi tesselation, which was previously developed for single-species hard-disk systems, is extended, along with a version of scaled-particle theory, to many-component mixtures. These systems are unusual in the sense...... and internal degrees of freedom leads to a rich phase structure that includes solid-liquid transitions (governed by the translational variables) as well as transitions involving changes in average disk size (governed by the internal variables). The relationship between these two types of transitions is studied...... by the method in the case of a binary mixture, and results are presented for varying disk-size ratios and degeneracies. The results are also compared with the predictions of the extended scaled-particle theory. Applications of the model are discussed in relation to lipid monolayers spread on air...

Determination of two-dimensional correlation lengths in an anisotropic two-component flow

International Nuclear Information System (INIS)

Thomson, O.

1994-05-01

Former studies have shown that correlation methods can be used for determination of various two-component flow parameters, among these the correlation length. In cases where the flow can be described as a mixture, in which the minority component forms spatially limited perturbations within the majority component, this parameter gives a good indication of the maximum extension of these perturbations. In the former studies, spherical symmetry of the perturbations has been assumed, and the correlation length has been measured in the direction of the flow (axially) only. However, if the flow structure is anisotropic, the correlation length will be different in different directions. In the present study, the method has been developed further, allowing also measurements perpendicular to the flow direction (radially). The measurements were carried out using laser beams and the two-component flows consisted of either glass beads and air or air and water. In order to make local measurements of both the axial and radial correlation length simultaneously, it is necessary to use 3 laser beams and to form the triple cross-covariance. This lead to some unforeseen complications, due to the character of this function. The experimental results are generally positive and size determinations with an accuracy of better than 10% have been achieved in most cases. Less accurate results appeared only for difficult conditions (symmetrical signals), when 3 beams were used. 5 refs, 13 figs, 3 tabs

Two-phase flow models

International Nuclear Information System (INIS)

Delaje, Dzh.

1984-01-01

General hypothesis used to simplify the equations, describing two-phase flows, are considered. Two-component and one-component models of two-phase flow, as well as Zuber and Findlay model for actual volumetric steam content, and Wallis model, describing the given phase rates, are presented. The conclusion is made, that the two-component model, in which values averaged in time are included, is applicable for the solving of three-dimensional tasks for unsteady two-phase flow. At the same time, using the two-component model, including values, averaged in space only one-dimensional tasks for unsteady two-phase flow can be solved

The predatory mite Phytoseiulus persimilis does not perceive odor mixtures as strictly elemental objects.

Science.gov (United States)

van Wijk, Michiel; de Bruijn, Paulien J A; Sabelis, Maurice W

2010-11-01

Phytoseiulus persimilis is a predatory mite that in absence of vision relies on the detection of herbivore-induced plant odors to locate its prey, the two-spotted spider-mite Tetranychus urticae. This herbivorous prey is feeding on leaves of a wide variety of plant species in different families. The predatory mites respond to numerous structurally different compounds. However, typical spider-mite induced plant compounds do not attract more predatory mites than plant compounds not associated with prey. Because the mites are sensitive to many compounds, components of odor mixtures may affect each other's perception. Although the response to pure compounds has been well documented, little is known how interactions among compounds affect the response to odor mixtures. We assessed the relation between the mites' responses elicited by simple mixtures of two compounds and by the single components of these mixtures. The preference for the mixture was compared to predictions under three conceptual models, each based on one of the following assumptions: (1) the responses elicited by each of the individual components can be added to each other; (2) they can be averaged; or (3) one response overshadows the other. The observed response differed significantly from the response predicted under the additive response, average response, and overshadowing response model in 52, 36, and 32% of the experimental tests, respectively. Moreover, the behavioral responses elicited by individual compounds and their binary mixtures were determined as a function of the odor concentration. The relative contribution of each component to the behavioral response elicited by the mixture varied with the odor concentration, even though the ratio of both compounds in the mixture was kept constant. Our experiments revealed that compounds that elicited no response had an effect on the response elicited by binary mixtures that they were part of. The results are not consistent with the hypothesis that P

Gaussian Process-Mixture Conditional Heteroscedasticity.

Science.gov (United States)

Platanios, Emmanouil A; Chatzis, Sotirios P

2014-05-01

Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning. Specifically, we propose a novel nonparametric Bayesian mixture of Gaussian process regression models, each component of which models the noise variance process that contaminates the observed data as a separate latent Gaussian process driven by the observed data. This way, we essentially obtain a Gaussian process-mixture conditional heteroscedasticity (GPMCH) model for volatility modeling in financial return series. We impose a nonparametric prior with power-law nature over the distribution of the model mixture components, namely the Pitman-Yor process prior, to allow for better capturing modeled data distributions with heavy tails and skewness. Finally, we provide a copula-based approach for obtaining a predictive posterior for the covariances over the asset returns modeled by means of a postulated GPMCH model. We evaluate the efficacy of our approach in a number of benchmark scenarios, and compare its performance to state-of-the-art methodologies.

Nonparametric Fine Tuning of Mixtures: Application to Non-Life Insurance Claims Distribution Estimation

Science.gov (United States)

Sardet, Laure; Patilea, Valentin

When pricing a specific insurance premium, actuary needs to evaluate the claims cost distribution for the warranty. Traditional actuarial methods use parametric specifications to model claims distribution, like lognormal, Weibull and Pareto laws. Mixtures of such distributions allow to improve the flexibility of the parametric approach and seem to be quite well-adapted to capture the skewness, the long tails as well as the unobserved heterogeneity among the claims. In this paper, instead of looking for a finely tuned mixture with many components, we choose a parsimonious mixture modeling, typically a two or three-component mixture. Next, we use the mixture cumulative distribution function (CDF) to transform data into the unit interval where we apply a beta-kernel smoothing procedure. A bandwidth rule adapted to our methodology is proposed. Finally, the beta-kernel density estimate is back-transformed to recover an estimate of the original claims density. The beta-kernel smoothing provides an automatic fine-tuning of the parsimonious mixture and thus avoids inference in more complex mixture models with many parameters. We investigate the empirical performance of the new method in the estimation of the quantiles with simulated nonnegative data and the quantiles of the individual claims distribution in a non-life insurance application.

Heat transfer from a high temperature condensable mixture

International Nuclear Information System (INIS)

Chan, S.H.; Cho, D.H.; Condiff, D.W.

1980-01-01

Bulk condensation and heat transfer in a very hot gaseous mixture that contains a vapor component condensable at high temperature are investigated. A general formulation of the problem is presented in various forms. Analytical solutions for three specific cases involving both one- and two-component two-phase mixtures are obtained. It is shown that a detached fog formation is induced by rapid radiative cooling from the mixture. The formation of radiatively induced fog is found to be an interesting and important phenomenon as it not only exhibits unique features different from the conventional diffusion induced fog, but also greatly enhances heat transfer from the mixture to the boundary. (author)

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

Energy Technology Data Exchange (ETDEWEB)

Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model

KAUST Repository

Liu, Bo

2016-02-03

An ensemble-based Gaussian mixture (GM) filtering framework is studied in this paper in term of its dependence on the choice of the clustering method to construct the GM. In this approach, a number of particles sampled from the posterior distribution are first integrated forward with the dynamical model for forecasting. A GM representation of the forecast distribution is then constructed from the forecast particles. Once an observation becomes available, the forecast GM is updated according to Bayes’ rule. This leads to (i) a Kalman filter-like update of the particles, and (ii) a Particle filter-like update of their weights, generalizing the ensemble Kalman filter update to non-Gaussian distributions. We focus on investigating the impact of the clustering strategy on the behavior of the filter. Three different clustering methods for constructing the prior GM are considered: (i) a standard kernel density estimation, (ii) clustering with a specified mixture component size, and (iii) adaptive clustering (with a variable GM size). Numerical experiments are performed using a two-dimensional reactive contaminant transport model in which the contaminant concentration and the heterogenous hydraulic conductivity fields are estimated within a confined aquifer using solute concentration data. The experimental results suggest that the performance of the GM filter is sensitive to the choice of the GM model. In particular, increasing the size of the GM does not necessarily result in improved performances. In this respect, the best results are obtained with the proposed adaptive clustering scheme.

A predictive model of natural gas mixture combustion in internal combustion engines

Directory of Open Access Journals (Sweden)

Henry Espinoza

2007-05-01

Full Text Available This study shows the development of a predictive natural gas mixture combustion model for conventional com-bustion (ignition engines. The model was based on resolving two areas; one having unburned combustion mixture and another having combustion products. Energy and matter conservation equations were solved for each crankshaft turn angle for each area. Nonlinear differential equations for each phase’s energy (considering compression, combustion and expansion were solved by applying the fourth-order Runge-Kutta method. The model also enabled studying different natural gas components’ composition and evaluating combustion in the presence of dry and humid air. Validation results are shown with experimental data, demonstrating the software’s precision and accuracy in the results so produced. The results showed cylinder pressure, unburned and burned mixture temperature, burned mass fraction and combustion reaction heat for the engine being modelled using a natural gas mixture.

Exploring the Validity Range of the Polarimetric Two-Scale Two-Component Model for Soil Moisture Retrieval by Using AGRISAR Data

Science.gov (United States)

Di Martino, Gerardo; Iodice, Antonio; Natale, Antonio; Riccio, Daniele; Ruello, Giuseppe

2015-04-01

The recently proposed polarimetric two-scale two- component model (PTSTCM) in principle allows us obtaining a reasonable estimation of the soil moisture even in moderately vegetated areas, where the volumetric scattering contribution is non-negligible, provided that the surface component is dominant and the double-bounce component is negligible. Here we test the PTSTCM validity range by applying it to polarimetric SAR data acquired on areas for which, at the same times of SAR acquisitions, ground measurements of soil moisture were performed. In particular, we employ the AGRISAR'06 database, which includes data from several fields covering a period that spans all the phases of vegetation growth.

KONVERGENSI ESTIMATOR DALAM MODEL MIXTURE BERBASIS MISSING DATA

Directory of Open Access Journals (Sweden)

N Dwidayati

2014-06-01

Full Text Available Abstrak __________________________________________________________________________________________ Model mixture dapat mengestimasi proporsi pasien yang sembuh (cured dan fungsi survival pasien tak sembuh (uncured. Pada kajian ini, model mixture dikembangkan untuk  analisis cure rate berbasis missing data. Ada beberapa metode yang dapat digunakan untuk analisis missing data. Salah satu metode yang dapat digunakan adalah Algoritma EM, Metode ini didasarkan pada 2 (dua langkah, yaitu: (1 Expectation Step dan (2 Maximization Step. Algoritma EM merupakan pendekatan iterasi untuk mempelajari model dari data dengan nilai hilang melalui 4 (empat langkah, yaitu(1 pilih himpunan inisial dari parameter untuk sebuah model, (2 tentukan nilai ekspektasi untuk data hilang, (3 buat induksi parameter model baru dari gabungan nilai ekspekstasi dan data asli, dan (4 jika parameter tidak converged, ulangi langkah 2 menggunakan model baru. Berdasar kajian yang dilakukan dapat ditunjukkan bahwa pada algoritma EM, log-likelihood untuk missing data mengalami kenaikan setelah dilakukan setiap iterasi dari algoritmanya. Dengan demikian berdasar algoritma EM, barisan likelihood konvergen jika likelihood terbatas ke bawah.   Abstract __________________________________________________________________________________________ Model mixture can estimate proportion of recovering patient  and function of patient survival do not recover. At this study, model mixture developed to analyse cure rate bases on missing data. There are some method which applicable to analyse missing data. One of method which can be applied is Algoritma EM, This method based on 2 ( two step, that is: ( 1 Expectation Step and ( 2 Maximization Step. EM Algorithm is approach of iteration to study model from data with value loses through 4 ( four step, yaitu(1 select;chooses initial gathering from parameter for a model, ( 2 determines expectation value for data to lose, ( 3 induce newfangled parameter

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

Science.gov (United States)

Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

2016-08-15

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of association models to mixtures containing alkanolamines

DEFF Research Database (Denmark)

Avlund, Ane Søgaard; Eriksen, Daniel Kunisch; Kontogeorgis, Georgios

2011-01-01

Two association models,the CPA and sPC-SAFT equations of state, are applied to binarymixtures containing alkanolamines and hydrocarbons or water. CPA is applied to mixtures of MEA and DEA, while sPC-SAFT is applied to MEA–n-heptane liquid–liquid equilibria and MEA–water vapor–liquid equilibria. T...

Improved gas mixtures for gas-filled particle detectors

Science.gov (United States)

Christophorou, L.G.; McCorkle, D.L.; Maxey, D.V.; Carter, J.G.

Improved binary and tertiary gas mixture for gas-filled particle detectors are provided. The components are chosen on the basis of the principle that the first component is one gas or mixture of two gases having a large electron scattering cross section at energies of about 0.5 eV and higher, and the second component is a gas (Ar) having a very small cross section at and below about 0.5 eV; whereby fast electrons in the gaseous mixture are slowed into the energy range of about 0.5 eV where the cross section for the mixture is small and hence the electron mean free path is large. The reduction in both the cross section and the electron energy results in an increase in the drift velocity of the electrons in the gas mixtures over that for the separate components for a range of E/P (pressure-reduced electron field) values. Several gas mixtures are provided that provide faster response in gas-filled detectors for convenient E/P ranges as compared with conventional gas mixtures.

Simultaneous biodegradation of volatile and toxic contaminant mixtures by solid–liquid two-phase partitioning bioreactors

Energy Technology Data Exchange (ETDEWEB)

Poleo, Eduardo E.; Daugulis, Andrew J., E-mail: andrew.daugulis@chee.queensu.ca

2013-06-15

Highlights: • We investigate the simultaneous biodegradation of phenol and butyl acetate. • We identify an effective polymer mixture to selectively absorb each of the substrates and decrease their initial concentration. •The polymer mixture is used to overcome the high phenol cytotoxicity and reduce the abiotic losses of butyl acetate associated with volatility. • The solid–liquid Two Phase Partitioning Bioreactor (TPPB) outperforms the liquid–liquid TPPB and the single phase systems. -- Abstract: Microbial inhibition and stripping of volatile compounds are two common problems encountered in the biotreatment of contaminated wastewaters. Both can be addressed by the addition of a hydrophobic auxiliary phase that can absorb and subsequently re-release the substrates, lowering their initial aqueous concentrations. Such systems have been described as Two Phase Partitioning Bioreactors (TPPBs). In the current work the performances of a solid–liquid TPPB, a liquid–liquid TPPB and a single phase reactor for the simultaneous degradation of butyl acetate (the volatile component) and phenol (the toxic component) have been compared. The auxiliary phase used in the solid–liquid TPPB was a 50:50 polymer mixture of styrene–butadiene rubber and Hytrel{sup ®} 8206, with high affinities for butyl acetate and phenol, respectively. The liquid–liquid TPPB employed silicone oil which has fixed physical properties, and had no capacity to absorb the toxic contaminant (phenol). Butyl acetate degradation was enhanced in both TPPBs relative to the single phase, arising from its sequestration into the auxiliary phase, thereby reducing volatilization losses. The solid–liquid TPPB additionally showed a substantial increase in the phenol degradation rate, relative to the silicone oil system, demonstrating the superiority and versatility of polymer based systems.

Investigating Individual Differences in Toddler Search with Mixture Models

Science.gov (United States)

Berthier, Neil E.; Boucher, Kelsea; Weisner, Nina

2015-01-01

Children's performance on cognitive tasks is often described in categorical terms in that a child is described as either passing or failing a test, or knowing or not knowing some concept. We used binomial mixture models to determine whether individual children could be classified as passing or failing two search tasks, the DeLoache model room…

A numerical study of blood flow using mixture theory.

Science.gov (United States)

Wu, Wei-Tao; Aubry, Nadine; Massoudi, Mehrdad; Kim, Jeongho; Antaki, James F

2014-03-01

In this paper, we consider the two dimensional flow of blood in a rectangular microfluidic channel. We use Mixture Theory to treat this problem as a two-component system: One component is the red blood cells (RBCs) modeled as a generalized Reiner-Rivlin type fluid, which considers the effects of volume fraction (hematocrit) and influence of shear rate upon viscosity. The other component, plasma, is assumed to behave as a linear viscous fluid. A CFD solver based on OpenFOAM ® was developed and employed to simulate a specific problem, namely blood flow in a two dimensional micro-channel, is studied. Finally to better understand this two-component flow system and the effects of the different parameters, the equations are made dimensionless and a parametric study is performed.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng; Sun, Shuyu

2016-01-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic

Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising.

Science.gov (United States)

Mina, Faten; Attina, Virginie; Duroc, Yvan; Veuillet, Evelyne; Truy, Eric; Thai-Van, Hung

2017-01-01

Auditory steady state responses (ASSRs) in cochlear implant (CI) patients are contaminated by the spread of a continuous CI electrical stimulation artifact. The aim of this work was to model the electrophysiological mixture of the CI artifact and the corresponding evoked potentials on scalp electrodes in order to evaluate the performance of denoising algorithms in eliminating the CI artifact in a controlled environment. The basis of the proposed computational framework is a neural mass model representing the nodes of the auditory pathways. Six main contributors to auditory evoked potentials from the cochlear level and up to the auditory cortex were taken into consideration. The simulated dynamics were then projected into a 3-layer realistic head model. 32-channel scalp recordings of the CI artifact-response were then generated by solving the electromagnetic forward problem. As an application, the framework's simulated 32-channel datasets were used to compare the performance of 4 commonly used Independent Component Analysis (ICA) algorithms: infomax, extended infomax, jade and fastICA in eliminating the CI artifact. As expected, two major components were detectable in the simulated datasets, a low frequency component at the modulation frequency and a pulsatile high frequency component related to the stimulation frequency. The first can be attributed to the phase-locked ASSR and the second to the stimulation artifact. Among the ICA algorithms tested, simulations showed that infomax was the most efficient and reliable in denoising the CI artifact-response mixture. Denoising algorithms can induce undesirable deformation of the signal of interest in real CI patient recordings. The proposed framework is a valuable tool for evaluating these algorithms in a controllable environment ahead of experimental or clinical applications.

Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising.

Directory of Open Access Journals (Sweden)

Faten Mina

Full Text Available Auditory steady state responses (ASSRs in cochlear implant (CI patients are contaminated by the spread of a continuous CI electrical stimulation artifact. The aim of this work was to model the electrophysiological mixture of the CI artifact and the corresponding evoked potentials on scalp electrodes in order to evaluate the performance of denoising algorithms in eliminating the CI artifact in a controlled environment. The basis of the proposed computational framework is a neural mass model representing the nodes of the auditory pathways. Six main contributors to auditory evoked potentials from the cochlear level and up to the auditory cortex were taken into consideration. The simulated dynamics were then projected into a 3-layer realistic head model. 32-channel scalp recordings of the CI artifact-response were then generated by solving the electromagnetic forward problem. As an application, the framework's simulated 32-channel datasets were used to compare the performance of 4 commonly used Independent Component Analysis (ICA algorithms: infomax, extended infomax, jade and fastICA in eliminating the CI artifact. As expected, two major components were detectable in the simulated datasets, a low frequency component at the modulation frequency and a pulsatile high frequency component related to the stimulation frequency. The first can be attributed to the phase-locked ASSR and the second to the stimulation artifact. Among the ICA algorithms tested, simulations showed that infomax was the most efficient and reliable in denoising the CI artifact-response mixture. Denoising algorithms can induce undesirable deformation of the signal of interest in real CI patient recordings. The proposed framework is a valuable tool for evaluating these algorithms in a controllable environment ahead of experimental or clinical applications.

The impact of covariance misspecification in multivariate Gaussian mixtures on estimation and inference: an application to longitudinal modeling.

Science.gov (United States)

Heggeseth, Brianna C; Jewell, Nicholas P

2013-07-20

Multivariate Gaussian mixtures are a class of models that provide a flexible parametric approach for the representation of heterogeneous multivariate outcomes. When the outcome is a vector of repeated measurements taken on the same subject, there is often inherent dependence between observations. However, a common covariance assumption is conditional independence-that is, given the mixture component label, the outcomes for subjects are independent. In this paper, we study, through asymptotic bias calculations and simulation, the impact of covariance misspecification in multivariate Gaussian mixtures. Although maximum likelihood estimators of regression and mixing probability parameters are not consistent under misspecification, they have little asymptotic bias when mixture components are well separated or if the assumed correlation is close to the truth even when the covariance is misspecified. We also present a robust standard error estimator and show that it outperforms conventional estimators in simulations and can indicate that the model is misspecified. Body mass index data from a national longitudinal study are used to demonstrate the effects of misspecification on potential inferences made in practice. Copyright © 2013 John Wiley & Sons, Ltd.

Effect of a mixture of caffeine and nicotinamide on the solubility of vitamin (B2) in aqueous solution.

Science.gov (United States)

Evstigneev, M P; Evstigneev, V P; Santiago, A A Hernandez; Davies, D B

2006-05-01

The effect of caffeine (CAF) and nicotinamide (NMD) on the solubility of a vitamin B2 derivative (FMN) has been evaluated for mixtures containing either a single hydrotrope (CAF or NMD) or the two hydrotropes simultaneously. A model for analysis of ternary systems, which takes into account all possible complexes between the molecules, has been developed and tested with experimental NMR data on the three-component mixture FMN-CAF-NMD. The results indicate that special attention should be given to the concentration of a hydrotropic agent used to enhance the solubility of a particular drug. A decrease in the efficacy of solubility of the vitamin on addition of large amounts of hydrotropic agent is expected in the two-component systems due to the increased proportion of self-association of the hydrotrope. It is found that a mixture of two hydrotropic agents leads to an increase in the solubility of the vitamin in three-component compared to the two-component system. Rather than using just one hydrotropic agent, it is proposed that a strategy for optimising the solubility of aromatic drugs is to use a mixture of hydrotropic agents.

Quantum particle-number fluctuations in a two-component Bose gas in a double-well potential

International Nuclear Information System (INIS)

Zin, Pawel; Oles, Bartlomiej; Sacha, Krzysztof

2011-01-01

A two-component Bose gas in a double-well potential with repulsive interactions may undergo a phase separation transition if the interspecies interactions outweigh the intraspecies ones. We analyze the transition in the strong interaction limit within the two-mode approximation. Numbers of particles in each potential well are equal and constant. However, at the transition point, the ground state of the system reveals huge fluctuations of numbers of particles belonging to the different gas components; that is, the probability for observation of any mixture of particles in each potential well becomes uniform.

A numerical model for boiling heat transfer coefficient of zeotropic mixtures

Science.gov (United States)

Barraza Vicencio, Rodrigo; Caviedes Aedo, Eduardo

2017-12-01

Zeotropic mixtures never have the same liquid and vapor composition in the liquid-vapor equilibrium. Also, the bubble and the dew point are separated; this gap is called glide temperature (Tglide). Those characteristics have made these mixtures suitable for cryogenics Joule-Thomson (JT) refrigeration cycles. Zeotropic mixtures as working fluid in JT cycles improve their performance in an order of magnitude. Optimization of JT cycles have earned substantial importance for cryogenics applications (e.g, gas liquefaction, cryosurgery probes, cooling of infrared sensors, cryopreservation, and biomedical samples). Heat exchangers design on those cycles is a critical point; consequently, heat transfer coefficient and pressure drop of two-phase zeotropic mixtures are relevant. In this work, it will be applied a methodology in order to calculate the local convective heat transfer coefficients based on the law of the wall approach for turbulent flows. The flow and heat transfer characteristics of zeotropic mixtures in a heated horizontal tube are investigated numerically. The temperature profile and heat transfer coefficient for zeotropic mixtures of different bulk compositions are analysed. The numerical model has been developed and locally applied in a fully developed, constant temperature wall, and two-phase annular flow in a duct. Numerical results have been obtained using this model taking into account continuity, momentum, and energy equations. Local heat transfer coefficient results are compared with available experimental data published by Barraza et al. (2016), and they have shown good agreement.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

International Nuclear Information System (INIS)

Teng, S.; Tebby, C.; Barcellini-Couget, S.; De Sousa, G.; Brochot, C.; Rahmani, R.; Pery, A.R.R.

2016-01-01

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

Energy Technology Data Exchange (ETDEWEB)

Teng, S.; Tebby, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Barcellini-Couget, S. [ODESIA Neosciences, Sophia Antipolis, 400 route des chappes, 06903 Sophia Antipolis (France); De Sousa, G. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Brochot, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Rahmani, R. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Pery, A.R.R., E-mail: alexandre.pery@agroparistech.fr [AgroParisTech, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France); INRA, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France)

2016-08-15

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

Directory of Open Access Journals (Sweden)

Hiekata Takashi

2006-01-01

Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.

XeBr excilamp based on a non-toxic component mixture

Energy Technology Data Exchange (ETDEWEB)

Kelman, V A; Shpenik, Yu O; Zhmenyak, Yu V, E-mail: mironkle@rambler.ru [Institute of Electron Physics, National Academy of Sciences of Ukraine, Universitetska 21, 88017 Uzhgorod (Ukraine)

2011-06-29

This paper presents the results of experimental studies on obtaining UV luminescence of XeBr* molecules at the excitation of a non-toxic Xe-CsBr gas-vapour mixture by a longitudinal pulse-periodic discharge. Effective UV emission yield of the exciplex XeBr* molecules (spectral maximum at 282 nm) is observed within a wide range of excitation conditions. The spectral distribution in the UV emission under the optimal excitation conditions does not differ essentially from that in other XeBr excilamps based on toxic components. The emission of the B {yields} X band of the XeBr* molecules provides the main contribution to the total power of the discharge UV emission. The determined average power of the UV emission for the experimental discharge tube is 12 W at an efficiency of 1%. Spectral, power-related and time-dependent parameters of the laboratory excilamp are presented for a wide range of excitation parameters. A new mechanism of exciplex molecule formation at the excitation of a rare gas/alkali halide vapour mixture is discussed.

XeBr excilamp based on a non-toxic component mixture

International Nuclear Information System (INIS)

Kelman, V A; Shpenik, Yu O; Zhmenyak, Yu V

2011-01-01

This paper presents the results of experimental studies on obtaining UV luminescence of XeBr* molecules at the excitation of a non-toxic Xe-CsBr gas-vapour mixture by a longitudinal pulse-periodic discharge. Effective UV emission yield of the exciplex XeBr* molecules (spectral maximum at 282 nm) is observed within a wide range of excitation conditions. The spectral distribution in the UV emission under the optimal excitation conditions does not differ essentially from that in other XeBr excilamps based on toxic components. The emission of the B → X band of the XeBr* molecules provides the main contribution to the total power of the discharge UV emission. The determined average power of the UV emission for the experimental discharge tube is 12 W at an efficiency of 1%. Spectral, power-related and time-dependent parameters of the laboratory excilamp are presented for a wide range of excitation parameters. A new mechanism of exciplex molecule formation at the excitation of a rare gas/alkali halide vapour mixture is discussed.

Mathematical modeling and the two-phase constitutive equations

International Nuclear Information System (INIS)

Boure, J.A.

1975-01-01

The problems raised by the mathematical modeling of two-phase flows are summarized. The models include several kinds of equations, which cannot be discussed independently, such as the balance equations and the constitutive equations. A review of the various two-phase one-dimensional models proposed to date, and of the constitutive equations they imply, is made. These models are either mixture models or two-fluid models. Due to their potentialities, the two-fluid models are discussed in more detail. To avoid contradictions, the form of the constitutive equations involved in two-fluid models must be sufficiently general. A special form of the two-fluid models, which has particular advantages, is proposed. It involves three mixture balance equations, three balance equations for slip and thermal non-equilibriums, and the necessary constitutive equations [fr

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

Science.gov (United States)

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

Thermodynamically consistent modeling and simulation of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng; Sun, Shuyu

2017-01-01

A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is an attractive

An odor interaction model of binary odorant mixtures by a partial differential equation method.

Science.gov (United States)

Yan, Luchun; Liu, Jiemin; Wang, Guihua; Wu, Chuandong

2014-07-09

A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.

Modeling Organic Contaminant Desorption from Municipal Solid Waste Components

Science.gov (United States)

Knappe, D. R.; Wu, B.; Barlaz, M. A.

2002-12-01

Approximately 25% of the sites on the National Priority List (NPL) of Superfund are municipal landfills that accepted hazardous waste. Unlined landfills typically result in groundwater contamination, and priority pollutants such as alkylbenzenes are often present. To select cost-effective risk management alternatives, better information on factors controlling the fate of hydrophobic organic contaminants (HOCs) in landfills is required. The objectives of this study were (1) to investigate the effects of HOC aging time, anaerobic sorbent decomposition, and leachate composition on HOC desorption rates, and (2) to simulate HOC desorption rates from polymers and biopolymer composites with suitable diffusion models. Experiments were conducted with individual components of municipal solid waste (MSW) including polyvinyl chloride (PVC), high-density polyethylene (HDPE), newsprint, office paper, and model food and yard waste (rabbit food). Each of the biopolymer composites (office paper, newsprint, rabbit food) was tested in both fresh and anaerobically decomposed form. To determine the effects of aging on alkylbenzene desorption rates, batch desorption tests were performed after sorbents were exposed to toluene for 30 and 250 days in flame-sealed ampules. Desorption tests showed that alkylbenzene desorption rates varied greatly among MSW components (PVC slowest, fresh rabbit food and newsprint fastest). Furthermore, desorption rates decreased as aging time increased. A single-parameter polymer diffusion model successfully described PVC and HDPE desorption data, but it failed to simulate desorption rate data for biopolymer composites. For biopolymer composites, a three-parameter biphasic polymer diffusion model was employed, which successfully simulated both the initial rapid and the subsequent slow desorption of toluene. Toluene desorption rates from MSW mixtures were predicted for typical MSW compositions in the years 1960 and 1997. For the older MSW mixture, which had a

Two subgroups of antipsychotic-naive, first-episode schizophrenia patients identified with a Gaussian mixture model on cognition and electrophysiology

DEFF Research Database (Denmark)

Bak, N.; Ebdrup, B.H.; Oranje, B

2017-01-01

Deficits in information processing and cognition are among the most robust findings in schizophrenia patients. Previous efforts to translate group-level deficits into clinically relevant and individualized information have, however, been non-successful, which is possibly explained by biologically...... and sixty-five healthy controls underwent extensive electrophysiological and neurocognitive test batteries. Patients were assessed on the Positive and Negative Syndrome Scale (PANSS) before and after 6 weeks of monotherapy with the relatively selective D2 receptor antagonist, amisulpride (280.3±159 mg per...... day). A reduced principal component space based on 19 electrophysiological variables and 26 cognitive variables was used as input for a Gaussian mixture model to identify subgroups of patients. With support vector machines, we explored the relation between PANSS subscores and the identified subgroups...

Investigations of an excimer laser working with a four-component gaseous mixture He-Kr:Xe-HCl

Science.gov (United States)

Iwanejko, Leszek; Pokora, Ludwik J.

1991-08-01

The paper presnts working conditions of an XCI excimer laser untypical gas mixture based on KrzXe instead of pure Xe. Such a choice was influenced by the necessity of Findin9 the way to replace imported and expensive Xe by gaseous components accesible in Poland. Determining the range of changes of laser extrnal parameters which enables its proper work with the new gas mixture was the aim of same investigations results of which are presented in this paper. The laser pulse output energy and the pulse duration as a Function of supply voltage and the mixture composition are presented. The range of proper conditions for the laser working with the new mixture He-Kr:Xe--HC1 was determined. The analysis of experimental results showed that using the new mixture ensures value of energy and pulse duration comparable with the ones obtained for the mixture He-''Xe--HCl. Spectral investigations showed the lack of influence of Kr presence in the mixture on the generation spectrum of the laser. L.

Mapping behavioral landscapes for animal movement: a finite mixture modeling approach

Science.gov (United States)

Tracey, Jeff A.; Zhu, Jun; Boydston, Erin E.; Lyren, Lisa M.; Fisher, Robert N.; Crooks, Kevin R.

2013-01-01

Because of its role in many ecological processes, movement of animals in response to landscape features is an important subject in ecology and conservation biology. In this paper, we develop models of animal movement in relation to objects or fields in a landscape. We take a finite mixture modeling approach in which the component densities are conceptually related to different choices for movement in response to a landscape feature, and the mixing proportions are related to the probability of selecting each response as a function of one or more covariates. We combine particle swarm optimization and an Expectation-Maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. We use this approach to analyze data for movement of three bobcats in relation to urban areas in southern California, USA. A behavioral interpretation of the models revealed similarities and differences in bobcat movement response to urbanization. All three bobcats avoided urbanization by moving either parallel to urban boundaries or toward less urban areas as the proportion of urban land cover in the surrounding area increased. However, one bobcat, a male with a dispersal-like large-scale movement pattern, avoided urbanization at lower densities and responded strictly by moving parallel to the urban edge. The other two bobcats, which were both residents and occupied similar geographic areas, avoided urban areas using a combination of movements parallel to the urban edge and movement toward areas of less urbanization. However, the resident female appeared to exhibit greater repulsion at lower levels of urbanization than the resident male, consistent with empirical observations of bobcats in southern California. Using the parameterized finite mixture models, we mapped behavioral states to geographic space, creating a representation of a behavioral landscape. This approach can provide guidance for conservation planning based on analysis of animal movement data using

Multi-component fiber track modelling of diffusion-weighted magnetic resonance imaging data

Directory of Open Access Journals (Sweden)

Yasser M. Kadah

2010-01-01

Full Text Available In conventional diffusion tensor imaging (DTI based on magnetic resonance data, each voxel is assumed to contain a single component having diffusion properties that can be fully represented by a single tensor. Even though this assumption can be valid in some cases, the general case involves the mixing of components, resulting in significant deviation from the single tensor model. Hence, a strategy that allows the decomposition of data based on a mixture model has the potential of enhancing the diagnostic value of DTI. This project aims to work towards the development and experimental verification of a robust method for solving the problem of multi-component modelling of diffusion tensor imaging data. The new method demonstrates significant error reduction from the single-component model while maintaining practicality for clinical applications, obtaining more accurate Fiber tracking results.

A two component model describing nucleon structure functions in the low-x region

Energy Technology Data Exchange (ETDEWEB)

Bugaev, E.V. [Institute for Nuclear Research of the Russian Academy of Sciences, 7a, 60th October Anniversary prospect, Moscow 117312 (Russian Federation); Mangazeev, B.V. [Irkutsk State University, 1, Karl Marx Street, Irkutsk 664003 (Russian Federation)

2009-12-15

A two component model describing the electromagnetic nucleon structure functions in the low-x region, based on generalized vector dominance and color dipole approaches is briefly described. The model operates with the mesons of rho-family having the mass spectrum of the form m{sub n}{sup 2}=m{sub r}ho{sup 2}(1+2n) and takes into account the nondiagonal transitions in meson-nucleon scattering. The special cut-off factors are introduced in the model, to exclude the gamma-qq-bar-V transitions in the case of narrow qq-bar-pairs. For the color dipole part of the model the well known FKS-parameterization is used.

Segregation of granular binary mixtures by a ratchet mechanism.

Science.gov (United States)

Farkas, Zénó; Szalai, Ferenc; Wolf, Dietrich E; Vicsek, Tamás

2002-02-01

We report on a segregation scheme for granular binary mixtures, where the segregation is performed by a ratchet mechanism realized by a vertically shaken asymmetric sawtooth-shaped base in a quasi-two-dimensional box. We have studied this system by computer simulations and found that most binary mixtures can be segregated using an appropriately chosen ratchet, even when the particles in the two components have the same size and differ only in their normal restitution coefficient or friction coefficient. These results suggest that the components of otherwise nonsegregating granular mixtures may be separated using our method.

A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

International Nuclear Information System (INIS)

Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

2013-01-01

Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

Space-time latent component Modeling of Geo-referenced health data

OpenAIRE

Lawson, Andrew B.; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-01-01

Latent structure models have been proposed in many applications. For space time health data it is often important to be able to find underlying trends in time which are supported by subsets of small areas. Latent structure modeling is one approach to this analysis. This paper presents a mixture-based approach that can be appied to component selction. The analysis of a Georgia ambulatory asthma county level data set is presented and a simulation-based evaluation is made.

Reduced chemical kinetic model of detonation combustion of one- and multi-fuel gaseous mixtures with air

Science.gov (United States)

Fomin, P. A.

2018-03-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one hydrocarbon fuel CnHm (for example, methane, propane, cyclohexane etc.) and (ii) multi-fuel gaseous mixtures (∑aiCniHmi) (for example, mixture of methane and propane, synthesis gas, benzene and kerosene) are presented for the first time. The models can be used for any stoichiometry, including fuel/fuels-rich mixtures, when reaction products contain molecules of carbon. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier's principle. Constants of the models have a clear physical meaning. The models can be used for calculation thermodynamic parameters of the mixture in a state of chemical equilibrium.

Mixture Design and Its Application in Cement Solidification for Spent Resin

International Nuclear Information System (INIS)

Gan, Xueying; Lin, Meiqing; Chen, Hui

1994-01-01

The study is aimed to assess the usefulness of the mixture design for spent resin immobilization in cement. Although a considerable amount of research has been carried out to determine the limits for the composition of an acceptable resin-cement mixture, no efficient experimental strategy exists that explores the full properties of waste form against composition relationship. In order to gain an overall view, this report introduces the method of mixture design and mixture analysis, and describes the design of experiment of the 5-component mixture with the constraint conditions. The mathematic models of 28-day compressive strength varying with the ingredients are fitted, and the main effect and interaction effect of two ingredients are identified quantitatively along with the graphical interpretation using the response trace plot and contour plots

Droplet size and velocity at the exit of a nozzle with two-component near critical and critical flow

International Nuclear Information System (INIS)

Lemonnier, H.; Camelo-Cavalcanti, E.S.

1993-01-01

Two-component critical flow modelling is an important issue for safety studies of various hazardous industrial activities. When the flow quality is high, the critical flow rate prediction is sensitive to the modelling of gas droplet mixture interfacial area. In order to improve the description of these flows, experiments were conducted with air-water flows in converging nozzles. The pressure was 2 and 4 bar and the gas mass quality ranged between 100% and 20%. The droplets size and velocity have been measured close to the outlet section of a nozzle with a 10 mm diameter throat. Subcritical and critical conditions were observed. These data are compared with the predictions of a critical flow model which includes an interfacial area model based on the classical ideas of Hinze and Kolmogorov. (authors). 9 figs., 12 refs

Phase Diagram in a Random Mixture of Two Antiferromagnets with Competing Spin Anisotropies. I

Science.gov (United States)

Someya, Yoshiko

1981-12-01

The phase diagram of a random mixture of two antiferromagnets with competing spin anisotropies (A1-xBx) has been analyzed by extending the theory of Matsubara and Inawashiro, and Oguchi and Ishikawa. In the model assumed, the anisotropy energies are expressed by the anisotropic exchange interactions. According to this formulation, it has been shown that the concentration dependence of TN becomes a function of \\includegraphics{dummy.eps}, where P, Q=A, B; SP is a magnitude of P-spin, and JPQη is a η component of exchange integral between P- and Q-spin). Further, the phase boundary between an AF phase and an OAF (oblique antiferromagnetic) phase at T{=}0 K has been shown to be determined by α({\\equiv}SB/SA), if \\includegraphics{dummy.eps} are given. The obtained phase diagrams for Fe1-xCoxCl2, K2Mn1-xFexF4 and Fe1-xCoxCl2\\cdot2H2O are compared with the experimental ones.

Level shift two-components autoregressive conditional heteroscedasticity modelling for WTI crude oil market

Science.gov (United States)

Sin, Kuek Jia; Cheong, Chin Wen; Hooi, Tan Siow

2017-04-01

This study aims to investigate the crude oil volatility using a two components autoregressive conditional heteroscedasticity (ARCH) model with the inclusion of abrupt jump feature. The model is able to capture abrupt jumps, news impact, clustering volatility, long persistence volatility and heavy-tailed distributed error which are commonly observed in the crude oil time series. For the empirical study, we have selected the WTI crude oil index from year 2000 to 2016. The results found that by including the multiple-abrupt jumps in ARCH model, there are significant improvements of estimation evaluations as compared with the standard ARCH models. The outcomes of this study can provide useful information for risk management and portfolio analysis in the crude oil markets.

Detecting Math Anxiety with a Mixture Partial Credit Model

Science.gov (United States)

Ölmez, Ibrahim Burak; Cohen, Allan S.

2017-01-01

The purpose of this study was to investigate a new methodology for detection of differences in middle grades students' math anxiety. A mixture partial credit model analysis revealed two distinct latent classes based on homogeneities in response patterns within each latent class. Students in Class 1 had less anxiety about apprehension of math…

Modeling text with generalizable Gaussian mixtures

DEFF Research Database (Denmark)

Hansen, Lars Kai; Sigurdsson, Sigurdur; Kolenda, Thomas

2000-01-01

We apply and discuss generalizable Gaussian mixture (GGM) models for text mining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of these models depends on the dimensionality of the representation and the sample size. We discuss...

Densities of Pure Ionic Liquids and Mixtures: Modeling and Data Analysis

DEFF Research Database (Denmark)

Abildskov, Jens; O’Connell, John P.

2015-01-01

Our two-parameter corresponding states model for liquid densities and compressibilities has been extended to more pure ionic liquids and to their mixtures with one or two solvents. A total of 19 new group contributions (5 new cations and 14 new anions) have been obtained for predicting pressure...

Use of finite mixture distribution models in the analysis of wind energy in the Canarian Archipelago

International Nuclear Information System (INIS)

Carta, Jose Antonio; Ramirez, Penelope

2007-01-01

The statistical characteristics of hourly mean wind speed data recorded at 16 weather stations located in the Canarian Archipelago are analyzed in this paper. As a result of this analysis we see that the typical two parameter Weibull wind speed distribution (W-pdf) does not accurately represent all wind regimes observed in that region. However, a Singly Truncated from below Normal Weibull mixture distribution (TNW-pdf) and a two component mixture Weibull distribution (WW-pdf) developed here do provide very good fits for both unimodal and bimodal wind speed frequency distributions observed in that region and offer less relative errors in determining the annual mean wind power density. The parameters of the distributions are estimated using the least squares method, which is resolved in this paper using the Levenberg-Marquardt algorithm. The suitability of the distributions is judged from the probability plot correlation coefficient plot R 2 , adjusted for degrees of freedom. Based on the results obtained, we conclude that the two mixture distributions proposed here provide very flexible models for wind speed studies and can be applied in a widespread manner to represent the wind regimes in the Canarian archipelago and in other regions with similar characteristics. The TNW-pdf takes into account the frequency of null winds, whereas the WW-pdf and W-pdf do not. It can, therefore, better represent wind regimes with high percentages of null wind speeds. However, calculation of the TNW-pdf is markedly slower

Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

Science.gov (United States)

Ouyang, Yicun; Yin, Hujun

2018-05-01

Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions.

Science.gov (United States)

Böhning, Dankmar; Kuhnert, Ronny

2006-12-01

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

Modeling the surface tension of complex, reactive organic-inorganic mixtures

Science.gov (United States)

Schwier, A. N.; Viglione, G. A.; Li, Z.; McNeill, V. Faye

2013-11-01

Atmospheric aerosols can contain thousands of organic compounds which impact aerosol surface tension, affecting aerosol properties such as heterogeneous reactivity, ice nucleation, and cloud droplet formation. We present new experimental data for the surface tension of complex, reactive organic-inorganic aqueous mixtures mimicking tropospheric aerosols. Each solution contained 2-6 organic compounds, including methylglyoxal, glyoxal, formaldehyde, acetaldehyde, oxalic acid, succinic acid, leucine, alanine, glycine, and serine, with and without ammonium sulfate. We test two semi-empirical surface tension models and find that most reactive, complex, aqueous organic mixtures which do not contain salt are well described by a weighted Szyszkowski-Langmuir (S-L) model which was first presented by Henning et al. (2005). Two approaches for modeling the effects of salt were tested: (1) the Tuckermann approach (an extension of the Henning model with an additional explicit salt term), and (2) a new implicit method proposed here which employs experimental surface tension data obtained for each organic species in the presence of salt used with the Henning model. We recommend the use of method (2) for surface tension modeling of aerosol systems because the Henning model (using data obtained from organic-inorganic systems) and Tuckermann approach provide similar modeling results and goodness-of-fit (χ2) values, yet the Henning model is a simpler and more physical approach to modeling the effects of salt, requiring less empirically determined parameters.

Experimental and predicted refractive index properties in ternary mixtures of associated liquids

International Nuclear Information System (INIS)

Sechenyh, Vitaliy V.; Legros, Jean-Claude; Shevtsova, Valentina

2011-01-01

Highlights: → Measurements of refractive indices of 200 different aqueous ternary mixtures have been performed for two wave lengths. → Refractive indices of the associated ternary mixtures can be modeled with a relative error of about 0.9. → Difference between experimental and calculated derivatives of refractive index with concentration is unsatisfactory large. - Abstract: Refractive indices of ternary mixtures formed by (water + ethanol + k-ethylene glycol) (when k is mono, di or tri) and (water + t-butanol + dimethyl sulfoxide) are presented over a wide range of mixture compositions. All measurements have been conducted at 298.15 K and atmospheric pressure using two light sources: one in the visible (λ = 670 nm) and the other in the infrared (λ = 925 nm) spectrum. The performance of several mixing rules that are commonly used in modeling optical constants are examined. We demonstrate that the refractive indices of the associated ternary mixtures can be modeled with a relative error of about 0.9% by using the thermodynamical properties of the pure components. The concentration derivatives of the refractive index are an important parameter, as they are required for different experimental techniques. These derivatives have been determined from the experimental data on refractive indices. However, applying mixing rules for calculation of the derivatives of the refractive indices with respect to concentrations does not provide satisfactory results in the case of ternary mixtures of associated liquids.

Abnormal breakdown characteristic in a two-phase mixture

International Nuclear Information System (INIS)

Ye Qizheng; Li Jin; Lu Fei

2006-01-01

A two-phase mixture (TPM) is a mixture of gas and macroparticles of high concentration. Based on Townsend's theory, a new cell-iterative model in analytical form for the breakdown mechanism in TPM is presented. Compared with the original cell-iterative model in our previous paper, the obstructive factor of the macroparticles that influences the electron avalanche propagation is considered, except for the macroparticles distorting the electrical field and capture of the electrons. The cell attractive parameter k is presented according to the classical continuum theory for field charging. The modified Paschen law for a TPM is presented to calculate the breakdown voltage. The breakdown voltage of the TPM, U TPM , increases gradually with an increase in the macroparticle number density (m). The voltage U TPM is lower than that of the pure gas at low m values and larger at high m values. With a decrease of the macroparticle volume fraction and the dielectric mismatch, the voltage U TPM increases gradually at low m values and decreases gradually at high m values. The voltage U TPM at pd 200 cm Torr is lower than that at pd = 760 cm Torr for low m values and larger for high m values. This kind of abnormal breakdown characteristic in the TPM occurs in the case of high macroparticle volume fraction. On the other hand, the minimum of the TPM's Paschen curve increases with increase in m. It provides the possibility and the conditions of greatly increasing the breakdown voltage in a nearly uniform field

Abnormal breakdown characteristic in a two-phase mixture

Energy Technology Data Exchange (ETDEWEB)

Ye Qizheng; Li Jin; Lu Fei [College of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, 430074 (China)

2006-05-21

A two-phase mixture (TPM) is a mixture of gas and macroparticles of high concentration. Based on Townsend's theory, a new cell-iterative model in analytical form for the breakdown mechanism in TPM is presented. Compared with the original cell-iterative model in our previous paper, the obstructive factor of the macroparticles that influences the electron avalanche propagation is considered, except for the macroparticles distorting the electrical field and capture of the electrons. The cell attractive parameter k is presented according to the classical continuum theory for field charging. The modified Paschen law for a TPM is presented to calculate the breakdown voltage. The breakdown voltage of the TPM, U{sub TPM}, increases gradually with an increase in the macroparticle number density (m). The voltage U{sub TPM} is lower than that of the pure gas at low m values and larger at high m values. With a decrease of the macroparticle volume fraction and the dielectric mismatch, the voltage U{sub TPM} increases gradually at low m values and decreases gradually at high m values. The voltage U{sub TPM} at pd 200 cm Torr is lower than that at pd = 760 cm Torr for low m values and larger for high m values. This kind of abnormal breakdown characteristic in the TPM occurs in the case of high macroparticle volume fraction. On the other hand, the minimum of the TPM's Paschen curve increases with increase in m. It provides the possibility and the conditions of greatly increasing the breakdown voltage in a nearly uniform field.

Environmental risk assessment of biocidal products: identification of relevant components and reliability of a component-based mixture assessment.

Science.gov (United States)

Coors, Anja; Vollmar, Pia; Heim, Jennifer; Sacher, Frank; Kehrer, Anja

2018-01-01

Biocidal products are mixtures of one or more active substances (a.s.) and a broad range of formulation additives. There is regulatory guidance currently under development that will specify how the combined effects of the a.s. and any relevant formulation additives shall be considered in the environmental risk assessment of biocidal products. The default option is a component-based approach (CBA) by which the toxicity of the product is predicted from the toxicity of 'relevant' components using concentration addition. Hence, unequivocal and practicable criteria are required for identifying the 'relevant' components to ensure protectiveness of the CBA, while avoiding unnecessary workload resulting from including by default components that do not significantly contribute to the product toxicity. The present study evaluated a set of different criteria for identifying 'relevant' components using confidential information on the composition of 21 wood preservative products. Theoretical approaches were complemented by experimentally testing the aquatic toxicity of seven selected products. For three of the seven tested products, the toxicity was underestimated for the most sensitive endpoint (green algae) by more than factor 2 if only the a.s. were considered in the CBA. This illustrated the necessity of including at least some additives along with the a.s. Considering additives that were deemed 'relevant' by the tentatively established criteria reduced the underestimation of toxicity for two of the three products. A lack of data for one specific additive was identified as the most likely reason for the remaining toxicity underestimation of the third product. In three other products, toxicity was overestimated by more than factor 2, while prediction and observation fitted well for the seventh product. Considering all additives in the prediction increased only the degree of overestimation. Supported by theoretical calculations and experimental verifications, the present

Morphology-tunable and photoresponsive properties in a self-assembled two-component gel system.

Science.gov (United States)

Zhou, Yifeng; Xu, Miao; Yi, Tao; Xiao, Shuzhang; Zhou, Zhiguo; Li, Fuyou; Huang, Chunhui

2007-01-02

Photoresponsive C3-symmetrical trisurea self-assembling building blocks containing three azobenzene groups (LC10 and LC4) at the rim were designed and synthesized. By introducing a trisamide gelator (G18), which can self-aggregate through hydrogen bonds of acylamino moieties to form a fibrous network, the mixture of LC10 (or LC4) and G18 forms an organogel with coral-like supramolecular structure from 1,4-dioxane. The cooperation of hydrogen bonding and the hydrophobic diversity between these components are the main contributions to the specific superstructure. The two-component gel exhibits reversible photoisomerization from trans to cis transition without breakage of the gel state.

Assessment of competition and yield advantage in addition series of barley variety mixtures

Directory of Open Access Journals (Sweden)

Kari Jokinen

1991-09-01

Full Text Available In an addition series experiment the competition between three barley varieties (Agneta, Arra and Porno and the yield performance of mixtures were evaluated. Also two levels of nitrogen fertilization (50 and 100 kgN/ha were applied. Two approaches (the replacement series and the linear regression equation were used to analyse the competitive relationship based on grain yields in two-component mixtures. In three component mixtures the replacement series approach was applied. Both methods showed a similar dominance order of the varieties with Arra always being dominant and Agneta subordinate. The relationship between varieties was independent of the number of varieties in the mixture. Increase in available nitrogen strengthened the competitiveness of Arra especially in the dense, two-variety mixtures. Some mixtures over yielded but the differences were not statistically significant. The yield advantage based on relative yield total or on the ratio of actual and expected yield was greatest when the density and nitrogen fertilization were low and especially when one component in the mixture was a rather low yielding variety (Agneta. The land equivalent ratios (LER (the reference pure culture yield was the maximum yield of each variety were close to one, suggesting that under optimal growing conditions the yield advantage of barley varietal mixtures is marginal.

Calculation of Transport Coefficients in Dense Plasma Mixtures

Science.gov (United States)

Haxhimali, T.; Cabot, W. H.; Caspersen, K. J.; Greenough, J.; Miller, P. L.; Rudd, R. E.; Schwegler, E. R.

2011-10-01

We use classical molecular dynamics (MD) to estimate species diffusivity and viscosity in mixed dense plasmas. The Yukawa potential is used to describe the screened Coulomb interaction between the ions. This potential has been used widely, providing the basis for models of dense stellar materials, inertial confined plasmas, and colloidal particles in electrolytes. We calculate transport coefficients in equilibrium simulations using the Green- Kubo relation over a range of thermodynamic conditions including the viscosity and the self - diffusivity for each component of the mixture. The interdiffusivity (or mutual diffusivity) can then be related to the self-diffusivities by using a generalization of the Darken equation. We have also employed non-equilibrium MD to estimate interdiffusivity during the broadening of the interface between two regions each with a high concentration of either species. Here we present results for an asymmetric mixture between Ar and H. These can easily be extended to other plasma mixtures. A main motivation for this study is to develop accurate transport models that can be incorporated into the hydrodynamic codes to study hydrodynamic instabilities. We use classical molecular dynamics (MD) to estimate species diffusivity and viscosity in mixed dense plasmas. The Yukawa potential is used to describe the screened Coulomb interaction between the ions. This potential has been used widely, providing the basis for models of dense stellar materials, inertial confined plasmas, and colloidal particles in electrolytes. We calculate transport coefficients in equilibrium simulations using the Green- Kubo relation over a range of thermodynamic conditions including the viscosity and the self - diffusivity for each component of the mixture. The interdiffusivity (or mutual diffusivity) can then be related to the self-diffusivities by using a generalization of the Darken equation. We have also employed non-equilibrium MD to estimate interdiffusivity during

Volatilization of multicomponent mixtures in soil vapor extraction applications

International Nuclear Information System (INIS)

Bass, D.H.

1995-01-01

In soil vapor extraction (SVE) applications involving multicomponent mixtures, prediction of mass removal by volatilization as a function remediation extent is required to estimate remediation time and to size offgas treatment equipment. SVE is a commonly used remediation technology which volatilizes and enhances aerobic biodegradation of contamination adsorbed to vadose zone soils. SVE is often applied at sites contaminated with petroleum products, which are usually mixtures of many different compounds with vapor pressures spanning several orders of magnitude. The most volatile components are removed first, so the vapor pressure of the remaining contaminant continually decreases over the course of the remediation. A method for assessing how vapor pressure, and hence the rate of volatilization, of a multicomponent mixture changes over the course of a vapor extraction remedy has been developed. Each component is listed, alone, with its mass fraction in the mixture, in decreasing order of pure component vapor pressure (where component analyses are unavailable, model compounds can be used), For most petroleum distillates, the vapor pressure for each component plotted against the cumulative mass fraction of the component in the mixture on semilog coordinates will produce a straight line with a high correlation coefficient. This regression can be integrated to produce an expression for vapor pressure of the overall mixture as a function of extent or remediation

On thermal conductivity of gas mixtures containing hydrogen

Science.gov (United States)

Zhukov, Victor P.; Pätz, Markus

2017-06-01

A brief review of formulas used for the thermal conductivity of gas mixtures in CFD simulations of rocket combustion chambers is carried out in the present work. In most cases, the transport properties of mixtures are calculated from the properties of individual components using special mixing rules. The analysis of different mixing rules starts from basic equations and ends by very complex semi-empirical expressions. The formulas for the thermal conductivity are taken for the analysis from the works on modelling of rocket combustion chambers. \\hbox {H}_2{-}\\hbox {O}_2 mixtures are chosen for the evaluation of the accuracy of the considered mixing rules. The analysis shows that two of them, of Mathur et al. (Mol Phys 12(6):569-579, 1967), and of Mason and Saxena (Phys Fluids 1(5):361-369, 1958), have better agreement with the experimental data than other equations for the thermal conductivity of multicomponent gas mixtures.

Assessment of an ultrasonic sensor and a capacitance probe for measurement of two-phase mixture level

International Nuclear Information System (INIS)

Kim, Chang Hyun; Lee, Dong Won; No, Hee Cheon

2004-01-01

We performed a comparison of two-phase mixture levels measured by an ultrasonic sensor and a two-wire type capacitance probe with visual data under the same experimental conditions. A series of experiments are performed with various combinations of airflow and initial water level using a test vessel with a height of 2m and an inner diameter of 0.3m. The ultrasonic sensor measured the two-phase mixture level with a maximum error of 1.77% with respect to the visual data. The capacitance probe severely under-predicted the level data in the high void fraction region. The cause of the error was identified as the change of the dielectric constant as the void fraction changes when the probe is applied to the measurement of the two-phase mixture levels. A correction method for the capacitance probe is proposed by correcting the change of the dielectric constant of the two-phase mixture. The correction method for the capacitance probe produces a r.m.s. error of 5.4%. The present experimental data are compared with the existing pool void fraction correlations based on drift-flux model. The Kataoka-Ishii correlation has the best agreement with the present experimental data with an r.m.s error of 2.5%

Self-selection of two diet components by Tennebrio molitor (Coleoptera: Tenebrionidae) larvae and its impact on fitness

Science.gov (United States)

We studied the ability of Tenebrio molitor L. (Coleoptera: Tenebrionidae) to self-select optimal ratios of two dietary components to approach nutritional balance and maximum fitness. Life table analysis was used to determine the fitness of T. molitor developing in diet mixtures comprised of four dif...

Space-time latent component modeling of geo-referenced health data.

Science.gov (United States)

Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-08-30

Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.

A study of chemical equilibrium of tri-component mixtures of hydrogen isotopes

International Nuclear Information System (INIS)

Cristescu, Ioana; Cristescu, I.; Peculea, M.

1998-01-01

In this paper we present a model for computing the equilibrium constants for chemical reactions between hydrogen's isotopes as function of temperature. The equilibrium constants were expressed with the aid of Gibbs potential and the partition function of the mixture. We assessed the partition function for hydrogen's isotopes having in view that some nuclei are fermions and other bosons. As results we plotted the values of equilibrium constants as function of temperature. Knowing these values we determined the deuterium distribution on species (for mixture H 2 -HD-D 2 ) as function of total deuterium concentration and the tritium distribution on species (for mixtures D 2 -DT-T 2 and H 2 -HT-T 2 ) as function of total tritium concentration. (authors)

Radiation-energy partition among mixture components: current ideas on an old question

International Nuclear Information System (INIS)

Swallow, A.J.

1988-01-01

We review the basis of the familiar idea that the energy partition among mixture components in the initial stage would be governed by the total electron fraction. For considerations of many problems in radiation chemistry, it is better to use the valence-electron fraction. We also point out recent developments in more detailed treatments, which indicate limitations of the very concept of the energy partition for the determination of the yields of initial molecular species that appear under irradiation. (author)

Modeling abundance using N-mixture models: the importance of considering ecological mechanisms.

Science.gov (United States)

Joseph, Liana N; Elkin, Ché; Martin, Tara G; Possinghami, Hugh P

2009-04-01

Predicting abundance across a species' distribution is useful for studies of ecology and biodiversity management. Modeling of survey data in relation to environmental variables can be a powerful method for extrapolating abundances across a species' distribution and, consequently, calculating total abundances and ultimately trends. Research in this area has demonstrated that models of abundance are often unstable and produce spurious estimates, and until recently our ability to remove detection error limited the development of accurate models. The N-mixture model accounts for detection and abundance simultaneously and has been a significant advance in abundance modeling. Case studies that have tested these new models have demonstrated success for some species, but doubt remains over the appropriateness of standard N-mixture models for many species. Here we develop the N-mixture model to accommodate zero-inflated data, a common occurrence in ecology, by employing zero-inflated count models. To our knowledge, this is the first application of this method to modeling count data. We use four variants of the N-mixture model (Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial) to model abundance, occupancy (zero-inflated models only) and detection probability of six birds in South Australia. We assess models by their statistical fit and the ecological realism of the parameter estimates. Specifically, we assess the statistical fit with AIC and assess the ecological realism by comparing the parameter estimates with expected values derived from literature, ecological theory, and expert opinion. We demonstrate that, despite being frequently ranked the "best model" according to AIC, the negative binomial variants of the N-mixture often produce ecologically unrealistic parameter estimates. The zero-inflated Poisson variant is preferable to the negative binomial variants of the N-mixture, as it models an ecological mechanism rather than a

Self-organising mixture autoregressive model for non-stationary time series modelling.

Science.gov (United States)

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Cold water injection into two-phase mixtures

International Nuclear Information System (INIS)

1989-07-01

This report presents the results of a review of the international literature regarding the dynamic loadings associated with the injection of cold water into two-phase mixtures. The review placed emphasis on waterhammer in nuclear power plants. Waterhammmer incidence data were reviewed for information related to thermalhydraulic conditions, underlying causes and consequential damage. Condensation induced waterhammer was found to be the most significant consequence of injecting cold water into a two-phase system. Several severe waterhammer incidents have been attributed to slug formation and steam bubble collapse under conditions of stratified steam and cold water flows. These phenomena are complex and not well understood. The current body of experimental and analytical knowledge is not large enough to establish maps of expected regimes of condensation induced waterhammer. The Electric Power Research Institute, in the United States, has undertaken a major research and development programme to develop the knowledge base for this area. The limited models and data currently available show that mechanical parameters are as important as thermodynamic conditions for the initiation of condensation induced waterhammer. Examples of bounds for avoiding two-phase waterhammer are given. These bounds are system specific and depend upon parameters such as pump capacity, pipe length and pipe orientation

Multivariate spatial Gaussian mixture modeling for statistical clustering of hemodynamic parameters in functional MRI

International Nuclear Information System (INIS)

Fouque, A.L.; Ciuciu, Ph.; Risser, L.; Fouque, A.L.; Ciuciu, Ph.; Risser, L.

2009-01-01

In this paper, a novel statistical parcellation of intra-subject functional MRI (fMRI) data is proposed. The key idea is to identify functionally homogenous regions of interest from their hemodynamic parameters. To this end, a non-parametric voxel-based estimation of hemodynamic response function is performed as a prerequisite. Then, the extracted hemodynamic features are entered as the input data of a Multivariate Spatial Gaussian Mixture Model (MSGMM) to be fitted. The goal of the spatial aspect is to favor the recovery of connected components in the mixture. Our statistical clustering approach is original in the sense that it extends existing works done on univariate spatially regularized Gaussian mixtures. A specific Gibbs sampler is derived to account for different covariance structures in the feature space. On realistic artificial fMRI datasets, it is shown that our algorithm is helpful for identifying a parsimonious functional parcellation required in the context of joint detection estimation of brain activity. This allows us to overcome the classical assumption of spatial stationarity of the BOLD signal model. (authors)

A two-component dark matter model with real singlet scalars ...

Indian Academy of Sciences (India)

2016-01-05

component dark matter model with real singlet scalars confronting GeV -ray excess from galactic centre and Fermi bubble. Debasish Majumdar Kamakshya Prasad Modak Subhendu Rakshit. Special: Cosmology Volume 86 Issue ...

Fluid-elastic force measurements acting on a tube bundle in two-phase cross flow

International Nuclear Information System (INIS)

Inada, Fumio; Kawamura, Koji; Yasuo, Akira

1996-01-01

Fluid-elastic force acting on a square tube bundle of P/D = 1.47 in air-water two-phase cross flow was measured to investigate the characteristics and to clarify whether the fluid elastic vibration characteristics could be expressed using two-phase mixture characteristics. Measured fluid elastic forces were separated into fluid-elastic force coefficients such as added mass, added stiffness, and added damping coefficient. The added damping coefficient was separated into a two-phase damping and a flow-dependent component as in previous research (Carlucci, 1981 and 1983; Pettigrew, 1994). These coefficients were nondimensionalized with two-phase mixture characteristics such as void fraction, mixture density and mixture velocity, which were obtained using the drift-flux model with consideration given to the model. The result was compared with the result obtained with the homogeneous model. It was found that fluid-elastic force coefficients could be expressed with two-phase flow mixture characteristics very well in the experimental result, and that better result can be derived using the slip model as compared to the homogeneous model. Added two-phase flow, which could be expressed as a function of void fraction, where two-phase damping was nondimensionalized with the relative velocity between the gas and liquid phases used as a reference velocity. Using these, the added stiffness coefficient and flow-dependent component of damping could be expressed very well as a function of nondimensional mixture velocity

Modeling of Multicomponent Mixture Separation Processes Using Hollow fiber Membrane

Energy Technology Data Exchange (ETDEWEB)

Kim, Sin-Ah; Kim, Jin-Kuk; Lee, Young Moo; Yeo, Yeong-Koo [Hanyang University, Seoul (Korea, Republic of)

2015-02-15

So far, most of research activities on modeling of membrane separation processes have been focused on binary feed mixture. But, in actual separation operations, binary feed is hard to find and most separation processes involve multicomponent feed mixture. In this work models for membrane separation processes treating multicomponent feed mixture are developed. Various model types are investigated and validity of proposed models are analysed based on experimental data obtained using hollowfiber membranes. The proposed separation models show quick convergence and exhibit good tracking performance.

Two component memory of Rotstein effect in nuclear emulsions

International Nuclear Information System (INIS)

Gushchin, E.M.; Lebedev, A.N.; Somov, S.V.; Timofeev, M.K.; Tipografshchik, G.I.

1991-01-01

Two sharply differing memory components - fast and slow -are simultaneously detected during investigation into the controlled mode of fast charged particle detection in simple nuclear emulsions, with the emulsion trace sensitivity, corresponding to these components, being about 5 time different. The value of memory time is T m ≅40 μs for fast memory and T m ≅3.5 ms for the slow one. The detection of two Rotstein effect memory components confirms the correctness of the trap model

Solid-Liquid Equilibria for Many-component Mixtures Using Cubic-Plus-Association (CPA) equation of state

DEFF Research Database (Denmark)

Fettouhi, André; Thomsen, Kaj

2010-01-01

In the creation of liquefied natural gas the formation of solids play a substantial role, hence detailed knowledge is needed about solid-liquid equilibria (SLE). In this abstract we shortly summarize the work we have carried out at CERE over the past year with SLE for many-component mixtures usin...... the Cubic-Plus-Association (CPA) equation of state. Components used in this work are highly relevant to the oil and gas industry and include light and heavy hydrocarbons, alcohols, water and carbon dioxide....

Human toxicology of chemical mixtures toxic consequences beyond the impact of one-component product and environmental exposures

CERN Document Server

Zeliger, Harold I

2011-01-01

In this important reference work, Zeliger catalogs the known effects of chemical mixtures on the human body and also proposes a framework for understanding and predicting their actions in terms of lipophile (fat soluble)/hydrophile (water soluble) interactions. The author's focus is on illnesses that ensue following exposures to mixtures of chemicals that cannot be attributed to any one component of the mixture. In the first part the mechanisms of chemical absorption at a molecular and macromolecular level are explained, as well as the body's methods of defending itself against xenobiotic intrusion. Part II examines the sources of the chemicals discussed, looking at air and water pollution, food additives, pharmaceuticals, etc. Part III, which includes numerous case studies, examines specific effects of particular mixtures on particular body systems and organs and presents a theoretical framework for predicting what the effects of uncharacterized mixtures might be. Part IV covers regulatory requirements and t...

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

Science.gov (United States)

Chen, D G; Pounds, J G

1998-12-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium.

Application of approximations for joint cumulative k-distributions for mixtures to FSK radiation heat transfer in multi-component high temperature non-LTE plasmas

International Nuclear Information System (INIS)

Maurente, André; França, Francis H.R.; Miki, Kenji; Howell, John R.

2012-01-01

Approximations for joint cumulative k-distribution for mixtures are efficient for full spectrum k-distribution (FSK) computations. These approximations provide reduction of the database that is necessary to perform FSK computation when compared to the direct approach, which uses cumulative k-distributions computed from the spectrum of the mixture, and also less computational expensive when compared to techniques in which RTE's are required to be solved for each component of the mixture. The aim of the present paper is to extend the approximations for joint cumulative k-distributions for non-LTE media. For doing that, a FSK to non-LTE media formulation well-suited to be applied along with approximations for joint cumulative k-distributions is presented. The application of the proposed methodology is demonstrated by solving the radiation heat transfer in non-LTE high temperature plasmas composed of N, O, N 2 , NO, N 2 + and mixtures of these species. The two more efficient approximations, that is, the superposition and multiplication are employed and analyzed.

Generalized modeling of multi-component vaporization/condensation phenomena for multi-phase-flow analysis

International Nuclear Information System (INIS)

Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.

2003-01-01

A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)

A Concentration Addition Model to Assess Activation of the Pregnane X Receptor (PXR) by Pesticide Mixtures Found in the French Diet

OpenAIRE

de Sousa, Georges; Nawaz, Ahmad; Cravedi, Jean-Pierre; Rahmani, Roger

2014-01-01

French consumers are exposed to mixtures of pesticide residues in part through food consumption. As a xenosensor, the pregnane X receptor (hPXR) is activated by numerous pesticides, the combined effect of which is currently unknown. We examined the activation of hPXR by seven pesticide mixtures most likely found in the French diet and their individual components. The mixture's effect was estimated using the concentration addition (CA) model. PXR transactivation was measured by monitoring luci...

Two component systems: physiological effect of a third component.

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Baldiri Salvado

Full Text Available Signal transduction systems mediate the response and adaptation of organisms to environmental changes. In prokaryotes, this signal transduction is often done through Two Component Systems (TCS. These TCS are phosphotransfer protein cascades, and in their prototypical form they are composed by a kinase that senses the environmental signals (SK and by a response regulator (RR that regulates the cellular response. This basic motif can be modified by the addition of a third protein that interacts either with the SK or the RR in a way that could change the dynamic response of the TCS module. In this work we aim at understanding the effect of such an additional protein (which we call "third component" on the functional properties of a prototypical TCS. To do so we build mathematical models of TCS with alternative designs for their interaction with that third component. These mathematical models are analyzed in order to identify the differences in dynamic behavior inherent to each design, with respect to functionally relevant properties such as sensitivity to changes in either the parameter values or the molecular concentrations, temporal responsiveness, possibility of multiple steady states, or stochastic fluctuations in the system. The differences are then correlated to the physiological requirements that impinge on the functioning of the TCS. This analysis sheds light on both, the dynamic behavior of synthetically designed TCS, and the conditions under which natural selection might favor each of the designs. We find that a third component that modulates SK activity increases the parameter space where a bistable response of the TCS module to signals is possible, if SK is monofunctional, but decreases it when the SK is bifunctional. The presence of a third component that modulates RR activity decreases the parameter space where a bistable response of the TCS module to signals is possible.

A two-dimensional, transient, compressible isothermal and two-phase model for the air-side electrode of PEM fuel cells

International Nuclear Information System (INIS)

Khakbaz Baboli, M.; Kermani, M.J.

2008-01-01

A two-dimensional, transient, compressible, isothermal and two-phase flow of reactant-product mixture in the air-side electrode of proton exchange membrane fuel cells (PEMFC) are numerically studied in the present paper. The mixture is composed of four species: oxygen, nitrogen, liquid water and water vapor. The governing PDE's are conservation of the water vapor and oxygen species, momentum equation of the mixture (gas+liquid), mass conservation of the liquid phase, and mass conservation of the mixture. In this study, a separate PDE for the mass conservation of the liquid water is solved to calculate the saturation levels. The capillary pressure was used to determine the slip velocity between the phases. A full compressible form of the momentum equation was used, with the ∇.V preserved in the equation. The Maxwell-Stefan equation was used to model the diffusive fluxes of the multi-component gas mixture. The strongly coupled equations are solved based on a recently developed finite volume SIMPLER scheme of S.V. Patankar, Numerical Heat Transfer and Fluid Flow, Hemisphere Publishing Corp., McGraw-Hill Book Company, 1984. The computational domain consists of two regions; an open area (gas delivery channel) linked to a porous gas diffusion layer (GDL). A single (unified) set of the PDE's are used for the whole domain with the corresponding properties of each sub-domain. A polarization curve for the whole spectrum of the dry and wet regions were obtained. The results were compared with the experiments of E.A. Ticianelli, C.R. Derouin, A. Redondo, S. Srinivasan, J. Electrochem. Soc. 135 (1988) 2209, and good agreements were achieved

Self-consistent calculation of atomic structure for mixture

International Nuclear Information System (INIS)

Meng Xujun; Bai Yun; Sun Yongsheng; Zhang Jinglin; Zong Xiaoping

2000-01-01

Based on relativistic Hartree-Fock-Slater self-consistent average atomic model, atomic structure for mixture is studied by summing up component volumes in mixture. Algorithmic procedure for solving both the group of Thomas-Fermi equations and the self-consistent atomic structure is presented in detail, and, some numerical results are discussed

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions

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Yoon Soo ePark

2016-02-01

Full Text Available This study investigates the impact of item parameter drift (IPD on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effect on item parameters and examinee ability.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions.

Science.gov (United States)

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.

Generalized structured component analysis a component-based approach to structural equation modeling

CERN Document Server

Hwang, Heungsun

2014-01-01

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...

A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models.

Science.gov (United States)

Fronczyk, Kassandra; Kottas, Athanasios

2014-03-01

We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is placed on the key risk assessment goal of calibration for the dose level that corresponds to a specified response. The proposed methodology yields flexible inference for the dose-response relationship as well as for other inferential objectives, as illustrated with two data sets from the literature. © 2013, The International Biometric Society.

A comparison of two-component and quadratic models to assess survival of irradiated stage-7 oocytes of Drosophila melanogaster

International Nuclear Information System (INIS)

Peres, C.A.; Koo, J.O.

1981-01-01

In this paper, the quadratic model to analyse data of this kind, i.e. S/S 0 = exp(-αD-bD 2 ), where S and Ssub(o) are defined as before is proposed is shown that the same biological interpretation can be given to the parameters α and A and to the parameters β and B. Furthermore it is shown that the quadratic model involves one probabilistic stage more than the two-component model, and therefore the quadratic model would perhaps be more appropriate as a dose-response model for survival of irradiated stage-7 oocytes of Drosophila melanogaster. In order to apply these results, the data presented by Sankaranarayanan and Sankaranarayanan and Volkers are reanalysed using the quadratic model. It is shown that the quadratic model fits better than the two-component model to the data in most situations. (orig./AJ)

A new correlation for nucleate pool boiling of aqueous mixtures

International Nuclear Information System (INIS)

Thome, J.R.; Shakir, S.

1987-01-01

A new mixture boiling correlation was developed for nucleate pool boiling of aqueous mixtures on plain, smooth tubes. The semi-empirical correlation models the rise in the local bubble point temperature in a mixture caused by the preferential evaporation of the more volatile component during bubble growth. This rise varies from zero at low heat fluxes (where only single-phase natural convection is present) up to nearly the entire boiling range at the peak heat flux (where latent heat transport is dominant). The boiling range, which is the temperature difference between the dew point and bubble point of a mixture, is used to characterize phase equilibrium effects. An exponential term models the rise in the local bubble point temperature as a function of heat flux. The correlation was compared against binary mixture boiling data for ethanol-water, methanol-water, n-propanol-water, and acetone-water. The majority of the data was predicted to within 20%. Further experimental research is currently underway to obtain multicomponent boiling data for aqueous mixtures with up to five components and for wider boiling ranges

Mixture

Directory of Open Access Journals (Sweden)

Silva-Aguilar Martín

2011-01-01

Full Text Available Metals are ubiquitous pollutants present as mixtures. In particular, mixture of arsenic-cadmium-lead is among the leading toxic agents detected in the environment. These metals have carcinogenic and cell-transforming potential. In this study, we used a two step cell transformation model, to determine the role of oxidative stress in transformation induced by a mixture of arsenic-cadmium-lead. Oxidative damage and antioxidant response were determined. Metal mixture treatment induces the increase of damage markers and the antioxidant response. Loss of cell viability and increased transforming potential were observed during the promotion phase. This finding correlated significantly with generation of reactive oxygen species. Cotreatment with N-acetyl-cysteine induces effect on the transforming capacity; while a diminution was found in initiation, in promotion phase a total block of the transforming capacity was observed. Our results suggest that oxidative stress generated by metal mixture plays an important role only in promotion phase promoting transforming capacity.

Two-component network model in voice identification technologies

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Edita K. Kuular

2018-03-01

Full Text Available Among the most important parameters of biometric systems with voice modalities that determine their effectiveness, along with reliability and noise immunity, a speed of identification and verification of a person has been accentuated. This parameter is especially sensitive while processing large-scale voice databases in real time regime. Many research studies in this area are aimed at developing new and improving existing algorithms for presentation and processing voice records to ensure high performance of voice biometric systems. Here, it seems promising to apply a modern approach, which is based on complex network platform for solving complex massive problems with a large number of elements and taking into account their interrelationships. Thus, there are known some works which while solving problems of analysis and recognition of faces from photographs, transform images into complex networks for their subsequent processing by standard techniques. One of the first applications of complex networks to sound series (musical and speech analysis are description of frequency characteristics by constructing network models - converting the series into networks. On the network ontology platform a previously proposed technique of audio information representation aimed on its automatic analysis and speaker recognition has been developed. This implies converting information into the form of associative semantic (cognitive network structure with amplitude and frequency components both. Two speaker exemplars have been recorded and transformed into pertinent networks with consequent comparison of their topological metrics. The set of topological metrics for each of network models (amplitude and frequency one is a vector, and together  those combine a matrix, as a digital "network" voiceprint. The proposed network approach, with its sensitivity to personal conditions-physiological, psychological, emotional, might be useful not only for person identification

A Dirichlet process mixture model for brain MRI tissue classification.

Science.gov (United States)

Ferreira da Silva, Adelino R

2007-04-01

Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain. However, performance and robustness of finite mixture models deteriorate when the models have to deal with a variety of anatomical structures. In this paper, we propose a nonparametric Bayesian model for tissue classification of MR images of the brain. The model, known as Dirichlet process mixture model, uses Dirichlet process priors to overcome the limitations of current parametric finite mixture models. To validate the accuracy and robustness of our method we present the results of experiments carried out on simulated MR brain scans, as well as on real MR image data. The results are compared with similar results from other well-known MRI segmentation methods.

Dissolution and biodegradation of a mixture of immiscible liquids

International Nuclear Information System (INIS)

Gandhi, P.; Erickson, L.E.; Fan, L.T.

1994-01-01

Subsurface contaminants are frequently encountered as mixtures of nonaqueous phase liquids (NAPLs) at sites contaminated by gasoline or coal tar comprising organic mixtures. The leaching of these organic mixtures from the aquifer has been examined with and without biodegradation. The results obtained have been compared with the limiting case of a single component NAPL. Various physical processes involved have been quantified based on the assumptions that liquid-liquid and sorption equilibria are established at the beginning of each flushing; oxygen required for biochemical oxidation is completely consumed by the end of each flushing; and the rate of biochemical oxidation obeys the Monod kinetics for a multi-substrate system, characterized by an oxygen utilization factor. This has given rise to an equilibrium model expressing the mass fraction of any component remaining in the aquifer, its aqueous concentration, and the composition of the NAPL as functions of the number of flushings. The results of the simulation with the model demonstrate that bioremediation can significantly reduce the time necessary for removing the components of intermediate solubility such as xylene. Highly soluble components of the NAPL are mainly removed by the pump-and-treat mechanism while the components of extremely low solubility are unavailable to the microbes as substrates in a multi-component system

An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies

DEFF Research Database (Denmark)

Thompson, Wesley K.; Wang, Yunpeng; Schork, Andrew J.

2015-01-01

-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via...... analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn’s disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While...... minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local...

I. A model for the magnetic equation of state of liquid 3He. II. An induced interaction model for a two-component Fermi liquid

International Nuclear Information System (INIS)

Sanchez-Castro, C.R.

1988-01-01

This dissertation is divided in six chapters. Chapter 1 is an introduction to the rest of the dissertation. In it, the author presents the different models for the magnetic equation state of liquid 3 He, a derivation of the induced interaction equations for a one component Fermi liquid, and discuss the basic hamiltonian describing the heavy fermion compounds. In Chapter 2 and Chapter 3, he presents a complete discussion of the thermodynamics and Landau theory of a spin polarized Fermi liquid. A phenomenological model is then developed to predict the polarization dependence of the longitudinal Landau parameters in liquid 3 He. This model predicts a new magnetic equation of state and the possibility of liquid 3 He being 'nearly metamagnetic' at high pressures. Chapter 4 contains a microscopic calculation of the magnetic field dependence of the Landau parameters in a strongly correlated Fermi system using the induced interaction model. The system he studied consists of a single component Fermi liquid with parabolic energy bands, and a large on-site repulsive interaction. In Chapter 5, he presents a complete discussion of the Landau theory of a two component Fermi liquid. Then, he generalizes the induced interaction equations to calculate Landau parameters and scattering amplitudes for an arbitrary, spin polarized, two component Fermi liquid. The resulting equations are used to study a model for the heavy fermion Fermi liquid state: a two band electronic system with an antiferromagnetic interaction between the two bands. Chapter 6 contains the concluding remarks of the dissertation

An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

Directory of Open Access Journals (Sweden)

Wesley K Thompson

2015-12-01

Full Text Available Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD and the other for schizophrenia (SZ. A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the

An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

Science.gov (United States)

Thompson, Wesley K; Wang, Yunpeng; Schork, Andrew J; Witoelar, Aree; Zuber, Verena; Xu, Shujing; Werge, Thomas; Holland, Dominic; Andreassen, Ole A; Dale, Anders M

2015-12-01

Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of

Rheology of petrolatum-paraffin oil mixtures : Applications to analogue modelling of geological processes

NARCIS (Netherlands)

Duarte, João C.; Schellart, Wouter P.; Cruden, Alexander R.

2014-01-01

Paraffins have been widely used in analogue modelling of geological processes. Petrolatum and paraffin oil are commonly used to lubricate model boundaries and to simulate weak layers. In this paper, we present rheological tests of petrolatum, paraffin oil and several homogeneous mixtures of the two.

The mathematics of a successful deconvolution: a quantitative assessment of mixture-based combinatorial libraries screened against two formylpeptide receptors.

Science.gov (United States)

Santos, Radleigh G; Appel, Jon R; Giulianotti, Marc A; Edwards, Bruce S; Sklar, Larry A; Houghten, Richard A; Pinilla, Clemencia

2013-05-30

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays.

Efficient implementation of one- and two-component analytical energy gradients in exact two-component theory

Science.gov (United States)

Franzke, Yannick J.; Middendorf, Nils; Weigend, Florian

2018-03-01

We present an efficient algorithm for one- and two-component analytical energy gradients with respect to nuclear displacements in the exact two-component decoupling approach to the one-electron Dirac equation (X2C). Our approach is a generalization of the spin-free ansatz by Cheng and Gauss [J. Chem. Phys. 135, 084114 (2011)], where the perturbed one-electron Hamiltonian is calculated by solving a first-order response equation. Computational costs are drastically reduced by applying the diagonal local approximation to the unitary decoupling transformation (DLU) [D. Peng and M. Reiher, J. Chem. Phys. 136, 244108 (2012)] to the X2C Hamiltonian. The introduced error is found to be almost negligible as the mean absolute error of the optimized structures amounts to only 0.01 pm. Our implementation in TURBOMOLE is also available within the finite nucleus model based on a Gaussian charge distribution. For a X2C/DLU gradient calculation, computational effort scales cubically with the molecular size, while storage increases quadratically. The efficiency is demonstrated in calculations of large silver clusters and organometallic iridium complexes.

The Component Slope Linear Model for Calculating Intensive Partial Molar Properties: Application to Waste Glasses

International Nuclear Information System (INIS)

Reynolds, Jacob G.

2013-01-01

Partial molar properties are the changes occurring when the fraction of one component is varied while the fractions of all other component mole fractions change proportionally. They have many practical and theoretical applications in chemical thermodynamics. Partial molar properties of chemical mixtures are difficult to measure because the component mole fractions must sum to one, so a change in fraction of one component must be offset with a change in one or more other components. Given that more than one component fraction is changing at a time, it is difficult to assign a change in measured response to a change in a single component. In this study, the Component Slope Linear Model (CSLM), a model previously published in the statistics literature, is shown to have coefficients that correspond to the intensive partial molar properties. If a measured property is plotted against the mole fraction of a component while keeping the proportions of all other components constant, the slope at any given point on a graph of this curve is the partial molar property for that constituent. Actually plotting this graph has been used to determine partial molar properties for many years. The CSLM directly includes this slope in a model that predicts properties as a function of the component mole fractions. This model is demonstrated by applying it to the constant pressure heat capacity data from the NaOH-NaAl(OH 4 H 2 O system, a system that simplifies Hanford nuclear waste. The partial molar properties of H 2 O, NaOH, and NaAl(OH) 4 are determined. The equivalence of the CSLM and the graphical method is verified by comparing results detennined by the two methods. The CSLM model has been previously used to predict the liquidus temperature of spinel crystals precipitated from Hanford waste glass. Those model coefficients are re-interpreted here as the partial molar spinel liquidus temperature of the glass components

Modelling phase equilibria for acid gas mixtures using the CPA equation of state. Part V: Multicomponent mixtures containing CO₂ and alcohols

DEFF Research Database (Denmark)

Tsivintzelis, Ioannis; Kontogeorgis, Georgios M.

2015-01-01

of CPA for ternary and multicomponent CO2 mixtures containing alcohols (methanol, ethanol or propanol) water and hydrocarbons. This work belongs to a series of studies aiming to arrive in a single "engineering approach" for applying CPA to acid gas mixtures, without introducing significant changes...... to the model. In this direction, CPA results were obtained using various approaches, i.e. different association schemes for pure CO2 (assuming that it is a non-associating compound, or that it is a self-associating fluid with two, three or four association sites) and different possibilities for modelling...... mixtures of CO2 with water and alcohols (only use of one interaction parameter kij or assuming cross-association interactions and obtaining the relevant parameters either via a combining rule or using an experimental value for the cross-association energy). It is concluded that CPA is a powerful model...

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.

Directory of Open Access Journals (Sweden)

Kezi Yu

Full Text Available In this paper, we propose an application of non-parametric Bayesian (NPB models for classification of fetal heart rate (FHR recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP and the Chinese restaurant process with finite capacity (CRFC. Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR recordings in a real-time setting.

Mixture toxicity of PBT-like chemicals

DEFF Research Database (Denmark)

Syberg, Kristian; Dai, Lina; Ramskov, Tina

addition is a suitable model for default estimations of mixture effects. One of the major challenges is therefore how to select specific chemicals for actual mixture toxicity assessments. Persistant chemicals are likely to be present in the environment for an extended period of time, thus increasing...... the likelihood of them being present in environmentally found mixtures. Persistant, bioaccumulative and toxic (PBT) chemicals are therefore a highly relevant group of chemicals to consider for mixture toxicity regulation. The present study evaluates to what extent a number of PBT-like chemicals posess concern...... beyond that of the individual components. Firstly, the effects of three chemicals with PBT-like properties (acetyl cedrene, pyrene and triclosan) was examined on the freshwater snail, Potamopyrgus antipodarum. Secondly, mixture bioaccumulation of the same three chemicals were assessed experimentally...

Phase equilibria for mixtures containing very many components. development and application of continuous thermodynamics for chemical process design

International Nuclear Information System (INIS)

Cotterman, R.L.; Bender, R.; Prausnitz, J.M.

1984-01-01

For some multicomponent mixtures, where detailed chemical analysis is not feasible, the compositio of the mixture may be described by a continuous distribution function of some convenient macroscopic property suc as normal boiling point or molecular weight. To attain a quantitative description of phase equilibria for such mixtures, this work has developed thermodynamic procedures for continuous systems; that procedure is called continuous thermodynamics. To illustrate, continuous thermodynamics is used to calculate dew points for natural-gas mixtures, solvent loss in a high-pressure absorber, and liquid-liquid phase equilibria in a polymer fractionation process. Continuous thermodynamics provides a rational method for calculating phase equilibria for those mixtures where complete chemical analysis is not available but where composition can be given by some statistical description. While continuous thermodynamics is only the logical limit of the well-known pseudo-component method, it is more efficient than that method because it is less arbitrary and it often requires less computer time

A new decomposition-based computer-aided molecular/mixture design methodology for the design of optimal solvents and solvent mixtures

DEFF Research Database (Denmark)

Karunanithi, A.T.; Achenie, L.E.K.; Gani, Rafiqul

2005-01-01

This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective is to be optim......This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective...... is to be optimized subject to structural, property, and process constraints. The general molecular/mixture design problem is divided into two parts. For optimal single-compound design, the first part is solved. For mixture design, the single-compound design is first carried out to identify candidates...... and then the second part is solved to determine the optimal mixture. The decomposition of the CAMD MINLP model into relatively easy to solve subproblems is essentially a partitioning of the constraints from the original set. This approach is illustrated through two case studies. The first case study involves...

Bonding and structure in dense multi-component molecular mixtures.

Science.gov (United States)

Meyer, Edmund R; Ticknor, Christopher; Bethkenhagen, Mandy; Hamel, Sebastien; Redmer, Ronald; Kress, Joel D; Collins, Lee A

2015-10-28

We have performed finite-temperature density functional theory molecular dynamics simulations on dense methane, ammonia, and water mixtures (CH4:NH3:H2O) for various compositions and temperatures (2000 K ≤ T ≤ 10,000 K) that span a set of possible conditions in the interiors of ice-giant exoplanets. The equation-of-state, pair distribution functions, and bond autocorrelation functions (BACF) were used to probe the structure and dynamics of these complex fluids. In particular, an improvement to the choice of the cutoff in the BACF was developed that allowed analysis refinements for density and temperature effects. We note the relative changes in the nature of these systems engendered by variations in the concentration ratios. A basic tenet emerges from all these comparisons that varying the relative amounts of the three heavy components (C,N,O) can effect considerable changes in the nature of the fluid and may in turn have ramifications for the structure and composition of various planetary layers.

Mixtures of Two Bile Alcohol Sulfates Function as a Proximity Pheromone in Sea Lamprey.

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Cory O Brant

Full Text Available Unique mixtures of pheromone components are commonly identified in insects, and have been shown to increase attractiveness towards conspecifics when reconstructed at the natural ratio released by the signaler. In previous field studies of pheromones that attract female sea lamprey (Petromyzon marinus, L., putative components of the male-released mating pheromone included the newly described bile alcohol 3,12-diketo-4,6-petromyzonene-24-sulfate (DkPES and the well characterized 3-keto petromyzonol sulfate (3kPZS. Here, we show chemical evidence that unequivocally confirms the elucidated structure of DkPES, electrophysiological evidence that each component is independently detected by the olfactory epithelium, and behavioral evidence that mature female sea lamprey prefer artificial nests activated with a mixture that reconstructs the male-released component ratio of 30:1 (3kPZS:DkPES, molar:molar. In addition, we characterize search behavior (sinuosity of swim paths of females approaching ratio treatment sources. These results suggest unique pheromone ratios may underlie reproductive isolating mechanisms in vertebrates, as well as provide utility in pheromone-integrated control of invasive sea lamprey in the Great Lakes.

An Odor Interaction Model of Binary Odorant Mixtures by a Partial Differential Equation Method

Directory of Open Access Journals (Sweden)

Luchun Yan

2014-07-01

Full Text Available A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE method. Based on the measurement method (tangent-intercept method of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture’s odor intensity to the individual odorant’s relative odor activity value (OAV. Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.

Two-phase interfacial area and flow regime modeling in FLOWTRAN-TF code

International Nuclear Information System (INIS)

Smith, F.G. III; Lee, S.Y.; Flach, G.P.; Hamm, L.L.

1992-01-01

FLOWTRAN-TF is a new two-component, two-phase thermal-hydraulics code to capture the detailed assembly behavior associated with loss-of-coolant accident analyses in multichannel assemblies of the SRS reactors. The local interfacial area of the two-phase mixture is computed by summing the interfacial areas contributed by each of three flow regimes. For smooth flow regime transitions, the code uses an interpolation technique in terms of component void fraction for each basic flow regime

Two-way and three-way approaches to ultra high performance liquid chromatography-photodiode array dataset for the quantitative resolution of a two-component mixture containing ciprofloxacin and ornidazole.

Science.gov (United States)

Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda

2016-09-01

Two-way and three-way calibration models were applied to ultra high performance liquid chromatography with photodiode array data with coeluted peaks in the same wavelength and time regions for the simultaneous quantitation of ciprofloxacin and ornidazole in tablets. The chromatographic data cube (tensor) was obtained by recording chromatographic spectra of the standard and sample solutions containing ciprofloxacin and ornidazole with sulfadiazine as an internal standard as a function of time and wavelength. Parallel factor analysis and trilinear partial least squares were used as three-way calibrations for the decomposition of the tensor, whereas three-way unfolded partial least squares was applied as a two-way calibration to the unfolded dataset obtained from the data array of ultra high performance liquid chromatography with photodiode array detection. The validity and ability of two-way and three-way analysis methods were tested by analyzing validation samples: synthetic mixture, interday and intraday samples, and standard addition samples. Results obtained from two-way and three-way calibrations were compared to those provided by traditional ultra high performance liquid chromatography. The proposed methods, parallel factor analysis, trilinear partial least squares, unfolded partial least squares, and traditional ultra high performance liquid chromatography were successfully applied to the quantitative estimation of the solid dosage form containing ciprofloxacin and ornidazole. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Equilibrium moisture content of waste mixtures from post-consumer carton packaging.

Science.gov (United States)

Bacelos, M S; Freire, J T

2012-01-01

The manufacturing of boards and roof tiles is one of the routes to reuse waste from the recycled-carton-packaging process. Such a process requires knowledge of the hygroscopic behaviour of these carton-packaging waste mixtures in order to guarantee the quality of the final product (e.g. boards and roof tiles). Thus, with four carton-packaging waste mixtures of selected compositions (A, B, C and D), the sorption isotherms were obtained at air temperature of 20, 40 and 60 degrees C by using the static method. This permits one to investigate which model can relate the equilibrium moisture content of the mixture with that of a pure component through the mass fraction of each component in the mixtures. The results show that the experimental data can be well described by the weighted harmonic mean model. This suggests that the mean equilibrium moisture content of the carton-packaging mixture presents a non-linear relationship with each single, pure compound.

Biomarker- and similarity coefficient-based approaches to bacterial mixture characterization using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).

Science.gov (United States)

Zhang, Lin; Smart, Sonja; Sandrin, Todd R

2015-11-05

MALDI-TOF MS profiling has been shown to be a rapid and reliable method to characterize pure cultures of bacteria. Currently, there is keen interest in using this technique to identify bacteria in mixtures. Promising results have been reported with two- or three-isolate model systems using biomarker-based approaches. In this work, we applied MALDI-TOF MS-based methods to a more complex model mixture containing six bacteria. We employed: 1) a biomarker-based approach that has previously been shown to be useful in identification of individual bacteria in pure cultures and simple mixtures and 2) a similarity coefficient-based approach that is routinely and nearly exclusively applied to identification of individual bacteria in pure cultures. Both strategies were developed and evaluated using blind-coded mixtures. With regard to the biomarker-based approach, results showed that most peaks in mixture spectra could be assigned to those found in spectra of each component bacterium; however, peaks shared by two isolates as well as peaks that could not be assigned to any individual component isolate were observed. For two-isolate blind-coded samples, bacteria were correctly identified using both similarity coefficient- and biomarker-based strategies, while for blind-coded samples containing more than two isolates, bacteria were more effectively identified using a biomarker-based strategy.

Identifiability in N-mixture models: a large-scale screening test with bird data.

Science.gov (United States)

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

Nature and prevalence of non-additive toxic effects in industrially relevant mixtures of organic chemicals.

Science.gov (United States)

Parvez, Shahid; Venkataraman, Chandra; Mukherji, Suparna

2009-06-01

The concentration addition (CA) and the independent action (IA) models are widely used for predicting mixture toxicity based on its composition and individual component dose-response profiles. However, the prediction based on these models may be inaccurate due to interaction among mixture components. In this work, the nature and prevalence of non-additive effects were explored for binary, ternary and quaternary mixtures composed of hydrophobic organic compounds (HOCs). The toxicity of each individual component and mixture was determined using the Vibrio fischeri bioluminescence inhibition assay. For each combination of chemicals specified by the 2(n) factorial design, the percent deviation of the predicted toxic effect from the measured value was used to characterize mixtures as synergistic (positive deviation) and antagonistic (negative deviation). An arbitrary classification scheme was proposed based on the magnitude of deviation (d) as: additive (50%, class-IV) antagonistic/synergistic. Naphthalene, n-butanol, o-xylene, catechol and p-cresol led to synergism in mixtures while 1, 2, 4-trimethylbenzene and 1, 3-dimethylnaphthalene contributed to antagonism. Most of the mixtures depicted additive or antagonistic effect. Synergism was prominent in some of the mixtures, such as, pulp and paper, textile dyes, and a mixture composed of polynuclear aromatic hydrocarbons. The organic chemical industry mixture depicted the highest abundance of antagonism and least synergism. Mixture toxicity was found to depend on partition coefficient, molecular connectivity index and relative concentration of the components.

Anomalous relaxation in binary mixtures: a dynamic facilitation picture

International Nuclear Information System (INIS)

Moreno, A J; Colmenero, J

2007-01-01

Recent computational investigations of polymeric and non-polymeric binary mixtures have reported anomalous relaxation features when both components exhibit very different mobilities. Anomalous relaxation is characterized by sublinear power-law behaviour for mean-squared displacements, logarithmic decay in dynamic correlators, and a striking concave-to-convex crossover in the latter by tuning the relevant control parameter, in analogy with predictions of the mode-coupling theory for state points close to higher-order transitions. We present Monte Carlo simulations on a coarse-grained model for relaxation in binary mixtures. The liquid structure is substituted by a three-dimensional array of cells. A spin variable is assigned to each cell, representing unexcited and excited local states of a mobility field. Changes in local mobility (spin flip) are permitted according to kinetic constraints determined by the mobilities of the neighbouring cells. We introduce two types of cell ('fast' and 'slow') with very different rates for spin flip. This coarse-grained model qualitatively reproduces the mentioned anomalous relaxation features observed for real binary mixtures

Two-component gravitational instability in spiral galaxies

Science.gov (United States)

Marchuk, A. A.; Sotnikova, N. Y.

2018-04-01

We applied a criterion of gravitational instability, valid for two-component and infinitesimally thin discs, to observational data along the major axis for seven spiral galaxies of early types. Unlike most papers, the dispersion equation corresponding to the criterion was solved directly without using any approximation. The velocity dispersion of stars in the radial direction σR was limited by the range of possible values instead of a fixed value. For all galaxies, the outer regions of the disc were analysed up to R ≤ 130 arcsec. The maximal and sub-maximal disc models were used to translate surface brightness into surface density. The largest destabilizing disturbance stars can exert on a gaseous disc was estimated. It was shown that the two-component criterion differs a little from the one-fluid criterion for galaxies with a large surface gas density, but it allows to explain large-scale star formation in those regions where the gaseous disc is stable. In the galaxy NGC 1167 star formation is entirely driven by the self-gravity of the stars. A comparison is made with the conventional approximations which also include the thickness effect and with models for different sound speed cg. It is shown that values of the effective Toomre parameter correspond to the instability criterion of a two-component disc Qeff < 1.5-2.5. This result is consistent with previous theoretical and observational studies.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

Directory of Open Access Journals (Sweden)

Jan Hasenauer

2014-07-01

Full Text Available Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

Science.gov (United States)

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

RETRAN nonequilibrium two-phase flow model for operational transient analyses

International Nuclear Information System (INIS)

Paulsen, M.P.; Hughes, E.D.

1982-01-01

The field balance equations, flow-field models, and equation of state for a nonequilibrium two-phase flow model for RETRAN are given. The differential field balance model equations are: (1) conservation of mixture mass; (2) conservation of vapor mass; (3) balance of mixture momentum; (4) a dynamic-slip model for the velocity difference; and (5) conservation of mixture energy. The equation of state is formulated such that the liquid phase may be subcooled, saturated, or superheated. The vapor phase is constrained to be at the saturation state. The dynamic-slip model includes wall-to-phase and interphase momentum exchanges. A mechanistic vapor generation model is used to describe vapor production under bulk subcooling conditions. The speed of sound for the mixture under nonequilibrium conditions is obtained from the equation of state formulation. The steady-state and transient solution methods are described

Multi Parameter Flow Meter for On-Line Measurement of Gas Mixture Composition

Directory of Open Access Journals (Sweden)

Egbert van der Wouden

2015-04-01

Full Text Available In this paper we describe the development of a system and model to analyze the composition of gas mixtures up to four components. The system consists of a Coriolis mass flow sensor, density, pressure and thermal flow sensor. With this system it is possible to measure the viscosity, density, heat capacity and flow rate of the medium. In a next step the composition can be analyzed if the constituents of the mixture are known. This makes the approach universally applicable to all gasses as long as the number of components does not exceed the number of measured properties and as long as the properties are measured with a sufficient accuracy. We present measurements with binary and ternary gas mixtures, on compositions that range over an order of magnitude in value for the physical properties. Two platforms for analyses are presented. The first platform consists of sensors realized with MEMS fabrication technology. This approach allows for a system with a high level of integration. With this system we demonstrate a proof of principle for the analyses of binary mixtures with an accuracy of 10%. In the second platform we utilize more mature steel sensor technology to demonstrate the potential of this approach. We show that with this technique, binary mixtures can be measured within 1% and ternary gas mixtures within 3%.

Estimating animal abundance with N-mixture models using the R-INLA package for R

KAUST Repository

Meehan, Timothy D.

2017-05-03

Successful management of wildlife populations requires accurate estimates of abundance. Abundance estimates can be confounded by imperfect detection during wildlife surveys. N-mixture models enable quantification of detection probability and often produce abundance estimates that are less biased. The purpose of this study was to demonstrate the use of the R-INLA package to analyze N-mixture models and to compare performance of R-INLA to two other common approaches -- JAGS (via the runjags package), which uses Markov chain Monte Carlo and allows Bayesian inference, and unmarked, which uses Maximum Likelihood and allows frequentist inference. We show that R-INLA is an attractive option for analyzing N-mixture models when (1) familiar model syntax and data format (relative to other R packages) are desired, (2) survey level covariates of detection are not essential, (3) fast computing times are necessary (R-INLA is 10 times faster than unmarked, 300 times faster than JAGS), and (4) Bayesian inference is preferred.

Developing a Model Component

Science.gov (United States)

Fields, Christina M.

2013-01-01

The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) was a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The initial purpose of the UCTS was to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The UCTS is designed with the capability of servicing future space vehicles; including all Space Station Requirements necessary for the MPLM Modules. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems during their development. As an intern at Kennedy Space Center (KSC), my assignment was to develop a model component for the UCTS. I was given a fluid component (dryer) to model in Simulink. I completed training for UNIX and Simulink. The dryer is a Catch All replaceable core type filter-dryer. The filter-dryer provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-dryer also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. The filter-dryer was modeled by determining affects it has on the pressure and velocity of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my filter-dryer model in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements. I participated in Simulation meetings and was involved in the subsystem design process and team collaborations. I gained valuable work experience and insight into a career path as an engineer.

A hybrid pareto mixture for conditional asymmetric fat-tailed distributions.

Science.gov (United States)

Carreau, Julie; Bengio, Yoshua

2009-07-01

In many cases, we observe some variables X that contain predictive information over a scalar variable of interest Y , with (X,Y) pairs observed in a training set. We can take advantage of this information to estimate the conditional density p(Y|X = x). In this paper, we propose a conditional mixture model with hybrid Pareto components to estimate p(Y|X = x). The hybrid Pareto is a Gaussian whose upper tail has been replaced by a generalized Pareto tail. A third parameter, in addition to the location and spread parameters of the Gaussian, controls the heaviness of the upper tail. Using the hybrid Pareto in a mixture model results in a nonparametric estimator that can adapt to multimodality, asymmetry, and heavy tails. A conditional density estimator is built by modeling the parameters of the mixture estimator as functions of X. We use a neural network to implement these functions. Such conditional density estimators have important applications in many domains such as finance and insurance. We show experimentally that this novel approach better models the conditional density in terms of likelihood, compared to competing algorithms: conditional mixture models with other types of components and a classical kernel-based nonparametric model.

Optimal mixture experiments

CERN Document Server

Sinha, B K; Pal, Manisha; Das, P

2014-01-01

The book dwells mainly on the optimality aspects of mixture designs. As mixture models are a special case of regression models, a general discussion on regression designs has been presented, which includes topics like continuous designs, de la Garza phenomenon, Loewner order domination, Equivalence theorems for different optimality criteria and standard optimality results for single variable polynomial regression and multivariate linear and quadratic regression models. This is followed by a review of the available literature on estimation of parameters in mixture models. Based on recent research findings, the volume also introduces optimal mixture designs for estimation of optimum mixing proportions in different mixture models, which include Scheffé’s quadratic model, Darroch-Waller model, log- contrast model, mixture-amount models, random coefficient models and multi-response model.  Robust mixture designs and mixture designs in blocks have been also reviewed. Moreover, some applications of mixture desig...

Heat transfer and pressure drop for air-water mixtures in an isoflux vertical annulus

International Nuclear Information System (INIS)

Khattab, M.; El-Sallak, M.; Morcos, S.M.; Salama, A.

1996-01-01

Heat transfer and pressure drop in flows of air-water mixtures have been investigated experimentally in an isoflux vertical annulus. The superficial liquid Reynolds number, as a reference parameter, varied from 4500 to 30 000, at different values of gas-to-liquid superficial velocity ratios up to 20 and surface heat fluxes from 50 to 240 kW/m 2 . Enhancement of the two-phase heat transfer coefficient is pronounced particularly at low liquid superficial velocities. The results are correlated and compared with some models of two-phase, two-component flows for air-water mixtures within their range of validity. Satisfactory agreement is obtained from the trend of the experimental data. (orig.) [de

General mixture item response models with different item response structures: Exposition with an application to Likert scales.

Science.gov (United States)

Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

2018-01-10

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person's responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category ("neither agree nor disagree") is taken to be qualitatively similar to the other categories, and is taken to provide information about the person's endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person's willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.

Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data

DEFF Research Database (Denmark)

Røge, Rasmus; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard

2017-01-01

spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises-Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain...... Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians......Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying...

Method for separating gaseous mixtures of isotopes

International Nuclear Information System (INIS)

Neimann, H.J.; Schuster, E.; Kersting, A.

1976-01-01

A gaseous mixture of isotopes is separated by laser excitation of the isotope mixture with a narrow band of wavelengths, molecularly exciting mainly the isotope to be separated and thereby promoting its reaction with its chemical partner which is excited in a separate chamber. The excited isotopes and the chemical partner are mixed, perhaps in a reaction chamber to which the two excited components are conducted by very short conduits. The improvement of this method is the physical separation of the isotope mixture and its partner during excitation. The reaction between HCl and the mixture of 238 UF 6 and 235 UF 6 is discussed

Toy model for two chiral nonets

International Nuclear Information System (INIS)

Fariborz, Amir H.; Jora, Renata; Schechter, Joseph

2005-01-01

Motivated by the possibility that nonets of scalar mesons might be described as mixtures of 'two quark' and 'four quark' components, we further study a toy model in which corresponding chiral nonets (containing also the pseudoscalar partners) interact with each other. Although the 'two quark' and 'four quark' chiral fields transform identically under SU(3) L xSU(3) R transformations, they transform differently under the U(1) A transformation which essentially counts total (quark+antiquark) content of the mesons. To implement this, we formulate an effective Lagrangian which mocks up the U(1) A behavior of the underlying QCD. We derive generating equations which yield Ward identity type relations based only on the assumed symmetry structure. This is applied to the mass spectrum of the low lying pseudoscalars and scalars, as well as their 'excitations'. Assuming isotopic spin invariance, it is possible to disentangle the amount of 'two quark' vs 'four quark' content in the pseudoscalar π,K,η-type states and in the scalar κ-type states. It is found that a small 'four quark' content in the lightest pseudoscalars is consistent with a large 'four quark' content in the lightest of the scalar κ mesons. The present toy model also allows one to easily estimate the strength of a 'four quark' vacuum condensate. There seems to be a rich and interesting structure

Toxicity of a binary mixture on Daphnia magna: biological effects of uranium and selenium isolated and in mixture

International Nuclear Information System (INIS)

Zeman, F.

2008-10-01

Among the multiple substances that affect freshwater ecosystems, uranium and selenium are two pollutants found worldwide in the environment, alone and in mixture. The aim of this thesis work was to investigate the effect of uranium and selenium mixture on daphnia (Daphnia magna). Studying effects of a mixture requires the assessment of the effect of single substances. Thus, the first experiments were performed on single substance. Acute toxicity data were obtained: EC 50 48h = 0, 39±0, 04 mg.L -1 for uranium and EC 50 48h 1, 86±0, 85 mg.L -1 for selenium. Chronic effects were also studied. Data on fecundity showed an EC 10 reproduction of 14±7 μg. L -1 for uranium and of 215±25 μg. L -1 for selenium. Uranium-selenium mixture toxicity experiments were performed and revealed an antagonistic effect. This study further demonstrates the importance of taking into consideration different elements in binary mixture studies such as the choice of reference models (concentration addition or independent action), statistical method, time exposure and endpoints. Using integrated parameters like energy budget was shown to be an interesting way to better understand interactions. An approach including calculation of chemical speciation in the medium and bioaccumulation measurements in the organism permits assumptions to be made on the nature of possible interactions between mixture components (toxico-dynamic et toxico-kinetic interactions). (author)

Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

Science.gov (United States)

Noma, Hisashi; Matsui, Shigeyuki

2013-05-20

The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

Annotated Computer Output for Illustrative Examples of Clustering Using the Mixture Method and Two Comparable Methods from SAS.

Science.gov (United States)

1987-06-26

BUREAU OF STANDAR-S1963-A Nw BOM -ILE COPY -. 4eo .?3sa.9"-,,A WIN* MAT HEMATICAL SCIENCES _*INSTITUTE AD-A184 687 DTICS!ELECTE ANNOTATED COMPUTER OUTPUT...intoduction to the use of mixture models in clustering. Cornell University Biometrics Unit Technical Report BU-920-M and Mathematical Sciences Institute...mixture method and two comparable methods from SAS. Cornell University Biometrics Unit Technical Report BU-921-M and Mathematical Sciences Institute

A GENERALIZED TWO-COMPONENT MODEL OF SOLAR WIND TURBULENCE AND AB INITIO DIFFUSION MEAN-FREE PATHS AND DRIFT LENGTHSCALES OF COSMIC RAYS

Energy Technology Data Exchange (ETDEWEB)

Wiengarten, T.; Fichtner, H.; Kleimann, J.; Scherer, K. [Institut für Theoretische Physik IV, Ruhr-Universität Bochum (Germany); Oughton, S. [Department of Mathematics, University of Waikato, Hamilton 3240 (New Zealand); Engelbrecht, N. E. [Center for Space Research, North-West University, Potchefstroom 2520 (South Africa)

2016-12-10

We extend a two-component model for the evolution of fluctuations in the solar wind plasma so that it is fully three-dimensional (3D) and also coupled self-consistently to the large-scale magnetohydrodynamic equations describing the background solar wind. The two classes of fluctuations considered are a high-frequency parallel-propagating wave-like piece and a low-frequency quasi-two-dimensional component. For both components, the nonlinear dynamics is dominanted by quasi-perpendicular spectral cascades of energy. Driving of the fluctuations by, for example, velocity shear and pickup ions is included. Numerical solutions to the new model are obtained using the Cronos framework, and validated against previous simpler models. Comparing results from the new model with spacecraft measurements, we find improved agreement relative to earlier models that employ prescribed background solar wind fields. Finally, the new results for the wave-like and quasi-two-dimensional fluctuations are used to calculate ab initio diffusion mean-free paths and drift lengthscales for the transport of cosmic rays in the turbulent solar wind.

A GENERALIZED TWO-COMPONENT MODEL OF SOLAR WIND TURBULENCE AND AB INITIO DIFFUSION MEAN-FREE PATHS AND DRIFT LENGTHSCALES OF COSMIC RAYS

International Nuclear Information System (INIS)

Wiengarten, T.; Fichtner, H.; Kleimann, J.; Scherer, K.; Oughton, S.; Engelbrecht, N. E.

2016-01-01

We extend a two-component model for the evolution of fluctuations in the solar wind plasma so that it is fully three-dimensional (3D) and also coupled self-consistently to the large-scale magnetohydrodynamic equations describing the background solar wind. The two classes of fluctuations considered are a high-frequency parallel-propagating wave-like piece and a low-frequency quasi-two-dimensional component. For both components, the nonlinear dynamics is dominanted by quasi-perpendicular spectral cascades of energy. Driving of the fluctuations by, for example, velocity shear and pickup ions is included. Numerical solutions to the new model are obtained using the Cronos framework, and validated against previous simpler models. Comparing results from the new model with spacecraft measurements, we find improved agreement relative to earlier models that employ prescribed background solar wind fields. Finally, the new results for the wave-like and quasi-two-dimensional fluctuations are used to calculate ab initio diffusion mean-free paths and drift lengthscales for the transport of cosmic rays in the turbulent solar wind.

Support vector regression and artificial neural network models for stability indicating analysis of mebeverine hydrochloride and sulpiride mixtures in pharmaceutical preparation: A comparative study

Science.gov (United States)

Naguib, Ibrahim A.; Darwish, Hany W.

2012-02-01

A comparison between support vector regression (SVR) and Artificial Neural Networks (ANNs) multivariate regression methods is established showing the underlying algorithm for each and making a comparison between them to indicate the inherent advantages and limitations. In this paper we compare SVR to ANN with and without variable selection procedure (genetic algorithm (GA)). To project the comparison in a sensible way, the methods are used for the stability indicating quantitative analysis of mixtures of mebeverine hydrochloride and sulpiride in binary mixtures as a case study in presence of their reported impurities and degradation products (summing up to 6 components) in raw materials and pharmaceutical dosage form via handling the UV spectral data. For proper analysis, a 6 factor 5 level experimental design was established resulting in a training set of 25 mixtures containing different ratios of the interfering species. An independent test set consisting of 5 mixtures was used to validate the prediction ability of the suggested models. The proposed methods (linear SVR (without GA) and linear GA-ANN) were successfully applied to the analysis of pharmaceutical tablets containing mebeverine hydrochloride and sulpiride mixtures. The results manifest the problem of nonlinearity and how models like the SVR and ANN can handle it. The methods indicate the ability of the mentioned multivariate calibration models to deconvolute the highly overlapped UV spectra of the 6 components' mixtures, yet using cheap and easy to handle instruments like the UV spectrophotometer.

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

International Nuclear Information System (INIS)

Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio

2013-01-01

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO 4 (NIS-inhibitor) dosed at a fixed ratio of EC 10 that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of mixtures of

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

Energy Technology Data Exchange (ETDEWEB)

Thienpont, Benedicte; Barata, Carlos [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Raldúa, Demetrio, E-mail: drpqam@cid.csic.es [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Maladies Rares: Génétique et Métabolisme (MRGM), University of Bordeaux, EA 4576, F-33400 Talence (France)

2013-06-01

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of

Equilibrium based analytical model for estimation of pressure magnification during deflagration of hydrogen air mixtures

Energy Technology Data Exchange (ETDEWEB)

Karanam, Aditya; Sharma, Pavan K.; Ganju, Sunil; Singh, Ram Kumar [Bhabha Atomic Research Centre (BARC), Mumbai (India). Reactor Safety Div.

2016-12-15

During postulated accident sequences in nuclear reactors, hydrogen may get released from the core and form a flammable mixture in the surrounding containment structure. Ignition of such mixtures and the subsequent pressure rise are an imminent threat for safe and sustainable operation of nuclear reactors. Methods for evaluating post ignition characteristics are important for determining the design safety margins in such scenarios. This study presents two thermo-chemical models for determining the post ignition state. The first model is based on internal energy balance while the second model uses the concept of element potentials to minimize the free energy of the system with internal energy imposed as a constraint. Predictions from both the models have been compared against published data over a wide range of mixture compositions. Important differences in the regions close to flammability limits and for stoichiometric mixtures have been identified and explained. The equilibrium model has been validated for varied temperatures and pressures representative of initial conditions that may be present in the containment during accidents. Special emphasis has been given to the understanding of the role of dissociation and its effect on equilibrium pressure, temperature and species concentrations.

Equilibrium based analytical model for estimation of pressure magnification during deflagration of hydrogen air mixtures

International Nuclear Information System (INIS)

Karanam, Aditya; Sharma, Pavan K.; Ganju, Sunil; Singh, Ram Kumar

2016-01-01

During postulated accident sequences in nuclear reactors, hydrogen may get released from the core and form a flammable mixture in the surrounding containment structure. Ignition of such mixtures and the subsequent pressure rise are an imminent threat for safe and sustainable operation of nuclear reactors. Methods for evaluating post ignition characteristics are important for determining the design safety margins in such scenarios. This study presents two thermo-chemical models for determining the post ignition state. The first model is based on internal energy balance while the second model uses the concept of element potentials to minimize the free energy of the system with internal energy imposed as a constraint. Predictions from both the models have been compared against published data over a wide range of mixture compositions. Important differences in the regions close to flammability limits and for stoichiometric mixtures have been identified and explained. The equilibrium model has been validated for varied temperatures and pressures representative of initial conditions that may be present in the containment during accidents. Special emphasis has been given to the understanding of the role of dissociation and its effect on equilibrium pressure, temperature and species concentrations.

Volatility of components of saturated vapours of UCl4-CsCl and UCl4-LiCl molten mixtures

International Nuclear Information System (INIS)

Smirnov, M.V.; Kudyakov, V.Ya.; Salyulev, A.B.; Komarov, V.E.; Posokhin, Yu.V.; Afonichkin, V.K.

1979-01-01

The flow method has been used for measuring the volatility of the components from UCl 4 -CsCl and UCl 4 -LiCl melted mixtures containing 2.0, 5.0, 12.0, 25.0, 33.0, 50.0, 67.0, and 83.0 mol.% of UCl 4 within the temperature ranges of 903-1188 K and 740-1200 K, respectively. The chemical composition of saturated vapours above the melted salts has been determined. The melted mixtures in question exhibit negative deviation from ideal behaviour. Made was the conclusion about the presence in a vapour phase, along with monomeric UCl 4 , LiCl, CsCl and Li 2 Cl 2 , Cs 2 Cl 2 dimers of double compounds of the MeUCl 5 most probable composition. Their absolute contribution into a total pressure above the UCl 4 -CsCl melted mixtures is considerably smaller than above the UCl 4 -LiCl mixtures

Global existence and blow-up phenomena for two-component Degasperis-Procesi system and two-component b-family system

OpenAIRE

Liu, Jingjing; Yin, Zhaoyang

2014-01-01

This paper is concerned with global existence and blow-up phenomena for two-component Degasperis-Procesi system and two-component b-family system. The strategy relies on our observation on new conservative quantities of these systems. Several new global existence results and a new blowup result of strong solutions to the two-component Degasperis- Procesi system and the two-component b-family system are presented by using these new conservative quantities.

[Theoretical modeling and experimental research on direct compaction characteristics of multi-component pharmaceutical powders based on the Kawakita equation].

Science.gov (United States)

Si, Guo-Ning; Chen, Lan; Li, Bao-Guo

2014-04-01

Base on the Kawakita powder compression equation, a general theoretical model for predicting the compression characteristics of multi-components pharmaceutical powders with different mass ratios was developed. The uniaxial flat-face compression tests of powder lactose, starch and microcrystalline cellulose were carried out, separately. Therefore, the Kawakita equation parameters of the powder materials were obtained. The uniaxial flat-face compression tests of the powder mixtures of lactose, starch, microcrystalline cellulose and sodium stearyl fumarate with five mass ratios were conducted, through which, the correlation between mixture density and loading pressure and the Kawakita equation curves were obtained. Finally, the theoretical prediction values were compared with experimental results. The analysis showed that the errors in predicting mixture densities were less than 5.0% and the errors of Kawakita vertical coordinate were within 4.6%, which indicated that the theoretical model could be used to predict the direct compaction characteristics of multi-component pharmaceutical powders.

Component separation in harmonically trapped boson-fermion mixtures

DEFF Research Database (Denmark)

Nygaard, Nicolai; Mølmer, Klaus

1999-01-01

We present a numerical study of mixed boson-fermion systems at zero temperature in isotropic and anise tropic harmonic traps. We investigate the phenomenon of component separation as a function of the strength ut the interparticle interaction. While solving a Gross-Pitaevskii mean-field equation ...... for the boson distribution in the trap, we utilize two different methods to extract the density profile of the fermion component; a semiclassical Thomas-Fermi approximation and a quantum-mechanical Slater determinant Schrodinger equation....

Modeling the effects of binary mixtures on survival in time.

NARCIS (Netherlands)

Baas, J.; van Houte, B.P.P.; van Gestel, C.A.M.; Kooijman, S.A.L.M.

2007-01-01

In general, effects of mixtures are difficult to describe, and most of the models in use are descriptive in nature and lack a strong mechanistic basis. The aim of this experiment was to develop a process-based model for the interpretation of mixture toxicity measurements, with effects of binary

Validation of a mixture-averaged thermal diffusion model for premixed lean hydrogen flames

Science.gov (United States)

Schlup, Jason; Blanquart, Guillaume

2018-03-01

The mixture-averaged thermal diffusion model originally proposed by Chapman and Cowling is validated using multiple flame configurations. Simulations using detailed hydrogen chemistry are done on one-, two-, and three-dimensional flames. The analysis spans flat and stretched, steady and unsteady, and laminar and turbulent flames. Quantitative and qualitative results using the thermal diffusion model compare very well with the more complex multicomponent diffusion model. Comparisons are made using flame speeds, surface areas, species profiles, and chemical source terms. Once validated, this model is applied to three-dimensional laminar and turbulent flames. For these cases, thermal diffusion causes an increase in the propagation speed of the flames as well as increased product chemical source terms in regions of high positive curvature. The results illustrate the necessity for including thermal diffusion, and the accuracy and computational efficiency of the mixture-averaged thermal diffusion model.

A Mixture Model of Consumers' Intended Purchase Decisions for Genetically Modified Foods

OpenAIRE

Kristine M. Grimsrud; Robert P. Berrens; Ron C. Mittelhammer

2006-01-01

A finite probability mixture model is used to analyze the existence of multiple market segments for a pre-market good. The approach has at least two principal benefits. First, the model is capable of identifying likely market segments and their differentiating characteristics. Second, the model can be used to estimate the discount different consumer groups require to purchase the good. The model is illustrated using stated preference survey data collected on consumer responses to the potentia...

[A study of the properties of tablets from mixtures of two size degrees of alpha-lactose monohydrate and microcrystalline cellulose].

Science.gov (United States)

Muzíková, J

2006-03-01

The paper examines the strength and disintegration time of compacts from the mixtures of two types of Tablettosas. Tablettosa 70 and Tablettosa 100 with microcrystalline cellulose represented by Vivapur 102. The mixtures of dry binders were prepared in the ratios of 3:1, 1:1, and 1:3. The effect of two concentrations of the lubricant magnesium stearate on the strength and disintegration time of compacts was also examined. Tablet strength increased with higher representation of microcrystalline cellulose in the mixture, and decreased with higher stearate concentration. The compacts from the mixtures with Tablettosa 100 showed higher strength. Disintegration time was highest in the compacts with the largest perccintage of microcrystalline cellulose, and longer in the case of the mixtures with Tablettosa 100. Stearate did not exert a negative effect on disintegration time. In the mixtures of Tablettosas with Vivapur 102 in a ratio of 1:1, the effect of the model active ingredient acetylsalicylic acid on the above-mentioned properties of tablets was tested. acetylsalicylic acid produced a further decrease in the strength of compacts and shortened the disintegration time in more instances in the cased of the mixtures with Tahlettosa 100.

Gaussian mixture models and semantic gating improve reconstructions from human brain activity

Directory of Open Access Journals (Sweden)

Sanne eSchoenmakers

2015-01-01

Full Text Available Better acquisition protocols and analysis techniques are making it possible to use fMRI to obtain highly detailed visualizations of brain processes. In particular we focus on the reconstruction of natural images from BOLD responses in visual cortex. We expand our linear Gaussian framework for percept decoding with Gaussian mixture models to better represent the prior distribution of natural images. Reconstruction of such images then boils down to probabilistic inference in a hybrid Bayesian network. In our set-up, different mixture components correspond to different character categories. Our framework can automatically infer higher-order semantic categories from lower-level brain areas. Furthermore the framework can gate semantic information from higher-order brain areas to enforce the correct category during reconstruction. When categorical information is not available, we show that automatically learned clusters in the data give a similar improvement in reconstruction. The hybrid Bayesian network leads to highly accurate reconstructions in both supervised and unsupervised settings.

Variable selection for mixture and promotion time cure rate models.

Science.gov (United States)

Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

2016-11-16

Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

Overview of online two-dimensional liquid chromatography based on cell membrane chromatography for screening target components from traditional Chinese medicines.

Science.gov (United States)

Muhammad, Saqib; Han, Shengli; Xie, Xiaoyu; Wang, Sicen; Aziz, Muhammad Majid

2017-01-01

Cell membrane chromatography is a simple, specific, and time-saving technique for studying drug-receptor interactions, screening of active components from complex mixtures, and quality control of traditional Chinese medicines. However, the short column life, low sensitivity, low column efficiency (so cannot resolve satisfactorily mixture of compounds), low peak capacity, and inefficient in structure identification were bottleneck in its application. Combinations of cell membrane chromatography with multidimensional chromatography such as two-dimensional liquid chromatography and high sensitivity detectors like mass have significantly reduced many of the above-mentioned shortcomings. This paper provides an overview of the current advances in online two-dimensional-based cell membrane chromatography for screening target components from traditional Chinese medicines with particular emphasis on the instrumentation, preparation of cell membrane stationary phase, advantages, and disadvantages compared to alternative approaches. The last section of the review summarizes the applications of the online two-dimensional high-performance liquid chromatography based cell membrane chromatography reported since its emergence to date (2010-June 2016). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

Directory of Open Access Journals (Sweden)

Tabitha A Graves

Full Text Available Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic and bear rubs (opportunistic. We used hierarchical abundance models (N-mixture models with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1 lead to the selection of the same variables as important and (2 provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3 yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight, and (4 improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed

A two-component copula with links to insurance

Directory of Open Access Journals (Sweden)

Ismail S.

2017-12-01

Full Text Available This paper presents a new copula to model dependencies between insurance entities, by considering how insurance entities are affected by both macro and micro factors. The model used to build the copula assumes that the insurance losses of two companies or lines of business are related through a random common loss factor which is then multiplied by an individual random company factor to get the total loss amounts. The new two-component copula is not Archimedean and it extends the toolkit of copulas for the insurance industry.

Analysis of Influence of Foaming Mixture Components on Structure and Properties of Foam Glass

Science.gov (United States)

Karandashova, N. S.; Goltsman, B. M.; Yatsenko, E. A.

2017-11-01

It is recommended to use high-quality thermal insulation materials to increase the energy efficiency of buildings. One of the best thermal insulation materials is foam glass - durable, porous material that is resistant to almost any effect of substance. Glass foaming is a complex process depending on the foaming mode and the initial mixture composition. This paper discusses the influence of all components of the mixture - glass powder, foaming agent, enveloping material and water - on the foam glass structure. It was determined that glass powder is the basis of the future material. A foaming agent forms a gas phase in the process of thermal decomposition. This aforementioned gas foams the viscous glass mass. The unreacted residue thus changes a colour of the material. The enveloping agent slows the foaming agent decomposition preventing its premature burning out and, in addition, helps to accelerate the sintering of glass particles. The introduction of water reduces the viscosity of the foaming mixture making it evenly distributed and also promotes the formation of water gas that additionally foams the glass mass. The optimal composition for producing the foam glass with the density of 150 kg/m3 is defined according to the results of the research.

Challenges in modelling the random structure correctly in growth mixture models and the impact this has on model mixtures.

Science.gov (United States)

Gilthorpe, M S; Dahly, D L; Tu, Y K; Kubzansky, L D; Goodman, E

2014-06-01

Lifecourse trajectories of clinical or anthropological attributes are useful for identifying how our early-life experiences influence later-life morbidity and mortality. Researchers often use growth mixture models (GMMs) to estimate such phenomena. It is common to place constrains on the random part of the GMM to improve parsimony or to aid convergence, but this can lead to an autoregressive structure that distorts the nature of the mixtures and subsequent model interpretation. This is especially true if changes in the outcome within individuals are gradual compared with the magnitude of differences between individuals. This is not widely appreciated, nor is its impact well understood. Using repeat measures of body mass index (BMI) for 1528 US adolescents, we estimated GMMs that required variance-covariance constraints to attain convergence. We contrasted constrained models with and without an autocorrelation structure to assess the impact this had on the ideal number of latent classes, their size and composition. We also contrasted model options using simulations. When the GMM variance-covariance structure was constrained, a within-class autocorrelation structure emerged. When not modelled explicitly, this led to poorer model fit and models that differed substantially in the ideal number of latent classes, as well as class size and composition. Failure to carefully consider the random structure of data within a GMM framework may lead to erroneous model inferences, especially for outcomes with greater within-person than between-person homogeneity, such as BMI. It is crucial to reflect on the underlying data generation processes when building such models.

Composition measurements of binary mixture droplets by rainbow refractometry.

Science.gov (United States)

Wilms, J; Weigand, B

2007-04-10

So far, refractive index measurements by rainbow refractometry have been used to determine the temperature of single droplets and ensembles of droplets. Rainbow refractometry is, for the first time, to the best of our knowledge, applied to measure composition histories of evaporating, binary mixture droplets. An evaluation method is presented that makes use of Airy theory and the simultaneous size measurement by Mie scattering imaging. The method further includes an empirical correction function for a certain diameter and refractive index range. The measurement uncertainty was investigated by numerical simulations with Lorenz-Mie theory. For the experiments, an optical levitation setup was used allowing for long measurement periods. Temperature measurements of single-component droplets at different temperature levels are shown to demonstrate the accuracy of rainbow refractometry. Measurements of size and composition histories of binary mixture droplets are presented for two different mixtures. Experimental results show good agreement with numerical results using a rapid-mixing model.

Composition measurements of binary mixture droplets by rainbow refractometry

International Nuclear Information System (INIS)

Wilms, J.; Weigand, B.

2007-01-01

So far, refractive index measurements by rainbow refractometry have been used to determine the temperature of single droplets and ensembles of droplets. Rainbow refractometry is, for the first time, to the best of our knowledge, applied to measure composition histories of evaporating, binary mixture droplets. An evaluation method is presented that makes use of Airy theory and the simultaneous size measurement by Mie scattering imaging. The method further includes an empirical correction function for a certain diameter and refractive index range. The measurement uncertainty was investigated by numerical simulations with Lorenz-Mie theory. For the experiments, an optical levitation setup was used allowing for long measurement periods. Temperature measurements of single-component droplets at different temperature levels are shown to demonstrate the accuracy of rainbow refractometry. Measurements of size and composition histories of binary mixture droplets are presented for two different mixtures. Experimental results show good agreement with numerical results using a rapid-mixing model

Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency.

Science.gov (United States)

Tan, Yin-Yin Sarah; Mueller, Shane T

2016-09-01

Previous research (e.g., cultural consensus theory (Romney, Weller, & Batchelder, American Anthropologist, 88, 313-338, 1986); cultural mixture modeling (Mueller & Veinott, 2008)) has used overt response patterns (i.e., responses to questionnaires and surveys) to identify whether a group shares a single coherent attitude or belief set. Yet many domains in social science have focused on implicit attitudes that are not apparent in overt responses but still may be detected via response time patterns. We propose a method for modeling response times as a mixture of Gaussians, adapting the strong-consensus model of cultural mixture modeling to model this implicit measure of knowledge strength. We report the results of two behavioral experiments and one simulation experiment that establish the usefulness of the approach, as well as some of the boundary conditions under which distinct groups of shared agreement might be recovered, even when the group identity is not known. The results reveal that the ability to recover and identify shared-belief groups depends on (1) the level of noise in the measurement, (2) the differential signals for strong versus weak attitudes, and (3) the similarity between group attitudes. Consequently, the method shows promise for identifying latent groups among a population whose overt attitudes do not differ, but whose implicit or covert attitudes or knowledge may differ.

Investigation into the performance of different models for predicting stutter.

Science.gov (United States)

Bright, Jo-Anne; Curran, James M; Buckleton, John S

2013-07-01

In this paper we have examined five possible models for the behaviour of the stutter ratio, SR. These were two log-normal models, two gamma models, and a two-component normal mixture model. A two-component normal mixture model was chosen with different behaviours of variance; at each locus SR was described with two distributions, both with the same mean. The distributions have difference variances: one for the majority of the observations and a second for the less well-behaved ones. We apply each model to a set of known single source Identifiler™, NGM SElect™ and PowerPlex(®) 21 DNA profiles to show the applicability of our findings to different data sets. SR determined from the single source profiles were compared to the calculated SR after application of the models. The model performance was tested by calculating the log-likelihoods and comparing the difference in Akaike information criterion (AIC). The two-component normal mixture model systematically outperformed all others, despite the increase in the number of parameters. This model, as well as performing well statistically, has intuitive appeal for forensic biologists and could be implemented in an expert system with a continuous method for DNA interpretation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Are separate-phase thermal-hydraulic models better than mixture-fluid approaches? It depends. Rather not

International Nuclear Information System (INIS)

Hoeld, A.

2004-01-01

The thermal-hydraulic theory of single- and especially two-phase flow systems used for plant transient analysis is dominated by separate-phase models. The corresponding mostly very comprehensive codes (TRAC, RELAP, CATHARE, ATHLET etc.) are looked as to be by far more efficient than a 3 eq. mixture-fluid approach and code also if they show deficiencies in describing flow situations within inner loops as for example the distribution into parallel channels (and thus the simulation of 3D thermal-hydraulic phenomena). This may be justified if comparing them to the very simple 'homogeneous equilibrium models (HEM)', but not if looking to the more refined non-homogeneous 'separate-region' mixture-fluid approaches based on appropriate drift-flux correlation packages which can have, on the contrary, enormous advantages with respect to such separate-phase models. Especially if comparing the basic (and starting) eqs. of such theoretical models of both types the differences are remarkable. Single-phase and mixture-fluid models start from genuine conservation eqs. for mass, energy and momentum, demanding (in case of two-phase flow) additionally an adequate drift flux package (in order to get a relation for a fourth independent variable), a heat transfer coefficients package (over the whole range of the possible fields of application) and correlations for single- and two-phase friction. The other types of models are looking at each phase separately with corresponding 'field' eqs. for each phase, connected by exchange (=closure) terms which substitute the classical constitutive packages for drift, heat transfer and friction. That the drift-flux, heat transfer into a coolant channel and friction along a wall and between the phases is described better by a separate-phase approach is at least doubtful. The corresponding mixture-fluid correlations are based over a wide range on a treasure of experience and measurements, their pseudo-stationary treatment can (due to their small time

Feedback loops and temporal misalignment in component-based hydrologic modeling

Science.gov (United States)

Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.

2011-12-01

In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.

Two-component model application for error calculus in the environmental monitoring data analysis

International Nuclear Information System (INIS)

Carvalho, Maria Angelica G.; Hiromoto, Goro

2002-01-01

Analysis and interpretation of results of an environmental monitoring program is often based on the evaluation of the mean value of a particular set of data, which is strongly affected by the analytical errors associated with each measurement. A model proposed by Rocke and Lorenzato assumes two error components, one additive and one multiplicative, to deal with lower and higher concentration values in a single model. In this communication, an application of this method for re-evaluation of the errors reported in a large set of results of total alpha measurements in a environmental sample is presented. The results show that the mean values calculated taking into account the new errors is higher than as obtained with the original errors, being an indicative that the analytical errors reported before were underestimated in the region of lower concentrations. (author)

Thermodynamically consistent modeling and simulation of multi-component two-phase flow model with partial miscibility

KAUST Repository

Kou, Jisheng

2016-11-25

A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is a latest alternative over the NPT-based framework to model the realistic fluids. The proposed model uses the Helmholtz free energy rather than Gibbs free energy in the NPT-based framework. Different from the classical routines, we combine the first law of thermodynamics and related thermodynamical relations to derive the entropy balance equation, and then we derive a transport equation of the Helmholtz free energy density. Furthermore, by using the second law of thermodynamics, we derive a set of unified equations for both interfaces and bulk phases that can describe the partial miscibility of two fluids. A relation between the pressure gradient and chemical potential gradients is established, and this relation leads to a new formulation of the momentum balance equation, which demonstrates that chemical potential gradients become the primary driving force of fluid motion. Moreover, we prove that the proposed model satisfies the total (free) energy dissipation with time. For numerical simulation of the proposed model, the key difficulties result from the strong nonlinearity of Helmholtz free energy density and tight coupling relations between molar densities and velocity. To resolve these problems, we propose a novel convex-concave splitting of Helmholtz free energy density and deal well with the coupling relations between molar densities and velocity through very careful physical observations with a mathematical rigor. We prove that the proposed numerical scheme can preserve the discrete (free) energy dissipation. Numerical tests are carried out to verify the effectiveness of the proposed method.

Hydrogenic ionization model for mixtures in non-LTE plasmas

International Nuclear Information System (INIS)

Djaoui, A.

1999-01-01

The Hydrogenic Ionization Model for Mixtures (HIMM) is a non-Local Thermodynamic Equilibrium (non-LTE), time-dependent ionization model for laser-produced plasmas containing mixtures of elements (species). In this version, both collisional and radiative rates are taken into account. An ionization distribution for each species which is consistent with the ambient electron density is obtained by use of an iterative procedure in a single calculation for all species. Energy levels for each shell having a given principal quantum number and for each ion stage of each species in the mixture are calculated using screening constants. Steady-state non-LTE as well as LTE solutions are also provided. The non-LTE rate equations converge to the LTE solution at sufficiently high densities or as the radiation temperature approaches the electron temperature. The model is particularly useful at low temperatures where convergence problems are usually encountered in our previous models. We apply our model to typical situation in x-ray laser research, laser-produced plasmas and inertial confinement fusion. Our results compare well with previously published results for a selenium plasma. (author)

Toxicity of binary mixtures of metals and pyrethroid insecticides to Daphnia magna Straus. Implications for multi-substance risks assessment

Energy Technology Data Exchange (ETDEWEB)

Barata, Carlos [Laboratory of Environmental Toxicology, Universitat Poltiecnica de Catalunya, CN 150 Km 14.5, Terrassa 08220 (Spain)]. E-mail: barata@intexter.upc.edu; Baird, D.J. [National Water Research Institute (Environment Canada) at Canadian Rivers Institute, 10 Bailey Drive, PO Box 45111, University of New Brunswick, Fredericton E3B 6E1, New Brunswick (Canada); Nogueira, A.J.A. [Departamento de Biologia, Universidade de Aveiro, 3810-193 Aveiro (Portugal); Soares, A.M.V.M. [Departamento de Biologia, Universidade de Aveiro, 3810-193 Aveiro (Portugal); Riva, M.C. [Laboratory of Environmental Toxicology, Universitat Poltiecnica de Catalunya, CN 150 Km 14.5, Terrassa 08220 (Spain)

2006-06-10

Two different concepts, termed concentration addition (CA) and independent action (IA), describe general relationships between the effects of single substances and their corresponding mixtures allowing calculation of an expected mixture toxicity on the basis of known toxicities of the mixture components. Both concepts are limited to cases in which all substances in a mixture influence the same experimental endpoint, and are usually tested against a 'fixed ratio design' where the mixture ratio is kept constant throughout the studies and the overall concentration of the mixture is systematically varied. With this design, interaction among toxic components across different mixture ratios and endpoints (i.e. lethal versus sublethal) is not assessed. In this study lethal and sublethal (feeding) responses of Daphnia magna individuals to single and binary combinations of similarly and dissimilarly acting chemicals including the metals (cadmium, copper) and the pyrethroid insecticides ({lambda}-cyhalothrin and deltamethrin) were assayed using a composite experimental design to test for interactions among toxic components across mixture effect levels, mixture ratios, lethal and sublethal toxic effects. To account for inter-experiment response variability, in each binary mixture toxicity assay the toxicity of the individual mixture constituents was also assessed. Model adequacy was then evaluated comparing the slopes and elevations of predicted versus observed mixture toxicity curves with those estimated for the individual components. Model predictive abilities changed across endpoints. The IA concept was able to predict accurately mixture toxicities of dissimilarly acting chemicals for lethal responses, whereas the CA concept did so in three out of four pairings for feeding response, irrespective of the chemical mode of action. Interaction effects across mixture effect levels, evidenced by crossing slopes, were only observed for the binary mixture Cd and Cu for

Toxicity of binary mixtures of metals and pyrethroid insecticides to Daphnia magna Straus. Implications for multi-substance risks assessment

International Nuclear Information System (INIS)

Barata, Carlos; Baird, D.J.; Nogueira, A.J.A.; Soares, A.M.V.M.; Riva, M.C.

2006-01-01

Two different concepts, termed concentration addition (CA) and independent action (IA), describe general relationships between the effects of single substances and their corresponding mixtures allowing calculation of an expected mixture toxicity on the basis of known toxicities of the mixture components. Both concepts are limited to cases in which all substances in a mixture influence the same experimental endpoint, and are usually tested against a 'fixed ratio design' where the mixture ratio is kept constant throughout the studies and the overall concentration of the mixture is systematically varied. With this design, interaction among toxic components across different mixture ratios and endpoints (i.e. lethal versus sublethal) is not assessed. In this study lethal and sublethal (feeding) responses of Daphnia magna individuals to single and binary combinations of similarly and dissimilarly acting chemicals including the metals (cadmium, copper) and the pyrethroid insecticides (λ-cyhalothrin and deltamethrin) were assayed using a composite experimental design to test for interactions among toxic components across mixture effect levels, mixture ratios, lethal and sublethal toxic effects. To account for inter-experiment response variability, in each binary mixture toxicity assay the toxicity of the individual mixture constituents was also assessed. Model adequacy was then evaluated comparing the slopes and elevations of predicted versus observed mixture toxicity curves with those estimated for the individual components. Model predictive abilities changed across endpoints. The IA concept was able to predict accurately mixture toxicities of dissimilarly acting chemicals for lethal responses, whereas the CA concept did so in three out of four pairings for feeding response, irrespective of the chemical mode of action. Interaction effects across mixture effect levels, evidenced by crossing slopes, were only observed for the binary mixture Cd and Cu for lethal effects

Predicting skin permeability from complex chemical mixtures

International Nuclear Information System (INIS)

Riviere, Jim E.; Brooks, James D.

2005-01-01

Occupational and environmental exposure to topical chemicals is usually in the form of complex chemical mixtures, yet risk assessment is based on experimentally derived data from individual chemical exposures from a single, usually aqueous vehicle, or from computed physiochemical properties. We present an approach using hybrid quantitative structure permeation relationships (QSPeR) models where absorption through porcine skin flow-through diffusion cells is well predicted using a QSPeR model describing the individual penetrants, coupled with a mixture factor (MF) that accounts for physicochemical properties of the vehicle/mixture components. The baseline equation is log k p = c + mMF + aΣα 2 H + bΣβ 2 H + sπ 2 H + rR 2 + vV x where Σα 2 H is the hydrogen-bond donor acidity, Σβ 2 H is the hydrogen-bond acceptor basicity, π 2 H is the dipolarity/polarizability, R 2 represents the excess molar refractivity, and V x is the McGowan volume of the penetrants of interest; c, m, a, b, s, r, and v are strength coefficients coupling these descriptors to skin permeability (k p ) of 12 penetrants (atrazine, chlorpyrifos, ethylparathion, fenthion, methylparathion, nonylphenol, ρ-nitrophenol, pentachlorophenol, phenol, propazine, simazine, and triazine) in 24 mixtures. Mixtures consisted of full factorial combinations of vehicles (water, ethanol, propylene glycol) and additives (sodium lauryl sulfate, methyl nicotinate). An additional set of 4 penetrants (DEET, SDS, permethrin, ricinoleic acid) in different mixtures were included to assess applicability of this approach. This resulted in a dataset of 16 compounds administered in 344 treatment combinations. Across all exposures with no MF, R 2 for absorption was 0.62. With the MF, correlations increased up to 0.78. Parameters correlated to the MF include refractive index, polarizability and log (1/Henry's Law Constant) of the mixture components. These factors should not be considered final as the focus of these studies

Single- and mixture toxicity of three organic UV-filters, ethylhexyl methoxycinnamate, octocrylene, and avobenzone on Daphnia magna.

Science.gov (United States)

Park, Chang-Beom; Jang, Jiyi; Kim, Sanghun; Kim, Young Jun

2017-03-01

In freshwater environments, aquatic organisms are generally exposed to mixtures of various chemical substances. In this study, we tested the toxicity of three organic UV-filters (ethylhexyl methoxycinnamate, octocrylene, and avobenzone) to Daphnia magna in order to evaluate the combined toxicity of these substances when in they occur in a mixture. The values of effective concentrations (ECx) for each UV-filter were calculated by concentration-response curves; concentration-combinations of three different UV-filters in a mixture were determined by the fraction of components based on EC 25 values predicted by concentration addition (CA) model. The interaction between the UV-filters were also assessed by model deviation ratio (MDR) using observed and predicted toxicity values obtained from mixture-exposure tests and CA model. The results from this study indicated that observed ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values obtained from mixture-exposure tests were higher than predicted ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values calculated by CA model. MDR values were also less than a factor of 1.0 in a mixtures of three different UV-filters. Based on these results, we suggest for the first time a reduction of toxic effects in the mixtures of three UV-filters, caused by antagonistic action of the components. Our findings from this study will provide important information for hazard or risk assessment of organic UV-filters, when they existed together in the aquatic environment. To better understand the mixture toxicity and the interaction of components in a mixture, further studies for various combinations of mixture components are also required. Copyright © 2016 Elsevier Inc. All rights reserved.

Nonlinear Structured Growth Mixture Models in M"plus" and OpenMx

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2010-01-01

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…

Deciding which chemical mixtures risk assessment methods work best for what mixtures

International Nuclear Information System (INIS)

Teuschler, Linda K.

2007-01-01

The most commonly used chemical mixtures risk assessment methods involve simple notions of additivity and toxicological similarity. Newer methods are emerging in response to the complexities of chemical mixture exposures and effects. Factors based on both science and policy drive decisions regarding whether to conduct a chemical mixtures risk assessment and, if so, which methods to employ. Scientific considerations are based on positive evidence of joint toxic action, elevated human exposure conditions or the potential for significant impacts on human health. Policy issues include legislative drivers that may mandate action even though adequate toxicity data on a specific mixture may not be available and risk assessment goals that impact the choice of risk assessment method to obtain the amount of health protection desired. This paper discusses three important concepts used to choose among available approaches for conducting a chemical mixtures risk assessment: (1) additive joint toxic action of mixture components; (2) toxicological interactions of mixture components; and (3) chemical composition of complex mixtures. It is proposed that scientific support for basic assumptions used in chemical mixtures risk assessment should be developed by expert panels, risk assessment methods experts, and laboratory toxicologists. This is imperative to further develop and refine quantitative methods and provide guidance on their appropriate applications. Risk assessors need scientific support for chemical mixtures risk assessment methods in the form of toxicological data on joint toxic action for high priority mixtures, statistical methods for analyzing dose-response for mixtures, and toxicological and statistical criteria for determining sufficient similarity of complex mixtures

Communication: Modeling electrolyte mixtures with concentration dependent dielectric permittivity

Science.gov (United States)

Chen, Hsieh; Panagiotopoulos, Athanassios Z.

2018-01-01

We report a new implicit-solvent simulation model for electrolyte mixtures based on the concept of concentration dependent dielectric permittivity. A combining rule is found to predict the dielectric permittivity of electrolyte mixtures based on the experimentally measured dielectric permittivity for pure electrolytes as well as the mole fractions of the electrolytes in mixtures. Using grand canonical Monte Carlo simulations, we demonstrate that this approach allows us to accurately reproduce the mean ionic activity coefficients of NaCl in NaCl-CaCl2 mixtures at ionic strengths up to I = 3M. These results are important for thermodynamic studies of geologically relevant brines and physiological fluids.

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

International Nuclear Information System (INIS)

Ellefsen, Karl J.; Smith, David B.

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples. - Highlights: • We evaluate a clustering procedure by applying it to geochemical data. • The procedure generates a hierarchy of clusters. • Different levels of the hierarchy show geochemical processes at different spatial scales. • The clustering method is Bayesian finite mixture modeling. • Model parameters are estimated with Hamiltonian Monte Carlo sampling.

Principal Component Analysis Based Two-Dimensional (PCA-2D) Correlation Spectroscopy: PCA Denoising for 2D Correlation Spectroscopy

International Nuclear Information System (INIS)

Jung, Young Mee

2003-01-01

Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra

Flexible Mixture-Amount Models for Business and Industry Using Gaussian Processes

NARCIS (Netherlands)

A. Ruseckaite (Aiste); D. Fok (Dennis); P.P. Goos (Peter)

2016-01-01

markdownabstractMany products and services can be described as mixtures of ingredients whose proportions sum to one. Specialized models have been developed for linking the mixture proportions to outcome variables, such as preference, quality and liking. In many scenarios, only the mixture

Sound speed models for a noncondensible gas-steam-water mixture

International Nuclear Information System (INIS)

Ransom, V.H.; Trapp, J.A.

1984-01-01

An analytical expression is derived for the homogeneous equilibrium speed of sound in a mixture of noncondensible gas, steam, and water. The expression is based on the Gibbs free energy interphase equilibrium condition for a Gibbs-Dalton mixture in contact with a pure liquid phase. Several simplified models are discussed including the homogeneous frozen model. These idealized models can be used as a reference for data comparison and also serve as a basis for empirically corrected nonhomogeneous and nonequilibrium models

On population size estimators in the Poisson mixture model.

Science.gov (United States)

Mao, Chang Xuan; Yang, Nan; Zhong, Jinhua

2013-09-01

Estimating population sizes via capture-recapture experiments has enormous applications. The Poisson mixture model can be adopted for those applications with a single list in which individuals appear one or more times. We compare several nonparametric estimators, including the Chao estimator, the Zelterman estimator, two jackknife estimators and the bootstrap estimator. The target parameter of the Chao estimator is a lower bound of the population size. Those of the other four estimators are not lower bounds, and they may produce lower confidence limits for the population size with poor coverage probabilities. A simulation study is reported and two examples are investigated. © 2013, The International Biometric Society.

To the elementary theory of critical (maximum) flow rate of two-phase mixture in channels with various sections

International Nuclear Information System (INIS)

Nigmatulin, B.I.; Soplenkov, K.I.

1978-01-01

On the basis of the concepts of two-phase dispersive flow with various structures (bubble, vapour-drop etc) in the framework of the two-speed and two-temperature one-dimension stationary model of the current with provision for phase transitions the conditions, under which a critical (maximum) flow rate of two-phase mixture is achieved during its outflowing from a channel with the pre-set geometry, have been determined. It is shown, that for the choosen set of two-phase flow equations with the known parameters of deceleration and structure one of the critical conditions is satisfied: either solution of the set of equations corresponding a critical flow rate is a special one, i.e. passes through a special point locating between minimum and outlet channel sections where the carrying phase velocity approaches the value of decelerated sound speed in the mixture or the determinator of the initial set of equations equals zero for the outlet channel sections, i.e. gradients of the main flow parameters tend to +-infinity in this section, and carrying phase velocity also approaches the value of the decelerated sound velocity in the mixture

Efficient transfer of sensitivity information in multi-component models

International Nuclear Information System (INIS)

Abdel-Khalik, Hany S.; Rabiti, Cristian

2011-01-01

In support of adjoint-based sensitivity analysis, this manuscript presents a new method to efficiently transfer adjoint information between components in a multi-component model, whereas the output of one component is passed as input to the next component. Often, one is interested in evaluating the sensitivities of the responses calculated by the last component to the inputs of the first component in the overall model. The presented method has two advantages over existing methods which may be classified into two broad categories: brute force-type methods and amalgamated-type methods. First, the presented method determines the minimum number of adjoint evaluations for each component as opposed to the brute force-type methods which require full evaluation of all sensitivities for all responses calculated by each component in the overall model, which proves computationally prohibitive for realistic problems. Second, the new method treats each component as a black-box as opposed to amalgamated-type methods which requires explicit knowledge of the system of equations associated with each component in order to reach the minimum number of adjoint evaluations. (author)

A Generic Model for Prediction of Separation Performance of Olefin/Paraffin Mixture by Glassy Polymer Membranes

Directory of Open Access Journals (Sweden)

A.A. Ghoreyshi

2008-02-01

Full Text Available The separation of olefin/paraffin mixtures is an important process in petrochemical industries, which is traditionally performed by low temperature distillation with a high-energy consumption, or complex extractive distillationand adsorption techniques. Membrane separation process is emerging as an alternative for traditional separation processes with respect to low energy and simple operation. Investigations made by various researchers on polymeric membranes it is found that special glassy polymers render them as suitable materials for olefin/paraffin mixture separation. In this regard, having some knowledge on the possible transport mechanism of these processes would play a significant role in their design and applications. In this study, separation behavior of olefin/paraffin mixtures through glassy polymers was modeled by three different approaches: the so-called dual transport model, the basic adsorption-diffusion theory and the general Maxwell-Stefan formulation. The systems chosen to validate the developed transport models are separation of ethane-ethylene mixture by 6FDA-6FpDA polyimide membrane and propane-propylene mixture by 6FDA-TrMPD polyimide membrane for which the individual sorption and permeation data are available in the literature. Acritical examination of dual transport model shows that this model fails clearly to predict even the proper trend for selectivities. The adjustment of pemeabilities by accounting for the contribution of non-selective bulk flow in the transport model introduced no improvement in the predictability of the model. The modeling results based on the basic adsorption-diffusion theory revealed that in this approach only using mixed permeability data, an acceptable result is attainable which fades out the advantages of predictibility of multicomponent separation performance from pure component data. Finally, the results obtained from the model developed based on Maxwell-Stefan formulation approach show a

Gas-particle partitioning of semivolatile organic compounds (SOCs) on mixtures of aerosols in a smog chamber.

Science.gov (United States)

Chandramouli, Bharadwaj; Jang, Myoseon; Kamens, Richard M

2003-09-15

The partitioning behavior of a set of diverse SOCs on two and three component mixtures of aerosols from different sources was studied using smog chamber experimental data. A set of SOCs of different compound types was introduced into a system containing a mixture of aerosols from two or more sources. Gas and particle samples were taken using a filter-filter-denuder sampling system, and a partitioning coefficient Kp was estimated using Kp = Cp/(CgTSP). Particle size distributions were measured using a differential mobility analyzer and a light scattering detector. Gas and particle samples were analyzed using GCMS. The aerosol composition in the chamber was tracked chemically using a combination of signature compounds and the organic matter mass fraction (f(om)) of the individual aerosol sources. The physical nature of the aerosol mixture in the chamber was determined using particle size distributions, and an aggregate Kp was estimated from theoretically calculated Kp on the individual sources. Model fits for Kp showed that when the mixture involved primary sources of aerosol, the aggregate Kp of the mixture could be successfully modeled as an external mixture of the Kp on the individual aerosols. There were significant differences observed for some SOCs between modeling the system as an external and as an internal mixture. However, when one of the aerosol sources was secondary, the aggregate model Kp required incorporation of the secondary aerosol products on the preexisting aerosol for adequate model fits. Modeling such a system as an external mixture grossly overpredicted the Kp of alkanes in the mixture. Indirect evidence of heterogeneous, acid-catalyzed reactions in the particle phase was also seen, leading to a significant increase in the polarity of the resulting aerosol mix and a resulting decrease in the observed Kp of alkanes in the chamber. The model was partly consistent with this decrease but could not completely explain the reduction in Kp because of

Numerical analysis of mass transfer with graphite oxidation in a laminar flow of multi-component gas mixture through a circular tube

International Nuclear Information System (INIS)

Ogawa, Masuro

1992-10-01

In the present paper, mass transfer has been numerically studied in a laminar flow through a circular graphite tube to evaluate graphite corrosion rate and generation rate of carbon monoxide during a pipe rupture accident in a high temperature gas cooled reactor. In the analysis, heterogeneous (graphite oxidation and graphite/carbon dioxide reaction) and homogeneous (carbon monoxide combustion) chemical reactions were dealt in the multi-component gas mixture; helium, oxygen, carbon monoxide and carbon dioxide. Multi-component diffusion coefficients were used in a diffusion term. Mass conservation equations of each gas component, mass conservation equation and momentum conservation equations of the gas mixture were solved by using SIMPLE algorism. Chemical reactions between graphite and oxygen, graphite and carbon dioxide, and carbon monoxide combustion were taken into account in the present numerical analysis. An energy equation for the gas mixture was not solved and temperature was held to be constant in order to understand basic mass transfer characteristics without heat transfer. But, an energy conservation equation for single component gas was added to know heat transfer characteristics without mass transfer. The effects of these chemical reactions on the mass transfer coefficients were quantitatively and qualitatively clarified in the range of 50 to 1000 of inlet Reynolds numbers, 0 to 0.5 of inlet oxygen mass fraction and 800 to 1600degC of temperature. (author)

Fitting a mixture of von Mises distributions in order to model data on wind direction in Peninsular Malaysia

International Nuclear Information System (INIS)

Masseran, N.; Razali, A.M.; Ibrahim, K.; Latif, M.T.

2013-01-01

Highlights: • We suggest a simple way for wind direction modeling using the mixture of von Mises distribution. • We determine the most suitable probability model for wind direction regime in Malaysia. • We provide the circular density plots to show the most prominent directions of wind blows. - Abstract: A statistical distribution for describing wind direction provides information about the wind regime at a particular location. In addition, this information complements knowledge of wind speed, which allows researchers to draw some conclusions about the energy potential of wind and aids the development of efficient wind energy generation. This study focuses on modeling the frequency distribution of wind direction, including some characteristics of wind regime that cannot be represented by a unimodal distribution. To identify the most suitable model, a finite mixture of von Mises distributions were fitted to the average hourly wind direction data for nine wind stations located in Peninsular Malaysia. The data used were from the years 2000 to 2009. The suitability of each mixture distribution was judged based on the R 2 coefficient and the histogram plot with a density line. The results showed that the finite mixture of the von Mises distribution with H number of components was the best distribution to describe the wind direction distributions in Malaysia. In addition, the circular density plots of the suitable model clearly showed the most prominent directions of wind blows than the other directions

Conductivity of two-component systems

Energy Technology Data Exchange (ETDEWEB)

Kuijper, A. de; Hofman, J.P.; Waal, J.A. de [Shell Research BV, Rijswijk (Netherlands). Koninklijke/Shell Exploratie en Productie Lab.; Sandor, R.K.J. [Shell International Petroleum Maatschappij, The Hague (Netherlands)

1996-01-01

The authors present measurements and computer simulation results on the electrical conductivity of nonconducting grains embedded in a conductive brine host. The shapes of the grains ranged from prolate-ellipsoidal (with an axis ratio of 5:1) through spherical to oblate-ellipsoidal (with an axis ratio of 1:5). The conductivity was studied as a function of porosity and packing, and Archie`s cementation exponent was found to depend on porosity. They used spatially regular and random configurations with aligned and nonaligned packings. The experimental results agree well with the computer simulation data. This data set will enable extensive tests of models for calculating the anisotropic conductivity of two-component systems.

Simulation and thermodynamic modeling of the extraction of tocopherol from a synthetic mixture of tocopherol, squalene and CO2

Directory of Open Access Journals (Sweden)

M.F. Mendes

2000-12-01

Full Text Available Soybean oil is the most consumed vegetable oil in the world, representing 54% of the total world production. Brazil is the second country in the world that produces and export soybean seeds, almost 20%. One of the most important by-product of the soybean oil is the deodorizer distillate, commonly known as soybean sludge. This residue is rich in many high value compounds as tocopherols, squalene and sterols. Tocopherols are the major components in the deodorized distillated due to their characteristics as an antioxidant agent. So, the objective of this work is to study the concentration of tocopherols presented in this raw material, using the operational conditions obtained from the equilibrium data and using supercritical carbon dioxide as a solvent. The deodorizer distillate is a complex mixture of more than 200 components, so a synthetic mixture was chosen to represent the deodorizer distillate. The synthetic mixture used in this work is composed by tocopherols, fatty acids and squalene. The simulation was carried out using ASPEN+ simulator and the LCVM thermodynamic model was used to correlate the available equilibrium data.