Spatio-temporal Bayesian model selection for disease mapping

PubMed Central

Carroll, R; Lawson, AB; Faes, C; Kirby, RS; Aregay, M; Watjou, K

2016-01-01

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor. PMID:28070156

Designing a mixture experiment when the components are subject to a nonlinear multiple-component constraint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piepel, Greg F.; Cooley, Scott K.; Vienna, John D.

This article presents a case study of developing an experimental design for a constrained mixture experiment when the experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directly applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this article. The case study involves a 15-component nuclear waste glass example in which SO3 is one of the components. SO3 has a solubility limit inmore » glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO3 solubility limit had previously been modeled by a partial quadratic mixture (PQM) model expressed in the relative proportions of the 14 other components. The PQM model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This article discusses the waste glass example and how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study.« less

Solving a mixture of many random linear equations by tensor decomposition and alternating minimization.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of solving mixed random linear equations with k components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels (which sample...

On hydrodynamic phase field models for binary fluid mixtures

NASA Astrophysics Data System (ADS)

Yang, Xiaogang; Gong, Yuezheng; Li, Jun; Zhao, Jia; Wang, Qi

2018-05-01

Two classes of thermodynamically consistent hydrodynamic phase field models have been developed for binary fluid mixtures of incompressible viscous fluids of possibly different densities and viscosities. One is quasi-incompressible, while the other is incompressible. For the same binary fluid mixture of two incompressible viscous fluid components, which one is more appropriate? To answer this question, we conduct a comparative study in this paper. First, we visit their derivation, conservation and energy dissipation properties and show that the quasi-incompressible model conserves both mass and linear momentum, while the incompressible one does not. We then show that the quasi-incompressible model is sensitive to the density deviation of the fluid components, while the incompressible model is not in a linear stability analysis. Second, we conduct a numerical investigation on coarsening or coalescent dynamics of protuberances using the two models. We find that they can predict quite different transient dynamics depending on the initial conditions and the density difference although they predict essentially the same quasi-steady results in some cases. This study thus cast a doubt on the applicability of the incompressible model to describe dynamics of binary mixtures of two incompressible viscous fluids especially when the two fluid components have a large density deviation.

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

PubMed

Sentürk, Damla; Dalrymple, Lorien S; Nguyen, Danh V

2014-11-30

We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression. Copyright © 2014 John Wiley & Sons, Ltd.

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

NASA Astrophysics Data System (ADS)

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 of active transmembrane transport in a mixture theory framework.

PubMed

Ateshian, Gerard A; Morrison, Barclay; Hung, Clark T

2010-05-01

This study formulates governing equations for active transport across semi-permeable membranes within the framework of the theory of mixtures. In mixture theory, which models the interactions of any number of fluid and solid constituents, a supply term appears in the conservation of linear momentum to describe momentum exchanges among the constituents. In past applications, this momentum supply was used to model frictional interactions only, thereby describing passive transport processes. In this study, it is shown that active transport processes, which impart momentum to solutes or solvent, may also be incorporated in this term. By projecting the equation of conservation of linear momentum along the normal to the membrane, a jump condition is formulated for the mechano-electrochemical potential of fluid constituents which is generally applicable to nonequilibrium processes involving active transport. The resulting relations are simple and easy to use, and address an important need in the membrane transport literature.

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression.

PubMed

Lemieux, Sébastien

2006-08-25

The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model) method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication. On a wholly defined dataset, the PL-LM method was able to identify 75% of the differentially expressed genes within 10% of false positives. This accuracy was achieved both using the three replicates per conditions available in the dataset and using only one replicate per condition. The method achieves, on this dataset, a higher accuracy than the best set of tools identified by the authors of the dataset, and does so using only one replicate per condition.

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models.

PubMed

Li, Yanyan; Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Planetary Ices and the Linear Mixing Approximation

DOE PAGES

Bethkenhagen, M.; Meyer, Edmund Richard; Hamel, S.; ...

2017-10-10

Here, the validity of the widely used linear mixing approximation (LMA) for the equations of state (EOSs) of planetary ices is investigated at pressure–temperature conditions typical for the interiors of Uranus and Neptune. The basis of this study is ab initio data ranging up to 1000 GPa and 20,000 K, calculated via density functional theory molecular dynamics simulations. In particular, we determine a new EOS for methane and EOS data for the 1:1 binary mixtures of methane, ammonia, and water, as well as their 2:1:4 ternary mixture. Additionally, the self-diffusion coefficients in the ternary mixture are calculated along three different Uranus interior profiles and compared to the values of the pure compounds. We find that deviations of the LMA from the results of the real mixture are generally small; for the thermal EOSs they amount to 4% or less. The diffusion coefficients in the mixture agree with those of the pure compounds within 20% or better. Finally, a new adiabatic model of Uranus with an inner layer of almost pure ices is developed. The model is consistent with the gravity field data and results in a rather cold interior (more » $${T}_{\\mathrm{core}}\\sim 4000$$ K).« less

Modeling the soil water retention curves of soil-gravel mixtures with regression method on the Loess Plateau of China.

PubMed

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present.

Modeling the Soil Water Retention Curves of Soil-Gravel Mixtures with Regression Method on the Loess Plateau of China

PubMed Central

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present. PMID:23555040

Insight into Signal Response of Protein Ions in Native ESI-MS from the Analysis of Model Mixtures of Covalently Linked Protein Oligomers.

PubMed

Root, Katharina; Wittwer, Yves; Barylyuk, Konstantin; Anders, Ulrike; Zenobi, Renato

2017-09-01

Native ESI-MS is increasingly used for quantitative analysis of biomolecular interactions. In such analyses, peak intensity ratios measured in mass spectra are treated as abundance ratios of the respective molecules in solution. While signal intensities of similar-size analytes, such as a protein and its complex with a small molecule, can be directly compared, significant distortions of the peak ratio due to unequal signal response of analytes impede the application of this approach for large oligomeric biomolecular complexes. We use a model system based on concatenated maltose binding protein units (MBPn, n = 1, 2, 3) to systematically study the behavior of protein mixtures in ESI-MS. The MBP concatamers differ from each other only by their mass while the chemical composition and other properties remain identical. We used native ESI-MS to analyze model mixtures of MBP oligomers, including equimolar mixtures of two proteins, as well as binary mixtures containing different fractions of the individual components. Pronounced deviation from a linear dependence of the signal intensity with concentration was observed for all binary mixtures investigated. While equimolar mixtures showed linear signal dependence at low concentrations, distinct ion suppression was observed above 20 μM. We systematically studied factors that are most often used in the literature to explain the origin of suppression effects. Implications of this effect for quantifying protein-protein binding affinity by native ESI-MS are discussed in general and demonstrated for an example of an anti-MBP antibody with its ligand, MBP. Graphical Abstract ᅟ.

Evaluating differential effects using regression interactions and regression mixture models

PubMed Central

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models

PubMed Central

Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. In This Paper, Extensions Of The D-Optimal Minimal Designs Are Developed For A General Mixture Model To Allow Additional Interior Points In The Design Space To Enable Prediction Of The Entire Response Surface Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations. PMID:29081574

[Ionization in liquids: Request for 1992--1993 funding and 1991--1992 progress report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-12-31

Studies of the influence of solvent composition on electron mobility, {mu}{sub e}, which we reported for mixtures of neopentane (NP) and tetramethysilane (TMS) were extended to mixtures of TMS with isooctane (i-octane) or cyclohexane (c-hexane). Whereas our initial TMS /NP study focused on an electron transport regime in which {mu}{sub e} varied only from 67 cm{sup 2}/Vs in NP to 100 cm{sup 2}/Vs in TMS, the more recent studies extended to values of {mu}{sub e} of 7.5 and 0.22 cm{sup 2}/Vs in i-octane and c-hexane, respectively. Whereas a linear dependence of log {mu}{sub e} on solvent composition had been foundmore » in earlier studies of electron transport in mixtures, a negative deviation from this dependence was found in TMS/NP mixtures. In contrast, a positive deviation from linearity was observed in TMS/c-hexane mixtures. Despite the markedly different dependences of {mu}{sub e} on solvent composition for these mixtures, the observed dependences are consistent with the percolation model of electron transport that Schiller has developed.« less

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Analysis of Forest Foliage Using a Multivariate Mixture Model

NASA Technical Reports Server (NTRS)

Hlavka, C. A.; Peterson, David L.; Johnson, L. F.; Ganapol, B.

1997-01-01

Data with wet chemical measurements and near infrared spectra of ground leaf samples were analyzed to test a multivariate regression technique for estimating component spectra which is based on a linear mixture model for absorbance. The resulting unmixed spectra for carbohydrates, lignin, and protein resemble the spectra of extracted plant starches, cellulose, lignin, and protein. The unmixed protein spectrum has prominent absorption spectra at wavelengths which have been associated with nitrogen bonds.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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 modelling, 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 suggests the Umov effect may also be observed in more complex mixtures.

Spectral mixture analyses of hyperspectral data acquired using a tethered balloon

USGS Publications Warehouse

Chen, Xuexia; Vierling, Lee

2006-01-01

Tethered balloon remote sensing platforms can be used to study radiometric issues in terrestrial ecosystems by effectively bridging the spatial gap between measurements made on the ground and those acquired via airplane or satellite. In this study, the Short Wave Aerostat-Mounted Imager (SWAMI) tethered balloon-mounted platform was utilized to evaluate linear and nonlinear spectral mixture analysis (SMA) for a grassland-conifer forest ecotone during the summer of 2003. Hyperspectral measurement of a 74-m diameter ground instantaneous field of view (GIFOV) attained by the SWAMI was studied. Hyperspectral spectra of four common endmembers, bare soil, grass, tree, and shadow, were collected in situ, and images captured via video camera were interpreted into accurate areal ground cover fractions for evaluating the mixture models. The comparison between the SWAMI spectrum and the spectrum derived by combining in situ spectral data with video-derived areal fractions indicated that nonlinear effects occurred in the near infrared (NIR) region, while nonlinear influences were minimal in the visible region. The evaluation of hyperspectral and multispectral mixture models indicated that nonlinear mixture model-derived areal fractions were sensitive to the model input data, while the linear mixture model performed more stably. Areal fractions of bare soil were overestimated in all models due to the increased radiance of bare soil resulting from side scattering of NIR radiation by adjacent grass and trees. Unmixing errors occurred mainly due to multiple scattering as well as close endmember spectral correlation. In addition, though an apparent endmember assemblage could be derived using linear approaches to yield low residual error, the tree and shade endmember fractions calculated using this technique were erroneous and therefore separate treatment of endmembers subject to high amounts of multiple scattering (i.e. shadows and trees) must be done with caution. Including the short wave infrared (SWIR) region in the hyperspectral and multispectral endmember data significantly reduced the Pearson correlation coefficient values among endmember spectra. Therefore, combination of visible, NIR, and SWIR information is likely to further improve the utility of SMA in understanding ecosystem structure and function and may help narrow uncertainties when utilizing remotely sensed data to extrapolate trace glas flux measurements from the canopy scale to the landscape scale.

Experimentally Derived Mechanical and Flow Properties of Fine-grained Soil Mixtures

NASA Astrophysics Data System (ADS)

Schneider, J.; Peets, C. S.; Flemings, P. B.; Day-Stirrat, R. J.; Germaine, J. T.

2009-12-01

As silt content in mudrocks increases, compressibility linearly decreases and permeability exponentially increases. We prepared mixtures of natural Boston Blue Clay (BBC) and synthetic silt in the ratios of 100:0, 86:14, 68:32, and 50:50, respectively. To recreate natural conditions yet remove variability and soil disturbance, we resedimented all mixtures to a total stress of 100 kPa. We then loaded them to approximately 2.3 MPa in a CRS (constant-rate-of-strain) uniaxial consolidation device. The analyses show that the higher the silt content in the mixture, the stiffer the material is. Compression index as well as liquid and plastic limits linearly decrease with increasing silt content. Vertical permeability increases exponentially with porosity as well as with silt content. Fabric alignment determined through High Resolution X-ray Texture Goniometry (HRXTG) expressed as maximum pole density (m.r.d.) decreases with silt content at a given stress. However, this relationship is not linear instead there are two clusters: the mixtures with higher clay contents (100:0, 84:16) have m.r.d. around 3.9 and mixtures with higher silt contents (68:32, 50:50) have m.r.d. around 2.5. Specific surface area (SSA) measurements show a positive correlation to the total clay content. The amount of silt added to the clay reduces specific surface area, grain orientation, and fabric alignment; thus, it affects compression and fluid flow behavior on a micro- and macroscale. Our results are comparable with previous studies such as kaolinite / silt mixtures (Konrad & Samson [2000], Wagg & Konrad [1990]). We are studying this behavior to understand how fine-grained rocks consolidate. This problem is important to practical and fundamental programs. For example, these sediments can potentially act as either a tight gas reservoir or a seal for hydrocarbons or geologic storage of CO2. This study also provides a systematic approach for developing models of permeability and compressibility behavior needed as inputs for basin modeling.

Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation.

PubMed

Priol, Pauline; Mazerolle, Marc J; Imbeau, Louis; Drapeau, Pierre; Trudeau, Caroline; Ramière, Jessica

2014-06-01

Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577-587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture-mark-recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack-Jolly-Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture-mark-recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise than those from CJS models. However, N-mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.

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

PubMed

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.

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

PubMed Central

Chen, D G; Pounds, J G

1998-01-01

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. PMID:9860894

Nonlinear Structured Growth Mixture Models in Mplus and OpenMx

PubMed Central

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

2014-01-01

Growth mixture models (GMMs; Muthén & Muthén, 2000; Muthén & 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 because of their common use, flexibility in modeling many types of change patterns, the availability of statistical programs to fit such models, and the ease of programming. In this paper, we present additional ways of modeling nonlinear change patterns with GMMs. Specifically, we show how LCMs that follow specific nonlinear functions can be extended to examine the presence of multiple latent classes using the Mplus and OpenMx computer programs. These models are fit to longitudinal reading data from the Early Childhood Longitudinal Study-Kindergarten Cohort to illustrate their use. PMID:25419006

Gaussian Mixture Model of Heart Rate Variability

PubMed Central

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

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

PubMed

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.

Suppressor Variables and Multilevel Mixture Modelling

ERIC Educational Resources Information Center

Darmawan, I Gusti Ngurah; Keeves, John P.

2006-01-01

A major issue in educational research involves taking into consideration the multilevel nature of the data. Since the late 1980s, attempts have been made to model social science data that conform to a nested structure. Among other models, two-level structural equation modelling or two-level path modelling and hierarchical linear modelling are two…

Spectral variability of plagioclase-mafic mixtures (3): Quantitative analysis applying the MGM algorithm

NASA Astrophysics Data System (ADS)

Serventi, Giovanna; Carli, Cristian; Sgavetti, Maria

2015-07-01

Among the techniques to detect planet's mineralogical composition remote sensing, visible and near-infrared (VNIR) reflectance spectroscopy is a powerful tool, because crystal field absorption bands are related to particular transitional metals in well-defined crystal structures, e.g., Fe2+ in M1 and M2 sites of olivine (OL) or pyroxene (PX). Although OL, PX and their mixtures have been widely studied, plagioclase (PL), considered a spectroscopically transparent mineral, has been poorly analyzed. In this work we quantitatively investigate the influence of plagioclase absorption band on the absorption bands of Fe, Mg minerals using the Modified Gaussian Model - MGM (Sunshine, J.M. et al. [1990]. J. Geophys. Res. 95, 6955-6966). We consider three plagioclase compositions of varying FeO wt.% contents and five mafic end-members (1) 56% orthopyroxene and 44% clinopyroxene, (2) 28% olivine and 72% orthopyroxene, (3) 30% orthopyroxene and 70% olivine, (4) 100% olivine and (5) 100% orthopyroxene, at two different particle sizes. The spectral parameters considered here are: band depth, band center, band width, c0 (the continuum intercept) and c1 (the continuum offset). In particular, we show the variation of the plagioclase and composite (plagioclase-olivine) band spectral parameters versus the volumetric iron content related to the plagioclase abundance in mixtures. Generally, increasing the vol. FeO% due to the PL: (1) 1250 nm band deepens with linear trend in mixtures with pyroxenes, while it decreases in mixtures with olivine, with trend shifting from parabolic to linear increasing the olivine content in end-member; (2) 1250 nm band center moves towards longer wavelengths with linear trend in pyroxene-rich mixtures and parabolic trend in olivine-rich mixtures; and (3) 1250 nm band clearly widens with linear trend in olivine-free mixtures, while the widening is only slight in olivine-rich mixtures. We also outline how spectral parameters can be ambiguous leading to an incorrect mineralogical interpretation. Furthermore, we show the presence of an asymmetry of the plagioclase band towards the IR region, resolvable adding a Gaussian in the 1600-1800 nm spectral region.

Direct Importance Estimation with Gaussian Mixture Models

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

PubMed

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

Technical note: A linear model for predicting δ13 Cprotein.

PubMed

Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M

2015-08-01

Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2)  = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ(13) Cprotein . This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.

D-optimal experimental designs to test for departure from additivity in a fixed-ratio mixture ray.

PubMed

Coffey, Todd; Gennings, Chris; Simmons, Jane Ellen; Herr, David W

2005-12-01

Traditional factorial designs for evaluating interactions among chemicals in a mixture may be prohibitive when the number of chemicals is large. Using a mixture of chemicals with a fixed ratio (mixture ray) results in an economical design that allows estimation of additivity or nonadditive interaction for a mixture of interest. This methodology is extended easily to a mixture with a large number of chemicals. Optimal experimental conditions can be chosen that result in increased power to detect departures from additivity. Although these designs are used widely for linear models, optimal designs for nonlinear threshold models are less well known. In the present work, the use of D-optimal designs is demonstrated for nonlinear threshold models applied to a fixed-ratio mixture ray. For a fixed sample size, this design criterion selects the experimental doses and number of subjects per dose level that result in minimum variance of the model parameters and thus increased power to detect departures from additivity. An optimal design is illustrated for a 2:1 ratio (chlorpyrifos:carbaryl) mixture experiment. For this example, and in general, the optimal designs for the nonlinear threshold model depend on prior specification of the slope and dose threshold parameters. Use of a D-optimal criterion produces experimental designs with increased power, whereas standard nonoptimal designs with equally spaced dose groups may result in low power if the active range or threshold is missed.

Interpreting spectral unmixing coefficients: From spectral weights to mass fractions

NASA Astrophysics Data System (ADS)

Grumpe, Arne; Mengewein, Natascha; Rommel, Daniela; Mall, Urs; Wöhler, Christian

2018-01-01

It is well known that many common planetary minerals exhibit prominent absorption features. Consequently, the analysis of spectral reflectance measurements has become a major tool of remote sensing. Quantifying the mineral abundances, however, is not a trivial task. The interaction between the incident light rays and particulate surfaces, e.g., the lunar regolith, leads to a non-linear relationship between the reflectance spectra of the pure minerals, the so-called ;endmembers;, and the surface's reflectance spectrum. It is, however, possible to transform the non-linear reflectance mixture into a linear mixture of single-scattering albedos of the Hapke model. The abundances obtained by inverting the linear single-scattering albedo mixture may be interpreted as volume fractions which are weighted by the endmember's extinction coefficient. Commonly, identical extinction coefficients are assumed throughout all endmembers and the obtained volume fractions are converted to mass fractions using either measured or assumed densities. In theory, the proposed method may cover different grain sizes if each grain size range of a mineral is treated as a distinct endmember. Here, we present a method to transform the mixing coefficients to mass fractions for arbitrary combinations of extinction coefficients and densities. The required parameters are computed from reflectance measurements of well defined endmember mixtures. Consequently, additional measurements, e.g., the endmember density, are no longer required. We evaluate the method based on laboratory measurements and various results presented in the literature, respectively. It is shown that the procedure transforms the mixing coefficients to mass fractions yielding an accuracy comparable to carefully calibrated laboratory measurements without additional knowledge. For our laboratory measurements, the square root of the mean squared error is less than 4.82 wt%. In addition, the method corrects for systematic effects originating from mixtures of endmembers showing a highly varying albedo, e.g., plagioclase and pyroxene.

Acute toxicity to goldfish of mixtures of chloramines, copper, and linear alkylate sulfonate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, C.F.; McKee, J.A.

1980-01-01

The toxicity to goldfish (Carassius auratus) of mixtures of chloramines, copper, and linear alkylate sulfonate (LAS) was studied by continuous-flow toxicity tests during an exposure period of 96 hours. The individual toxicities of these three chemicals are either additive or synergistic in mixtures, depending on the rate of toxic action of the individual chemical, the toxicity ratio of the chemicals in the mixtures, and the concentration of the mixtures.

Vibration effect on the Soret-induced convection of ternary mixture in a rectangular cavity heated from below

NASA Astrophysics Data System (ADS)

Lyubimova, T. P.; Zubova, N. A.

2017-06-01

This paper presents the results of numerical simulation of the Soret-induced convection of ternary mixture in the rectangular cavity elongated in horizontal direction in gravity field. The cavity has rigid impermeable boundaries. It is heated from the bellow and undergoes translational linearly polarized vibrations of finite amplitude and frequency in the horizontal direction. The problem is solved by finite difference method in the framework of full unsteady non-linear approach. The procedure of diagonalization of the molecular diffusion coefficient matrix is applied, allowing to eliminate cross-diffusion components in the equations and to reduce the number of the governing parameters. The calculations are performed for model ternary mixture with positive separation ratios of the components. The data on the vibration effect on temporal evolution of instantaneous and average fields and integral characteristics of the flow and heat and mass transfer at different levels of gravity are obtained.

Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression

NASA Astrophysics Data System (ADS)

Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem

2010-09-01

In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate

PubMed Central

Pradines, Joël R.; Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Farutin, Victor; Huang, Yongqing; Gunay, Nur Sibel; Capila, Ishan

2016-01-01

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements. PMID:27112127

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate.

PubMed

Pradines, Joël R; Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Farutin, Victor; Huang, Yongqing; Gunay, Nur Sibel; Capila, Ishan

2016-04-26

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements.

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate

NASA Astrophysics Data System (ADS)

Pradines, Joël R.; Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Farutin, Victor; Huang, Yongqing; Gunay, Nur Sibel; Capila, Ishan

2016-04-01

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements.

INCORPORATING CONCENTRATION DEPENDENCE IN STABLE ISOTOPE MIXING MODELS

EPA Science Inventory

Stable isotopes are frequently used to quantify the contributions of multiple sources to a mixture; e.g., C and N isotopic signatures can be used to determine the fraction of three food sources in a consumer's diet. The standard dual isotope, three source linear mixing model ass...

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

PubMed

Yan, Luchun; Liu, Jiemin; Qu, Chen; Gu, Xingye; Zhao, Xia

2015-01-28

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

Linking asphalt binder fatigue to asphalt mixture fatigue performance using viscoelastic continuum damage modeling

NASA Astrophysics Data System (ADS)

Safaei, Farinaz; Castorena, Cassie; Kim, Y. Richard

2016-08-01

Fatigue cracking is a major form of distress in asphalt pavements. Asphalt binder is the weakest asphalt concrete constituent and, thus, plays a critical role in determining the fatigue resistance of pavements. Therefore, the ability to characterize and model the inherent fatigue performance of an asphalt binder is a necessary first step to design mixtures and pavements that are not susceptible to premature fatigue failure. The simplified viscoelastic continuum damage (S-VECD) model has been used successfully by researchers to predict the damage evolution in asphalt mixtures for various traffic and climatic conditions using limited uniaxial test data. In this study, the S-VECD model, developed for asphalt mixtures, is adapted for asphalt binders tested under cyclic torsion in a dynamic shear rheometer. Derivation of the model framework is presented. The model is verified by producing damage characteristic curves that are both temperature- and loading history-independent based on time sweep tests, given that the effects of plasticity and adhesion loss on the material behavior are minimal. The applicability of the S-VECD model to the accelerated loading that is inherent of the linear amplitude sweep test is demonstrated, which reveals reasonable performance predictions, but with some loss in accuracy compared to time sweep tests due to the confounding effects of nonlinearity imposed by the high strain amplitudes included in the test. The asphalt binder S-VECD model is validated through comparisons to asphalt mixture S-VECD model results derived from cyclic direct tension tests and Accelerated Loading Facility performance tests. The results demonstrate good agreement between the asphalt binder and mixture test results and pavement performance, indicating that the developed model framework is able to capture the asphalt binder's contribution to mixture fatigue and pavement fatigue cracking performance.

Solubility of Naproxen in Polyethylene Glycol 200 + Water Mixtures at Various Temperatures

PubMed Central

Panahi-Azar, Vahid; Soltanpour, Shahla; Martinez, Fleming; Jouyban, Abolghasem

2015-01-01

The solubility of naproxen in binary mixtures of polyethylene glycol 200 (PEG 200) + water at the temperature range from 298.0 K to 318.0 K were reported. The combinations of Jouyban-Acree model + van’t Hoff and Jouyban-Acree model + partial solubility parameters were used to predict the solubility of naproxen in PEG 200 + water mixtures at different temperatures. Combination of Jouyban-Acree model with van’t Hoff equation can be used to predict solubility in PEG 200 + water with only four solubility data in mono-solvents. The obtained solubility calculation errors vary from ~ 17 % up to 35 % depend on the number of required input data. Non-linear enthalpy-entropy compensation was found for naproxen in the investigated solvent system and the Jouyban−Acree model provides reasonably accurate mathematical descriptions of the thermodynamic data of naproxen in the investigated binary solvent systems. PMID:26664370

Modelling interactions of acid–base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica

PubMed Central

Macey, Brett M.; Jenny, Matthew J.; Williams, Heidi R.; Thibodeaux, Lindy K.; Beal, Marion; Almeida, Jonas S.; Cunningham, Charles; Mancia, Annalaura; Warr, Gregory W.; Burge, Erin J.; Holland, A. Fred; Gross, Paul S.; Hikima, Sonomi; Burnett, Karen G.; Burnett, Louis; Chapman, Robert W.

2010-01-01

Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001–0.400 µM), Zn (0.001–3.059 µM) or Cu (0.002–0.787 µM), either alone or in combination for 1 to 27 days. We measured indicators of acid–base balance (hemolymph pH and total CO2), gas exchange (Po2), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid–base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid–base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of subacute exposure to contaminant mixtures. PMID:19958840

Modeling the formation of ordered nano-assemblies comprised by dendrimers and linear polyelectrolytes: The role of Coulombic interactions

NASA Astrophysics Data System (ADS)

Eleftheriou, E.; Karatasos, K.

2012-10-01

Models of mixtures of peripherally charged dendrimers with oppositely charged linear polyelectrolytes in the presence of explicit solvent are studied by means of molecular dynamics simulations. Under the influence of varying strength of electrostatic interactions, these systems appear to form dynamically arrested film-like interconnected structures in the polymer-rich phase. Acting like a pseudo-thermodynamic inverse temperature, the increase of the strength of the Coulombic interactions drive the polymeric constituents of the mixture to a gradual dynamic freezing-in. The timescale of the average density fluctuations of the formed complexes initially increases in the weak electrostatic regime reaching a finite limit as the strength of electrostatic interactions grow. Although the models are overall electrically neutral, during this process the dendrimer/linear complexes develop a polar character with an excess charge mainly close to the periphery of the dendrimers. The morphological characteristics of the resulted pattern are found to depend on the size of the polymer chains on account of the distinct conformational features assumed by the complexed linear polyelectrolytes of different length. In addition, the length of the polymer chain appears to affect the dynamics of the counterions, thus affecting the ionic transport properties of the system. It appears, therefore, that the strength of electrostatic interactions together with the length of the linear polyelectrolytes are parameters to which these systems are particularly responsive, offering thus the possibility for a better control of the resulted structure and the electric properties of these soft-colloidal systems.

Large eddy simulation of the low temperature ignition and combustion processes on spray flame with the linear eddy model

NASA Astrophysics Data System (ADS)

Wei, Haiqiao; Zhao, Wanhui; Zhou, Lei; Chen, Ceyuan; Shu, Gequn

2018-03-01

Large eddy simulation coupled with the linear eddy model (LEM) is employed for the simulation of n-heptane spray flames to investigate the low temperature ignition and combustion process in a constant-volume combustion vessel under diesel-engine relevant conditions. Parametric studies are performed to give a comprehensive understanding of the ignition processes. The non-reacting case is firstly carried out to validate the present model by comparing the predicted results with the experimental data from the Engine Combustion Network (ECN). Good agreements are observed in terms of liquid and vapour penetration length, as well as the mixture fraction distributions at different times and different axial locations. For the reacting cases, the flame index was introduced to distinguish between the premixed and non-premixed combustion. A reaction region (RR) parameter is used to investigate the ignition and combustion characteristics, and to distinguish the different combustion stages. Results show that the two-stage combustion process can be identified in spray flames, and different ignition positions in the mixture fraction versus RR space are well described at low and high initial ambient temperatures. At an initial condition of 850 K, the first-stage ignition is initiated at the fuel-lean region, followed by the reactions in fuel-rich regions. Then high-temperature reaction occurs mainly at the places with mixture concentration around stoichiometric mixture fraction. While at an initial temperature of 1000 K, the first-stage ignition occurs at the fuel-rich region first, then it moves towards fuel-richer region. Afterwards, the high-temperature reactions move back to the stoichiometric mixture fraction region. For all of the initial temperatures considered, high-temperature ignition kernels are initiated at the regions richer than stoichiometric mixture fraction. By increasing the initial ambient temperature, the high-temperature ignition kernels move towards richer mixture regions. And after the spray flames gets quasi-steady, most heat is released at the stoichiometric mixture fraction regions. In addition, combustion mode analysis based on key intermediate species illustrates three-mode combustion processes in diesel spray flames.

Establishment method of a mixture model and its practical application for transmission gears in an engineering vehicle

NASA Astrophysics Data System (ADS)

Wang, Jixin; Wang, Zhenyu; Yu, Xiangjun; Yao, Mingyao; Yao, Zongwei; Zhang, Erping

2012-09-01

Highly versatile machines, such as wheel loaders, forklifts, and mining haulers, are subject to many kinds of working conditions, as well as indefinite factors that lead to the complexity of the load. The load probability distribution function (PDF) of transmission gears has many distributions centers; thus, its PDF cannot be well represented by just a single-peak function. For the purpose of representing the distribution characteristics of the complicated phenomenon accurately, this paper proposes a novel method to establish a mixture model. Based on linear regression models and correlation coefficients, the proposed method can be used to automatically select the best-fitting function in the mixture model. Coefficient of determination, the mean square error, and the maximum deviation are chosen and then used as judging criteria to describe the fitting precision between the theoretical distribution and the corresponding histogram of the available load data. The applicability of this modeling method is illustrated by the field testing data of a wheel loader. Meanwhile, the load spectra based on the mixture model are compiled. The comparison results show that the mixture model is more suitable for the description of the load-distribution characteristics. The proposed research improves the flexibility and intelligence of modeling, reduces the statistical error and enhances the fitting accuracy, and the load spectra complied by this method can better reflect the actual load characteristic of the gear component.

Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model

PubMed Central

Zhao, Rui; Catalano, Paul; DeGruttola, Victor G.; Michor, Franziska

2017-01-01

The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time. Simulation results show that our method was able to classify subjects according to their patterns of treatment response with greater than 80% accuracy in the three scenarios tested. We then applied our model to a large randomized controlled phase III clinical trial of multiple myeloma patients. Analysis results suggest that the longitudinal tumor burden trajectories in multiple myeloma patients are heterogeneous and nonlinear, even among patients assigned to the same treatment cohort. In addition, between cohorts, there are distinct differences in terms of the regression parameters and the distributions among categories in the mixture. Those results imply that longitudinal data from clinical trials may harbor unobserved subgroups and nonlinear relationships; accounting for both may be important for analyzing longitudinal data. PMID:28723910

Separation mechanism of nortriptyline and amytriptyline in RPLC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gritti, Fabrice; Guiochon, Georges A

2005-08-01

The single and the competitive equilibrium isotherms of nortriptyline and amytriptyline were acquired by frontal analysis (FA) on the C{sub 18}-bonded discovery column, using a 28/72 (v/v) mixture of acetonitrile and water buffered with phosphate (20 mM, pH 2.70). The adsorption energy distributions (AED) of each compound were calculated from the raw adsorption data. Both the fitting of the adsorption data using multi-linear regression analysis and the AEDs are consistent with a trimodal isotherm model. The single-component isotherm data fit well to the tri-Langmuir isotherm model. The extension to a competitive two-component tri-Langmuir isotherm model based on the best parametersmore » of the single-component isotherms does not account well for the breakthrough curves nor for the overloaded band profiles measured for mixtures of nortriptyline and amytriptyline. However, it was possible to derive adjusted parameters of a competitive tri-Langmuir model based on the fitting of the adsorption data obtained for these mixtures. A very good agreement was then found between the calculated and the experimental overloaded band profiles of all the mixtures injected.« less

Functional mixture regression.

PubMed

Yao, Fang; Fu, Yuejiao; Lee, Thomas C M

2011-04-01

In functional linear models (FLMs), the relationship between the scalar response and the functional predictor process is often assumed to be identical for all subjects. Motivated by both practical and methodological considerations, we relax this assumption and propose a new class of functional regression models that allow the regression structure to vary for different groups of subjects. By projecting the predictor process onto its eigenspace, the new functional regression model is simplified to a framework that is similar to classical mixture regression models. This leads to the proposed approach named as functional mixture regression (FMR). The estimation of FMR can be readily carried out using existing software implemented for functional principal component analysis and mixture regression. The practical necessity and performance of FMR are illustrated through applications to a longevity analysis of female medflies and a human growth study. Theoretical investigations concerning the consistent estimation and prediction properties of FMR along with simulation experiments illustrating its empirical properties are presented in the supplementary material available at Biostatistics online. Corresponding results demonstrate that the proposed approach could potentially achieve substantial gains over traditional FLMs.

Approximation of a radial diffusion model with a multiple-rate model for hetero-disperse particle mixtures

PubMed Central

Ju, Daeyoung; Young, Thomas M.; Ginn, Timothy R.

2012-01-01

An innovative method is proposed for approximation of the set of radial diffusion equations governing mass exchange between aqueous bulk phase and intra-particle phase for a hetero-disperse mixture of particles such as occur in suspension in surface water, in riverine/estuarine sediment beds, in soils and in aquifer materials. For this purpose the temporal variation of concentration at several uniformly distributed points within a normalized representative particle with spherical, cylindrical or planar shape is fitted with a 2-domain linear reversible mass exchange model. The approximation method is then superposed in order to generalize the model to a hetero-disperse mixture of particles. The method can reduce the computational effort needed in solving the intra-particle mass exchange of a hetero-disperse mixture of particles significantly and also the error due to the approximation is shown to be relatively small. The method is applied to describe desorption batch experiment of 1,2-Dichlorobenzene from four different soils with known particle size distributions and it could produce good agreement with experimental data. PMID:18304692

The Linear Mixing Approximation for Planetary Ices

NASA Astrophysics Data System (ADS)

Bethkenhagen, M.; Meyer, E. R.; Hamel, S.; Nettelmann, N.; French, M.; Scheibe, L.; Ticknor, C.; Collins, L. A.; Kress, J. D.; Fortney, J. J.; Redmer, R.

2017-12-01

We investigate the validity of the widely used linear mixing approximation for the equations of state (EOS) of planetary ices, which are thought to dominate the interior of the ice giant planets Uranus and Neptune. For that purpose we perform density functional theory molecular dynamics simulations using the VASP code.[1] In particular, we compute 1:1 binary mixtures of water, ammonia, and methane, as well as their 2:1:4 ternary mixture at pressure-temperature conditions typical for the interior of Uranus and Neptune.[2,3] In addition, a new ab initio EOS for methane is presented. The linear mixing approximation is verified for the conditions present inside Uranus ranging up to 10 Mbar based on the comprehensive EOS data set. We also calculate the diffusion coefficients for the ternary mixture along different Uranus interior profiles and compare them to the values of the pure compounds. We find that deviations of the linear mixing approximation from the real mixture are generally small; for the EOS they fall within about 4% uncertainty while the diffusion coefficients deviate up to 20% . The EOS of planetary ices are applied to adiabatic models of Uranus. It turns out that a deep interior of almost pure ices is consistent with the gravity field data, in which case the planet becomes rather cold (T core ˜ 4000 K). [1] G. Kresse and J. Hafner, Physical Review B 47, 558 (1993). [2] R. Redmer, T.R. Mattsson, N. Nettelmann and M. French, Icarus 211, 798 (2011). [3] N. Nettelmann, K. Wang, J. J. Fortney, S. Hamel, S. Yellamilli, M. Bethkenhagen and R. Redmer, Icarus 275, 107 (2016).

Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields.

PubMed

Yousefi, Siamak; Balasubramanian, Madhusudhanan; Goldbaum, Michael H; Medeiros, Felipe A; Zangwill, Linda M; Weinreb, Robert N; Liebmann, Jeffrey M; Girkin, Christopher A; Bowd, Christopher

2016-05-01

To validate Gaussian mixture-model with expectation maximization (GEM) and variational Bayesian independent component analysis mixture-models (VIM) for detecting glaucomatous progression along visual field (VF) defect patterns (GEM-progression of patterns (POP) and VIM-POP). To compare GEM-POP and VIM-POP with other methods. GEM and VIM models separated cross-sectional abnormal VFs from 859 eyes and normal VFs from 1117 eyes into abnormal and normal clusters. Clusters were decomposed into independent axes. The confidence limit (CL) of stability was established for each axis with a set of 84 stable eyes. Sensitivity for detecting progression was assessed in a sample of 83 eyes with known progressive glaucomatous optic neuropathy (PGON). Eyes were classified as progressed if any defect pattern progressed beyond the CL of stability. Performance of GEM-POP and VIM-POP was compared to point-wise linear regression (PLR), permutation analysis of PLR (PoPLR), and linear regression (LR) of mean deviation (MD), and visual field index (VFI). Sensitivity and specificity for detecting glaucomatous VFs were 89.9% and 93.8%, respectively, for GEM and 93.0% and 97.0%, respectively, for VIM. Receiver operating characteristic (ROC) curve areas for classifying progressed eyes were 0.82 for VIM-POP, 0.86 for GEM-POP, 0.81 for PoPLR, 0.69 for LR of MD, and 0.76 for LR of VFI. GEM-POP was significantly more sensitive to PGON than PoPLR and linear regression of MD and VFI in our sample, while providing localized progression information. Detection of glaucomatous progression can be improved by assessing longitudinal changes in localized patterns of glaucomatous defect identified by unsupervised machine learning.

Isomer-Specific Binding Affinity of Perfluorooctanesulfonate (PFOS) and Perfluorooctanoate (PFOA) to Serum Proteins.

PubMed

Beesoon, Sanjay; Martin, Jonathan W

2015-05-05

Perfluorooctanesulfonate (PFOS) and perfluorooctanoate (PFOA) are among the most prominent contaminants in human serum, and these were historically manufactured as technical mixtures of linear and branched isomers. The isomers display unique pharmacokinetics in humans and in animal models, but molecular mechanisms underlying isomer-specific PFOS and PFOA disposition have not previously been studied. Here, ultrafiltration devices were used to examine (i) the dissociation constants (Kd) of individual PFOS and PFOA isomers with human serum albumin (HSA) and (ii) relative binding affinity of isomers in technical mixtures spiked to whole calf serum and human serum. Measurement of HSA Kd's demonstrated that linear PFOS (Kd=8(±4)×10(-8) M) was much more tightly bound than branched PFOS isomers (Kd range from 8(±1)×10(-5) M to 4(±2)×10(-4) M). Similarly, linear PFOA (Kd=1(±0.9)×10(-4) M) was more strongly bound to HSA compared to branched PFOA isomers (Kd range from 4(±2)×10(-4) M to 3(±2)×10(-4) M). The higher binding affinities of linear PFOS and PFOA to total serum protein were confirmed when both calf serum and human serum were spiked with technical mixtures. Overall, these data provide a mechanistic explanation for the longer biological half-life of PFOS in humans, compared to PFOA, and for the higher transplacental transfer efficiencies and renal clearance of branched PFOS and PFOA isomers, compared to the respective linear isomer.

A continuum theory for multicomponent chromatography modeling.

PubMed

Pfister, David; Morbidelli, Massimo; Nicoud, Roger-Marc

2016-05-13

A continuum theory is proposed for modeling multicomponent chromatographic systems under linear conditions. The model is based on the description of complex mixtures, possibly involving tens or hundreds of solutes, by a continuum. The present approach is shown to be very efficient when dealing with a large number of similar components presenting close elution behaviors and whose individual analytical characterization is impossible. Moreover, approximating complex mixtures by continuous distributions of solutes reduces the required number of model parameters to the few ones specific to the characterization of the selected continuous distributions. Therefore, in the frame of the continuum theory, the simulation of large multicomponent systems gets simplified and the computational effectiveness of the chromatographic model is thus dramatically improved. Copyright © 2016 Elsevier B.V. All rights reserved.

Finite mixture models for the computation of isotope ratios in mixed isotopic samples

NASA Astrophysics Data System (ADS)

Koffler, Daniel; Laaha, Gregor; Leisch, Friedrich; Kappel, Stefanie; Prohaska, Thomas

2013-04-01

Finite mixture models have been used for more than 100 years, but have seen a real boost in popularity over the last two decades due to the tremendous increase in available computing power. The areas of application of mixture models range from biology and medicine to physics, economics and marketing. These models can be applied to data where observations originate from various groups and where group affiliations are not known, as is the case for multiple isotope ratios present in mixed isotopic samples. Recently, the potential of finite mixture models for the computation of 235U/238U isotope ratios from transient signals measured in individual (sub-)µm-sized particles by laser ablation - multi-collector - inductively coupled plasma mass spectrometry (LA-MC-ICPMS) was demonstrated by Kappel et al. [1]. The particles, which were deposited on the same substrate, were certified with respect to their isotopic compositions. Here, we focus on the statistical model and its application to isotope data in ecogeochemistry. Commonly applied evaluation approaches for mixed isotopic samples are time-consuming and are dependent on the judgement of the analyst. Thus, isotopic compositions may be overlooked due to the presence of more dominant constituents. Evaluation using finite mixture models can be accomplished unsupervised and automatically. The models try to fit several linear models (regression lines) to subgroups of data taking the respective slope as estimation for the isotope ratio. The finite mixture models are parameterised by: • The number of different ratios. • Number of points belonging to each ratio-group. • The ratios (i.e. slopes) of each group. Fitting of the parameters is done by maximising the log-likelihood function using an iterative expectation-maximisation (EM) algorithm. In each iteration step, groups of size smaller than a control parameter are dropped; thereby the number of different ratios is determined. The analyst only influences some control parameters of the algorithm, i.e. the maximum count of ratios, the minimum relative group-size of data points belonging to each ratio has to be defined. Computation of the models can be done with statistical software. In this study Leisch and Grün's flexmix package [2] for the statistical open-source software R was applied. A code example is available in the electronic supplementary material of Kappel et al. [1]. In order to demonstrate the usefulness of finite mixture models in fields dealing with the computation of multiple isotope ratios in mixed samples, a transparent example based on simulated data is presented and problems regarding small group-sizes are illustrated. In addition, the application of finite mixture models to isotope ratio data measured in uranium oxide particles is shown. The results indicate that finite mixture models perform well in computing isotope ratios relative to traditional estimation procedures and can be recommended for more objective and straightforward calculation of isotope ratios in geochemistry than it is current practice. [1] S. Kappel, S. Boulyga, L. Dorta, D. Günther, B. Hattendorf, D. Koffler, G. Laaha, F. Leisch and T. Prohaska: Evaluation Strategies for Isotope Ratio Measurements of Single Particles by LA-MC-ICPMS, Analytical and Bioanalytical Chemistry, 2013, accepted for publication on 2012-12-18 (doi: 10.1007/s00216-012-6674-3) [2] B. Grün and F. Leisch: Fitting finite mixtures of generalized linear regressions in R. Computational Statistics & Data Analysis, 51(11), 5247-5252, 2007. (doi:10.1016/j.csda.2006.08.014)

Thermodynamic properties of model CdTe/CdSe mixtures

DOE PAGES

van Swol, Frank; Zhou, Xiaowang W.; Challa, Sivakumar R.; ...

2015-02-20

We report on the thermodynamic properties of binary compound mixtures of model groups II–VI semiconductors. We use the recently introduced Stillinger–Weber Hamiltonian to model binary mixtures of CdTe and CdSe. We use molecular dynamics simulations to calculate the volume and enthalpy of mixing as a function of mole fraction. The lattice parameter of the mixture closely follows Vegard's law: a linear relation. This implies that the excess volume is a cubic function of mole fraction. A connection is made with hard sphere models of mixed fcc and zincblende structures. We found that the potential energy exhibits a positive deviation frommore » ideal soluton behaviour; the excess enthalpy is nearly independent of temperatures studied (300 and 533 K) and is well described by a simple cubic function of the mole fraction. Using a regular solution approach (combining non-ideal behaviour for the enthalpy with ideal solution behaviour for the entropy of mixing), we arrive at the Gibbs free energy of the mixture. The Gibbs free energy results indicate that the CdTe and CdSe mixtures exhibit phase separation. The upper consolute temperature is found to be 335 K. Finally, we provide the surface energy as a function of composition. Moreover, it roughly follows ideal solution theory, but with a negative deviation (negative excess surface energy). This indicates that alloying increases the stability, even for nano-particles.« less

Cilazapril stability in the presence of hydrochlorothiazide in model mixtures and fixed dose combination.

PubMed

Paszun, Sylwia K; Stanisz, Beata J; Gradowska, Agnieszka

2013-01-01

The presented study aimed at the evaluation of hydrochlorothiazide influence on cilazapril stability in model mixture and fixed dose tablet formulation. The degradation of cilazapril in the presence of hydrochlorothiazide took place according to autocatalytic reaction kinetic mechanism, described mathematically by Prout-Tompkins equation. Hydrochlorothiazide coexistence with cilazapril in model mixture and fixed dose tablet without blister package accelerated cilazapril degradation in comparison with degradation of cilazapril substance. Values of reaction induction time shortened, while those of observed reaction rate constant increased. Increasing values of relative humidity and temperature have negative impact on cilazapril stability. Determined semi-logarithmic relationships: In k = f(RH) and Arrhenius ln k = f(1/T) are linear and are cilazapril stability predictive. The blister (OPA/Alu/PVC//Alu) package of fixed dose tablets, constitutes absolute moisture protection and prevent cilazapril--hydrochlorothiazide interaction occurrence.

Estimation of affinities of ligands in mixtures via magnetic recovery of target-ligand complexes and chromatographic analyses: chemometrics and an experimental model

PubMed Central

2011-01-01

Abstract Background The combinatorial library strategy of using multiple candidate ligands in mixtures as library members is ideal in terms of cost and efficiency, but needs special screening methods to estimate the affinities of candidate ligands in such mixtures. Herein, a new method to screen candidate ligands present in unknown molar quantities in mixtures was investigated. Results The proposed method involves preparing a processed-mixture-for-screening (PMFS) with each mixture sample and an exogenous reference ligand, initiating competitive binding among ligands from the PMFS to a target immobilized on magnetic particles, recovering target-ligand complexes in equilibrium by magnetic force, extracting and concentrating bound ligands, and analyzing ligands in the PMFS and the concentrated extract by chromatography. The relative affinity of each candidate ligand to its reference ligand is estimated via an approximation equation assuming (a) the candidate ligand and its reference ligand bind to the same site(s) on the target, (b) their chromatographic peak areas are over five times their intercepts of linear response but within their linear ranges, (c) their binding ratios are below 10%. These prerequisites are met by optimizing primarily the quantity of the target used and the PMFS composition ratio. The new method was tested using the competitive binding of biotin derivatives from mixtures to streptavidin immobilized on magnetic particles as a model. Each mixture sample containing a limited number of candidate biotin derivatives with moderate differences in their molar quantities were prepared via parallel-combinatorial-synthesis (PCS) without purification, or via the pooling of individual compounds. Some purified biotin derivatives were used as reference ligands. This method showed resistance to variations in chromatographic quantification sensitivity and concentration ratios; optimized conditions to validate the approximation equation could be applied to different mixture samples. Relative affinities of candidate biotin derivatives with unknown molar quantities in each mixture sample were consistent with those estimated by a homogenous method using their purified counterparts as samples. Conclusions This new method is robust and effective for each mixture possessing a limited number of candidate ligands whose molar quantities have moderate differences, and its integration with PCS has promise to routinely practice the mixture-based library strategy. PMID:21545719

Accuracy assessment of linear spectral mixture model due to terrain undulation

NASA Astrophysics Data System (ADS)

Wang, Tianxing; Chen, Songlin; Ma, Ya

2008-12-01

Mixture spectra are common in remote sensing due to the limitations of spatial resolution and the heterogeneity of land surface. During the past 30 years, a lot of subpixel model have developed to investigate the information within mixture pixels. Linear spectral mixture model (LSMM) is a simper and more general subpixel model. LSMM also known as spectral mixture analysis is a widely used procedure to determine the proportion of endmembers (constituent materials) within a pixel based on the endmembers' spectral characteristics. The unmixing accuracy of LSMM is restricted by variety of factors, but now the research about LSMM is mostly focused on appraisement of nonlinear effect relating to itself and techniques used to select endmembers, unfortunately, the environment conditions of study area which could sway the unmixing-accuracy, such as atmospheric scatting and terrain undulation, are not studied. This paper probes emphatically into the accuracy uncertainty of LSMM resulting from the terrain undulation. ASTER dataset was chosen and the C terrain correction algorithm was applied to it. Based on this, fractional abundances for different cover types were extracted from both pre- and post-C terrain illumination corrected ASTER using LSMM. Simultaneously, the regression analyses and the IKONOS image were introduced to assess the unmixing accuracy. Results showed that terrain undulation could dramatically constrain the application of LSMM in mountain area. Specifically, for vegetation abundances, a improved unmixing accuracy of 17.6% (regression against to NDVI) and 18.6% (regression against to MVI) for R2 was achieved respectively by removing terrain undulation. Anyway, this study indicated in a quantitative way that effective removal or minimization of terrain illumination effects was essential for applying LSMM. This paper could also provide a new instance for LSMM applications in mountainous areas. In addition, the methods employed in this study could be effectively used to evaluate different algorithms of terrain undulation correction for further study.

A new hybrid double divisor ratio spectra method for the analysis of ternary mixtures

NASA Astrophysics Data System (ADS)

Youssef, Rasha M.; Maher, Hadir M.

2008-10-01

A new spectrophotometric method was developed for the simultaneous determination of ternary mixtures, without prior separation steps. This method is based on convolution of the double divisor ratio spectra, obtained by dividing the absorption spectrum of the ternary mixture by a standard spectrum of two of the three compounds in the mixture, using combined trigonometric Fourier functions. The magnitude of the Fourier function coefficients, at either maximum or minimum points, is related to the concentration of each drug in the mixture. The mathematical explanation of the procedure is illustrated. The method was applied for the assay of a model mixture consisting of isoniazid (ISN), rifampicin (RIF) and pyrazinamide (PYZ) in synthetic mixtures, commercial tablets and human urine samples. The developed method was compared with the double divisor ratio spectra derivative method (DDRD) and derivative ratio spectra-zero-crossing method (DRSZ). Linearity, validation, accuracy, precision, limits of detection, limits of quantitation, and other aspects of analytical validation are included in the text.

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

PubMed

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.

On some problems in a theory of thermally and mechanically interacting continuous media. Ph.D. Thesis; [linearized theory of interacting mixture of elastic solid and viscous fluid

NASA Technical Reports Server (NTRS)

Lee, Y. M.

1971-01-01

Using a linearized theory of thermally and mechanically interacting mixture of linear elastic solid and viscous fluid, we derive a fundamental relation in an integral form called a reciprocity relation. This reciprocity relation relates the solution of one initial-boundary value problem with a given set of initial and boundary data to the solution of a second initial-boundary value problem corresponding to a different initial and boundary data for a given interacting mixture. From this general integral relation, reciprocity relations are derived for a heat-conducting linear elastic solid, and for a heat-conducting viscous fluid. An initial-boundary value problem is posed and solved for the mixture of linear elastic solid and viscous fluid. With the aid of the Laplace transform and the contour integration, a real integral representation for the displacement of the solid constituent is obtained as one of the principal results of the analysis.

Quantiles for Finite Mixtures of Normal Distributions

ERIC Educational Resources Information Center

Rahman, Mezbahur; Rahman, Rumanur; Pearson, Larry M.

2006-01-01

Quantiles for finite mixtures of normal distributions are computed. The difference between a linear combination of independent normal random variables and a linear combination of independent normal densities is emphasized. (Contains 3 tables and 1 figure.)

Non-linear models for the detection of impaired cerebral blood flow autoregulation.

PubMed

Chacón, Max; Jara, José Luis; Miranda, Rodrigo; Katsogridakis, Emmanuel; Panerai, Ronney B

2018-01-01

The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxide and air. Non-linear models with BP as input and CBF velocity (CBFV) as output, were implemented with support vector machines (SVM) using separate recordings for learning and validation. Dynamic SVM implementations used either moving average or autoregressive structures. The efficiency of dynamic CA was estimated from the model's derived CBFV response to a step change in BP as an autoregulation index for both linear and non-linear models. Non-linear models with recurrences (autoregressive) showed the best results, with CA indexes of 5.9 ± 1.5 in normocapnia, and 2.5 ± 1.2 for hypercapnia with an area under the receiver-operator curve of 0.955. The high performance achieved by non-linear SVM models to detect deterioration of dynamic CA should encourage further assessment of its applicability to clinical conditions where CA might be impaired.

Multiscale Constitutive Modeling of Asphalt Concrete

NASA Astrophysics Data System (ADS)

Underwood, Benjamin Shane

Multiscale modeling of asphalt concrete has become a popular technique for gaining improved insight into the physical mechanisms that affect the material's behavior and ultimately its performance. This type of modeling considers asphalt concrete, not as a homogeneous mass, but rather as an assemblage of materials at different characteristic length scales. For proper modeling these characteristic scales should be functionally definable and should have known properties. Thus far, research in this area has not focused significant attention on functionally defining what the characteristic scales within asphalt concrete should be. Instead, many have made assumptions on the characteristic scales and even the characteristic behaviors of these scales with little to no support. This research addresses these shortcomings by directly evaluating the microstructure of the material and uses these results to create materials of different characteristic length scales as they exist within the asphalt concrete mixture. The objectives of this work are to; 1) develop mechanistic models for the linear viscoelastic (LVE) and damage behaviors in asphalt concrete at different length scales and 2) develop a mechanistic, mechanistic/empirical, or phenomenological formulation to link the different length scales into a model capable of predicting the effects of microstructural changes on the linear viscoelastic behaviors of asphalt concrete mixture, e.g., a microstructure association model for asphalt concrete mixture. Through the microstructural study it is found that asphalt concrete mixture can be considered as a build-up of three different phases; asphalt mastic, fine aggregate matrix (FAM), and finally the coarse aggregate particles. The asphalt mastic is found to exist as a homogenous material throughout the mixture and FAM, and the filler content within this material is consistent with the volumetric averaged concentration, which can be calculated from the job mix formula. It is also found that the maximum aggregate size of the FAM is mixture dependent, but consistent with a gradation parameter from the Baily Method of mixture design. Mechanistic modeling of these different length scales reveals that although many consider asphalt concrete to be a LVE material, it is in fact only quasi-LVE because it shows some tendencies that are inconsistent with LVE theory. Asphalt FAM and asphalt mastic show similar nonlinear tendencies although the exact magnitude of the effect differs. These tendencies can be ignored for damage modeling in the mixture and FAM scales as long as the effects are consistently ignored, but it is found that they must be accounted for in mastic and binder damage modeling. The viscoelastic continuum damage (VECD) model is used for damage modeling in this research. To aid in characterization and application of the VECD model for cyclic testing, a simplified version (S-VECD) is rigorously derived and verified. Through the modeling efforts at each scale, various factors affecting the fundamental and engineering properties at each scale are observed and documented. A microstructure association model that accounts for particle interaction through physico-chemical processes and the effects of aggregate structuralization is developed to links the moduli at each scale. This model is shown to be capable of upscaling the mixture modulus from either the experimentally determined mastic modulus or FAM modulus. Finally, an initial attempt at upscaling the damage and nonlinearity phenomenon is shown.

Linear viscoelastic limits of asphalt concrete at low and intermediate temperatures

NASA Astrophysics Data System (ADS)

Mehta, Yusuf A.

The purpose of this dissertation is to demonstrate the hypothesis that a region at which the behavior of asphalt concrete can be represented as a linear viscoelastic material can be determined at low and intermediate temperatures considering the stresses and strains typically developed in the pavements under traffic loading. Six mixtures containing different aggregate gradations and nominal maximum aggregate sizes varying from 12.5 to 37.5 mm were used in this study. The asphalt binder grade was the same for all mixtures. The mixtures were compacted to 7 +/- 1% air voids, using the Superpave Gyratory Compactor. Tests were conducted at low temperatures (-20°C and -10°C), using the indirect tensile test machine, and at intermediate temperatures (4°C and 20°C), using the Superpave shear machine. To determine the linear viscoelastic range of asphalt concrete, a relaxation test for 150 s, followed by a creep test for another 150 s, was conducted at 150 and 200 microstrains (1 microstrain = 1 x 10-6), at -20°C, and at 150 and 300 microstrains, at -10°C. A creep test for 200 s, followed by a recovery test for another 200 s, was conducted at stress levels up to 800 kPa at 4°C and up to 500 kPa at 20°C. At -20°C and -10°C, the behavior of the mixtures was linear viscoelastic at 200 and 300 microstrains, respectively. At intermediate temperatures (4°C and 20°C), an envelope defining the linear and nonlinear region in terms of stress as a function of shear creep compliance was constructed for all the mixtures. For creep tests conducted at 20°C, it was discovered that the commonly used protocol to verify the proportionality condition of linear viscoelastic behavior was unable to detect the appearance of nonlinear behavior at certain imposed shear stress levels. Said nonlinear behavior was easily detected, however, when checking the satisfaction of the superposition condition. The envelope constructed for determining when the material becomes nonlinear should be valid for mixtures similar to the ones tested in this study. Different envelopes should be used in the case of mixtures containing a very soft or a very stiff polymer modified binder. At 4°C, the typical values of stresses and material properties of mixtures fell within the linear viscoelastic region, considering the typical shear creep compliance values at loading times and stresses experienced in the field. However, typical values at 20°C fell within a region in which some, but not all of the mixtures tested in this study behaved linearly. It is known that the behavior of asphalt concrete mixture changes from linear to nonlinear, depending on the temperature and loading conditions. However, this study is the first of its kind in which both the proportionality and the superposition condition were evaluated. The experimental design and the analysis procedures presented in this study can be applied to similar experiments that may be conducted in the future to evaluate linearity of different types of asphalt concrete mixtures.

Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

PubMed Central

Zhang, Jinming; Cavallari, Jennifer M; Fang, Shona C; Weisskopf, Marc G; Lin, Xihong; Mittleman, Murray A; Christiani, David C

2017-01-01

Background Environmental and occupational exposure to metals is ubiquitous worldwide, and understanding the hazardous metal components in this complex mixture is essential for environmental and occupational regulations. Objective To identify hazardous components from metal mixtures that are associated with alterations in cardiac autonomic responses. Methods Urinary concentrations of 16 types of metals were examined and ‘acceleration capacity’ (AC) and ‘deceleration capacity’ (DC), indicators of cardiac autonomic effects, were quantified from ECG recordings among 54 welders. We fitted linear mixed-effects models with least absolute shrinkage and selection operator (LASSO) to identify metal components that are associated with AC and DC. The Bayesian Information Criterion was used as the criterion for model selection procedures. Results Mercury and chromium were selected for DC analysis, whereas mercury, chromium and manganese were selected for AC analysis through the LASSO approach. When we fitted the linear mixed-effects models with ‘selected’ metal components only, the effect of mercury remained significant. Every 1 µg/L increase in urinary mercury was associated with −0.58 ms (−1.03, –0.13) changes in DC and 0.67 ms (0.25, 1.10) changes in AC. Conclusion Our study suggests that exposure to several metals is associated with impaired cardiac autonomic functions. Our findings should be replicated in future studies with larger sample sizes. PMID:28663305

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perera, Aurélien; Mazighi, Redha

Computer simulation studies of aqueous dimethyl sulfoxyde (DMSO) mixtures show micro-heterogeneous structures, just like aqueous alcohol mixtures. However, there is a marked difference in the aggregate structure of water between the two types of systems. While water molecules form multiconnected globular clusters in alcohols, we report herein that the typical water aggregates in aqueous DMSO mixtures are linear, favouring a 2 hydrogen bond structure per water molecule, and for all DMSO mole fractions ranging from 0.1 to 0.9. This linear-aggregate structure produces a particular signature in the water site-site structure factors, in the form of a pre-peak at k ≈more » 0.2–0.8 Å{sup −1}, depending on DMSO concentration. This pre-peak is either absent in other aqueous mixtures, such as aqueous methanol mixtures, or very difficult to see through computer simulations, such as in aqueous-t-butanol mixtures. This difference in the topology of the aggregates explains why the Kirkwood-Buff integrals of aqueous-DMSO mixture look nearly ideal, in contrast with those of aqueous alcohol mixtures, suggesting a connection between the shape of the water aggregates, its fluctuations, and the concentration fluctuations. In order to further study this discrepancy between aqueous DMSO and aqueous alcohol mixture, two models of pseudo-DMSO are introduced, where the size of the sulfur atom is increased by a factor 1.6 and 1.7, respectively, hence increasing the hydrophobicity of the molecule. The study shows that these mixtures become closer to the emulsion type seen in aqueous alcohol mixtures, with more globular clustering of the water molecules, long range domain oscillations in the water-water correlations and increased water-water Kirkwood-Buff integrals. It demonstrates that the local ordering of the water molecules is influenced by the nature of the solute molecules, with very different consequences for structural properties and related thermodynamic quantities. This study illustrates the unique plasticity of water in presence of different types of solutes.« less

Human Language Technology: Opportunities and Challenges

DTIC Science & Technology

2005-01-01

because of the connections to and reliance on signal processing. Audio diarization critically includes indexing of speakers [12], since speaker ...to reduce inter- speaker variability in training. Standard techniques include vocal-tract length normalization, adaptation of acoustic models using...maximum likelihood linear regression (MLLR), and speaker -adaptive training based on MLLR. The acoustic models are mixtures of Gaussians, typically with

Non-linear models for the detection of impaired cerebral blood flow autoregulation

PubMed Central

Miranda, Rodrigo; Katsogridakis, Emmanuel

2018-01-01

The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxide and air. Non-linear models with BP as input and CBF velocity (CBFV) as output, were implemented with support vector machines (SVM) using separate recordings for learning and validation. Dynamic SVM implementations used either moving average or autoregressive structures. The efficiency of dynamic CA was estimated from the model’s derived CBFV response to a step change in BP as an autoregulation index for both linear and non-linear models. Non-linear models with recurrences (autoregressive) showed the best results, with CA indexes of 5.9 ± 1.5 in normocapnia, and 2.5 ± 1.2 for hypercapnia with an area under the receiver-operator curve of 0.955. The high performance achieved by non-linear SVM models to detect deterioration of dynamic CA should encourage further assessment of its applicability to clinical conditions where CA might be impaired. PMID:29381724

Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

NASA Astrophysics Data System (ADS)

Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke

2016-01-01

Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations.

PubMed

Elkhoudary, Mahmoud M; Abdel Salam, Randa A; Hadad, Ghada M

2014-09-15

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components' mixtures using easy and widely used UV spectrophotometer. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations

NASA Astrophysics Data System (ADS)

Elkhoudary, Mahmoud M.; Abdel Salam, Randa A.; Hadad, Ghada M.

2014-09-01

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components’ mixtures using easy and widely used UV spectrophotometer.

Mixtures of Berkson and classical covariate measurement error in the linear mixed model: Bias analysis and application to a study on ultrafine particles.

PubMed

Deffner, Veronika; Küchenhoff, Helmut; Breitner, Susanne; Schneider, Alexandra; Cyrys, Josef; Peters, Annette

2018-05-01

The ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual-specific measurement error; Berkson-type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual-specific error components, autocorrelated errors, and a mixture of classical and Berkson error. Theoretical considerations and simulation results show, that autocorrelation may severely change the attenuation of the effect estimations. Furthermore, unbalanced designs and the inclusion of confounding variables influence the degree of attenuation. Bias correction with the method of moments using data with mixture measurement error partially yielded better results compared to the usage of incomplete data with classical error. Confidence intervals (CIs) based on the delta method achieved better coverage probabilities than those based on Bootstrap samples. Moreover, we present the application of these new methods to heart rate measurements within the Augsburger Umweltstudie: the corrected effect estimates were slightly higher than their naive equivalents. The substantial measurement error of ultrafine particle measurements has little impact on the results. The developed methodology is generally applicable to longitudinal data with measurement error. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining Mixture Components for Clustering*

PubMed Central

Baudry, Jean-Patrick; Raftery, Adrian E.; Celeux, Gilles; Lo, Kenneth; Gottardo, Raphaël

2010-01-01

Model-based clustering consists of fitting a mixture model to data and identifying each cluster with one of its components. Multivariate normal distributions are typically used. The number of clusters is usually determined from the data, often using BIC. In practice, however, individual clusters can be poorly fitted by Gaussian distributions, and in that case model-based clustering tends to represent one non-Gaussian cluster by a mixture of two or more Gaussian distributions. If the number of mixture components is interpreted as the number of clusters, this can lead to overestimation of the number of clusters. This is because BIC selects the number of mixture components needed to provide a good approximation to the density, rather than the number of clusters as such. We propose first selecting the total number of Gaussian mixture components, K, using BIC and then combining them hierarchically according to an entropy criterion. This yields a unique soft clustering for each number of clusters less than or equal to K. These clusterings can be compared on substantive grounds, and we also describe an automatic way of selecting the number of clusters via a piecewise linear regression fit to the rescaled entropy plot. We illustrate the method with simulated data and a flow cytometry dataset. Supplemental Materials are available on the journal Web site and described at the end of the paper. PMID:20953302

A reciprocal theorem for a mixture theory. [development of linearized theory of interacting media

NASA Technical Reports Server (NTRS)

Martin, C. J.; Lee, Y. M.

1972-01-01

A dynamic reciprocal theorem for a linearized theory of interacting media is developed. The constituents of the mixture are a linear elastic solid and a linearly viscous fluid. In addition to Steel's field equations, boundary conditions and inequalities on the material constants that have been shown by Atkin, Chadwick and Steel to be sufficient to guarantee uniqueness of solution to initial-boundary value problems are used. The elements of the theory are given and two different boundary value problems are considered. The reciprocal theorem is derived with the aid of the Laplace transform and the divergence theorem and this section is concluded with a discussion of the special cases which arise when one of the constituents of the mixture is absent.

Model-based design of an intermittent simulated moving bed process for recovering lactic acid from ternary mixture.

PubMed

Song, Mingkai; Cui, Linlin; Kuang, Han; Zhou, Jingwei; Yang, Pengpeng; Zhuang, Wei; Chen, Yong; Liu, Dong; Zhu, Chenjie; Chen, Xiaochun; Ying, Hanjie; Wu, Jinglan

2018-08-10

An intermittent simulated moving bed (3F-ISMB) operation scheme, the extension of the 3W-ISMB to the non-linear adsorption region, has been introduced for separation of glucose, lactic acid and acetic acid ternary-mixture. This work focuses on exploring the feasibility of the proposed process theoretically and experimentally. Firstly, the real 3F-ISMB model coupled with the transport dispersive model (TDM) and the Modified-Langmuir isotherm was established to build up the separation parameter plane. Subsequently, three operating conditions were selected from the plane to run the 3F-ISMB unit. The experimental results were used to verify the model. Afterwards, the influences of the various flow rates on the separation performances were investigated systematically by means of the validated 3F-ISMB model. The intermittent-retained component lactic acid was finally obtained with the purity of 98.5%, recovery of 95.5% and the average concentration of 38 g/L. The proposed 3F-ISMB process can efficiently separate the mixture with low selectivity into three fractions. Copyright © 2018 Elsevier B.V. All rights reserved.

A varying-coefficient method for analyzing longitudinal clinical trials data with nonignorable dropout

PubMed Central

Forster, Jeri E.; MaWhinney, Samantha; Ball, Erika L.; Fairclough, Diane

2011-01-01

Dropout is common in longitudinal clinical trials and when the probability of dropout depends on unobserved outcomes even after conditioning on available data, it is considered missing not at random and therefore nonignorable. To address this problem, mixture models can be used to account for the relationship between a longitudinal outcome and dropout. We propose a Natural Spline Varying-coefficient mixture model (NSV), which is a straightforward extension of the parametric Conditional Linear Model (CLM). We assume that the outcome follows a varying-coefficient model conditional on a continuous dropout distribution. Natural cubic B-splines are used to allow the regression coefficients to semiparametrically depend on dropout and inference is therefore more robust. Additionally, this method is computationally stable and relatively simple to implement. We conduct simulation studies to evaluate performance and compare methodologies in settings where the longitudinal trajectories are linear and dropout time is observed for all individuals. Performance is assessed under conditions where model assumptions are both met and violated. In addition, we compare the NSV to the CLM and a standard random-effects model using an HIV/AIDS clinical trial with probable nonignorable dropout. The simulation studies suggest that the NSV is an improvement over the CLM when dropout has a nonlinear dependence on the outcome. PMID:22101223

Physiologically based pharmacokinetic modeling of tea catechin mixture in rats and humans.

PubMed

Law, Francis C P; Yao, Meicun; Bi, Hui-Chang; Lam, Stephen

2017-06-01

Although green tea ( Camellia sinensis) (GT) contains a large number of polyphenolic compounds with anti-oxidative and anti-proliferative activities, little is known of the pharmacokinetics and tissue dose of tea catechins (TCs) as a chemical mixture in humans. The objectives of this study were to develop and validate a physiologically based pharmacokinetic (PBPK) model of tea catechin mixture (TCM) in rats and humans, and to predict an integrated or total concentration of TCM in the plasma of humans after consuming GT or Polyphenon E (PE). To this end, a PBPK model of epigallocatechin gallate (EGCg) consisting of 13 first-order, blood flow-limited tissue compartments was first developed in rats. The rat model was scaled up to humans by replacing its physiological parameters, pharmacokinetic parameters and tissue/blood partition coefficients (PCs) with human-specific values. Both rat and human EGCg models were then extrapolated to other TCs by substituting its physicochemical parameters, pharmacokinetic parameters, and PCs with catechin-specific values. Finally, a PBPK model of TCM was constructed by linking three rat (or human) tea catechin models together without including a description for pharmacokinetic interaction between the TCs. The mixture PBPK model accurately predicted the pharmacokinetic behaviors of three individual TCs in the plasma of rats and humans after GT or PE consumption. Model-predicted total TCM concentration in the plasma was linearly related to the dose consumed by humans. The mixture PBPK model is able to translate an external dose of TCM into internal target tissue doses for future safety assessment and dose-response analysis studies in humans. The modeling framework as described in this paper is also applicable to the bioactive chemical in other plant-based health products.

Investigation on the quality of bio-oil produced through fast pyrolysis of biomass-polymer waste mixture

NASA Astrophysics Data System (ADS)

Jourabchi, S. A.; Ng, H. K.; Gan, S.; Yap, Z. Y.

2016-06-01

A high-impact poly-styrene (HIPS) was mixed with dried and ground coconut shell (CS) at equal weight percentage. Fast pyrolysis was carried out on the mixture in a fixed bed reactor over a temperature range of 573 K to 1073 K, and a nitrogen (N2) linear velocity range of 7.8x10-5 m/s to 6.7x10-2 m/s to produce bio-oil. Heat transfer and fluid dynamics of the pyrolysis process inside the reactor was visualised by using Computational Fluid Dynamics (CFD). The CFD modelling was validated by experimental results and they both indicated that at temperature of 923 K and N2 linear velocity of 7.8x10-5 m/s, the maximum bio-oil yield of 52.02 wt% is achieved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethkenhagen, M.; Meyer, Edmund Richard; Hamel, S.

Here, the validity of the widely used linear mixing approximation (LMA) for the equations of state (EOSs) of planetary ices is investigated at pressure–temperature conditions typical for the interiors of Uranus and Neptune. The basis of this study is ab initio data ranging up to 1000 GPa and 20,000 K, calculated via density functional theory molecular dynamics simulations. In particular, we determine a new EOS for methane and EOS data for the 1:1 binary mixtures of methane, ammonia, and water, as well as their 2:1:4 ternary mixture. Additionally, the self-diffusion coefficients in the ternary mixture are calculated along three different Uranus interior profiles and compared to the values of the pure compounds. We find that deviations of the LMA from the results of the real mixture are generally small; for the thermal EOSs they amount to 4% or less. The diffusion coefficients in the mixture agree with those of the pure compounds within 20% or better. Finally, a new adiabatic model of Uranus with an inner layer of almost pure ices is developed. The model is consistent with the gravity field data and results in a rather cold interior (more » $${T}_{\\mathrm{core}}\\sim 4000$$ K).« less

The linear stability of vertical mixture seepage into the close porous filter with clogging

NASA Astrophysics Data System (ADS)

Maryshev, Boris S.

2017-02-01

In the present paper, filtration of a mixture through a close porous filter is considered. A heavy solute penetrates from the upper side of the filter into the filter body due to seepage flow and diffusion. In the presence of heavy solute a domain with a heavy fluid is formed near the upper boundary of the filter. The stratification, at which the heavy fluid is located above the light, is unstable. When the mass of the heavy solute exceeds the critical value, one can observe the onset of instability. As a result, two regimes of vertical filtration can occur: (1) homogeneous seepage and (2) convective filtration. Filtration of a mixture in porous media is a complex process. It is necessary to take into account the solute immobilization (or sorption) and clogging of porous medium. We consider the case of low solute concentrations, in which the immobilization is described by the linear MIM (mobile/immobile media) model. The clogging is described by the dependence of permeability on porosity in terms of the Carman-Kozeny formula. The presence of immobile (or adsorbed) particles of the solute decreases the porosity of media and porous media becomes less permeable. The purpose of the paper is to find the stability conditions for the homogeneous vertical seepage of the mixture into the close porous filter. The linear stability problem is solved using the quasi-static approach. The critical times of instability are estimated. The stability maps have been plotted in the space of system parameters. The applicability of quasi-static approach is substantiated by direct numerical simulation.

Compressible or incompressible blend of interacting monodisperse star and linear polymers near a surface.

PubMed

Batman, Richard; Gujrati, P D

2008-03-28

We consider a lattice model of a mixture of repulsive, attractive, or neutral monodisperse star (species A) and linear (species B) polymers with a third monomeric species C, which may represent free volume. The mixture is next to a hard, infinite plate whose interactions with A and C can be attractive, repulsive, or neutral. These two interactions are the only parameters necessary to specify the effect of the surface on all three components. We numerically study monomer density profiles using the method of Gujrati and Chhajer that has already been previously applied to study polydisperse and monodisperse linear-linear blends next to surfaces. The resulting density profiles always show an enrichment of linear polymers in the immediate vicinity of the surface due to entropic repulsion of the star core. However, the integrated surface excess of star monomers is sometimes positive, indicating an overall enrichment of stars. This excess increases with the number of star arms only up to a certain critical number and decreases thereafter. The critical arm number increases with compressibility (bulk concentration of C). The method of Gujrati and Chhajer is computationally ultrafast and can be carried out on a personal computer (PC), even in the incompressible case, when simulations are unfeasible. Calculations of density profiles usually take less than 20 min on PCs.

UNCERTAINTY IN SOURCE PARTITIONING USING STABLE ISOTOPES

EPA Science Inventory

Stable isotope analyses are often used to quantify the contribution of multiple sources to a mixture, such as proportions of food sources in an animal's diet, C3 vs. C4 plant inputs to soil organic carbon, etc. Linear mixing models can be used to partition two sources with a sin...

Diffraction of a Shock Wave on a Wedge in a Dusty Gas

NASA Astrophysics Data System (ADS)

Surov, V. S.

2017-09-01

Within the framework of one- and multivelocity dusty-gas models, the author has investigated, on a curvilinear grid, flow in reflection of a shock wave from the wedge-shaped surface in an air-droplet mixture using the Godunov method with a linearized Riemannian solver.

Reduced-order modellin for high-pressure transient flow of hydrogen-natural gas mixture

NASA Astrophysics Data System (ADS)

Agaie, Baba G.; Khan, Ilyas; Alshomrani, Ali Saleh; Alqahtani, Aisha M.

2017-05-01

In this paper the transient flow of hydrogen compressed-natural gas (HCNG) mixture which is also referred to as hydrogen-natural gas mixture in a pipeline is numerically computed using the reduced-order modelling technique. The study on transient conditions is important because the pipeline flows are normally in the unsteady state due to the sudden opening and closure of control valves, but most of the existing studies only analyse the flow in the steady-state conditions. The mathematical model consists in a set of non-linear conservation forms of partial differential equations. The objective of this paper is to improve the accuracy in the prediction of the HCNG transient flow parameters using the Reduced-Order Modelling (ROM). The ROM technique has been successfully used in single-gas and aerodynamic flow problems, the gas mixture has not been done using the ROM. The study is based on the velocity change created by the operation of the valves upstream and downstream the pipeline. Results on the flow characteristics, namely the pressure, density, celerity and mass flux are based on variations of the mixing ratio and valve reaction and actuation time; the ROM computational time cost advantage are also presented.

Mixture Model for Determination of Shock Equation of State

DTIC Science & Technology

2012-07-25

not considered in this paper. III. COMPARISON WITH EXPERIMENTAL DATA A. Two-constituent composites 1. Uranium- rhodium composite Uranium- rhodium (U...sound speed, Co, and S were determined from linear least squares fit to the available data22 as shown in Figs. 1(a) and 1(b) for uranium and rhodium ...overpredicts the experimental data, with an average deviation, dUs,/Us of 0.05, shown in Fig. 2(b). The linear fits for uranium and rhodium are shown for

Linear kinetic theory and particle transport in stochastic mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pomraning, G.C.

We consider the formulation of linear transport and kinetic theory describing energy and particle flow in a random mixture of two or more immiscible materials. Following an introduction, we summarize early and fundamental work in this area, and we conclude with a brief discussion of recent results.

Application of pattern mixture models to address missing data in longitudinal data analysis using SPSS.

PubMed

Son, Heesook; Friedmann, Erika; Thomas, Sue A

2012-01-01

Longitudinal studies are used in nursing research to examine changes over time in health indicators. Traditional approaches to longitudinal analysis of means, such as analysis of variance with repeated measures, are limited to analyzing complete cases. This limitation can lead to biased results due to withdrawal or data omission bias or to imputation of missing data, which can lead to bias toward the null if data are not missing completely at random. Pattern mixture models are useful to evaluate the informativeness of missing data and to adjust linear mixed model (LMM) analyses if missing data are informative. The aim of this study was to provide an example of statistical procedures for applying a pattern mixture model to evaluate the informativeness of missing data and conduct analyses of data with informative missingness in longitudinal studies using SPSS. The data set from the Patients' and Families' Psychological Response to Home Automated External Defibrillator Trial was used as an example to examine informativeness of missing data with pattern mixture models and to use a missing data pattern in analysis of longitudinal data. Prevention of withdrawal bias, omitted data bias, and bias toward the null in longitudinal LMMs requires the assessment of the informativeness of the occurrence of missing data. Missing data patterns can be incorporated as fixed effects into LMMs to evaluate the contribution of the presence of informative missingness to and control for the effects of missingness on outcomes. Pattern mixture models are a useful method to address the presence and effect of informative missingness in longitudinal studies.

Experimental and modeling study on effects of N2 and CO2 on ignition characteristics of methane/air mixture

PubMed Central

Zeng, Wen; Ma, Hongan; Liang, Yuntao; Hu, Erjiang

2014-01-01

The ignition delay times of methane/air mixture diluted by N2 and CO2 were experimentally measured in a chemical shock tube. The experiments were performed over the temperature range of 1300–2100 K, pressure range of 0.1–1.0 MPa, equivalence ratio range of 0.5–2.0 and for the dilution coefficients of 0%, 20% and 50%. The results suggest that a linear relationship exists between the reciprocal of temperature and the logarithm of the ignition delay times. Meanwhile, with ignition temperature and pressure increasing, the measured ignition delay times of methane/air mixture are decreasing. Furthermore, an increase in the dilution coefficient of N2 or CO2 results in increasing ignition delays and the inhibition effect of CO2 on methane/air mixture ignition is stronger than that of N2. Simulated ignition delays of methane/air mixture using three kinetic models were compared to the experimental data. Results show that GRI_3.0 mechanism gives the best prediction on ignition delays of methane/air mixture and it was selected to identify the effects of N2 and CO2 on ignition delays and the key elementary reactions in the ignition chemistry of methane/air mixture. Comparisons of the calculated ignition delays with the experimental data of methane/air mixture diluted by N2 and CO2 show excellent agreement, and sensitivity coefficients of chain branching reactions which promote mixture ignition decrease with increasing dilution coefficient of N2 or CO2. PMID:25750753

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Experimental Design for Hanford Low-Activity Waste Glasses with High Waste Loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piepel, Gregory F.; Cooley, Scott K.; Vienna, John D.

This report discusses the development of an experimental design for the initial phase of the Hanford low-activity waste (LAW) enhanced glass study. This report is based on a manuscript written for an applied statistics journal. Appendices A, B, and E include additional information relevant to the LAW enhanced glass experimental design that is not included in the journal manuscript. The glass composition experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC involving 15 LAW glass components. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directlymore » applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this report. One of the glass components, SO 3, has a solubility limit in glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO 3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO 3 solubility limit had previously been modeled by a partial quadratic mixture model expressed in the relative proportions of the 14 other components. The partial quadratic mixture model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This report describes how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study. A layered design consists of points on an outer layer, and inner layer, and a center point. There were 18 outer-layer glasses chosen using optimal experimental design software to augment 147 existing glass compositions that were within the LAW glass composition experimental region. Then 13 inner-layer glasses were chosen with the software to augment the existing and outer-layer glasses. The experimental design was completed by a center-point glass, a Vitreous State Laboratory glass, and replicates of the center point and Vitreous State Laboratory glasses.« less

Pyrolysis of polyethylene mixed with paper and wood: Interaction effects on tar, char and gas yields.

PubMed

Grieco, E M; Baldi, G

2012-05-01

In the present study the interactions between the main constituents of the refuse derived fuel (plastics, paper, and wood) during pyrolysis were studied. Binary mixtures of polyethylene-paper and polyethylene/sawdust have been transformed into pellets and pyrolyzed. Various mixtures with different composition were analyzed and pyrolysis products (tar, gas, and char) were collected. The mixtures of wood/PE and paper/PE have a different behavior. The wood/PE mixtures showed a much reduced interaction of the various compounds because the yields of pyrolysis products of the mixture can be predicted as linear combination of those of the pure components. On the contrary, a strong char yield increase was found at a low heating rate for paper/PE mixtures. In order to explain the results, the ability of wood and paper char to adsorb and convert the products of PE pyrolysis into was studied. Adsorption and desorption tests were performed on the char obtained by paper and wood by using n-hexadecane as a model compound for the heavy products of PE pyrolysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Do goethite surfaces really control the transport and retention of multi-walled carbon nanotubes in chemically heterogeneous porous media?

USDA-ARS?s Scientific Manuscript database

Transport and retention behavior of multiwalled carbon nanotubes (MWCNTs) was studied in mixtures of negatively charged quartz sand (QS) and positively charged goethite-coated sand (GQS) to assess the role of chemical heterogeneity. The linear equilibrium sorption model provided a good description o...

Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Susmikanti, Mike, E-mail: mike@batan.go.id; Sulistyo, Jos, E-mail: soj@batan.go.id

2014-09-30

Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to developmore » code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neural network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix.« less

Canopy reflectance modelling of semiarid vegetation

NASA Technical Reports Server (NTRS)

Franklin, Janet

1994-01-01

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Extending the Distributed Lag Model framework to handle chemical mixtures.

PubMed

Bello, Ghalib A; Arora, Manish; Austin, Christine; Horton, Megan K; Wright, Robert O; Gennings, Chris

2017-07-01

Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures. Copyright © 2017 Elsevier Inc. All rights reserved.

40 CFR 799.5025 - Testing consent orders for mixtures without Chemical Abstracts Service Registry Numbers.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Required test FR citation Di(heptyl, nonyl, undecyl) phthalate (D711P) as a mixture of the following six substances: (1) diheptyl phthalate (branched and linear isomers), CAS No. 68515-44-6 Environmental effects. January 9, 1989. (2) dinonyl phthalate (branched and linear isomers), CAS No. 68515-45-7 ......do Do. (3...

40 CFR 799.5025 - Testing consent orders for mixtures without Chemical Abstracts Service Registry Numbers.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Required test FR citation Di(heptyl, nonyl, undecyl) phthalate (D711P) as a mixture of the following six substances: (1) diheptyl phthalate (branched and linear isomers), CAS No. 68515-44-6 Environmental effects. January 9, 1989. (2) dinonyl phthalate (branched and linear isomers), CAS No. 68515-45-7 ......do Do. (3...

40 CFR 799.5025 - Testing consent orders for mixtures without Chemical Abstracts Service Registry Numbers.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Required test FR citation Di(heptyl, nonyl, undecyl) phthalate (D711P) as a mixture of the following six substances: (1) diheptyl phthalate (branched and linear isomers), CAS No. 68515-44-6 Environmental effects. January 9, 1989. (2) dinonyl phthalate (branched and linear isomers), CAS No. 68515-45-7 ......do Do. (3...

40 CFR 799.5025 - Testing consent orders for mixtures without Chemical Abstracts Service Registry Numbers.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Required test FR citation Di(heptyl, nonyl, undecyl) phthalate (D711P) as a mixture of the following six substances: (1) diheptyl phthalate (branched and linear isomers), CAS No. 68515-44-6 Environmental effects. January 9, 1989. (2) dinonyl phthalate (branched and linear isomers), CAS No. 68515-45-7 ......do Do. (3...

Unmixing Space Object’s Moderate Resolution Spectra

DTIC Science & Technology

2013-09-01

collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE SEP 2013 2. REPORT TYPE 3. DATES COVERED 00...result of spectral unmixing. In the visible, the non- resolved spectral signature is modeled as a linear mixture of spectral reflectance signatures...1 (3) In (3), the first term expresses the Euclidian distance (l2) between the observed data and the forward model . The second term (l1

Thermal infrared spectral analysis of compacted fine-grained mineral mixtures: implications for spectral interpretation of lithified sedimentary materials on Mars

NASA Astrophysics Data System (ADS)

Pan, C.; Rogers, D.

2012-12-01

Characterizing the thermal infrared (TIR) spectral mixing behavior of compacted fine-grained mineral assemblages is necessary for facilitating quantitative mineralogy of sedimentary surfaces from spectral measurements. Previous researchers have demonstrated that TIR spectra from igneous and metamorphic rocks as well as coarse-grained (>63 micron) sand mixtures combine in proportion to their volume abundance. However, the spectral mixing behavior of compacted, fine-grained mineral mixtures that would be characteristic of sedimentary depositional environments has received little attention. Here we characterize the spectral properties of pressed pellet samples of <10 micron mineral mixtures to 1) assess linearity of spectral combinations, 2) determine whether there are consistent over- or under-estimations of different types of minerals in spectral models and 3) determine if model accuracy can be improved by including both fine- and coarse-grained end-members. Major primary and secondary minerals found on the Martian surface including feldspar, pyroxene, smectite, sulfate and carbonate were crushed with an agate mortar and pestle and centrifuged to obtain less than 10 micron size. Pure phases and mixtures of two, three and four components were made in varying proportions by volume. All of the samples were pressed into pellets at 15000PSI to minimize volume scattering. Thermal infrared spectra of pellets were measured in the Vibrational Spectroscopy Laboratory at Stony Brook University with a Thermo Fisher Nicolet 6700 Fourier transform infrared Michelson interferometer from ~225 to 2000 cm-1. Our preliminary results indicate that some pelletized samples have contributions from volume scattering, which leads to non-linear spectral combinations. It is not clear if the transparency features (which arise from multiple surface reflections of incident photons) are due to minor clinging fines on an otherwise specular pellet surface or to partially transmitted energy through optically thin grains in the compacted mixture. Inclusion of loose powder (<10 μm) sample spectra improves mineral abundance estimates for some mixtures. In general, mineral abundances are predicted to within +/- 10% (absolute) for approximately 60% of our samples; thus far, there are no clear trends in which cases produce better model results. With the exception of pyroxene/feldspar ratios being consistently overestimated, there are no consistent trends in over- or under-estimation of minerals. The results described here are based on the unsubstantiated assumption that areal abundance on the pellet surface is equal to the volume abundance. Thus future work will include micro-imaging of our samples to constrain areal abundance. We will also prepareclay mixtures using a wetting/drying sequence rather than pressure, and expand our set of samples to include additional mixture combinations to further characterize the spectral behavior of compacted mixtures. This work will be directly applicable to analysis of TES and Mini-TES data of lithified sedimentary deposits.

Absorption by H2O and H2O-N2 mixtures at 153 GHz

NASA Technical Reports Server (NTRS)

Bauer, A.; Godon, M.; Carlier, J.; Ma, Q.; Tippings, R. H.

1993-01-01

New experimental data on and a theoretical analysis of the absorption coefficient at 153 GHz are presented for pure water vapor and water vapor-nitrogen mixtures. This frequency is 30 GHz lower than the resonant frequency of the nearest strong water line (183 GHz) and complements our previous measurements at 213 GHz. The pressure dependence is observed to be quadratic in the case of pure water vapor, while in the case of mixtures there are both linear and quadratic density components. By fitting our experimental data taken at several temperatures we have obtained the temperature dependence of the absorption. Our experimental data are compared to several theoretical models with and without a continuum contribution, and we find that none of the models is in very good agreement with the data; in the case of pure water vapor, the continuum contribution calculated using the recent theoretical absorption gives the best results. In general, the agreement between the data and the various models is less satisfactory than found previously in the high-frequency wing. The anisotropy in the observed absorption differs from that currently used in atmospheric models.

Influence of host diversity on development of epidemics: an evaluation and elaboration of mixture theory.

PubMed

Skelsey, P; Rossing, W A H; Kessel, G J T; Powell, J; van der Werf, W

2005-04-01

ABSTRACT A spatiotemporal/integro-difference equation model was developed and utilized to study the progress of epidemics in spatially heterogeneous mixtures of susceptible and resistant host plants. The effects of different scales and patterns of host genotypes on the development of focal and general epidemics were investigated using potato late blight as a case study. Two different radial Laplace kernels and a two-dimensional Gaussian kernel were used for modeling the dispersal of spores. An analytical expression for the apparent infection rate, r, in general epidemics was tested by comparison with dynamic simulations. A genotype connectivity parameter, q, was introduced into the formula for r. This parameter quantifies the probability of pathogen inoculum produced on a certain host genotype unit reaching the same or another unit of the same genotype. The analytical expression for the apparent infection rate provided accurate predictions of realized r in the simulations of general epidemics. The relationship between r and the radial velocity of focus expansion, c, in focal epidemics, was linear in accordance with theory for homogeneous genotype mixtures. The findings suggest that genotype mixtures that are effective in reducing general epidemics of Phytophthora infestans will likewise curtail focal epidemics and vice versa.

Lubrication model for evaporation of binary sessile drops

NASA Astrophysics Data System (ADS)

Williams, Adam; Sáenz, Pedro; Karapetsas, George; Matar, Omar; Sefiane, Khellil; Valluri, Prashant

2017-11-01

Evaporation of a binary mixture sessile drop from a solid substrate is a highly dynamic and complex process with flow driven both thermal and solutal Marangoni stresses. Experiments on ethanol/water drops have identified chaotic regimes on both the surface and interior of the droplet, while mixture composition has also been seen to govern drop wettability. Using a lubrication-type approach, we present a finite element model for the evaporation of an axisymmetric binary drop deposited on a heated substrate. We consider a thin drop with a moving contact line, taking also into account the commonly ignored effects of inertia which drives interfacial instability. We derive evolution equations for the film height, the temperature and the concentration field considering that the mixture comprises two ideally mixed volatile components with a surface tension linearly dependent on both temperature and concentration. The properties of the mixture such as viscosity also vary locally with concentration. We explore the parameter space to examine the resultant effects on wetting and evaporation where we find qualitative agreement with experiments in both these areas. This enables us to understand the nature of the instabilities that spontaneously emerge over the drop lifetime. EPSRC - EP/K00963X/1.

Generalized concentration addition: a method for examining mixtures containing partial agonists.

PubMed

Howard, Gregory J; Webster, Thomas F

2009-08-07

Environmentally relevant toxic exposures often consist of simultaneous exposure to multiple agents. Methods to predict the expected outcome of such combinations are critical both to risk assessment and to an accurate judgment of whether combinations are synergistic or antagonistic. Concentration addition (CA) has commonly been used to assess the presence of synergy or antagonism in combinations of similarly acting chemicals, and to predict effects of combinations of such agents. CA has the advantage of clear graphical interpretation: Curves of constant joint effect (isoboles) must be negatively sloped straight lines if the mixture is concentration additive. However, CA cannot be directly used to assess combinations that include partial agonists, although such agents are of considerable interest. Here, we propose a natural extension of CA to a functional form that may be applied to mixtures including full agonists and partial agonists. This extended definition, for which we suggest the term "generalized concentration addition," encompasses linear isoboles with slopes of any sign. We apply this approach to the simple example of agents with dose-response relationships described by Hill functions with slope parameter n=1. The resulting isoboles are in all cases linear, with negative, zero and positive slopes. Using simple mechanistic models of ligand-receptor systems, we show that the same isobole pattern and joint effects are generated by modeled combinations of full and partial agonists. Special cases include combinations of two full agonists and a full agonist plus a competitive antagonist.

A linear and nonlinear study of Mira

NASA Astrophysics Data System (ADS)

Cox, A. N.; Ostlie, D. A.

1993-12-01

Both linear and nonlinear calculations of the 331 day, long period variable star Mira have been undertaken to see what radial pulsation mode is naturally selected. Models are similar to those considered in the linear nonadiabatic stellar pulsation study of Ostlie and Cox (1986). Models are considered with masses near one solar mass, luminosities between 4000 and 5000 solar luminosities, and effective temperatures of approximately 3000 K. These models have fundamental mode periods that closely match the pulsation period of Mira. The equation of state for the stellar material is given by the Stellingwerf (1975ab) procedure, and the opacity is obtained from a fit by Cahn that matches the low temperature molecular absorption data for the poplulation I Ross-Aller 1 mixture calculated from the Los Alamos Astrophysical Opacity Library. For the linear study, the Cox, Brownlee, and Eilers (1966) approximation is used for the linear theory variation of the convection luminosity. For the nonlinear work, the method described by Ostlie (1990) and Cox (1990) is followed. Results showing internal details of the radial fundamental and first overtone modes behavior in linear theory are presented. Preliminary radial fundamental mode nonlinear calculations are discussed. The very tentative conclusion is that neither the fundamental or first overtone mode is excluded from being the actual observed one.

Combined acute ecotoxicity of malathion and deltamethrin to Daphnia magna (Crustacea, Cladocera): comparison of different data analysis approaches.

PubMed

Toumi, Héla; Boumaiza, Moncef; Millet, Maurice; Radetski, Claudemir Marcos; Camara, Baba Issa; Felten, Vincent; Masfaraud, Jean-François; Férard, Jean-François

2018-04-19

We studied the combined acute effect (i.e., after 48 h) of deltamethrin (a pyrethroid insecticide) and malathion (an organophosphate insecticide) on Daphnia magna. Two approaches were used to examine the potential interaction effects of eight mixtures of deltamethrin and malathion: (i) calculation of mixture toxicity index (MTI) and safety factor index (SFI) and (ii) response surface methodology coupled with isobole-based statistical model (using generalized linear model). According to the calculation of MTI and SFI, one tested mixture was found additive while the two other tested mixtures were found no additive (MTI) or antagonistic (SFI), but these differences between index responses are only due to differences in terminology related to these two indexes. Through the surface response approach and isobologram analysis, we concluded that there was a significant antagonistic effect of the binary mixtures of deltamethrin and malathion that occurs on D. magna immobilization, after 48 h of exposure. Index approaches and surface response approach with isobologram analysis are complementary. Calculation of mixture toxicity index and safety factor index allows identifying punctually the type of interaction for several tested mixtures, while the surface response approach with isobologram analysis integrates all the data providing a global outcome about the type of interactive effect. Only the surface response approach and isobologram analysis allowed the statistical assessment of the ecotoxicological interaction. Nevertheless, we recommend the use of both approaches (i) to identify the combined effects of contaminants and (ii) to improve risk assessment and environmental management.

Baldovin-Stella stochastic volatility process and Wiener process mixtures

NASA Astrophysics Data System (ADS)

Peirano, P. P.; Challet, D.

2012-08-01

Starting from inhomogeneous time scaling and linear decorrelation between successive price returns, Baldovin and Stella recently proposed a powerful and consistent way to build a model describing the time evolution of a financial index. We first make it fully explicit by using Student distributions instead of power law-truncated Lévy distributions and show that the analytic tractability of the model extends to the larger class of symmetric generalized hyperbolic distributions and provide a full computation of their multivariate characteristic functions; more generally, we show that the stochastic processes arising in this framework are representable as mixtures of Wiener processes. The basic Baldovin and Stella model, while mimicking well volatility relaxation phenomena such as the Omori law, fails to reproduce other stylized facts such as the leverage effect or some time reversal asymmetries. We discuss how to modify the dynamics of this process in order to reproduce real data more accurately.

Origin and Function of Tuning Diversity in Macaque Visual Cortex

PubMed Central

Goris, Robbe L.T.; Simoncelli, Eero P.; Movshon, J. Anthony

2016-01-01

SUMMARY Neurons in visual cortex vary in their orientation selectivity. We measured responses of V1 and V2 cells to orientation mixtures and fit them with a model whose stimulus selectivity arises from the combined effects of filtering, suppression, and response nonlinearity. The model explains the diversity of orientation selectivity with neuron-to-neuron variability in all three mechanisms, of which variability in the orientation bandwidth of linear filtering is the most important. The model also accounts for the cells’ diversity of spatial frequency selectivity. Tuning diversity is matched to the needs of visual encoding. The orientation content found in natural scenes is diverse, and neurons with different selectivities are adapted to different stimulus configurations. Single orientations are better encoded by highly selective neurons, while orientation mixtures are better encoded by less selective neurons. A diverse population of neurons therefore provides better overall discrimination capabilities for natural images than any homogeneous population. PMID:26549331

A two-phase micromorphic model for compressible granular materials

NASA Astrophysics Data System (ADS)

Paolucci, Samuel; Li, Weiming; Powers, Joseph

2009-11-01

We introduce a new two-phase continuum model for compressible granular material based on micromorphic theory and treat it as a two-phase mixture with inner structure. By taking an appropriate number of moments of the local micro scale balance equations, the average phase balance equations result from a systematic averaging procedure. In addition to equations for mass, momentum and energy, the balance equations also include evolution equations for microinertia and microspin tensors. The latter equations combine to yield a general form of a compaction equation when the material is assumed to be isotropic. When non-linear and inertial effects are neglected, the generalized compaction equation reduces to that originally proposed by Bear and Nunziato. We use the generalized compaction equation to numerically model a mixture of granular high explosive and interstitial gas. One-dimensional shock tube and piston-driven solutions are presented and compared with experimental results and other known solutions.

Constraints based analysis of extended cybernetic models.

PubMed

Mandli, Aravinda R; Venkatesh, Kareenhalli V; Modak, Jayant M

2015-11-01

The cybernetic modeling framework provides an interesting approach to model the regulatory phenomena occurring in microorganisms. In the present work, we adopt a constraints based approach to analyze the nonlinear behavior of the extended equations of the cybernetic model. We first show that the cybernetic model exhibits linear growth behavior under the constraint of no resource allocation for the induction of the key enzyme. We then quantify the maximum achievable specific growth rate of microorganisms on mixtures of substitutable substrates under various kinds of regulation and show its use in gaining an understanding of the regulatory strategies of microorganisms. Finally, we show that Saccharomyces cerevisiae exhibits suboptimal dynamic growth with a long diauxic lag phase when growing on a mixture of glucose and galactose and discuss on its potential to achieve optimal growth with a significantly reduced diauxic lag period. The analysis carried out in the present study illustrates the utility of adopting a constraints based approach to understand the dynamic growth strategies of microorganisms. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Finite-deformation phase-field chemomechanics for multiphase, multicomponent solids

NASA Astrophysics Data System (ADS)

Svendsen, Bob; Shanthraj, Pratheek; Raabe, Dierk

2018-03-01

The purpose of this work is the development of a framework for the formulation of geometrically non-linear inelastic chemomechanical models for a mixture of multiple chemical components diffusing among multiple transforming solid phases. The focus here is on general model formulation. No specific model or application is pursued in this work. To this end, basic balance and constitutive relations from non-equilibrium thermodynamics and continuum mixture theory are combined with a phase-field-based description of multicomponent solid phases and their interfaces. Solid phase modeling is based in particular on a chemomechanical free energy and stress relaxation via the evolution of phase-specific concentration fields, order-parameter fields (e.g., related to chemical ordering, structural ordering, or defects), and local internal variables. At the mixture level, differences or contrasts in phase composition and phase local deformation in phase interface regions are treated as mixture internal variables. In this context, various phase interface models are considered. In the equilibrium limit, phase contrasts in composition and local deformation in the phase interface region are determined via bulk energy minimization. On the chemical side, the equilibrium limit of the current model formulation reduces to a multicomponent, multiphase, generalization of existing two-phase binary alloy interface equilibrium conditions (e.g., KKS). On the mechanical side, the equilibrium limit of one interface model considered represents a multiphase generalization of Reuss-Sachs conditions from mechanical homogenization theory. Analogously, other interface models considered represent generalizations of interface equilibrium conditions consistent with laminate and sharp-interface theory. In the last part of the work, selected existing models are formulated within the current framework as special cases and discussed in detail.

Influence of smooth temperature variation on hotspot ignition

NASA Astrophysics Data System (ADS)

Reinbacher, Fynn; Regele, Jonathan David

2018-01-01

Autoignition in thermally stratified reactive mixtures originates in localised hotspots. The ignition behaviour is often characterised using linear temperature gradients and more recently constant temperature plateaus combined with temperature gradients. Acoustic timescale characterisation of plateau regions has been successfully used to characterise the type of mechanical disturbance that will be created from a plateau core ignition. This work combines linear temperature gradients with superelliptic cores in order to more accurately account for a local temperature maximum of finite size and the smooth temperature variation contained inside realistic hotspot centres. A one-step Arrhenius reaction is used to model a H2-air reactive mixture. Using the superelliptic approach a range of behaviours for temperature distributions are investigated by varying the temperature profile between the gradient only and plateau and gradient bounding cases. Each superelliptic case is compared to a respective plateau and gradient case where simple acoustic timescale characterisation may be performed. It is shown that hot spots equivalent with excitation-to-acoustic timescale ratios sufficiently greater than unity exhibit behaviour very similar to a simple plateau-gradient model. However, for larger hot spots with timescale ratios sufficiently less than unity the reaction behaviour is highly dependent on the smooth temperature profile contained within the core region.

Do Stress Trajectories Predict Mortality in Older Men? Longitudinal Findings from the VA Normative Aging Study

PubMed Central

Aldwin, Carolyn M.; Molitor, Nuoo-Ting; Avron, Spiro; Levenson, Michael R.; Molitor, John; Igarashi, Heidi

2011-01-01

We examined long-term patterns of stressful life events (SLE) and their impact on mortality contrasting two theoretical models: allostatic load (linear relationship) and hormesis (inverted U relationship) in 1443 NAS men (aged 41–87 in 1985; M = 60.30, SD = 7.3) with at least two reports of SLEs over 18 years (total observations = 7,634). Using a zero-inflated Poisson growth mixture model, we identified four patterns of SLE trajectories, three showing linear decreases over time with low, medium, and high intercepts, respectively, and one an inverted U, peaking at age 70. Repeating the analysis omitting two health-related SLEs yielded only the first three linear patterns. Compared to the low-stress group, both the moderate and the high-stress groups showed excess mortality, controlling for demographics and health behavior habits, HRs = 1.42 and 1.37, ps <.01 and <.05. The relationship between stress trajectories and mortality was complex and not easily explained by either theoretical model. PMID:21961066

Study of molecular carbon-hydrogen bond dissociation during shock compression

NASA Astrophysics Data System (ADS)

Hammel, Ben; Hawreliak, James

2017-06-01

Advancements in theory and experiment show that chemical interactions in warm dense mixtures play a non-negligible role in the high-temperature and high-pressure properties of a molecular compound. For example, recent work on polystyrene has observed features suggestive of molecular dissociation - non-linear ``kinks'' are evident in the material's Hugoniot, consistent with CH bond breaking. The assumption used in linear mixing models, that species are chemically inert, breaks down in warm dense mixtures. At the Institute for Shock Physics, we are developing the necessary capabilities to perform high-repetition-rate experiments needed to map out chemical-reaction features along a material's Hugoniot. Initially, we plan to benchmark our work to the data taken by Barrios et al., by reproducing the observed kink in the polystyrene Hugoniot. We then extend this capability to explore polypropylene, CH2, where we expect to observe multiple kink features - representative of the disassociation of multiple CH bonds. Work supported by DOE/NNSA, DOE/SC-OFES and Murdock Charitable Trust.

Multidimensional equilibria and their stability in copolymer-solvent mixtures

NASA Astrophysics Data System (ADS)

Glasner, Karl; Orizaga, Saulo

2018-06-01

This paper discusses localized equilibria which arise in copolymer-solvent mixtures. A free boundary problem associated with the sharp-interface limit of a density functional model is used to identify both lamellar and concentric domain patterns composed of a finite number of layers. Stability of these morphologies is studied through explicit linearization of the free boundary evolution. For the multilayered lamellar configuration, transverse instability is observed for sufficiently small dimensionless interfacial energies. Additionally, a crossover between small and large wavelength instabilities is observed depending on whether solvent-polymer or monomer-monomer interfacial energy is dominant. Concentric domain patterns resembling multilayered micelles and vesicles exhibit bifurcations wherein they only exist for sufficiently small dimensionless interfacial energies. The bifurcation of large radii vesicle solutions is studied analytically, and a crossover from a supercritical case with only one solution branch to a subcritical case with two is observed. Linearized stability of these configurations shows that azimuthal perturbation may lead to instabilities as interfacial energy is decreased.

Theoretical Thermodynamics of Mixtures at High Pressures

NASA Technical Reports Server (NTRS)

Hubbard, W. B.

1985-01-01

The development of an understanding of the chemistry of mixtures of metallic hydrogen and abundant, higher-z material such as oxygen, carbon, etc., is important for understanding of fundamental processes of energy release, differentiation, and development of atmospheric abundances in the Jovian planets. It provides a significant theoretical base for the interpretation of atmospheric elemental abundances to be provided by atmospheric entry probes in coming years. Significant differences are found when non-perturbative approaches such as Thomas-Fermi-Dirac (TFD) theory are used. Mapping of the phase diagrams of such binary mixtures in the pressure range from approx. 10 Mbar to approx. 1000 Mbar, using results from three-dimensional TFD calculations is undertaken. Derivation of a general and flexible thermodynamic model for such binary mixtures in the relevant pressure range was facilitated by the following breakthrough: there exists an accurate nd fairly simple thermodynamic representation of a liquid two-component plasma (TCP) in which the Helmholtz free energy is represented as a suitable linear combination of terms dependent only on density and terms which depend only on the ion coupling parameter. It is found that the crystal energies of mixtures of H-He, H-C, and H-O can be satisfactorily reproduced by the same type of model, except that an effective, density-dependent ionic charge must be used in place of the actual total ionic charge.

Quantification of live Lactobacillus acidophilus in mixed populations of live and killed by application of attenuated reflection Fourier transform infrared spectroscopy combined with chemometrics.

PubMed

Toziou, Peristera-Maria; Barmpalexis, Panagiotis; Boukouvala, Paraskevi; Verghese, Susan; Nikolakakis, Ioannis

2018-05-30

Since culture-based methods are costly and time consuming, alternative methods are investigated for the quantification of probiotics in commercial products. In this work ATR- FTIR vibration spectroscopy was applied for the differentiation and quantification of live Lactobacillus (La 5) in mixed populations of live and killed La 5, in the absence and in the presence of enteric polymer Eudragit ® L 100-55. Suspensions of live (La 5_L) and killed in acidic environment bacillus (La 5_K) were prepared and binary mixtures of different percentages were used to grow cell cultures for colony counting and spectral analysis. The increase in the number of colonies with added%La 5_L to the mixture was log-linear (r 2  = 0.926). Differentiation of La 5_L from La 5_K was possible directly from the peak area at 1635 cm -1 (amides of proteins and peptides) and a linear relationship between%La 5_L and peak area in the range 0-95% was obtained. Application of partial least squares regression (PLSR) gave reasonable prediction of%La 5_L (RMSEp = 6.48) in binary mixtures of live and killed La 5 but poor prediction (RMSEp = 11.75) when polymer was added to the La 5 mixture. Application of artificial neural networks (ANNs) improved greatly the predictive ability for%La 5_L both in the absence and in the presence of polymer (RMSEp = 8.11 × 10 -8 for La 5 only mixtures and RMSEp = 8.77 × 10 -8 with added polymer) due to their ability to express in the calibration models more hidden spectral information than PLSR. Copyright © 2018 Elsevier B.V. All rights reserved.

Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals

PubMed Central

Iliev, Filip L.; Stanev, Valentin G.; Vesselinov, Velimir V.

2018-01-01

Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free Blind Source Separation (BSS) algorithms. Most of the available BSS algorithms consider an instantaneous mixing of signals, while the case when the mixtures are linear combinations of signals with delays is less explored. Especially difficult is the case when the number of sources of the signals with delays is unknown and has to be determined from the data as well. To address this problem, in this paper, we present a new method based on Nonnegative Matrix Factorization (NMF) that is capable of identifying: (a) the unknown number of the sources, (b) the delays and speed of propagation of the signals, and (c) the locations of the sources. Our method can be used to decompose records of mixtures of signals with delays emitted by an unknown number of sources in a nondispersive medium, based only on recorded data. This is the case, for example, when electromagnetic signals from multiple antennas are received asynchronously; or mixtures of acoustic or seismic signals recorded by sensors located at different positions; or when a shift in frequency is induced by the Doppler effect. By applying our method to synthetic datasets, we demonstrate its ability to identify the unknown number of sources as well as the waveforms, the delays, and the strengths of the signals. Using Bayesian analysis, we also evaluate estimation uncertainties and identify the region of likelihood where the positions of the sources can be found. PMID:29518126

Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals.

PubMed

Iliev, Filip L; Stanev, Valentin G; Vesselinov, Velimir V; Alexandrov, Boian S

2018-01-01

Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free Blind Source Separation (BSS) algorithms. Most of the available BSS algorithms consider an instantaneous mixing of signals, while the case when the mixtures are linear combinations of signals with delays is less explored. Especially difficult is the case when the number of sources of the signals with delays is unknown and has to be determined from the data as well. To address this problem, in this paper, we present a new method based on Nonnegative Matrix Factorization (NMF) that is capable of identifying: (a) the unknown number of the sources, (b) the delays and speed of propagation of the signals, and (c) the locations of the sources. Our method can be used to decompose records of mixtures of signals with delays emitted by an unknown number of sources in a nondispersive medium, based only on recorded data. This is the case, for example, when electromagnetic signals from multiple antennas are received asynchronously; or mixtures of acoustic or seismic signals recorded by sensors located at different positions; or when a shift in frequency is induced by the Doppler effect. By applying our method to synthetic datasets, we demonstrate its ability to identify the unknown number of sources as well as the waveforms, the delays, and the strengths of the signals. Using Bayesian analysis, we also evaluate estimation uncertainties and identify the region of likelihood where the positions of the sources can be found.

Modeling avian abundance from replicated counts using binomial mixture models

USGS Publications Warehouse

Kery, Marc; Royle, J. Andrew; Schmid, Hans

2005-01-01

Abundance estimation in ecology is usually accomplished by capture–recapture, removal, or distance sampling methods. These may be hard to implement at large spatial scales. In contrast, binomial mixture models enable abundance estimation without individual identification, based simply on temporally and spatially replicated counts. Here, we evaluate mixture models using data from the national breeding bird monitoring program in Switzerland, where some 250 1-km2 quadrats are surveyed using the territory mapping method three times during each breeding season. We chose eight species with contrasting distribution (wide–narrow), abundance (high–low), and detectability (easy–difficult). Abundance was modeled as a random effect with a Poisson or negative binomial distribution, with mean affected by forest cover, elevation, and route length. Detectability was a logit-linear function of survey date, survey date-by-elevation, and sampling effort (time per transect unit). Resulting covariate effects and parameter estimates were consistent with expectations. Detectability per territory (for three surveys) ranged from 0.66 to 0.94 (mean 0.84) for easy species, and from 0.16 to 0.83 (mean 0.53) for difficult species, depended on survey effort for two easy and all four difficult species, and changed seasonally for three easy and three difficult species. Abundance was positively related to route length in three high-abundance and one low-abundance (one easy and three difficult) species, and increased with forest cover in five forest species, decreased for two nonforest species, and was unaffected for a generalist species. Abundance estimates under the most parsimonious mixture models were between 1.1 and 8.9 (median 1.8) times greater than estimates based on territory mapping; hence, three surveys were insufficient to detect all territories for each species. We conclude that binomial mixture models are an important new approach for estimating abundance corrected for detectability when only repeated-count data are available. Future developments envisioned include estimation of trend, occupancy, and total regional abundance.

Smectic phases in hard particle mixtures: Koda's theory

NASA Astrophysics Data System (ADS)

Vesely, Franz J.

Mixtures of parallel linear particles and spheres tend to demix upon compression. The linear species usually concentrates in regular layers, thus forming a smectic phase. With increasing concentration of spheres this 'smectic demixing' transition occurs at ever lower packing densities. For the specific case of hard spherocylinders and spheres Koda et al. [T. Koda, M. Numajiri, S. Ikeda, J. Phys. Jap., 65, 3551 (1996)] have explained the layering effect in terms of a second virial approximation to the free energy. We extend this approach from spherocylinders to other linear particles, namely fused spheres, ellipsoids and sphero-ellipsoids.

Fuel-air mixing and combustion in a two-dimensional Wankel engine

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Schock, H. J.; Ramos, J. I.

1987-01-01

A two-equation turbulence model, an algebraic grid generalization method, and an approximate factorization time-linearized numerical technique are used to study the effects of mixture stratification at the intake port and gaseous fuel injection on the flow field and fuel-air mixing in a two-dimensional rotary engine model. The fuel distribution in the combustion chamber is found to be a function of the air-fuel mixture fluctuations at the intake port. It is shown that the fuel is advected by the flow field induced by the rotor and is concentrated near the leading apex during the intake stroke, while during compression, the fuel concentration is highest near the trailing apex and is lowest near the rotor. It is also found that the fuel concentration near the trailing apex and rotor is small except at high injection velocities.

Structure-aware depth super-resolution using Gaussian mixture model

NASA Astrophysics Data System (ADS)

Kim, Sunok; Oh, Changjae; Kim, Youngjung; Sohn, Kwanghoon

2015-03-01

This paper presents a probabilistic optimization approach to enhance the resolution of a depth map. Conventionally, a high-resolution color image is considered as a cue for depth super-resolution under the assumption that the pixels with similar color likely belong to similar depth. This assumption might induce a texture transferring from the color image into the depth map and an edge blurring artifact to the depth boundaries. In order to alleviate these problems, we propose an efficient depth prior exploiting a Gaussian mixture model in which an estimated depth map is considered to a feature for computing affinity between two pixels. Furthermore, a fixed-point iteration scheme is adopted to address the non-linearity of a constraint derived from the proposed prior. The experimental results show that the proposed method outperforms state-of-the-art methods both quantitatively and qualitatively.

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Spatial generalised linear mixed models based on distances.

PubMed

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Linear mixing model applied to AVHRR LAC data

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.

Nonlinear effects of stretch on the flame front propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halter, F.; Tahtouh, T.; Mounaim-Rousselle, C.

2010-10-15

In all experimental configurations, the flames are affected by stretch (curvature and/or strain rate). To obtain the unstretched flame speed, independent of the experimental configuration, the measured flame speed needs to be corrected. Usually, a linear relationship linking the flame speed to stretch is used. However, this linear relation is the result of several assumptions, which may be incorrected. The present study aims at evaluating the error in the laminar burning speed evaluation induced by using the traditional linear methodology. Experiments were performed in a closed vessel at atmospheric pressure for two different mixtures: methane/air and iso-octane/air. The initial temperaturesmore » were respectively 300 K and 400 K for methane and iso-octane. Both methodologies (linear and nonlinear) are applied and results in terms of laminar speed and burned gas Markstein length are compared. Methane and iso-octane were chosen because they present opposite evolutions in their Markstein length when the equivalence ratio is increased. The error induced by the linear methodology is evaluated, taking the nonlinear methodology as the reference. It is observed that the use of the linear methodology starts to induce substantial errors after an equivalence ratio of 1.1 for methane/air mixtures and before an equivalence ratio of 1 for iso-octane/air mixtures. One solution to increase the accuracy of the linear methodology for these critical cases consists in reducing the number of points used in the linear methodology by increasing the initial flame radius used. (author)« less

Linear models for sound from supersonic reacting mixing layers

NASA Astrophysics Data System (ADS)

Chary, P. Shivakanth; Samanta, Arnab

2016-12-01

We perform a linearized reduced-order modeling of the aeroacoustic sound sources in supersonic reacting mixing layers to explore their sensitivities to some of the flow parameters in radiating sound. Specifically, we investigate the role of outer modes as the effective flow compressibility is raised, when some of these are expected to dominate over the traditional Kelvin-Helmholtz (K-H) -type central mode. Although the outer modes are known to be of lesser importance in the near-field mixing, how these radiate to the far-field is uncertain, on which we focus. On keeping the flow compressibility fixed, the outer modes are realized via biasing the respective mean densities of the fast (oxidizer) or slow (fuel) side. Here the mean flows are laminar solutions of two-dimensional compressible boundary layers with an imposed composite (turbulent) spreading rate, which we show to significantly alter the growth of instability waves by saturating them earlier, similar to in nonlinear calculations, achieved here via solving the linear parabolized stability equations. As the flow parameters are varied, instability of the slow modes is shown to be more sensitive to heat release, potentially exceeding equivalent central modes, as these modes yield relatively compact sound sources with lesser spreading of the mixing layer, when compared to the corresponding fast modes. In contrast, the radiated sound seems to be relatively unaffected when the mixture equivalence ratio is varied, except for a lean mixture which is shown to yield a pronounced effect on the slow mode radiation by reducing its modal growth.

Sustained modelling ability of artificial neural networks in the analysis of two pharmaceuticals (dextropropoxyphene and dipyrone) present in unequal concentrations.

PubMed

Cámara, María S; Ferroni, Félix M; De Zan, Mercedes; Goicoechea, Héctor C

2003-07-01

An improvement is presented on the simultaneous determination of two active ingredients present in unequal concentrations in injections. The analysis was carried out with spectrophotometric data and non-linear multivariate calibration methods, in particular artificial neural networks (ANNs). The presence of non-linearities caused by the major analyte concentrations which deviate from Beer's law was confirmed by plotting actual vs. predicted concentrations, and observing curvatures in the residuals for the estimated concentrations with linear methods. Mixtures of dextropropoxyphene and dipyrone have been analysed by using linear and non-linear partial least-squares (PLS and NPLSs) and ANNs. Notwithstanding the high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. A commercial sample was analysed by using the present methodology, and the obtained results show reasonably good agreement with those obtained by using high-performance liquid chromatography (HPLC) and a UV-spectrophotometric comparative methods.

The entrainment matrix of a superfluid nucleon mixture at finite temperatures

NASA Astrophysics Data System (ADS)

Leinson, Lev B.

2018-06-01

It is considered a closed system of non-linear equations for the entrainment matrix of a non-relativistic mixture of superfluid nucleons at arbitrary temperatures below the onset of neutron superfluidity, which takes into account the essential dependence of the superfluid energy gap in the nucleon spectra on the velocities of superfluid flows. It is assumed that the protons condense into the isotropic 1S0 state, and the neutrons are paired into the spin-triplet 3P2 state. It is derived an analytic solution to the non-linear equations for the entrainment matrix under temperatures just below the critical value for the neutron superfluidity onset. In general case of an arbitrary temperature of the superfluid mixture the non-linear equations are solved numerically and fitted by simple formulas convenient for a practical use with an arbitrary set of the Landau parameters.

Modelling of ceramide interactions with porous graphite carbon in non-aqueous liquid chromatography.

PubMed

West, C; Cilpa, G; Gaudin, K; Chaminade, P; Lesellier, E

2005-09-16

Interactions of solutes on porous graphitic carbon (PGC) with non-aqueous mobile phases are studied by the linear solvation energy relationship (LSER). Studies have been carried out with eight binary mixtures composed of a weak solvent (acetonitrile or methanol) and a strong solvent (tetrahydrofuran, n-butanol, CH2Cl2, 1,1,2-trichloro-2,2,1-trifluoroethane). The systematic analysis of a set of test compounds was performed for each solvent mixture in isocratic mode (50:50). The results were compared to those obtained on PGC with hydro-organic liquids and supercritical fluids. They were then correlated with the observed retention behaviour of lipid compounds, more particularly ceramides.

Application of Hyperspectral Techniques to Monitoring and Management of Invasive Plant Species Infestation

DTIC Science & Technology

2008-01-01

the sensor is a data cloud in multi- dimensional space with each band generating an axis of dimension. When the data cloud is viewed in two or three...endmember of interest is not a true endmember in the data space . A ) B) Figure 8: Linear mixture models. A ) two- dimensional ...multi- dimensional space . A classifier is a computer algorithm that takes

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dielectric gas mixtures containing sulfur hexafluoride

DOEpatents

Cooke, Chathan M.

1979-01-01

Electrically insulating gaseous media of unexpectedly high dielectric strength comprised of mixtures of two or more dielectric gases are disclosed wherein the dielectric strength of at least one gas in each mixture increases at less than a linear rate with increasing pressure and the mixture gases are present in such proportions that the sum of their electrical discharge voltages at their respective partial pressures exceeds the electrical discharge voltage of each individual gas at the same temperature and pressure as that of the mixture.

Spectrophotometric determination of ternary mixtures of thiamin, riboflavin and pyridoxal in pharmaceutical and human plasma by least-squares support vector machines.

PubMed

Niazi, Ali; Zolgharnein, Javad; Afiuni-Zadeh, Somaie

2007-11-01

Ternary mixtures of thiamin, riboflavin and pyridoxal have been simultaneously determined in synthetic and real samples by applications of spectrophotometric and least-squares support vector machines. The calibration graphs were linear in the ranges of 1.0 - 20.0, 1.0 - 10.0 and 1.0 - 20.0 microg ml(-1) with detection limits of 0.6, 0.5 and 0.7 microg ml(-1) for thiamin, riboflavin and pyridoxal, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graph concentrations of vitamins. The simultaneous determination of these vitamin mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares (PLS) modeling and least-squares support vector machines were used for the multivariate calibration of the spectrophotometric data. An excellent model was built using LS-SVM, with low prediction errors and superior performance in relation to PLS. The root mean square errors of prediction (RMSEP) for thiamin, riboflavin and pyridoxal with PLS and LS-SVM were 0.6926, 0.3755, 0.4322 and 0.0421, 0.0318, 0.0457, respectively. The proposed method was satisfactorily applied to the rapid simultaneous determination of thiamin, riboflavin and pyridoxal in commercial pharmaceutical preparations and human plasma samples.

Assessment of two-phase flow on the chemical alteration and sealing of leakage pathways in cemented wellbores

DOE PAGES

Iyer, Jaisree; Walsh, Stuart D. C.; Hao, Yue; ...

2018-01-08

Wellbore leakage tops the list of perceived risks to the long-term geologic storage of CO 2, because wells provide a direct path between the CO 2 storage reservoir and the atmosphere. In this paper, we have coupled a two-phase flow model with our original framework that combined models for reactive transport of carbonated brine, geochemistry of reacting cement, and geomechanics to predict the permeability evolution of cement fractures. Additionally, this makes the framework suitable for field conditions in geological storage sites, permitting simulation of contact between cement and mixtures of brine and supercritical CO 2. Due to lack of conclusivemore » experimental data, we tried both linear and Corey relative permeability models to simulate flow of the two phases in cement fractures. The model also includes two options to account for the inconsistent experimental observations regarding cement reactivity with two-phase CO 2-brine mixtures. One option assumes that the reactive surface area is independent of the brine saturation and the second option assumes that the reactive surface area is proportional to the brine saturation. We have applied the model to predict the extent of cement alteration, the conditions under which fractures seal, the time it takes to seal a fracture, and the leakage rates of CO 2 and brine when damage zones in the wellbore are exposed to two-phase CO 2-brine mixtures. Initial brine residence time and the initial fracture aperture are critical parameters that affect the fracture sealing behavior. We also evaluated the importance of the model assumptions regarding relative permeability and cement reactivity. These results illustrate the need to understand how mixtures of carbon dioxide and brine flow through fractures and react with cement to make reasonable predictions regarding well integrity. For example, a reduction in the cement reactivity with two-phase CO 2-brine mixture can not only significantly increase the sealing time for fractures but may also prevent fracture sealing.« less

Assessment of two-phase flow on the chemical alteration and sealing of leakage pathways in cemented wellbores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iyer, Jaisree; Walsh, Stuart D. C.; Hao, Yue

Wellbore leakage tops the list of perceived risks to the long-term geologic storage of CO 2, because wells provide a direct path between the CO 2 storage reservoir and the atmosphere. In this paper, we have coupled a two-phase flow model with our original framework that combined models for reactive transport of carbonated brine, geochemistry of reacting cement, and geomechanics to predict the permeability evolution of cement fractures. Additionally, this makes the framework suitable for field conditions in geological storage sites, permitting simulation of contact between cement and mixtures of brine and supercritical CO 2. Due to lack of conclusivemore » experimental data, we tried both linear and Corey relative permeability models to simulate flow of the two phases in cement fractures. The model also includes two options to account for the inconsistent experimental observations regarding cement reactivity with two-phase CO 2-brine mixtures. One option assumes that the reactive surface area is independent of the brine saturation and the second option assumes that the reactive surface area is proportional to the brine saturation. We have applied the model to predict the extent of cement alteration, the conditions under which fractures seal, the time it takes to seal a fracture, and the leakage rates of CO 2 and brine when damage zones in the wellbore are exposed to two-phase CO 2-brine mixtures. Initial brine residence time and the initial fracture aperture are critical parameters that affect the fracture sealing behavior. We also evaluated the importance of the model assumptions regarding relative permeability and cement reactivity. These results illustrate the need to understand how mixtures of carbon dioxide and brine flow through fractures and react with cement to make reasonable predictions regarding well integrity. For example, a reduction in the cement reactivity with two-phase CO 2-brine mixture can not only significantly increase the sealing time for fractures but may also prevent fracture sealing.« less

Physicochemical determinants of linear alkylbenzene sulfonate (LAS) disposition in skin exposed to aqueous cutting fluid mixtures.

PubMed

Baynes, Ronald E; Brooks, James D; Barlow, Beth M; Riviere, Jim E

2002-06-01

Linear alkylbenzene sulfonate (LAS) is added to cutting fluid formulations to enhance the performance of metal machining operations, but this surfactant can cause contact dermatitis in workers involved in these operations. The purpose of this study was to determine how cutting fluid additives influence dermal disposition of 14C-LAS in mineral oil- or polyethylene glycol 200 (PEG)-based mixtures when topically applied to silastic membranes and porcine skin in an in vitro flow-through diffusion cell system. 14C-LAS mixtures were formulated with three commonly used cutting fluid additives; 0 or 2% triazine (TRI), 0 or 5% triethanolamine (TEA), and 0 or 5% sulfurized ricinoleic acid (SRA). LAS absorption was limited to less than a 0.5% dose and the additives in various combinations influenced the physicochemical characteristics of the dosing mixture. LAS was more likely to partition into the stratum corneum (SC) in mineral oil mixtures, and LAS absorption was significantly greater in the complete mixture. TRI enhanced LAS transport, and the presence of SRA decreased LAS critical micelle concentration (CMC) which reduced LAS monomers available for transport. TEA increased mixture viscosity, and this may have negated the apparent enhancing properties of TRI in several mixtures. In summary, physicochemical interactions in these mixtures influenced availability of LAS for absorption and distribution in skin, and could ultimately influence toxicological responses in skin.

A model for predicting thermal properties of asphalt mixtures from their constituents

NASA Astrophysics Data System (ADS)

Keller, Merlin; Roche, Alexis; Lavielle, Marc

Numerous theoretical and experimental approaches have been developed to predict the effective thermal conductivity of composite materials such as polymers, foams, epoxies, soils and concrete. None of such models have been applied to asphalt concrete. This study attempts to develop a model to predict the thermal conductivity of asphalt concrete from its constituents that will contribute to the asphalt industry by reducing costs and saving time on laboratory testing. The necessity to do the laboratory testing would be no longer required when a mix for the pavement is created with desired thermal properties at the design stage by selecting correct constituents. This thesis investigated six existing predictive models for applicability to asphalt mixtures, and four standard mathematical techniques were used to develop a regression model to predict the effective thermal conductivity. The effective thermal conductivities of 81 asphalt specimens were used as the response variables, and the thermal conductivities and volume fractions of their constituents were used as the predictors. The conducted statistical analyses showed that the measured values of thermal conductivities of the mixtures are affected by the bitumen and aggregate content, but not by the air content. Contrarily, the predicted data for some investigated models are highly sensitive to air voids, but not to bitumen and/or aggregate content. Additionally, the comparison of the experimental with analytical data showed that none of the existing models gave satisfactory results; on the other hand, two regression models (Exponential 1* and Linear 3*) are promising for asphalt concrete.

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

Accurate coarse-grained models for mixtures of colloids and linear polymers under good-solvent conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

D’Adamo, Giuseppe, E-mail: giuseppe.dadamo@sissa.it; Pelissetto, Andrea, E-mail: andrea.pelissetto@roma1.infn.it; Pierleoni, Carlo, E-mail: carlo.pierleoni@aquila.infn.it

2014-12-28

A coarse-graining strategy, previously developed for polymer solutions, is extended here to mixtures of linear polymers and hard-sphere colloids. In this approach, groups of monomers are mapped onto a single pseudoatom (a blob) and the effective blob-blob interactions are obtained by requiring the model to reproduce some large-scale structural properties in the zero-density limit. We show that an accurate parametrization of the polymer-colloid interactions is obtained by simply introducing pair potentials between blobs and colloids. For the coarse-grained (CG) model in which polymers are modelled as four-blob chains (tetramers), the pair potentials are determined by means of the iterative Boltzmannmore » inversion scheme, taking full-monomer (FM) pair correlation functions at zero-density as targets. For a larger number n of blobs, pair potentials are determined by using a simple transferability assumption based on the polymer self-similarity. We validate the model by comparing its predictions with full-monomer results for the interfacial properties of polymer solutions in the presence of a single colloid and for thermodynamic and structural properties in the homogeneous phase at finite polymer and colloid density. The tetramer model is quite accurate for q ≲ 1 (q=R{sup ^}{sub g}/R{sub c}, where R{sup ^}{sub g} is the zero-density polymer radius of gyration and R{sub c} is the colloid radius) and reasonably good also for q = 2. For q = 2, an accurate coarse-grained description is obtained by using the n = 10 blob model. We also compare our results with those obtained by using single-blob models with state-dependent potentials.« less

Identification of isopropylbiphenyl, alkyl diphenylmethanes, diisopropylnaphthalene, linear alkyl benzenes and other polychlorinated biphenyl replacement compounds in effluents, sediments and fish in the Fox River System, Wisconsin

USGS Publications Warehouse

Peterman, Paul H.; Delfino, Joseph J.

1990-01-01

Five polychlorinated biphenyl replacement dye solvents and a diluent present in carbonless copy paper were identified by gas chromatography/mass spectrometry in the following matrices: effluents from a de-inking–recycling paper mill and a municipal wastewater treatment plant receiving wastewaters from a carbonless copy paper manufacturing plant; sediments; and fish collected near both discharges in the Fox River System, Wisconsin. An isopropylbiphenyl dye solvent mixture included mono-, di- and triisopropylbiphenyls. Also identified were two dye solvent mixtures marketed under the trade name Santosol. Santosol 100 comprised ethyl-diphenylmethanes (DPMs), benzyl-ethyl-DPMs, and dibenzyl-ethyl-DPMs. Similarly, Santosol 150 comprised dimethyl-DPMs, benzyl-dimethyl-DPMs, and dibenzyl-dimethyl-DPMs. Diisopropylnaphthalenes, widely used as a dye solvent in Japan, were identified for the first time in the US environment. sec-Butylbiphenyls and di-sec-butylbiphenyls, likely constituents of a sec-butylbiphenyl dye solvent mixture, were tentatively identified. Linear alkyl benzenes (C10 to C13-LABs) constituted the Alkylate 215 diluent mixture. Although known to occur as minor constituents in linear alkyl sulfonate detergents, LAB residues have not been previously attributed to commercial use of LABs.

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

Objective determination of image end-members in spectral mixture analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Tompkins, Stefanie; Mustard, John F.; Pieters, Carle M.; Forsyth, Donald W.

1993-01-01

Spectral mixture analysis has been shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. Applications of AVIRIS data have ranged from mapping soils and bedrock to ecosystem studies. During the first phase of the approach, a set of end-members are selected from an image cube (image end-members) that best account for its spectral variance within a constrained, linear least squares mixing model. These image end-members are usually selected using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. We approach the problem of image end-member determination objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Influence of smooth temperature variation on hotspot ignition

DOE PAGES

Reinbacher, Fynn; Regele, Jonathan David

2017-10-06

Autoignition in thermally stratified reactive mixtures originates in localised hotspots. The ignition behaviour is often characterised using linear temperature gradients and more recently constant temperature plateaus combined with temperature gradients. Acoustic timescale characterisation of plateau regions has been successfully used to characterise the type of mechanical disturbance that will be created from a plateau core ignition. This work combines linear temperature gradients with superelliptic cores in order to more accurately account for a local temperature maximum of finite size and the smooth temperature variation contained inside realistic hotspot centres. A one-step Arrhenius reaction is used to model a H 2–airmore » reactive mixture. Using the superelliptic approach a range of behaviours for temperature distributions are investigated by varying the temperature profile between the gradient only and plateau and gradient bounding cases. Each superelliptic case is compared to a respective plateau and gradient case where simple acoustic timescale characterisation may be performed. It is shown that hot spots equivalent with excitation-to-acoustic timescale ratios sufficiently greater than unity exhibit behaviour very similar to a simple plateau-gradient model. Furthermore, for larger hot spots with timescale ratios sufficiently less than unity the reaction behaviour is highly dependent on the smooth temperature profile contained within the core region.« less

Influence of smooth temperature variation on hotspot ignition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reinbacher, Fynn; Regele, Jonathan David

Autoignition in thermally stratified reactive mixtures originates in localised hotspots. The ignition behaviour is often characterised using linear temperature gradients and more recently constant temperature plateaus combined with temperature gradients. Acoustic timescale characterisation of plateau regions has been successfully used to characterise the type of mechanical disturbance that will be created from a plateau core ignition. This work combines linear temperature gradients with superelliptic cores in order to more accurately account for a local temperature maximum of finite size and the smooth temperature variation contained inside realistic hotspot centres. A one-step Arrhenius reaction is used to model a H 2–airmore » reactive mixture. Using the superelliptic approach a range of behaviours for temperature distributions are investigated by varying the temperature profile between the gradient only and plateau and gradient bounding cases. Each superelliptic case is compared to a respective plateau and gradient case where simple acoustic timescale characterisation may be performed. It is shown that hot spots equivalent with excitation-to-acoustic timescale ratios sufficiently greater than unity exhibit behaviour very similar to a simple plateau-gradient model. Furthermore, for larger hot spots with timescale ratios sufficiently less than unity the reaction behaviour is highly dependent on the smooth temperature profile contained within the core region.« less

Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil.

PubMed

Guimarães, Ricardo J P S; Freitas, Corina C; Dutra, Luciano V; Scholte, Ronaldo G C; Amaral, Ronaldo S; Drummond, Sandra C; Shimabukuro, Yosio E; Oliveira, Guilherme C; Carvalho, Omar S

2010-07-01

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

Origin and Function of Tuning Diversity in Macaque Visual Cortex.

PubMed

Goris, Robbe L T; Simoncelli, Eero P; Movshon, J Anthony

2015-11-18

Neurons in visual cortex vary in their orientation selectivity. We measured responses of V1 and V2 cells to orientation mixtures and fit them with a model whose stimulus selectivity arises from the combined effects of filtering, suppression, and response nonlinearity. The model explains the diversity of orientation selectivity with neuron-to-neuron variability in all three mechanisms, of which variability in the orientation bandwidth of linear filtering is the most important. The model also accounts for the cells' diversity of spatial frequency selectivity. Tuning diversity is matched to the needs of visual encoding. The orientation content found in natural scenes is diverse, and neurons with different selectivities are adapted to different stimulus configurations. Single orientations are better encoded by highly selective neurons, while orientation mixtures are better encoded by less selective neurons. A diverse population of neurons therefore provides better overall discrimination capabilities for natural images than any homogeneous population. Copyright © 2015 Elsevier Inc. All rights reserved.

Improved estimation of sediment source contributions by concentration-dependent Bayesian isotopic mixing model

NASA Astrophysics Data System (ADS)

Ram Upadhayay, Hari; Bodé, Samuel; Griepentrog, Marco; Bajracharya, Roshan Man; Blake, Will; Cornelis, Wim; Boeckx, Pascal

2017-04-01

The implementation of compound-specific stable isotope (CSSI) analyses of biotracers (e.g. fatty acids, FAs) as constraints on sediment-source contributions has become increasingly relevant to understand the origin of sediments in catchments. The CSSI fingerprinting of sediment utilizes CSSI signature of biotracer as input in an isotopic mixing model (IMM) to apportion source soil contributions. So far source studies relied on the linear mixing assumptions of CSSI signature of sources to the sediment without accounting for potential effects of source biotracer concentration. Here we evaluated the effect of FAs concentration in sources on the accuracy of source contribution estimations in artificial soil mixture of three well-separated land use sources. Soil samples from land use sources were mixed to create three groups of artificial mixture with known source contributions. Sources and artificial mixture were analysed for δ13C of FAs using gas chromatography-combustion-isotope ratio mass spectrometry. The source contributions to the mixture were estimated using with and without concentration-dependent MixSIAR, a Bayesian isotopic mixing model. The concentration-dependent MixSIAR provided the closest estimates to the known artificial mixture source contributions (mean absolute error, MAE = 10.9%, and standard error, SE = 1.4%). In contrast, the concentration-independent MixSIAR with post mixing correction of tracer proportions based on aggregated concentration of FAs of sources biased the source contributions (MAE = 22.0%, SE = 3.4%). This study highlights the importance of accounting the potential effect of a source FA concentration for isotopic mixing in sediments that adds realisms to mixing model and allows more accurate estimates of contributions of sources to the mixture. The potential influence of FA concentration on CSSI signature of sediments is an important underlying factor that determines whether the isotopic signature of a given source is observable even after equilibrium. Therefore inclusion of FA concentrations of the sources in the IMM formulation is standard procedure for accurate estimation of source contributions. The post model correction approach that dominates the CSSI fingerprinting causes bias, especially if the FAs concentration of sources differs substantially.

[Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

PubMed

Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

2015-05-01

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

On the modeling of the bottom particles segregation with non-linear diffusion equations: application to the marine sand ripples

NASA Astrophysics Data System (ADS)

Tiguercha, Djlalli; Bennis, Anne-claire; Ezersky, Alexander

2015-04-01

The elliptical motion in surface waves causes an oscillating motion of the sand grains leading to the formation of ripple patterns on the bottom. Investigation how the grains with different properties are distributed inside the ripples is a difficult task because of the segration of particle. The work of Fernandez et al. (2003) was extended from one-dimensional to two-dimensional case. A new numerical model, based on these non-linear diffusion equations, was developed to simulate the grain distribution inside the marine sand ripples. The one and two-dimensional models are validated on several test cases where segregation appears. Starting from an homogeneous mixture of grains, the two-dimensional simulations demonstrate different segregation patterns: a) formation of zones with high concentration of light and heavy particles, b) formation of «cat's eye» patterns, c) appearance of inverse Brazil nut effect. Comparisons of numerical results with the new set of field data and wave flume experiments show that the two-dimensional non-linear diffusion equations allow us to reproduce qualitatively experimental results on particles segregation.

Inferring Short-Range Linkage Information from Sequencing Chromatograms

PubMed Central

Beggel, Bastian; Neumann-Fraune, Maria; Kaiser, Rolf; Verheyen, Jens; Lengauer, Thomas

2013-01-01

Direct Sanger sequencing of viral genome populations yields multiple ambiguous sequence positions. It is not straightforward to derive linkage information from sequencing chromatograms, which in turn hampers the correct interpretation of the sequence data. We present a method for determining the variants existing in a viral quasispecies in the case of two nearby ambiguous sequence positions by exploiting the effect of sequence context-dependent incorporation of dideoxynucleotides. The computational model was trained on data from sequencing chromatograms of clonal variants and was evaluated on two test sets of in vitro mixtures. The approach achieved high accuracies in identifying the mixture components of 97.4% on a test set in which the positions to be analyzed are only one base apart from each other, and of 84.5% on a test set in which the ambiguous positions are separated by three bases. In silico experiments suggest two major limitations of our approach in terms of accuracy. First, due to a basic limitation of Sanger sequencing, it is not possible to reliably detect minor variants with a relative frequency of no more than 10%. Second, the model cannot distinguish between mixtures of two or four clonal variants, if one of two sets of linear constraints is fulfilled. Furthermore, the approach requires repetitive sequencing of all variants that might be present in the mixture to be analyzed. Nevertheless, the effectiveness of our method on the two in vitro test sets shows that short-range linkage information of two ambiguous sequence positions can be inferred from Sanger sequencing chromatograms without any further assumptions on the mixture composition. Additionally, our model provides new insights into the established and widely used Sanger sequencing technology. The source code of our method is made available at http://bioinf.mpi-inf.mpg.de/publications/beggel/linkageinformation.zip. PMID:24376502

Incorporating concentration dependence in stable isotope mixing models.

PubMed

Phillips, Donald L; Koch, Paul L

2002-01-01

Stable isotopes are often used as natural labels to quantify the contributions of multiple sources to a mixture. For example, C and N isotopic signatures can be used to determine the fraction of three food sources in a consumer's diet. The standard dual isotope, three source linear mixing model assumes that the proportional contribution of a source to a mixture is the same for both elements (e.g., C, N). This may be a reasonable assumption if the concentrations are similar among all sources. However, one source is often particularly rich or poor in one element (e.g., N), which logically leads to a proportionate increase or decrease in the contribution of that source to the mixture for that element relative to the other element (e.g., C). We have developed a concentration-weighted linear mixing model, which assumes that for each element, a source's contribution is proportional to the contributed mass times the elemental concentration in that source. The model is outlined for two elements and three sources, but can be generalized to n elements and n+1 sources. Sensitivity analyses for C and N in three sources indicated that varying the N concentration of just one source had large and differing effects on the estimated source contributions of mass, C, and N. The same was true for a case study of bears feeding on salmon, moose, and N-poor plants. In this example, the estimated biomass contribution of salmon from the concentration-weighted model was markedly less than the standard model estimate. Application of the model to a captive feeding study of captive mink fed on salmon, lean beef, and C-rich, N-poor beef fat reproduced very closely the known dietary proportions, whereas the standard model failed to yield a set of positive source proportions. Use of this concentration-weighted model is recommended whenever the elemental concentrations vary substantially among the sources, which may occur in a variety of ecological and geochemical applications of stable isotope analysis. Possible examples besides dietary and food web studies include stable isotope analysis of water sources in soils, plants, or water bodies; geological sources for soils or marine systems; decomposition and soil organic matter dynamics, and tracing animal migration patterns. A spreadsheet for performing the calculations for this model is available at http://www.epa.gov/wed/pages/models.htm.

Analysis of lithology: Vegetation mixes in multispectral images

NASA Technical Reports Server (NTRS)

Adams, J. B.; Smith, M.; Adams, J. D.

1982-01-01

Discrimination and identification of lithologies from multispectral images is discussed. Rock/soil identification can be facilitated by removing the component of the signal in the images that is contributed by the vegetation. Mixing models were developed to predict the spectra of combinations of pure end members, and those models were refined using laboratory measurements of real mixtures. Models in use include a simple linear (checkerboard) mix, granular mixing, semi-transparent coatings, and combinations of the above. The use of interactive computer techniques that allow quick comparison of the spectrum of a pixel stack (in a multiband set) with laboratory spectra is discussed.

Health-related quality of life and disease symptoms in postmenopausal women with HR(+), HER2(-) advanced breast cancer treated with everolimus plus exemestane versus exemestane monotherapy.

PubMed

Campone, Mario; Beck, J Thaddeus; Gnant, Michael; Neven, Patrick; Pritchard, Kathleen I; Bachelot, Thomas; Provencher, Louise; Rugo, Hope S; Piccart, Martine; Hortobagyi, Gabriel N; Nunzi, Martina; Heng, Daniel Y C; Baselga, José; Komorowski, Anna; Noguchi, Shinzaburo; Horiguchi, Jun; Bennett, Lee; Ziemiecki, Ryan; Zhang, Jie; Cahana, Ayelet; Taran, Tetiana; Sahmoud, Tarek; Burris, Howard A

2013-11-01

Everolimus (EVE)+exemestane (EXE; n = 485) more than doubled median progression-free survival versus placebo (PBO) + EXE (n = 239), with a manageable safety profile and no deterioration in health-related quality-of-life (HRQOL) in patients with hormone-receptor-positive (HR(+)) advanced breast cancer (ABC) who recurred or progressed on/after nonsteroidal aromatase inhibitor (NSAI) therapy. To further evaluate EVE + EXE impact on disease burden, we conducted additional post-hoc analyses of patient-reported HRQOL. HRQOL was assessed using EORTC QLQ-C30 and QLQ-BR23 questionnaires at baseline and every 6 weeks thereafter until treatment discontinuation because of disease progression, toxicity, or consent withdrawal. Endpoints included the QLQ-C30 Global Health Status (QL2) scale, the QLQ-BR23 breast symptom (BRBS), and arm symptom (BRAS) scales. Between-group differences in change from baseline were assessed using linear mixed models with selected covariates. Sensitivity analysis using pattern-mixture models determined the effect of study discontinuation on/before week 24. Treatment arms were compared using differences of least squares mean (LSM) changes from baseline and 95% confidence intervals (CIs) at each timepoint and overall. Clinicaltrials.gov: NCT00863655. Progression-free survival, survival, response rate, safety, and HRQOL. Linear mixed models (primary model) demonstrated no statistically significant overall difference between EVE + EXE and PBO + EXE for QL2 (LSM difference = -1.91; 95% CI = -4.61, 0.78), BRBS (LSM difference = -0.18; 95% CI = -1.98, 1.62), or BRAS (LSM difference = -0.42; 95% CI = -2.94, 2.10). Based on pattern-mixture models, patients who dropped out early had worse QL2 decline on both treatments. In the expanded pattern-mixture model, EVE + EXE-treated patients who did not drop out early had stable BRBS and BRAS relative to PBO + EXE. HRQOL data were not collected after disease progression. These analyses confirm that EVE + EXE provides clinical benefit without adversely impacting HRQOL in patients with HR(+) ABC who recurred/progressed on prior NSAIs versus endocrine therapy alone.

Multilevel Mixture Kalman Filter

NASA Astrophysics Data System (ADS)

Guo, Dong; Wang, Xiaodong; Chen, Rong

2004-12-01

The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS) and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.

General baseline toxicity QSAR for nonpolar, polar and ionisable chemicals and their mixtures in the bioluminescence inhibition assay with Aliivibrio fischeri.

PubMed

Escher, Beate I; Baumer, Andreas; Bittermann, Kai; Henneberger, Luise; König, Maria; Kühnert, Christin; Klüver, Nils

2017-03-22

The Microtox assay, a bioluminescence inhibition assay with the marine bacterium Aliivibrio fischeri, is one of the most popular bioassays for assessing the cytotoxicity of organic chemicals, mixtures and environmental samples. Most environmental chemicals act as baseline toxicants in this short-term screening assay, which is typically run with only 30 min of exposure duration. Numerous Quantitative Structure-Activity Relationships (QSARs) exist for the Microtox assay for nonpolar and polar narcosis. However, typical water pollutants, which have highly diverse structures covering a wide range of hydrophobicity and speciation from neutral to anionic and cationic, are often outside the applicability domain of these QSARs. To include all types of environmentally relevant organic pollutants we developed a general baseline toxicity QSAR using liposome-water distribution ratios as descriptors. Previous limitations in availability of experimental liposome-water partition constants were overcome by reliable prediction models based on polyparameter linear free energy relationships for neutral chemicals and the COSMOmic model for charged chemicals. With this QSAR and targeted mixture experiments we could demonstrate that ionisable chemicals fall in the applicability domain. Most investigated water pollutants acted as baseline toxicants in this bioassay, with the few outliers identified as uncouplers or reactive toxicants. The main limitation of the Microtox assay is that chemicals with a high melting point and/or high hydrophobicity were outside of the applicability domain because of their low water solubility. We quantitatively derived a solubility cut-off but also demonstrated with mixture experiments that chemicals inactive on their own can contribute to mixture toxicity, which is highly relevant for complex environmental mixtures, where these chemicals may be present at concentrations below the solubility cut-off.

Retrieval of microphysical characteristics of particles in atmospheres of distant comets from ground-based polarimetry

NASA Astrophysics Data System (ADS)

Dlugach, Janna M.; Ivanova, Oleksandra V.; Mishchenko, Michael I.; Afanasiev, Viktor L.

2018-01-01

We summarize unique aperture data on the degree of linear polarization observed for distant comets C/2010 S1, C/2010 R1, C/2011 KP36, C/2012 J1, C/2013 V4, and C/2014 A4 with heliocentric distances exceeding 3 AU. Observations have been carried out at the 6-m telescope of the Special Astrophysical Observatory of the Russian Academy of Sciences (Nizhnij Arkhyz, Russia) during the period from 2011 to 2016. The measured negative polarization proves to be significantly larger in absolute value than what is typically observed for comets close to the Sun. We compare the new observational data with the results of numerical modeling performed with the T-matrix and superposition T-matrix methods. In our computer simulations, we assume the cometary coma to be an optically thin cloud containing particles in the form of spheroids, fractal aggregates composed of spherical monomers, and mixtures of spheroids and aggregate particles. We obtain a good semi-quantitative agreement between all polarimetric data for the observed distant comets and the results of numerical modeling for the following models of the cometary dust: (i) a mixture of submicrometer water-ice oblate spheroids with aggregates composed of submicrometer silicate monomers; and (ii) a mixture of submicrometer water-ice oblate spheroids and aggregates consisting of both silicate and organic monomers. The microphysical parameters of these models are presented and discussed.

Hardness and compression resistance of natural rubber and synthetic rubber mixtures

NASA Astrophysics Data System (ADS)

Arguello, J. M.; Santos, A.

2016-02-01

This project aims to mechanically characterize through compression resistance and shore hardness tests, the mixture of hevea brasiliensis natural rubber with butadiene synthetic rubber (BR), styrene-butadiene rubber (SBR) and ethylene-propylene-diene monomer rubber (EPDM). For each of the studied mixtures were performed 10 tests, each of which increased by 10% the content of synthetic rubber in the mixture; each test consisted of carrying out five tests of compression resistance and five tests of shore hardness. The specimens were vulcanized on a temperature of 160°C, during an approximate time of 15 minutes, and the equipment used in the performance of the mechanical tests were a Shimadzu universal machine and a digital durometer. The results show that the A shore hardness increases directly proportional, with a linear trend, with the content of synthetic BR, SBR or EPDM rubber present in the mixture, being the EPDM the most influential. With respect to the compression resistance is observed that the content of BR or SBR increase this property directly proportional through a linear trend; while the EPDM content also increases but with a polynomial trend.

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Breakdown and Limit of Continuum Diffusion Velocity for Binary Gas Mixtures from Direct Simulation

NASA Astrophysics Data System (ADS)

Martin, Robert Scott; Najmabadi, Farrokh

2011-05-01

This work investigates the breakdown of the continuum relations for diffusion velocity in inert binary gas mixtures. Values of the relative diffusion velocities for components of a gas mixture may be calculated using of Chapman-Enskog theory and occur not only due to concentration gradients, but also pressure and temperature gradients in the flow as described by Hirschfelder. Because Chapman-Enskog theory employs a linear perturbation around equilibrium, it is expected to break down when the velocity distribution deviates significantly from equilibrium. This breakdown of the overall flow has long been an area of interest in rarefied gas dynamics. By comparing the continuum values to results from Bird's DS2V Monte Carlo code, we propose a new limit on the continuum approach specific to binary gases. To remove the confounding influence of an inconsistent molecular model, we also present the application of the variable hard sphere (VSS) model used in DS2V to the continuum diffusion velocity calculation. Fitting sample asymptotic curves to the breakdown, a limit, Vmax, that is a fraction of an analytically derived limit resulting from the kinetic temperature of the mixture is proposed. With an expected deviation of only 2% between the physical values and continuum calculations within ±Vmax/4, we suggest this as a conservative estimate on the range of applicability for the continuum theory.

Analysis of pulsating spray flames propagating in lean two-phase mixtures with unity Lewis number

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicoli, C.; Haldenwang, P.; Suard, S.

2005-11-01

Pulsating (or oscillatory) spray flames have recently been observed in experiments on two-phase combustion. Numerical studies have pointed out that such front oscillations can be obtained even with very simple models of homogeneous two-phase mixtures, including elementary vaporization schemes. The paper presents an analytical approach within the simple framework of the thermal-diffusive model, which is complemented by a vaporization rate independent of gas temperature, as soon as the latter reaches a certain thermal threshold ({theta}{sub v} in reduced form). The study involves the Damkoehler number (Da), the ratio of chemical reaction rate to vaporization rate, and the Zeldovich number (Ze)more » as essential parameters. We use the standard asymptotic method based on matched expansions in terms of 1/Ze. Linear analysis of two-phase flame stability is performed by studying, in the absence of differential diffusive effects (unity Lewis number), the linear growth rate of 2-D perturbations added to steady plane solutions and characterized by wavenumber k in the direction transverse to spreading. A domain of existence is found for the pulsating regime. It corresponds to mixture characteristics often met in air-fuel two-phase systems: low boiling temperature ({theta}{sub v} << 1), reaction rate not higher than vaporization rate (Da < 1, i.e., small droplets), and activation temperature assumed to be high compared with flame temperature (Ze {>=} 10). Satisfactory comparison with numerical simulations confirms the validity of the analytical approach; in particular, positive growth rates have been found for planar perturbations (k = 0) and for wrinkled fronts (k {ne} 0). Finally, comparison between predicted frequencies and experimental measurements is discussed.« less

The use of common bean (Phaseolus vulgaris) traditional varieties and their mixtures with commercial varieties to manage bean fly (Ophiomyia spp.) infestations in Uganda.

PubMed

Ssekandi, W; Mulumba, J W; Colangelo, P; Nankya, R; Fadda, C; Karungi, J; Otim, M; De Santis, P; Jarvis, D I

The bean fly ( Ophiomyia spp.) is considered the most economically damaging field insect pest of common beans in Uganda. Despite the use of existing pest management approaches, reported damage has remained high. Forty-eight traditional and improved common bean varieties currently grown in farmers' fields were evaluated for resistance against bean fly. Data on bean fly incidence, severity and root damage from bean stem maggot were collected. Generalized linear mixed model (GLMM) revealed significant resistance to bean fly in the Ugandan traditional varieties. A popular resistant traditional variety and a popular susceptible commercial variety were selected from the 48 varieties and evaluated in pure and mixed stands. The incidence of bean fly infestation on both varieties in mixtures with different arrangements (systematic random versus rows), and different proportions within each of the two arrangements, was measured and analysed using GLMMs. The proportion of resistant varieties in a mixture and the arrangement type significantly decreased bean fly damage compared to pure stands, with the highest decrease in damage registered in the systematic random mixture with at least 50 % of resistant variety. The highest reduction in root damage, obvious 21 days after planting, was found in systematic random mixtures with at least 50 % of the resistant variety. Small holder farmers in East Africa and elsewhere in the world have local preferences for growing bean varieties in genetic mixtures. These mixtures can be enhanced by the use of resistant varieties in the mixtures to reduce bean fly damage on susceptible popular varieties.

Chemical Reactions in Turbulent Mixing Flows.

DTIC Science & Technology

1986-06-15

length from Reynolds and Schmidt numbers at high Reynolds number, 2. the linear dependence of flame length on the stoichiometric mixture ratio, and, 3...processes are unsteady and the observed large scale flame length fluctuations are the best evidence of the individual cascade. A more detailed examination...Damk~hler number. When the same ideas are used in a model of fuel jets burning in air, it explains (Broadwell 1982): 1. the independence of flame

Effects of different levels of supplementation of a 50:50 mixture of molasses:crude glycerol on performance, Bermuda grass hay intake, and nutrient digestibility of beef cattle.

PubMed

Ciriaco, F M; Henry, D D; Mercadante, V R G; Schulmeister, T; Ruiz-Moreno, M; Lamb, G C; DiLorenzo, N

2015-05-01

Two experiments were performed to evaluate the effects of different levels of supplementation with a 50:50 (as-fed) mixture of molasses:crude glycerol on animal performance, total tract digestibility of nutrients, and ruminal in situ degradability of nutrients in beef heifers and steers consuming Tifton 85 Bermuda grass (Cynodon spp.) hay. For Exp. 1, 24 Angus crossbred heifers (380 ± 31 kg BW) were used in a generalized randomized block design. For Exp. 2, 8 ruminally cannulated Angus crossbred steers (323 ± 42 kg BW) were used in a 4 × 4 duplicated Latin square design. For both experiments, animals were housed in individual pens at the University of Florida Feed Efficiency Facility, had ad libitum access to Tifton 85 Bermuda grass hay, and were randomly assigned to 1 of 4 treatments: 1) CTRL, no supplementation; 2) SUP1, 0.45 kg/d (as fed) of 50:50 mixture; 3) SUP3, 1.36 kg/d (as fed) of 50:50 mixture; and 4) SUP5, 2.27 kg/d (as fed) of a 50:50 mixture. Individual feed intake was recorded. Total DMI increased linearly (P = 0.005) as the level of supplementation increased. Hay intake ranged from 1.36 (CTRL) to 1.23% (SUP5) of BW, and was not affected (P ≥ 0.10) by liquid supplementation. Final BW was not affected by liquid supplementation ( ≥ 0.10). There was a linear increase (P = 0.027) in ADG as the liquid supplementation amounts increased. Liquid supplementation did not affect G:F (P ≥ 0.10). Apparent total tract digestibility of DM, OM, NDF, and ADF increased linearly (P < 0.001), while CP total tract digestibility decreased linearly (P = 0.002) as the level of supplementation increased. Ruminal pH was decreased linearly (P = 0.012) as the level of supplementation increased. No effect (P ≥ 0.10) of liquid supplementation was detected on lag time for NDF and ADF content of bermudagrass hay; however, rate of degradation (Kd) of NDF tended (P = 0.076) to be affected cubically by liquid supplementation. In addition, liquid supplementation linearly decreased (P < 0.05) ED of OM, CP, NDF, and ADF. In conclusion, supplementing up to 2.27 kg/d of a 50:50 mixture of molasses:crude glycerol may stimulate microbial growth and fermentative activity, thereby increasing nutrient digestibility. Increased fiber digestion, along with energy supplementation, led to increased ADG in heifers consuming Bermuda grass hay.

Characterization of Mixed Polypeptide Colloidal Particles by Light Scattering

NASA Astrophysics Data System (ADS)

Shuman, Hannah E.; Gaeckle, Grace K.; Gavin, John; Holland, Nolan B.; Streletzky, Kiril A.

2014-03-01

Temperature-dependent polymer surfactants have been developed by connecting three elastin-like polypeptide (ELP) chains to a charged protein domain (foldon), forming a three-armed star polymer. At low temperatures the polymer is soluble, while at higher temperatures it forms micelles. The behavior of mixtures of the three-armed star ELP (E20-Foldon) and H40-Linear ELP chains was analyzed under different salt and protein concentrations and various foldon to linear ELP ratio using Depolarized Dynamic Light Scattering. It was expected that under certain conditions the pure E20-Foldon would form spherical micelles, which upon adding the linear ELP would change in size and possibly shape. The pure E20-Foldon indeed formed largely spherical micelles with Rh of 10-20nm in solutions with 15-100mM salt and protein concentration between 10 μM and 100 μM. For the mixtures of 50 μM E20-Foldon and varying concentrations of H40-Linear in 25mM of salt, it was discovered that low and high H40-Linear concentration (4 μM and 50 μM) had only one transition. For the mixtures with of 10 and 25 μM of H40-Linear the two distinct transition temperatures were observed by spectrophotometry. The first transition corresponded to significantly elongated diffusive particles of apparent Rh of 30-50nm, while the second transition corresponded to slightly anisotropic diffusive particles with apparent Rh of about 20nm. At all H40-Linear concentrations studied, diffusive particles were seen above the second transition. Their radius and ability to depolarize light increased with the increase of H40-Linear concentration.

Raman spectroscopy and imaging to detect contaminants for food safety applications

NASA Astrophysics Data System (ADS)

Chao, Kuanglin; Qin, Jianwei; Kim, Moon S.; Peng, Yankun; Chan, Diane; Cheng, Yu-Che

2013-05-01

This study presents the use of Raman chemical imaging for the screening of dry milk powder for the presence of chemical contaminants and Raman spectroscopy for quantitative assessment of chemical contaminants in liquid milk. For image-based screening, melamine was mixed into dry milk at concentrations (w/w) between 0.2% and 10.0%, and images of the mixtures were analyzed by a spectral information divergence algorithm. Ammonium sulfate, dicyandiamide, and urea were each separately mixed into dry milk at concentrations (w/w) between 0.5% and 5.0%, and an algorithm based on self-modeling mixture analysis was applied to these sample images. The contaminants were successfully detected and the spatial distribution of the contaminants within the sample mixtures was visualized using these algorithms. Liquid milk mixtures were prepared with melamine at concentrations between 0.04% and 0.30%, with ammonium sulfate and with urea at concentrations between 0.1% and 10.0%, and with dicyandiamide at concentrations between 0.1% and 4.0%. Analysis of the Raman spectra from the liquid mixtures showed linear relationships between the Raman intensities and the chemical concentrations. Although further studies are necessary, Raman chemical imaging and spectroscopy show promise for use in detecting and evaluating contaminants in food ingredients.

Stationary-phase optimized selectivity liquid chromatography: development of a linear gradient prediction algorithm.

PubMed

De Beer, Maarten; Lynen, Fréderic; Chen, Kai; Ferguson, Paul; Hanna-Brown, Melissa; Sandra, Pat

2010-03-01

Stationary-phase optimized selectivity liquid chromatography (SOS-LC) is a tool in reversed-phase LC (RP-LC) to optimize the selectivity for a given separation by combining stationary phases in a multisegment column. The presently (commercially) available SOS-LC optimization procedure and algorithm are only applicable to isocratic analyses. Step gradient SOS-LC has been developed, but this is still not very elegant for the analysis of complex mixtures composed of components covering a broad hydrophobicity range. A linear gradient prediction algorithm has been developed allowing one to apply SOS-LC as a generic RP-LC optimization method. The algorithm allows operation in isocratic, stepwise, and linear gradient run modes. The features of SOS-LC in the linear gradient mode are demonstrated by means of a mixture of 13 steroids, whereby baseline separation is predicted and experimentally demonstrated.

Effect of the concentration of magnetic grains on the linear-optical-absorption coefficient of ferrofluid-doped lyotropic mesophases: deviation from the Beer-Lambert law.

PubMed

Cuppo, F L S; Gómez, S L; Figueiredo Neto, A M

2004-04-01

In this paper is reported a systematic experimental study of the linear-optical-absorption coefficient of ferrofluid-doped isotropic lyotropic mixtures as a function of the magnetic-grains concentration. The linear optical absorption of ferrolyomesophases increases in a nonlinear manner with the concentration of magnetic grains, deviating from the usual Beer-Lambert law. This behavior is associated to the presence of correlated micelles in the mixture which favors the formation of small-scale aggregates of magnetic grains (dimers), which have a higher absorption coefficient with respect to that of isolated grains. We propose that the indirect heating of the micelles via the ferrofluid grains (hyperthermia) could account for this nonlinear increase of the linear-optical-absorption coefficient as a function of the grains concentration.

Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

NASA Astrophysics Data System (ADS)

Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

2017-06-01

Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

Coupled nonequilibrium flow, energy and radiation transport for hypersonic planetary entry

NASA Astrophysics Data System (ADS)

Frederick, Donald Jerome

An ever increasing demand for energy coupled with a need to mitigate climate change necessitates technology (and lifestyle) changes globally. An aspect of the needed change is a decrease in the amount of anthropogenically generated CO2 emitted to the atmosphere. The decrease needed cannot be expected to be achieved through only one source of change or technology, but rather a portfolio of solutions are needed. One possible technology is Carbon Capture and Storage (CCS), which is likely to play some role due to its combination of mature and promising emerging technologies, such as the burning of hydrogen in gas turbines created by pre-combustion CCS separation processes. Thus research on effective methods of burning turbulent hydrogen jet flames (mimicking gas turbine environments) are needed, both in terms of experimental investigation and model development. The challenge in burning (and modeling the burning of) hydrogen lies in its wide range of flammable conditions, its high diffusivity (often requiring a diluent such as nitrogen to produce a lifted turbulent jet flame), and its behavior under a wide range of pressures. In this work, numerical models are used to simulate the environment of a gas turbine combustion chamber. Concurrent experimental investigations are separately conducted using a vitiated coflow burner (which mimics the gas turbine environment) to guide the numerical work in this dissertation. A variety of models are used to simulate, and occasionally guide, the experiment. On the fundamental side, mixing and chemistry interactions motivated by a H2/N2 jet flame in a vitiated coflow are investigated using a 1-D numerical model for laminar flows and the Linear Eddy Model for turbulent flows. A radial profile of the jet in coflow can be modeled as fuel and oxidizer separated by an initial mixing width. The effects of species diffusion model, pressure, coflow composition, and turbulent mixing on the predicted autoignition delay times and mixture composition at ignition are considered. We find that in laminar simulations the differential diffusion model allows the mixture to autoignite sooner and at a fuel-richer mixture than the equal diffusion model. The effect of turbulence on autoignition is classified in two regimes, which are dependent on a reference laminar autoignition delay and turbulence time scale. For a turbulence timescale larger than the reference laminar autoignition time, turbulence has little influence on autoignition or the mixture at ignition. However, for a turbulence timescale smaller than the reference laminar timescale, the influence of turbulence on autoignition depends on the diffusion model. Differential diffusion simulations show an increase in autoignition delay time and a subsequent change in mixture composition at ignition with increasing turbulence. Equal diffusion simulations suggest the effect of increasing turbulence on autoignition delay time and the mixture fraction at ignition is minimal. More practically, the stabilizing mechanism of a lifted jet flame is thought to be controlled by either autoignition, flame propagation, or a combination of the two. Experimental data for a turbulent hydrogen diluted with nitrogen jet flame in a vitiated coflow at atmospheric pressure, demonstrates distinct stability regimes where the jet flame is either attached, lifted, lifted-unsteady, or blown out. A 1-D parabolic RANS model is used, where turbulence-chemistry interactions are modeled with the joint scalar-PDF approach, and mixing is modeled with the Linear Eddy Model. The model only accounts for autoignition as a flame stabilization mechanism. However, by comparing the local turbulent flame speed to the local turbulent mean velocity, maps of regions where the flame speed is greater than the flow speed are created, which allow an estimate of lift-off heights based on flame propagation. Model results for the attached, lifted, and lifted-unsteady regimes show that the correct trend is captured. Additionally, at lower coflow equivalence ratios flame propagation appears dominant, while at higher coflow equivalence ratios autoignition appears dominant.

Using Simulation Technique to overcome the multi-collinearity problem for estimating fuzzy linear regression parameters.

NASA Astrophysics Data System (ADS)

Mansoor Gorgees, Hazim; Hilal, Mariam Mohammed

2018-05-01

Fatigue cracking is one of the common types of pavement distresses and is an indicator of structural failure; cracks allow moisture infiltration, roughness, may further deteriorate to a pothole. Some causes of pavement deterioration are: traffic loading; environment influences; drainage deficiencies; materials quality problems; construction deficiencies and external contributors. Many researchers have made models that contain many variables like asphalt content, asphalt viscosity, fatigue life, stiffness of asphalt mixture, temperature and other parameters that affect the fatigue life. For this situation, a fuzzy linear regression model was employed and analyzed by using the traditional methods and our proposed method in order to overcome the multi-collinearity problem. The total spread error was used as a criterion to compare the performance of the studied methods. Simulation program was used to obtain the required results.

Consideration of some dilute-solution phenomena based on an expression for the Gibbs free energy

NASA Astrophysics Data System (ADS)

Jonah, D. A.

1986-07-01

Rigorous expressions based on the Lennard-Jones (6 12) potential, are presented for the Gibbs and Helmholtz free energy of a dilute mixture. These expressions give the free energy of the mixture in terms of the thermodynamic properties of the pure solvent, thereby providing a convenient means of correlating dilute mixture behavior with that of the pure solvent. Expressions for the following dilute binary solution properties are derived: Henry's constant, limiting activity coefficients with their derivatives, solid solubilities in supercritical gases, and mixed second virial coefficients. The Henry's constant expression suggests a linear temperature dependence; application to solubility data for various gases in methane and water shows a good agreement between theory and experiment. In the thermodynamic modeling of supercritical fluid extraction, we have demonstrated how to predict new solubility-pressure isotherms from a given isotherm, with encouraging results. The mixed second virial coefficient expression has also been applied to experimental data; the agreement with theory is good.

Agar-based bridges as biocompatible candidates to provide guide cues in spinal cord injury repair.

PubMed

Martín-López, Eduardo; Darder, Margarita; Ruiz-Hitzky, Eduardo; Nieto Sampedro, Manuel

2013-01-01

Spinal bridge implants are strategic to provide growth surfaces for axonal regeneration after spinal cord injuries. The design of an appropriate substrate, one that is suitable for implantation, must involve careful testing of the biomaterial properties both in vitro and in vivo. The goal of this work was to test the structure, stability and biological response after spinal bridges implantation of several biopolymers, composed of mixtures of agar (AG), as structural matrix scaffold, with κ-carrageenan (Kc), gelatin (G), xanthan gum (Xn) and polysulfone (PS). Biopolymer structures were studied by environmental scanning electron microscopy, whereas the stability of gels was analyzed by in vitro degradation and swelling tests. The biocompatibility of these materials and their ability to promote cell growth and axonal regeneration were studied by implantation of spinal bridges containing empty linear channels in an acute rat spinal cord transection model at thoracic level (T8). All gel mixtures gave rise to porous structures and they were stables to degradation, excepting the AG+G mixture. Spinal bridges constructed from all mixtures were implanted during a month in adult rats. After this time a low host reaction occurred to all bridge materials as well as neurite and cell ingrowths through the empty channels. Neurites within the bridges were mostly peripheral sensory fibers such as those positive for CGRP, whereas there was a lack of regeneration of central axons crossing from the spinal tissue to bridges. Many of these neurites established closed contacts with non-myelin Schwann cells. The histological analysis revealed a high accumulation of collagen fibers within the channels. Unexpected was the apparent loss of channels linearity which affected the growth of neurites and cells, indicating the need for additional regeneration strategies and vertebrae bridge fixing.

Method of Preparing Polymers with Low Melt Viscosity

NASA Technical Reports Server (NTRS)

Jensen, Brian J. (Inventor)

2001-01-01

This invention is an improvement in standard polymerizations procedures, i.e., addition-type and step-growth type polymerizations, wherein monomers are reacted to form a growing polymer chain. The improvement includes employing an effective amount of a trifunctional monomer (such as a trifunctional amine anhydride, or phenol) in the polymerization procedure to form a mixture of polymeric materials consisting of branced polymers, star-shaped polymers, and linear polymers. This mixture of polymeric materials has a lower melt temperature and a lower melt viscosity than corresponding linear polymeric materials of equivalent molecular weight.

LINEARIZATION OF EMPIRICAL RHEOLOGICAL DATA FOR USE IN COMPOSITION CONTROL OF MULTICOMPONENT FOODSTUFFS.

PubMed

Drake, Birger; Nádai, Béla

1970-03-01

An empirical measure of viscosity, which is often far from being a linear function of composition, was used together with refractive index to build up a function which bears a linear relationship to the composition of tomato paste-water-sucrose mixtures. The new function can be used directly for rapid composition control by linear vector-vector transformation.

A simple thermodynamic model useful for calculating gas solubilities in water/brine/hydrocarbon mixtures from 0 to 250 C and 1 to 150 bars

NASA Astrophysics Data System (ADS)

Perez, R. J.; Shevalier, M.; Hutcheon, I.

2004-05-01

Gas solubility is of considerable interest, not only for the theoretical understanding of vapor-liquid equilibria, but also due to extensive applications in combined geochemical, engineering, and environmental problems, such as greenhouse gas sequestration. Reliable models for gas solubility calculations in salt waters and hydrocarbons are also valuable when evaluating fluid inclusions saturated with gas components. We have modeled the solubility of methane, ethane, hydrogen, carbon dioxide, hydrogen sulfide, and five other gases in a water-brine-hydrocarbon system by solving a non-linear system of equations composed by modified Henry's Law Constants (HLC), gas fugacities, and assuming binary mixtures. HLCs are a function of pressure, temperature, brine salinity, and hydrocarbon density. Experimental data of vapor pressures and mutual solubilities of binary mixtures provide the basis for the calibration of the proposed model. It is demonstrated that, by using the Setchenow equation, only a relatively simple modification of the pure water model is required to assess the solubility of gases in brine solutions. Henry's Law constants for gases in hydrocarbons are derived using regular solution theory and Ostwald coefficients available from the literature. We present a set of two-parameter polynomial expressions, which allow simple computation and formulation of the model. Our calculations show that solubility predictions using modified HLCs are acceptable within 0 to 250 C, 1 to 150 bars, salinity up to 5 molar, and gas concentrations up to 4 molar. Our model is currently being used in the IEA Weyburn CO2 monitoring and storage project.

On studies of 3He and isobutane mixture as neutron proportional counter gas

NASA Astrophysics Data System (ADS)

Desai, S. S.; Shaikh, A. M.

2006-02-01

The performance of neutron detectors filled with 3He+iC 4H 10 (isobutane) gas mixtures has been studied and compared with the performance of detectors filled with 3He+Kr gas mixtures. The investigations are made to determine suitable concentration of isobutane in the gas mixture to design neutron proportional counters and linear position sensitive neutron detectors (1-D PSDs). Energy resolution, range of proportionality, plateau and gas gain characteristics are studied for various gas mixtures of 3He and isobutane. The values for various gas constants are determined by fitting the gas gains to Diethorn and Bateman's equations and their variation with isobutane concentration in the fill gas mixture is studied.

Temperature, concentration, and frequency dependence of the dielectric constant near the critical point of the binary liquid mixture nitrobenzene-tetradecane

NASA Astrophysics Data System (ADS)

Leys, Jan; Losada-Pérez, Patricia; Cordoyiannis, George; Cerdeiriña, Claudio A.; Glorieux, Christ; Thoen, Jan

2010-03-01

Detailed results are reported for the dielectric constant ɛ as a function of temperature, concentration, and frequency near the upper critical point of the binary liquid mixture nitrobenzene-tetradecane. The data have been analyzed in the context of the recently developed concept of complete scaling. It is shown that the amplitude of the low frequency critical Maxwell-Wagner relaxation (with a relaxation frequency around 10 kHz) along the critical isopleth is consistent with the predictions of a droplet model for the critical fluctuations. The temperature dependence of ɛ in the homogeneous phase can be well described with a combination of a (1-α) power law term (with α the heat capacity critical exponent) and a linear term in reduced temperature with the Ising value for α. For the proper description of the temperature dependence of the difference Δɛ between the two coexisting phases below the critical temperature, it turned out that good fits with the Ising value for the order parameter exponent β required the addition of a corrections-to-scaling contribution or a linear term in reduced temperature. Good fits to the dielectric diameter ɛd require a (1-α) power law term, a 2β power law term (in the past considered as spurious), and a linear term in reduced temperature, consistent with complete scaling.

The role of chemometrics in single and sequential extraction assays: a review. Part II. Cluster analysis, multiple linear regression, mixture resolution, experimental design and other techniques.

PubMed

Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo

2011-03-04

Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.

Phase equillibria and solidification behaviour in the vanillin- p-anisidine system

NASA Astrophysics Data System (ADS)

Singh, N. B.; Das, S. S.; Gupta, Preeti; Dwivedi, M. K.

2008-12-01

Phase diagram of the vanillin- p-anisidine system has been studied by the thaw melt method. Congruent melting-type phase diagram exhibiting two eutectic points was obtained. Vanillin and p-anisidine react in 1:1 M ratio and form N-(4-methoxy phenyl)-4-hydroxy-3-methoxy phenyl methanimine (NHM) and water. Heats of fusion of pure components and the eutectic mixtures ( E1 and E2) were obtained from DSC studies. Jackson's roughness parameters ( α) were calculated. Excess Gibbs free energy ( GE), excess entropy ( SE) and excess enthalpy ( HE) of mixing of pre-, post- and eutectic mixtures were also calculated by using activity coefficient data. Linear velocities of solidification of components and eutectic mixtures were determined at different undercoolings. The values of excess thermodynamic functions and linear velocity data have indicated the non-ideal nature of the eutectic mixtures. Interaction energies in the gaseous state, calculated from computer simulation, have also indicated that the eutectics are non-ideal mixtures. Microstructural studies of vanillin, p-anisidine and NHM show the formation of broken lamellar type structures. However, for the eutectic E1, an irregular type and for the eutectic E2, a lamellar type structures were obtained. The effect of impurity on the microstructures of eutectic mixtures was also studied.

Multi-objective experimental design for (13)C-based metabolic flux analysis.

PubMed

Bouvin, Jeroen; Cajot, Simon; D'Huys, Pieter-Jan; Ampofo-Asiama, Jerry; Anné, Jozef; Van Impe, Jan; Geeraerd, Annemie; Bernaerts, Kristel

2015-10-01

(13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi-objective design should stimulate its application within the field of (13)C-based metabolic flux analysis. Copyright © 2015 Elsevier Inc. All rights reserved.

Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control.

PubMed

Hahne, J M; Biessmann, F; Jiang, N; Rehbaum, H; Farina, D; Meinecke, F C; Muller, K-R; Parra, L C

2014-03-01

In recent years the number of active controllable joints in electrically powered hand-prostheses has increased significantly. However, the control strategies for these devices in current clinical use are inadequate as they require separate and sequential control of each degree-of-freedom (DoF). In this study we systematically compare linear and nonlinear regression techniques for an independent, simultaneous and proportional myoelectric control of wrist movements with two DoF. These techniques include linear regression, mixture of linear experts (ME), multilayer-perceptron, and kernel ridge regression (KRR). They are investigated offline with electro-myographic signals acquired from ten able-bodied subjects and one person with congenital upper limb deficiency. The control accuracy is reported as a function of the number of electrodes and the amount and diversity of training data providing guidance for the requirements in clinical practice. The results showed that KRR, a nonparametric statistical learning method, outperformed the other methods. However, simple transformations in the feature space could linearize the problem, so that linear models could achieve similar performance as KRR at much lower computational costs. Especially ME, a physiologically inspired extension of linear regression represents a promising candidate for the next generation of prosthetic devices.

Adsorption of proteins at the solution/air interface influenced by added nonionic surfactants at very low concentrations for both components. 3. Dilational surface rheology.

PubMed

Fainerman, V B; Aksenenko, E V; Lylyk, S V; Lotfi, M; Miller, R

2015-03-05

The influence of the addition of the nonionic surfactants C12DMPO, C14DMPO, C10OH, and C10EO5 at concentrations between 10(-5) and 10(-1) mmol/L to solutions of β-casein (BCS) and β-lactoglobulin (BLG) at a fixed concentration of 10(-5) mmol/L on the dilational surface rheology is studied. A maximum in the viscoelasticity modulus |E| occurs at very low surfactant concentrations (10(-4) to 10(-3) mmol/L) for mixtures of BCS with C12DMPO and C14DMPO and for mixtures of BLG with C10EO5, while for mixture of BCS with C10EO5 the value of |E| only slightly increased. The |E| values calculated with a recently developed model, which assumes changes in the interfacial molar area of the protein molecules due to the interaction with the surfactants, are in satisfactory agreement with experimental data. A linear dependence exists between the ratio of the maximum modulus for the mixture to the modulus of the single protein solution and the coefficient reflecting the influence of the surfactants on the adsorption activity of the protein.

A numerical study of blood flow using mixture theory

PubMed Central

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 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. PMID:24791016

A numerical study of blood flow using mixture theory.

PubMed

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.

Chemotaxis migration and morphogenesis of living colonies.

PubMed

Ben Amar, Martine

2013-06-01

Development of forms in living organisms is complex and fascinating. Morphogenetic theories that investigate these shapes range from discrete to continuous models, from the variational elasticity to time-dependent fluid approach. Here a mixture model is chosen to describe the mass transport in a morphogenetic gradient: it gives a mathematical description of a mixture involving several constituents in mechanical interactions. This model, which is highly flexible can incorporate many biological processes but also complex interactions between cells as well as between cells and their environment. We use this model to derive a free-boundary problem easier to handle analytically. We solve it in the simplest geometry: an infinite linear front advancing with a constant velocity. In all the cases investigated here as the 3 D diffusion, the increase of mitotic activity at the border, nonlinear laws for the uptake of morphogens or for the mobility coefficient, a planar front exists above a critical threshold for the mobility coefficient but it becomes unstable just above the threshold at long wavelengths due to the existence of a Goldstone mode. This explains why sparsely bacteria exhibit dendritic patterns experimentally in opposition to other colonies such as biofilms and epithelia which are more compact. In the most unstable situation, where all the laws: diffusion, chemotaxis driving and chemoattractant uptake are linear, we show also that the system can recover a dynamic stability. A second threshold for the mobility exists which has a lower value as the ratio between diffusion coefficients decreases. Within the framework of this model where the biomass is treated mainly as a viscous and diffusive fluid, we show that the multiplicity of independent parameters in real biologic experimental set-up may explain varieties of observed patterns.

Comparative analysis of multisensor satellite monitoring of Arctic sea-ice

USGS Publications Warehouse

Belchansky, G.I.; Mordvintsev, Ilia N.; Douglas, David C.

1999-01-01

This report represents comparative analysis of nearly coincident Russian OKEAN-01 polar orbiting satellite data, Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) imagery. OKEAN-01 ice concentration algorithms utilize active and passive microwave measurements and a linear mixture model for measured values of the brightness temperature and the radar backscatter. SSM/I and AVHRR ice concentrations were computed with NASA Team algorithm and visible and thermal-infrared wavelength AVHRR data, accordingly

Characterizing Intimate Mixtures of Materials in Hyperspectral Imagery with Albedo-based and Kernel-based Approaches

DTIC Science & Technology

2015-09-01

scattering albedo (SSA) according to Hapke theory assuming bidirectional scattering at nadir look angles and uses a constrained linear model on the computed...following Hapke 9 (1993); and Mustard and Pieters 18 (1987)) assuming the reflectance spectra are bidirectional . SSA spectra were also generated...from AVIRIS data collected during a JPL/USGS campaign in response to the Deep Water Horizon (DWH) oil spill incident. 27 Out of the numerous

Scaling effect of fraction of vegetation cover retrieved by algorithms based on linear mixture model

NASA Astrophysics Data System (ADS)

Obata, Kenta; Miura, Munenori; Yoshioka, Hiroki

2010-08-01

Differences in spatial resolution among sensors have been a source of error among satellite data products, known as a scaling effect. This study investigates the mechanism of the scaling effect on fraction of vegetation cover retrieved by a linear mixture model which employs NDVI as one of the constraints. The scaling effect is induced by the differences in texture, and the differences between the true endmember spectra and the endmember spectra assumed during retrievals. A mechanism of the scaling effect was analyzed by focusing on the monotonic behavior of spatially averaged FVC as a function of spatial resolution. The number of endmember is limited into two to proceed the investigation analytically. Although the spatially-averaged NDVI varies monotonically along with spatial resolution, the corresponding FVC values does not always vary monotonically. The conditions under which the averaged FVC varies monotonically for a certain sequence of spatial resolutions, were derived analytically. The increasing and decreasing trend of monotonic behavior can be predicted from the true and assumed endmember spectra of vegetation and non-vegetation classes regardless the distributions of the vegetation class within a fixed area. The results imply that the scaling effect on FVC is more complicated than that on NDVI, since, unlike NDVI, FVC becomes non-monotonic under a certain condition determined by the true and assumed endmember spectra.

Trend estimation in populations with imperfect detection

USGS Publications Warehouse

Kery, Marc; Dorazio, Robert M.; Soldaat, Leo; Van Strien, Arco; Zuiderwijk, Annie; Royle, J. Andrew

2009-01-01

1. Trends of animal populations are of great interest in ecology but cannot be directly observed owing to imperfect detection. Binomial mixture models use replicated counts to estimate abundance, corrected for detection, in demographically closed populations. Here, we extend these models to open populations and illustrate them using sand lizard Lacerta agilis counts from the national Dutch reptile monitoring scheme. 2. Our model requires replicated counts from multiple sites in each of several periods, within which population closure is assumed. Counts are described by a hierarchical generalized linear model, where the state model deals with spatio-temporal patterns in true abundance and the observation model with imperfect counts, given that true state. We used WinBUGS to fit the model to lizard counts from 208 transects with 1–10 (mean 3) replicate surveys during each spring 1994–2005. 3. Our state model for abundance contained two independent log-linear Poisson regressions on year for coastal and inland sites, and random site effects to account for unexplained heterogeneity. The observation model for detection of an individual lizard contained effects of region, survey date, temperature, observer experience and random survey effects. 4. Lizard populations increased in both regions but more steeply on the coast. Detectability increased over the first few years of the study, was greater on the coast and for the most experienced observers, and highest around 1 June. Interestingly, the population increase inland was not detectable when the observed counts were analysed without account of detectability. The proportional increase between 1994 and 2005 in total lizard abundance across all sites was estimated at 86% (95% CRI 35–151). 5. Synthesis and applications. Open-population binomial mixture models are attractive for studying true population dynamics while explicitly accounting for the observation process, i.e. imperfect detection. We emphasize the important conceptual benefit provided by temporal replicate observations in terms of the interpretability of animal counts.

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

DOE Office of Scientific and Technical Information (OSTI.GOV)

Madronich, Sasha; Kleinman, Larry; Conley, Andrew

Gas-to-particle partitioning of organic aerosols (OA) is represented in most models by Raoult’s law, and depends on the existing mass of particles into which organic gases can dissolve. This raises the possibility of non-linear response of particle-phase OA to the emissions of precursor volatile organic compounds (VOCs) that contribute to this partitioning mass. Implications for air quality management are evident: A strong non-linear dependence would suggest that reductions in VOC emission would have a more-than-proportionate benefit in lowering ambient OA concentrations. Chamber measurements on simple VOC mixtures generally confirm the non-linear scaling between OA and VOCs, usually stated as amore » mass-dependence of the measured OA yields. However, for realistic ambient conditions including urban settings, no single component dominates the composition of the organic particles, and deviations from linearity are presumed to be small. Here we re-examine the linearity question using volatility spectra from several sources: (1) chamber studies of selected aerosols, (2) volatility inferred for aerosols sampled in two megacities, Mexico City and Paris, and (3) an explicit chemistry model (GECKO-A). These few available volatility distributions suggest that urban OA may be only slightly super-linear, with most values of the sensitivity exponent in the range 1.1-1.3, also substantially lower than seen in chambers for some specific aerosols. Furthermore, the rather low values suggest that OA concentrations in megacities are not an inevitable convergence of non-linear effects, but can be addressed (much like in smaller urban areas) by proportionate reductions in emissions.« less

Providing a Spatial Context for Crop Insurance in Ethiopia: Multiscale Comparisons of Vegetation Metrics in Tigray

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

Weather-based index insurance projects are rapidly expanding across the developing world. Many of these projects use satellite-based observations to detect extreme weather events, which inform and trigger payouts to smallholder farmers. While most index insurance programs use precipitation measurements to determine payouts, the use of remotely sensed observations of vegetation is currently being explored. In order to use vegetation indices as a basis for payouts, it is necessary to establish a consistent relationship between the vegetation index and the health and abundance of agriculture on the ground. The accuracy with which remotely sensed vegetation indices can detect changes in agriculture depends on both the spatial scale of the agriculture and the spatial resolution of the sensor. This study analyzes the relationship between meter and decameter scale vegetation fraction estimates derived from linear spectral mixture models with a more commonly used vegetation index (NDVI, EVI) at hectometer spatial scales. In addition, the analysis incorporates land cover/land use field observations collected in Tigray Ethiopia in July 2013. . It also tests the flexibility and utility of a standardized spectral mixture model in which land cover is represented as continuous fields of rock and soil substrate (S), vegetation (V) and dark surfaces (D; water, shadow). This analysis found strong linear relationships with vegetation metrics at 1.6-meter, 30-meter and 250-meter resolutions across spectrally diverse subsets of Tigray, Ethiopia and significantly correlated relationships using the Spearman's rho statistic. The observed linear scaling has positive implications for future use of moderate resolution vegetation indices in similar landscapes; especially index insurance projects that are scaling up across the developing world using remotely-sensed environmental information.

Modeling of breakthrough curves of single and quaternary mixtures of ethanol, glucose, glycerol and acetic acid adsorption onto a microporous hyper-cross-linked resin.

PubMed

Zhou, Jingwei; Wu, Jinglan; Liu, Yanan; Zou, Fengxia; Wu, Jian; Li, Kechun; Chen, Yong; Xie, Jingjing; Ying, Hanjie

2013-09-01

The adsorption of quaternary mixtures of ethanol/glycerol/glucose/acetic acid onto a microporous hyper-cross-linked resin HD-01 was studied in fixed beds. A mass transport model based on film solid linear driving force and the competitive Langmuir isotherm equation for the equilibrium relationship was used to develop theoretical fixed bed breakthrough curves. It was observed that the outlet concentration of glucose and glycerol exceeded the inlet concentration (c/c0>1), which is an evidence of competitive adsorption. This phenomenon can be explained by the displacement of glucose and glycerol by ethanol molecules, owing to more intensive interactions with the resin surface. The model proposed was validated using experimental data and can be capable of foresee reasonably the breakthrough curve of specific component under different operating conditions. The results show that HD-01 is a promising adsorbent for recovery of ethanol from the fermentation broth due to its large capacity, high selectivity, and rapid adsorption rate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discontinuous finite volume element discretization for coupled flow-transport problems arising in models of sedimentation

NASA Astrophysics Data System (ADS)

Bürger, Raimund; Kumar, Sarvesh; Ruiz-Baier, Ricardo

2015-10-01

The sedimentation-consolidation and flow processes of a mixture of small particles dispersed in a viscous fluid at low Reynolds numbers can be described by a nonlinear transport equation for the solids concentration coupled with the Stokes problem written in terms of the mixture flow velocity and the pressure field. Here both the viscosity and the forcing term depend on the local solids concentration. A semi-discrete discontinuous finite volume element (DFVE) scheme is proposed for this model. The numerical method is constructed on a baseline finite element family of linear discontinuous elements for the approximation of velocity components and concentration field, whereas the pressure is approximated by piecewise constant elements. The unique solvability of both the nonlinear continuous problem and the semi-discrete DFVE scheme is discussed, and optimal convergence estimates in several spatial norms are derived. Properties of the model and the predicted space accuracy of the proposed formulation are illustrated by detailed numerical examples, including flows under gravity with changing direction, a secondary settling tank in an axisymmetric setting, and batch sedimentation in a tilted cylindrical vessel.

POWER AND SAMPLE SIZE CALCULATIONS FOR LINEAR HYPOTHESES ASSOCIATED WITH MIXTURES OF MANY COMPONENTS USING FIXED-RATIO RAY DESIGNS

EPA Science Inventory

Response surface methodology, often supported by factorial designs, is the classical experimental approach that is widely accepted for detecting and characterizing interactions among chemicals in a mixture. In an effort to reduce the experimental effort as the number of compound...

Evaluation of Measurement Instrument Criterion Validity in Finite Mixture Settings

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.; Li, Tenglong

2016-01-01

A method for evaluating the validity of multicomponent measurement instruments in heterogeneous populations is discussed. The procedure can be used for point and interval estimation of criterion validity of linear composites in populations representing mixtures of an unknown number of latent classes. The approach permits also the evaluation of…

Thermodiffusion Coefficient Analysis of n-Dodecane /n-Hexane Mixture at Different Mass Fractions and Pressure Conditions

NASA Astrophysics Data System (ADS)

Lizarraga, Ion; Bou-Ali, M. Mounir; Santamaría, C.

2018-03-01

In this study, the thermodiffusion coefficient of n-dodecane/n-hexane binary mixture at 25 ∘C mean temperature was determined for several pressure conditions and mass fractions. The experimental technique used to determine the thermodiffusion coefficient was the thermograviational column of cylindrical configuration. In turn, thermophysical properties, such as density, thermal expansion, mass expansion and dynamic viscosity up to 10 MPa were also determined. The results obtained in this work showed a linear relation between the thermophysical properties and the pressure. Thermodiffusion coefficient values confirm a linear effect when the pressure increases. Additionally, a new correlation based on the thermodiffusion coefficient for n C12/n C6 binary mixture at 25 ∘C temperature for any mass fraction and pressures, which reproduces the data within the experimental error, was proposed.

Development and Validation of a High-Performance Thin-Layer Chromatographic Method for the Simultaneous Determination of Two Binary Mixtures Containing Ketorolac Tromethamine with Phenylephrine Hydrochloride and with Febuxostat

PubMed Central

El Yazbi, Fawzy A.; Hassan, Ekram M.; Khamis, Essam F.; Ragab, Marwa A.A.; Hamdy, Mohamed M.A.

2016-01-01

A validated and highly selective high-performance thin-layer chromatography (HPTLC) method was developed for the determination of ketorolac tromethamine (KTC) with phenylephrine hydrochloride (PHE) (Mixture 1) and with febuxostat (FBX) (Mixture 2) in bulk drug and in combined dosage forms. The proposed method was based on HPTLC separation of the drugs followed by densitometric measurements of their spots at 273 and 320 nm for Mixtures 1 and 2, respectively. The separation was carried out on Merck HPTLC aluminum sheets of silica gel 60 F254 using chloroform–methanol–ammonia (7:3:0.1, v/v) and (7.5:2.5:0.1, v/v) as mobile phase for KTC/PHE and KTC/FBX mixtures, respectively. Linear regression lines were obtained over the concentration ranges 0.20–0.60 and 0.60–1.95 µg band−1 for KTC and PHE (Mixture 1), respectively, and 0.10–1.00 and 0.25–2.50 µg band−1 for KTC and FBX (Mixture 2), respectively, with correlation coefficients higher than 0.999. The method was successfully applied to the analysis of the two drugs in their synthetic mixtures and in their dosage forms. The mean percentage recoveries were in the range of 98–102%, and the RSD did not exceed 2%. The method was validated according to ICH guidelines and showed good performances in terms of linearity, sensitivity, precision, accuracy and stability. PMID:26847918

Rheology behaviour of modified silicone-dammar as a natural resin coating

NASA Astrophysics Data System (ADS)

Zakaria, Rosnah; Ahmad, Azizah Hanom

2015-08-01

Modified silicone-dammar (SD) was prepared by various weight percent from 5 - 45 wt% of dammar added. The n-value (viscosity index) of silicone with 5 and 10 % were turn to be 1.6 and 1.3 of viscosity index. While 15, 20, 25 and 30 wt% of dammar added gave 0.7, 0.3, 0.2 and 0.1 of viscosity index. On the other hand, 35, 40 and 45 wt% of dammar gave a fixed value of viscosity index of 0.03. This n-value shows the dispersion quality of paint mixture indicates that the modified silicone-dammar was followed the Bingham's Model. The rheology measurement of SD mixture was analysed by plotting ln shear stress vs shear rate value. Analysis of the graph showed a Bingham plastic model with regression R2 equivalent to 0.99. The linear viscoelastic behaviour of SD samples increased in parallel with increasing dammar content indicate that the suspension of dammar in silicone resin could flow steadily with time giving a pseudoplastic behaviour.

Additive effects in high-voltage layered-oxide cells: A statistics of mixtures approach

DOE PAGES

Sahore, Ritu; Peebles, Cameron; Abraham, Daniel P.; ...

2017-07-20

Li 1.03(Ni 0.5Mn 0.3Co 0.2) 0.97O 2 (NMC)-based coin cells containing the electrolyte additives vinylene carbonate (VC) and tris(trimethylsilyl)phosphite (TMSPi) in the range of 0-2 wt% were cycled between 3.0 and 4.4 V. The changes in capacity at rates of C/10 and C/1 and resistance at 60% state of charge were found to follow linear-with-time kinetic rate laws. Further, the C/10 capacity and resistance data were amenable to modeling by a statistics of mixtures approach. Applying physical meaning to the terms in the empirical models indicated that the interactions between the electrolyte and additives were not simple. For example, theremore » were strong, synergistic interactions between VC and TMSPi affecting C/10 capacity loss, as expected, but there were other, more subtle interactions between the electrolyte components. In conclusion, the interactions between these components controlled the C/10 capacity decline and resistance increase.« less

The Deformation Behavior Analysis and Mechanical Modeling of Step/Intercritical Quenching and Partitioning-Treated Multiphase Steels

NASA Astrophysics Data System (ADS)

Zhao, Hongshan; Li, Wei; Wang, Li; Zhou, Shu; Jin, Xuejun

2016-08-01

T wo types of multiphase steels containing blocky or fine martensite have been used to study the phase interaction and the TRIP effect. These steels were obtained by step-quenching and partitioning (S-QP820) or intercritical-quenching and partitioning (I-QP800 & I-QP820). The retained austenite (RA) in S-QP820 specimen containing blocky martensite transformed too early to prevent the local failure at high strain due to the local strain concentration. In contrast, plentiful RA in I-QP800 specimen containing finely dispersed martensite transformed uniformly at high strain, which led to optimized strength and elongation. By applying a coordinate conversion method to the microhardness test, the load partitioning between ferrite and partitioned martensite was proved to follow the linear mixture law. The mechanical behavior of multiphase S-QP820 steel can be modeled based on the Mecking-Kocks theory, Bouquerel's spherical assumption, and Gladman-type mixture law. Finally, the transformation-induced martensite hardening effect has been studied on a bake-hardened specimen.

Efficient parallel simulation of CO2 geologic sequestration insaline aquifers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Keni; Doughty, Christine; Wu, Yu-Shu

2007-01-01

An efficient parallel simulator for large-scale, long-termCO2 geologic sequestration in saline aquifers has been developed. Theparallel simulator is a three-dimensional, fully implicit model thatsolves large, sparse linear systems arising from discretization of thepartial differential equations for mass and energy balance in porous andfractured media. The simulator is based on the ECO2N module of the TOUGH2code and inherits all the process capabilities of the single-CPU TOUGH2code, including a comprehensive description of the thermodynamics andthermophysical properties of H2O-NaCl- CO2 mixtures, modeling singleand/or two-phase isothermal or non-isothermal flow processes, two-phasemixtures, fluid phases appearing or disappearing, as well as saltprecipitation or dissolution. The newmore » parallel simulator uses MPI forparallel implementation, the METIS software package for simulation domainpartitioning, and the iterative parallel linear solver package Aztec forsolving linear equations by multiple processors. In addition, theparallel simulator has been implemented with an efficient communicationscheme. Test examples show that a linear or super-linear speedup can beobtained on Linux clusters as well as on supercomputers. Because of thesignificant improvement in both simulation time and memory requirement,the new simulator provides a powerful tool for tackling larger scale andmore complex problems than can be solved by single-CPU codes. Ahigh-resolution simulation example is presented that models buoyantconvection, induced by a small increase in brine density caused bydissolution of CO2.« less

Dependence of frictional strength on compositional variations of Hayward fault rock gouges

USGS Publications Warehouse

Morrow, Carolyn A.; Moore, Diane E.; Lockner, David A.

2010-01-01

The northern termination of the locked portion of the Hayward Fault near Berkeley, California, is found to coincide with the transition from strong Franciscan metagraywacke to melange on the western side of the fault. Both of these units are juxtaposed with various serpentinite, gabbro and graywacke units to the east, suggesting that the gouges formed within the Hayward Fault zone may vary widely due to the mixing of adjacent rock units and that the mechanical behavior of the fault would be best modeled by determining the frictional properties of mixtures of the principal rock types. To this end, room temperature, water-saturated, triaxial shearing tests were conducted on binary and ternary mixtures of fine-grained gouges prepared from serpentinite and gabbro from the Coast Range Ophiolite, a Great Valley Sequence graywacke, and three different Franciscan Complex metasedimentary rocks. Friction coefficients ranged from 0.36 for the serpentinite to 0.84 for the gabbro, with four of the rock types having coefficients of friction ranging from 0.67-0.84. The friction coefficients of the mixtures can be predicted reliably by a simple weighted average of the end-member dry-weight percentages and strengths for all samples except those containing serpentinite. For the serpentinite mixtures, a linear trend between end-member values slightly overestimates the coefficients of friction in the midcomposition ranges. The range in strength for these rock admixtures suggests that both theoretical and numerical modeling of the fault should attempt to account for variations in rock and gouge properties.

Compressible or incompressible blend of interacting monodisperse linear polymers near a surface.

PubMed

Batman, Richard; Gujrati, P D

2007-08-28

We consider a lattice model of a mixture of repulsive, attractive, or neutral monodisperse linear polymers of two species, A and B, with a third monomeric species C, which may be taken to represent free volume. The mixture is confined between two hard, parallel plates of variable separation whose interactions with A and C may be attractive, repulsive, or neutral, and may be different from each other. The interactions with A and C are all that are required to completely specify the effect of each surface on all three components. We numerically study various density profiles as we move away from the surface, by using the recursive method of Gujrati and Chhajer [J. Chem. Phys. 106, 5599 (1997)] that has already been previously applied to study polydisperse solutions and blends next to surfaces. The resulting density profiles show the oscillations that are seen in Monte Carlo simulations and the enrichment of the smaller species at a neutral surface. The method is computationally ultrafast and can be carried out on a personal computer (PC), even in the incompressible case, when Monte Carlo simulations are not feasible. The calculations of density profiles usually take less than 20 min on a PC.

Reservoir Computing Beyond Memory-Nonlinearity Trade-off.

PubMed

Inubushi, Masanobu; Yoshimura, Kazuyuki

2017-08-31

Reservoir computing is a brain-inspired machine learning framework that employs a signal-driven dynamical system, in particular harnessing common-signal-induced synchronization which is a widely observed nonlinear phenomenon. Basic understanding of a working principle in reservoir computing can be expected to shed light on how information is stored and processed in nonlinear dynamical systems, potentially leading to progress in a broad range of nonlinear sciences. As a first step toward this goal, from the viewpoint of nonlinear physics and information theory, we study the memory-nonlinearity trade-off uncovered by Dambre et al. (2012). Focusing on a variational equation, we clarify a dynamical mechanism behind the trade-off, which illustrates why nonlinear dynamics degrades memory stored in dynamical system in general. Moreover, based on the trade-off, we propose a mixture reservoir endowed with both linear and nonlinear dynamics and show that it improves the performance of information processing. Interestingly, for some tasks, significant improvements are observed by adding a few linear dynamics to the nonlinear dynamical system. By employing the echo state network model, the effect of the mixture reservoir is numerically verified for a simple function approximation task and for more complex tasks.

Surface roughness effects on the solar reflectance of cool asphalt shingles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akbari, Hashem; Berdahl, Paul; Akbari, Hashem

2008-02-17

We analyze the solar reflectance of asphalt roofing shingles that are covered with pigmented mineral roofing granules. The reflecting surface is rough, with a total area approximately twice the nominal area. We introduce a simple analytical model that relates the 'micro-reflectance' of a small surface region to the 'macro-reflectance' of the shingle. This model uses a mean field approximation to account for multiple scattering effects. The model is then used to compute the reflectance of shingles with a mixture of different colored granules, when the reflectances of the corresponding mono-color shingles are known. Simple linear averaging works well, with smallmore » corrections to linear averaging derived for highly reflective materials. Reflective base granules and reflective surface coatings aid achievement of high solar reflectance. Other factors that influence the solar reflectance are the size distribution of the granules, coverage of the asphalt substrate, and orientation of the granules as affected by rollers during fabrication.« less

Estimation of aboveground biomass in Mediterranean forests by statistical modelling of ASTER fraction images

NASA Astrophysics Data System (ADS)

Fernández-Manso, O.; Fernández-Manso, A.; Quintano, C.

2014-09-01

Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression models of original or synthetic bands. To overcome the poor relation between AGB and spectral bands due to mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGB estimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is a managed Mediterranean pine woodland (Pinus pinaster Ait.) in central Spain. A total of 1033 circular field plots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression to identify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Difference Vegetation Index and Tasselled Cap components. Four linear models and one nonlinear model were tested. A linear combination of ASTER band 2 (red, 0.630-0.690 μm), band 8 (short wave infrared 5, 2.295-2.365 μm) and green vegetation fraction (from LSMA) was the best AGB predictor (Radj2=0.632, the root-mean-squared error of estimated AGB was 13.3 Mg ha-1 (or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests. The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be used as baseline information for forest managers in future studies, such as quantifying the regional carbon budget, fuel accumulation or monitoring of management practices.

FDATMOS16 non-linear partitioning and organic volatility distributions in urban aerosols

DOE PAGES

Madronich, Sasha; Kleinman, Larry; Conley, Andrew; ...

2015-12-17

Gas-to-particle partitioning of organic aerosols (OA) is represented in most models by Raoult’s law, and depends on the existing mass of particles into which organic gases can dissolve. This raises the possibility of non-linear response of particle-phase OA to the emissions of precursor volatile organic compounds (VOCs) that contribute to this partitioning mass. Implications for air quality management are evident: A strong non-linear dependence would suggest that reductions in VOC emission would have a more-than-proportionate benefit in lowering ambient OA concentrations. Chamber measurements on simple VOC mixtures generally confirm the non-linear scaling between OA and VOCs, usually stated as amore » mass-dependence of the measured OA yields. However, for realistic ambient conditions including urban settings, no single component dominates the composition of the organic particles, and deviations from linearity are presumed to be small. Here we re-examine the linearity question using volatility spectra from several sources: (1) chamber studies of selected aerosols, (2) volatility inferred for aerosols sampled in two megacities, Mexico City and Paris, and (3) an explicit chemistry model (GECKO-A). These few available volatility distributions suggest that urban OA may be only slightly super-linear, with most values of the sensitivity exponent in the range 1.1-1.3, also substantially lower than seen in chambers for some specific aerosols. Furthermore, the rather low values suggest that OA concentrations in megacities are not an inevitable convergence of non-linear effects, but can be addressed (much like in smaller urban areas) by proportionate reductions in emissions.« less

The influence of different loads on the remodeling process of a bone and bioresorbable material mixture with voids

NASA Astrophysics Data System (ADS)

Giorgio, Ivan; Andreaus, Ugo; Madeo, Angela

2016-03-01

A model of a mixture of bone tissue and bioresorbable material with voids was used to numerically analyze the physiological balance between the processes of bone growth and resorption and artificial material resorption in a plate-like sample. The adopted model was derived from a theory for the behavior of porous solids in which the matrix material is linearly elastic and the interstices are void of material. The specimen—constituted by a region of bone living tissue and one of bioresorbable material—was acted by different in-plane loading conditions, namely pure bending and shear. Ranges of load magnitudes were identified within which physiological states become possible. Furthermore, the consequences of applying different loading conditions are examined at the end of the remodeling process. In particular, maximum value of bone and material mass densities, and extensions of the zones where bone is reconstructed were identified and compared in the two different load conditions. From the practical view point, during surgery planning and later rehabilitation, some choice of the following parameters is given: porosity of the graft, material characteristics of the graft, and adjustment of initial mixture tissue/bioresorbable material and later, during healing and remodeling, optimal loading conditions.

Automating spectral unmixing of AVIRIS data using convex geometry concepts

NASA Technical Reports Server (NTRS)

Boardman, Joseph W.

1993-01-01

Spectral mixture analysis, or unmixing, has proven to be a useful tool in the semi-quantitative interpretation of AVIRIS data. Using a linear mixing model and a set of hypothesized endmember spectra, unmixing seeks to estimate the fractional abundance patterns of the various materials occurring within the imaged area. However, the validity and accuracy of the unmixing rest heavily on the 'user-supplied' set of endmember spectra. Current methods for emdmember determination are the weak link in the unmixing chain.

New spectrophotometric/chemometric assisted methods for the simultaneous determination of imatinib, gemifloxacin, nalbuphine and naproxen in pharmaceutical formulations and human urine

NASA Astrophysics Data System (ADS)

Belal, F.; Ibrahim, F.; Sheribah, Z. A.; Alaa, H.

2018-06-01

In this paper, novel univariate and multivariate regression methods along with model-updating technique were developed and validated for the simultaneous determination of quaternary mixture of imatinib (IMB), gemifloxacin (GMI), nalbuphine (NLP) and naproxen (NAP). The univariate method is extended derivative ratio (EDR) which depends on measuring every drug in the quaternary mixture by using a ternary mixture of the other three drugs as divisor. Peak amplitudes were measured at 294 nm, 250 nm, 283 nm and 239 nm within linear concentration ranges of 4.0-17.0, 3.0-15.0, 4.0-80.0 and 1.0-6.0 μg mL-1 for IMB, GMI, NLP and NAB, respectively. Multivariate methods adopted are partial least squares (PLS) in original and derivative mode. These models were constructed for simultaneous determination of the studied drugs in the ranges of 4.0-8.0, 3.0-11.0, 10.0-18.0 and 1.0-3.0 μg mL-1 for IMB, GMI, NLP and NAB, respectively, by using eighteen mixtures as a calibration set and seven mixtures as a validation set. The root mean square error of predication (RMSEP) were 0.09 and 0.06 for IMB, 0.14 and 0.13 for GMI, 0.07 and 0.02 for NLP and 0.64 and 0.27 for NAP by PLS in original and derivative mode, respectively. Both models were successfully applied for analysis of IMB, GMI, NLP and NAP in their dosage forms. Updated PLS in derivative mode and EDR were applied for determination of the studied drugs in spiked human urine. The obtained results were statistically compared with those obtained by the reported methods giving a conclusion that there is no significant difference regarding accuracy and precision.

New spectrophotometric/chemometric assisted methods for the simultaneous determination of imatinib, gemifloxacin, nalbuphine and naproxen in pharmaceutical formulations and human urine.

PubMed

Belal, F; Ibrahim, F; Sheribah, Z A; Alaa, H

2018-06-05

In this paper, novel univariate and multivariate regression methods along with model-updating technique were developed and validated for the simultaneous determination of quaternary mixture of imatinib (IMB), gemifloxacin (GMI), nalbuphine (NLP) and naproxen (NAP). The univariate method is extended derivative ratio (EDR) which depends on measuring every drug in the quaternary mixture by using a ternary mixture of the other three drugs as divisor. Peak amplitudes were measured at 294nm, 250nm, 283nm and 239nm within linear concentration ranges of 4.0-17.0, 3.0-15.0, 4.0-80.0 and 1.0-6.0μgmL -1 for IMB, GMI, NLP and NAB, respectively. Multivariate methods adopted are partial least squares (PLS) in original and derivative mode. These models were constructed for simultaneous determination of the studied drugs in the ranges of 4.0-8.0, 3.0-11.0, 10.0-18.0 and 1.0-3.0μgmL -1 for IMB, GMI, NLP and NAB, respectively, by using eighteen mixtures as a calibration set and seven mixtures as a validation set. The root mean square error of predication (RMSEP) were 0.09 and 0.06 for IMB, 0.14 and 0.13 for GMI, 0.07 and 0.02 for NLP and 0.64 and 0.27 for NAP by PLS in original and derivative mode, respectively. Both models were successfully applied for analysis of IMB, GMI, NLP and NAP in their dosage forms. Updated PLS in derivative mode and EDR were applied for determination of the studied drugs in spiked human urine. The obtained results were statistically compared with those obtained by the reported methods giving a conclusion that there is no significant difference regarding accuracy and precision. Copyright © 2018 Elsevier B.V. All rights reserved.

A weighted least squares estimation of the polynomial regression model on paddy production in the area of Kedah and Perlis

NASA Astrophysics Data System (ADS)

Musa, Rosliza; Ali, Zalila; Baharum, Adam; Nor, Norlida Mohd

2017-08-01

The linear regression model assumes that all random error components are identically and independently distributed with constant variance. Hence, each data point provides equally precise information about the deterministic part of the total variation. In other words, the standard deviations of the error terms are constant over all values of the predictor variables. When the assumption of constant variance is violated, the ordinary least squares estimator of regression coefficient lost its property of minimum variance in the class of linear and unbiased estimators. Weighted least squares estimation are often used to maximize the efficiency of parameter estimation. A procedure that treats all of the data equally would give less precisely measured points more influence than they should have and would give highly precise points too little influence. Optimizing the weighted fitting criterion to find the parameter estimates allows the weights to determine the contribution of each observation to the final parameter estimates. This study used polynomial model with weighted least squares estimation to investigate paddy production of different paddy lots based on paddy cultivation characteristics and environmental characteristics in the area of Kedah and Perlis. The results indicated that factors affecting paddy production are mixture fertilizer application cycle, average temperature, the squared effect of average rainfall, the squared effect of pest and disease, the interaction between acreage with amount of mixture fertilizer, the interaction between paddy variety and NPK fertilizer application cycle and the interaction between pest and disease and NPK fertilizer application cycle.

Rheology modification with ring polymers

NASA Astrophysics Data System (ADS)

Vlassopoulos, Dimitris

It is now established that experimental unconcatenated ring polymers can be purified effectively by means of fractionation at the critical condition. For molecular weights well above the entanglement threshold, purified rings relax stress via power-law (with an exponent of about -0.4), sharply departing from their linear counterparts. Experimental results are in harmony with modeling predictions and simulations. Here, we present results from recent interdisciplinary efforts and discuss two challenges: (i) the nonlinear shear rheology of purified ring melts is also very different from that of unlinked chains. Whereas the latter exhibit features that can be explained, to a first approach, in the framework in the tube model, the former behave akin to unentangled chains with finite extensibility and exhibit much small deformation at steady state. (ii) blends of rings and linear polymers exhibit unique features in different regimes: The addition of minute amounts of linear chains drastically affects ring dynamics. This relates to ring purity and the ability of unlinked linear chains to thread rings. With the help of simulations, it is possible to rationalize the observed surprisingly slow viscoelastic relaxation, which is attributed to ring-linear and ring-ring penetrations. On the other hand, adding small amounts of rings to linear polymers of different molecular weights influences their linear and nonlinear rheology in an unprecedented way. The blend viscosity exceeds that of the slower component (linear) in this non-interacting mixture, and its dependencies on composition and molecular weight ratio are examined, whereas the role of molecular architecture is also addressed. Consequently, closing the ends of a linear chain can serve as a powerful means for molecular manipulation of its rheology. This presentation reflects collaborative efforts with S. Costanzo, Z-C. Yan, R. Pasquino, M. Kaliva, S. Kamble, Y. Jeong, P. Lutz, J. Allgaier, T. Chang, D. Talikis, V. Mavrantzas and M. Rubinstein.

Dynamics of osmosis in a porous medium.

PubMed

Cardoso, Silvana S S; Cartwright, Julyan H E

2014-11-01

We derive from kinetic theory, fluid mechanics and thermodynamics the minimal continuum-level equations governing the flow of a binary, non-electrolytic mixture in an isotropic porous medium with osmotic effects. For dilute mixtures, these equations are linear and in this limit provide a theoretical basis for the widely used semi-empirical relations of Kedem & Katchalsky (Kedem & Katchalsky 1958 Biochim. Biophys. Acta 27, 229-246 (doi:10.1016/0006-3002(58)90330-5), which have hitherto been validated experimentally but not theoretically. The above linearity between the fluxes and the driving forces breaks down for concentrated or non-ideal mixtures, for which our equations go beyond the Kedem-Katchalsky formulation. We show that the heretofore empirical solute permeability coefficient reflects the momentum transfer between the solute molecules that are rejected at a pore entrance and the solvent molecules entering the pore space; it can be related to the inefficiency of a Maxwellian demi-demon.

Audio visual speech source separation via improved context dependent association model

NASA Astrophysics Data System (ADS)

Kazemi, Alireza; Boostani, Reza; Sobhanmanesh, Fariborz

2014-12-01

In this paper, we exploit the non-linear relation between a speech source and its associated lip video as a source of extra information to propose an improved audio-visual speech source separation (AVSS) algorithm. The audio-visual association is modeled using a neural associator which estimates the visual lip parameters from a temporal context of acoustic observation frames. We define an objective function based on mean square error (MSE) measure between estimated and target visual parameters. This function is minimized for estimation of the de-mixing vector/filters to separate the relevant source from linear instantaneous or time-domain convolutive mixtures. We have also proposed a hybrid criterion which uses AV coherency together with kurtosis as a non-Gaussianity measure. Experimental results are presented and compared in terms of visually relevant speech detection accuracy and output signal-to-interference ratio (SIR) of source separation. The suggested audio-visual model significantly improves relevant speech classification accuracy compared to existing GMM-based model and the proposed AVSS algorithm improves the speech separation quality compared to reference ICA- and AVSS-based methods.

An in-situ Raman study on pristane at high pressure and ambient temperature

NASA Astrophysics Data System (ADS)

Wu, Jia; Ni, Zhiyong; Wang, Shixia; Zheng, Haifei

2018-01-01

The Csbnd H Raman spectroscopic band (2800-3000 cm-1) of pristane was measured in a diamond anvil cell at 1.1-1532 MPa and ambient temperature. Three models are used for the peak-fitting of this Csbnd H Raman band, and the linear correlations between pressure and corresponding peak positions are calculated as well. The results demonstrate that 1) the number of peaks that one chooses to fit the spectrum affects the results, which indicates that the application of the spectroscopic barometry with a function group of organic matters suffers significant limitations; and 2) the linear correlation between pressure and fitted peak positions from one-peak model is more superior than that from multiple-peak model, meanwhile the standard error of the latter is much higher than that of the former. It indicates that the Raman shift of Csbnd H band fitted with one-peak model, which could be treated as a spectroscopic barometry, is more realistic in mixture systems than the traditional strategy which uses the Raman characteristic shift of one function group.

Unveiling the Dependence of Glass Transitions on Mixing Thermodynamics in Miscible Systems

NASA Astrophysics Data System (ADS)

Tu, Wenkang; Wang, Yunxi; Li, Xin; Zhang, Peng; Tian, Yongjun; Jin, Shaohua; Wang, Li-Min

2015-02-01

The dependence of the glass transition in mixtures on mixing thermodynamics is examined by focusing on enthalpy of mixing, ΔHmix with the change in sign (positive vs. negative) and magnitude (small vs. large). The effects of positive and negative ΔHmix are demonstrated based on two isomeric systems of o- vs. m- methoxymethylbenzene (MMB) and o- vs. m- dibromobenzene (DBB) with comparably small absolute ΔHmix. Two opposite composition dependences of the glass transition temperature, Tg, are observed with the MMB mixtures showing a distinct negative deviation from the ideal mixing rule and the DBB mixtures having a marginally positive deviation. The system of 1, 2- propanediamine (12PDA) vs. propylene glycol (PG) with large and negative ΔHmix is compared with the systems of small ΔHmix, and a considerably positive Tg shift is seen. Models involving the properties of pure components such as Tg, glass transition heat capacity increment, ΔCp, and density, ρ, do not interpret the observed Tg shifts in the systems. In contrast, a linear correlation is revealed between ΔHmix and maximum Tg shifts.

Exchangeable Ions Are Responsible for the In Vitro Antibacterial Properties of Natural Clay Mixtures

PubMed Central

Otto, Caitlin C.; Haydel, Shelley E.

2013-01-01

We have identified a natural clay mixture that exhibits in vitro antibacterial activity against a broad spectrum of bacterial pathogens. We collected four samples from the same source and demonstrated through antibacterial susceptibility testing that these clay mixtures have markedly different antibacterial activity against Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA). Here, we used X-ray diffraction (XRD) and inductively coupled plasma – optical emission spectroscopy (ICP-OES) and – mass spectrometry (ICP-MS) to characterize the mineralogical and chemical features of the four clay mixture samples. XRD analyses of the clay mixtures revealed minor mineralogical differences between the four samples. However, ICP analyses demonstrated that the concentrations of many elements, Fe, Co, Cu, Ni, and Zn, in particular, vary greatly across the four clay mixture leachates. Supplementation of a non-antibacterial leachate containing lower concentrations of Fe, Co, Ni, Cu, and Zn to final ion concentrations and a pH equivalent to that of the antibacterial leachate generated antibacterial activity against E. coli and MRSA, confirming the role of these ions in the antibacterial clay mixture leachates. Speciation modeling revealed increased concentrations of soluble Cu2+ and Fe2+ in the antibacterial leachates, compared to the non-antibacterial leachates, suggesting these ionic species specifically are modulating the antibacterial activity of the leachates. Finally, linear regression analyses comparing the log10 reduction in bacterial viability to the concentration of individual ion species revealed positive correlations with Zn2+ and Cu2+ and antibacterial activity, a negative correlation with Fe3+, and no correlation with pH. Together, these analyses further indicate that the ion concentration of specific species (Fe2+, Cu2+, and Zn2+) are responsible for antibacterial activity and that killing activity is not solely attributed to pH. PMID:23691149

Effect of clay content and mineralogy on frictional sliding behavior of simulated gouges: binary and ternary mixtures of quartz, illite, and montmorillonite

USGS Publications Warehouse

Tembe, Sheryl; Lockner, David A.; Wong, Teng-Fong

2010-01-01

We investigated the frictional sliding behavior of simulated quartz-clay gouges under stress conditions relevant to seismogenic depths. Conventional triaxial compression tests were conducted at 40 MPa effective normal stress on saturated saw cut samples containing binary and ternary mixtures of quartz, montmorillonite, and illite. In all cases, frictional strengths of mixtures fall between the end-members of pure quartz (strongest) and clay (weakest). The overall trend was a decrease in strength with increasing clay content. In the illite/quartz mixture the trend was nearly linear, while in the montmorillonite mixtures a sigmoidal trend with three strength regimes was noted. Microstructural observations were performed on the deformed samples to characterize the geometric attributes of shear localization within the gouge layers. Two micromechanical models were used to analyze the critical clay fractions for the two-regime transitions on the basis of clay porosity and packing of the quartz grains. The transition from regime 1 (high strength) to 2 (intermediate strength) is associated with the shift from a stress-supporting framework of quartz grains to a clay matrix embedded with disperse quartz grains, manifested by the development of P-foliation and reduction in Riedel shear angle. The transition from regime 2 (intermediate strength) to 3 (low strength) is attributed to the development of shear localization in the clay matrix, occurring only when the neighboring layers of quartz grains are separated by a critical clay thickness. Our mixture data relating strength degradation to clay content agree well with strengths of natural shear zone materials obtained from scientific deep drilling projects.

Seismic waveform inversion using neural networks

NASA Astrophysics Data System (ADS)

De Wit, R. W.; Trampert, J.

2012-12-01

Full waveform tomography aims to extract all available information on Earth structure and seismic sources from seismograms. The strongly non-linear nature of this inverse problem is often addressed through simplifying assumptions for the physical theory or data selection, thus potentially neglecting valuable information. Furthermore, the assessment of the quality of the inferred model is often lacking. This calls for the development of methods that fully appreciate the non-linear nature of the inverse problem, whilst providing a quantification of the uncertainties in the final model. We propose to invert seismic waveforms in a fully non-linear way by using artificial neural networks. Neural networks can be viewed as powerful and flexible non-linear filters. They are very common in speech, handwriting and pattern recognition. Mixture Density Networks (MDN) allow us to obtain marginal posterior probability density functions (pdfs) of all model parameters, conditioned on the data. An MDN can approximate an arbitrary conditional pdf as a linear combination of Gaussian kernels. Seismograms serve as input, Earth structure parameters are the so-called targets and network training aims to learn the relationship between input and targets. The network is trained on a large synthetic data set, which we construct by drawing many random Earth models from a prior model pdf and solving the forward problem for each of these models, thus generating synthetic seismograms. As a first step, we aim to construct a 1D Earth model. Training sets are constructed using the Mineos package, which computes synthetic seismograms in a spherically symmetric non-rotating Earth by summing normal modes. We train a network on the body waveforms present in these seismograms. Once the network has been trained, it can be presented with new unseen input data, in our case the body waves in real seismograms. We thus obtain the posterior pdf which represents our final state of knowledge given the information in the training set and the real data.

Adaptive Gaussian mixture models for pre-screening in GPR data

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Due to the large amount of data generated by vehicle-mounted ground penetrating radar (GPR) antennae arrays, advanced feature extraction and classification can only be performed on a small subset of data during real-time operation. As a result, most GPR based landmine detection systems implement "pre-screening" algorithms to processes all of the data generated by the antennae array and identify locations with anomalous signatures for more advanced processing. These pre-screening algorithms must be computationally efficient and obtain high probability of detection, but can permit a false alarm rate which might be higher than the total system requirements. Many approaches to prescreening have previously been proposed, including linear prediction coefficients, the LMS algorithm, and CFAR-based approaches. Similar pre-screening techniques have also been developed in the field of video processing to identify anomalous behavior or anomalous objects. One such algorithm, an online k-means approximation to an adaptive Gaussian mixture model (GMM), is particularly well-suited to application for pre-screening in GPR data due to its computational efficiency, non-linear nature, and relevance of the logic underlying the algorithm to GPR processing. In this work we explore the application of an adaptive GMM-based approach for anomaly detection from the video processing literature to pre-screening in GPR data. Results with the ARA Nemesis landmine detection system demonstrate significant pre-screening performance improvements compared to alternative approaches, and indicate that the proposed algorithm is a complimentary technique to existing methods.

A computational investigation of the thermodynamics and structure in colloid and polymer mixtures

NASA Astrophysics Data System (ADS)

Mahynski, Nathan Alexander

In this dissertation I use computational tools to study the structure and thermodynamics of colloid-polymer mixtures. I show that fluid-fluid phase separation in mixtures of colloids and linear polymers cannot be universally reduced using polymer-based scaling principles since these assume the binodals exist in a single scaling regime, whereas accurate simulations clearly demonstrate otherwise. I show that rethinking these solutions in terms of multiple length scales is necessary to properly explain the thermodynamic stability and structure of these fluid phases, and produce phase diagrams in nearly quantitative agreement with experimental results. I then extend this work to encompass more geometrically complex "star" polymers revealing how the phase behavior for many of these binary mixtures may be mapped onto that of mixtures containing only linear polymers. I further consider the depletion-driven crystallization of athermal colloidal hard spheres induced by polymers. I demonstrate how the partitioning of a finite amount of polymer into the colloidal crystal phase implies that the polymer's architecture can be tailored to interact with the internal void structure of different crystal polymorphs uniquely, thus providing a direct route to thermodynamically stabilizing one arbitrarily chosen structure over another, e.g., the hexagonal close-packed crystal over the face-centered cubic. I then begin to generalize this result by considering the consequences of thermal interactions and complex polymer architectures. These principles lay the groundwork for intelligently engineering co-solute additives in crystallizing colloidal suspensions that can be used to thermodynamically isolate single crystal morphologies. Finally, I examine the competition between self-assembly and phase separation in polymer-grafted nanoparticle systems by comparing and contrasting the validity of two different models for grafted nanoparticles: "nanoparticle amphiphiles" versus "patchy particles." The latter suggests these systems have some utility in forming novel "equilibrium gel" phases, however, I find that considering grafted nanoparticles as amphiphiles provides a qualitatively accurate description of their thermodynamics revealing either first-order phase separation into two isotropic phases or continuous self-assembly. I find no signs of empty liquid formation, suggesting that these nanoparticles do not provide a route to such phases.

HPLC determination of guaifenesin with selected medications on underivatized silica with an aqueous-organic mobile phase.

PubMed

Wilcox, M L; Stewart, J T

2000-10-01

A high performance liquid chromatography procedure has been developed for the simultaneous determination of guaifenesin pseudoephedrine-dextromethorphan and guaifenesin-pseudoephedrine in commercially available capsule dosage forms and guaifenesin-codeine in a commercial cough syrup dosage form. The separation and quantitation are achieved on a 25-cm underivatized silica column using a mobile phase of 60:40%) v/v 6.25 mM phosphate buffer, pH 3.0 - acetonitrile at a flow rate of 1 ml min(-1) with detection of all analytes at 216 nm. The separation is achieved within 10 min for each drug mixture. The method showed linearity for the guaifenesin-pseudoephedrine-dextromethorphan mixture in the 50-200, 7.5-30 and 2.5-10, microg ml(-1) ranges, respectively. The intra- and inter-day RSDs ranged from 0.23 to 4.20%, 0.18 to 2.85%, and 0.13 to 5.04% for guaifenesin, pseudoephedrine, and dextromethorphan, respectively. The guaifenesin pseudoephedrine mixture yielded linear ranges of 25-100 and 3.75-15 microg ml(-1) and intra- and inter-day RSDs ranged from 0.65 to 4.18% and 0.23 to 3.00% for guaifenesin and pseudoephedrine, respectively. The method showed linearity for the guaifenesin-codeine mixture in the 25-100 and 2.5-10 microg ml(-1) ranges and RSDs ranged from 0.37 to 4.25% and 0.14 to 2.08% for guaifenesin and codeine, respectively.

Hyper-Spectral Image Analysis With Partially Latent Regression and Spatial Markov Dependencies

NASA Astrophysics Data System (ADS)

Deleforge, Antoine; Forbes, Florence; Ba, Sileye; Horaud, Radu

2015-09-01

Hyper-spectral data can be analyzed to recover physical properties at large planetary scales. This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between physical parameters and spectra has been established in a data-driven fashion, the learned relationship can be used to estimate physical parameters for new hyper-spectral observations. Within this framework, we propose a spatially-constrained and partially-latent regression method which maps high-dimensional inputs (hyper-spectral images) onto low-dimensional responses (physical parameters such as the local chemical composition of the soil). The proposed regression model comprises two key features. Firstly, it combines a Gaussian mixture of locally-linear mappings (GLLiM) with a partially-latent response model. While the former makes high-dimensional regression tractable, the latter enables to deal with physical parameters that cannot be observed or, more generally, with data contaminated by experimental artifacts that cannot be explained with noise models. Secondly, spatial constraints are introduced in the model through a Markov random field (MRF) prior which provides a spatial structure to the Gaussian-mixture hidden variables. Experiments conducted on a database composed of remotely sensed observations collected from the Mars planet by the Mars Express orbiter demonstrate the effectiveness of the proposed model.

A Gaussian Mixture Model Representation of Endmember Variability in Hyperspectral Unmixing

NASA Astrophysics Data System (ADS)

Zhou, Yuan; Rangarajan, Anand; Gader, Paul D.

2018-05-01

Hyperspectral unmixing while considering endmember variability is usually performed by the normal compositional model (NCM), where the endmembers for each pixel are assumed to be sampled from unimodal Gaussian distributions. However, in real applications, the distribution of a material is often not Gaussian. In this paper, we use Gaussian mixture models (GMM) to represent the endmember variability. We show, given the GMM starting premise, that the distribution of the mixed pixel (under the linear mixing model) is also a GMM (and this is shown from two perspectives). The first perspective originates from the random variable transformation and gives a conditional density function of the pixels given the abundances and GMM parameters. With proper smoothness and sparsity prior constraints on the abundances, the conditional density function leads to a standard maximum a posteriori (MAP) problem which can be solved using generalized expectation maximization. The second perspective originates from marginalizing over the endmembers in the GMM, which provides us with a foundation to solve for the endmembers at each pixel. Hence, our model can not only estimate the abundances and distribution parameters, but also the distinct endmember set for each pixel. We tested the proposed GMM on several synthetic and real datasets, and showed its potential by comparing it to current popular methods.

Sorption of ionic and nonionic organic solutes onto giant Miscanthus-derived biochar from methanol-water mixtures.

PubMed

Kim, Juhee; Hyun, Seunghun

2018-02-15

The sorption of naphthalene (NAP) and 1-naphthoic acid (1-NAPA) onto giant Miscanthus-derived biochar was investigated in methanol volume fractions (f c ) of 0-0.6 as a function of ionic composition (5mM CaCl 2 and 10mM KCl) and liquid pH (2 and 7). The sorption onto biochar was nonlinear with 0.42≤N≤0.95; thus, a concentration-specific sorption constant (K m ) was compared. The K m log linearly decreased with increasing f c , except for 1-NAPA from a CaCl 2 mixture at pH7. Isotherm data was fitted with a cosolvency sorption model through which the slope (ασ) of the inverse log linear K m -f c plot and empirical constant (α) were obtained. NAP sorption was well described by the cosolvency model with the α value being 0.41-0.53, indicating a methanol-biochar interaction favoring more sorption than the cosolvency based prediction. In particular, the slope (ασ) of 1-NAPA was lower than that of NAP, indicating less reduction of 1-NAPA sorption (i.e., lower α value) by methanol. In comparison with other sorbents, the α value was approximately intermediate between a humic substance and kaolinite clay. An analysis of FT-IR spectra suggested the transformation of O-containing functional groups by methanol, which will subsequently boost the π-π interaction between an organic solute and biochar. Moreover, Ca 2+ -induced sorption between anionic 1-NAPA and a negatively charged biochar surface was also fortified in the methanol mixture. The results revealed unexplored cosolvent effects on organic solute sorption onto biochar and identified the hydrophobic and hydrophilic sorption moieties of biochar as affected by the cosolvent. Copyright © 2017 Elsevier B.V. All rights reserved.

A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation

NASA Astrophysics Data System (ADS)

Li, Zheng; Jiang, Yi-han; Duan, Lian; Zhu, Chao-zhe

2017-08-01

Objective. Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC). Approach. GMMAC can simultaneously classify and track activation pattern changes without the need for ground-truth labels. This adaptive classifier uses computationally efficient variational Bayesian inference to label new data points and update mixture model parameters, using the previous model parameters as priors. We test GMMAC in simulations in which neural activation patterns change over time and compare to static decoders and unsupervised adaptive linear discriminant analysis classifiers. Main results. Our simulation experiments show GMMAC can accurately decode under time-varying activation patterns: shifts of activation region, expansions of activation region, and combined contractions and shifts of activation region. Furthermore, the experiments show the proposed method can track the changing shape of the activation region. Compared to prior work, GMMAC performed significantly better than the other unsupervised adaptive classifiers on a difficult activation pattern change simulation: 99% versus  <54% in two-choice classification accuracy. Significance. We believe GMMAC will be useful for clinical fNIRS-based brain-computer interfaces, including neurofeedback training systems, where operation over long time spans is required.

Headspace quantification of pure and aqueous solutions of binary mixtures of key volatile organic compounds in Swiss cheeses using selected ion flow tube mass spectrometry.

PubMed

Castada, Hardy Z; Wick, Cheryl; Harper, W James; Barringer, Sheryl

2015-01-15

Twelve volatile organic compounds (VOCs) have recently been identified as key compounds in Swiss cheese with split defects. It is important to know how these VOCs interact in binary mixtures and if their behavior changes with concentration in binary mixtures. Selected ion flow tube mass spectrometry (SIFT-MS) was used for the headspace analysis of VOCs commonly found in Swiss cheeses. Headspace (H/S) sampling and quantification checks using SIFT-MS and further linear regression analyses were carried out on twelve selected aqueous solutions of VOCs. Five binary mixtures of standard solutions of VOCs were also prepared and the H/S profile of each mixture was analyzed. A very good fit of linearity for the twelve VOCs (95% confidence level) confirms direct proportionality between the H/S and the aqueous concentration of the standard solutions. Henry's Law coefficients were calculated with a high degree of confidence. SIFT-MS analysis of five binary mixtures showed that the more polar compounds reduced the H/S concentration of the less polar compounds, while the addition of a less polar compound increased the H/S concentration of the more polar compound. In the binary experiment, it was shown that the behavior of a compound in the headspace can be significantly affected by the presence of another compound. Thus, the matrix effect plays a significant role in the behavior of molecules in a mixed solution. Copyright © 2014 John Wiley & Sons, Ltd.

The Soret Effect in Liquid Mixtures - A Review

NASA Astrophysics Data System (ADS)

Köhler, Werner; Morozov, Konstantin I.

2016-07-01

The Soret effect describes diffusive motion that originates from a temperature gradient. It is observed in mixtures of gases, liquids and even solids. Although there is a formal phenomenological description based on linear nonequilibrium thermodynamics, the Soret effect is a multicause phenomenon and there is no univocal microscopic picture. After a brief historical overview and an outline of the fundamental thermodynamic concepts, this review focuses on thermodiffusion in binary and ternary liquid mixtures. The most important experimental techniques used nowadays are introduced. Then, a modern development in studying thermal diffusion, the discovery of both integral and specific additivity laws, is discussed. The former relate to the general behavior of the substances in a temperature field according to their thermophobicities, which prove to be pure component properties. The thermophobicities allow for a convenient classification of the phenomenon, a simple interpretation and a proper estimation and prediction of the thermodiffusion parameters. The specific laws relate to the additivity of the particular contributions. Among the latter, we discuss the isotopic Soret effect and the so-called chemical contribution. From the theoretical side, there are kinetic and thermodynamic theories, and the nature of the driving forces of thermodiffusion can be either of volume or surface type. Besides analytical models, computer simulations become increasingly important. Polymer solutions are special as they represent highly asymmetric molecular systems with a molar mass-independent thermophoretic mobility. Its origin is still under debate, and draining and non-draining models are presently discussed. Finally, some discussion is devoted to ternary mixtures, which only recently have been investigated in more detail.

Kinetics of hydrogen peroxide decomposition by catalase: hydroxylic solvent effects.

PubMed

Raducan, Adina; Cantemir, Anca Ruxandra; Puiu, Mihaela; Oancea, Dumitru

2012-11-01

The effect of water-alcohol (methanol, ethanol, propan-1-ol, propan-2-ol, ethane-1,2-diol and propane-1,2,3-triol) binary mixtures on the kinetics of hydrogen peroxide decomposition in the presence of bovine liver catalase is investigated. In all solvents, the activity of catalase is smaller than in water. The results are discussed on the basis of a simple kinetic model. The kinetic constants for product formation through enzyme-substrate complex decomposition and for inactivation of catalase are estimated. The organic solvents are characterized by several physical properties: dielectric constant (D), hydrophobicity (log P), concentration of hydroxyl groups ([OH]), polarizability (α), Kamlet-Taft parameter (β) and Kosower parameter (Z). The relationships between the initial rate, kinetic constants and medium properties are analyzed by linear and multiple linear regression.

Description of new dry granular materials of variable cohesion and friction coefficient: Implications for laboratory modeling of the brittle crust

NASA Astrophysics Data System (ADS)

Abdelmalak, M. M.; Bulois, C.; Mourgues, R.; Galland, O.; Legland, J.-B.; Gruber, C.

2016-08-01

Cohesion and friction coefficient are fundamental parameters for scaling brittle deformation in laboratory models of geological processes. However, they are commonly not experimental variable, whereas (1) rocks range from cohesion-less to strongly cohesive and from low friction to high friction and (2) strata exhibit substantial cohesion and friction contrasts. This brittle paradox implies that the effects of brittle properties on processes involving brittle deformation cannot be tested in laboratory models. Solving this paradox requires the use of dry granular materials of tunable and controllable brittle properties. In this paper, we describe dry mixtures of fine-grained cohesive, high friction silica powder (SP) and low-cohesion, low friction glass microspheres (GM) that fulfill this requirement. We systematically estimated the cohesions and friction coefficients of mixtures of variable proportions using two independent methods: (1) a classic Hubbert-type shear box to determine the extrapolated cohesion (C) and friction coefficient (μ), and (2) direct measurements of the tensile strength (T0) and the height (H) of open fractures to calculate the true cohesion (C0). The measured values of cohesion increase from 100 Pa for pure GM to 600 Pa for pure SP, with a sub-linear trend of the cohesion with the mixture GM content. The two independent cohesion measurement methods, from shear tests and tension/extensional tests, yield very similar results of extrapolated cohesion (C) and show that both are robust and can be used independently. The measured values of friction coefficients increase from 0.5 for pure GM to 1.05 for pure SP. The use of these granular material mixtures now allows testing (1) the effects of cohesion and friction coefficient in homogeneous laboratory models and (2) testing the effect of brittle layering on brittle deformation, as demonstrated by preliminary experiments. Therefore, the brittle properties become, at last, experimental variables.

Spatial resolution of the electrical conductance of ionic fluids using a Green-Kubo method.

PubMed

Jones, R E; Ward, D K; Templeton, J A

2014-11-14

We present a Green-Kubo method to spatially resolve transport coefficients in compositionally heterogeneous mixtures. We develop the underlying theory based on well-known results from mixture theory, Irving-Kirkwood field estimation, and linear response theory. Then, using standard molecular dynamics techniques, we apply the methodology to representative systems. With a homogeneous salt water system, where the expectation of the distribution of conductivity is clear, we demonstrate the sensitivities of the method to system size, and other physical and algorithmic parameters. Then we present a simple model of an electrochemical double layer where we explore the resolution limit of the method. In this system, we observe significant anisotropy in the wall-normal vs. transverse ionic conductances, as well as near wall effects. Finally, we discuss extensions and applications to more realistic systems such as batteries where detailed understanding of the transport properties in the vicinity of the electrodes is of technological importance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, J.; Walters, D. M.; Zhou, D.

Vapor-deposited glasses can be anisotropic and molecular orientation is important for organic electronics applications. In organic light emitting diodes (OLEDs), for example, the orientation of dye molecules in two-component emitting layers significantly influences emission efficiency. Here we investigate how substrate temperature during vapor deposition influences the orientation of dye molecules in a model two-component system. We determine the average orientation of a linear blue light emitter 1,4-di-[4-( N,N-diphenyl)amino]styrylbenzene (DSA-Ph) in mixtures with aluminum-tris(8-hydroxyquinoline) (Alq 3) by spectroscopic ellipsometry and IR dichroism. We find that molecular orientation is controlled by the ratio of the substrate temperature during deposition and the glassmore » transition temperature of the mixture. Furthermore, these findings extend recent results for single component vapor-deposited glasses and suggest that, during vapor deposition, surface mobility allows partial equilibration towards orientations preferred at the free surface of the equilibrium liquid.« less

Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors.

PubMed

Lee, David; Park, Sang-Hoon; Lee, Sang-Goog

2017-10-07

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG) and principal component analyses are used to reduce the dimensionality of the feature vectors and linearly combine them. Subsequently, the GMM universal background model is trained by the expectation-maximization (EM) algorithm to purify the training data and reduce its size. Finally, a purified and reduced GMM-supervector is used to train the support vector machine classifier. The performance of the proposed method was evaluated for three different motor imagery datasets in terms of accuracy, kappa, mutual information, and computation time, and compared with the state-of-the-art algorithms. The results from the study indicate that the proposed method achieves high accuracy with a small amount of training data compared with the state-of-the-art algorithms in motor imagery EEG classification.

Solubility of polyethers in hydrocarbons at low temperatures. A model for potential genetic backbones on warm titans.

PubMed

McLendon, Christopher; Opalko, F Jeffrey; Illangkoon, Heshan I; Benner, Steven A

2015-03-01

Ethers are proposed here as the repeating backbone linking units in linear genetic biopolymers that might support Darwinian evolution in hydrocarbon oceans. Hydrocarbon oceans are found in our own solar system as methane mixtures on Titan. They may be found as mixtures of higher alkanes (propane, for example) on warmer hydrocarbon-rich planets in exosolar systems ("warm Titans"). We report studies on the solubility of several short polyethers in propane over its liquid range (from 85 to 231 K, or -188 °C to -42 °C). These show that polyethers are reasonably soluble in propane at temperatures down to ca. 200 K. However, their solubilities drop dramatically at still lower temperatures and become immeasurably low below 170 K, still well above the ∼ 95 K in Titan's oceans. Assuming that a liquid phase is essential for any living system, and genetic biopolymers must dissolve in that biosolvent to support Darwinism, these data suggest that we must look elsewhere to identify linear biopolymers that might support genetics in Titan's surface oceans. However, genetic molecules with polyether backbones may be suitable to support life in hydrocarbon oceans on warm Titans, where abundant organics and environments lacking corrosive water might make it easier for life to originate.

Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models.

PubMed

Pütter, Carolin; Pechlivanis, Sonali; Nöthen, Markus M; Jöckel, Karl-Heinz; Wichmann, Heinz-Erich; Scherag, André

2011-01-01

Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright © 2011 S. Karger AG, Basel.

Slug Flow Analysis in Vertical Large Diameter Pipes

NASA Astrophysics Data System (ADS)

Roullier, David

The existence of slug flow in vertical co-current two-phase flow is studied experimentally and theoretically. The existence of slug flow in vertical direction implies the presence of Taylor bubbles separated by hydraulically sealed liquid slugs. Previous experimental studies such as Ombere-Ayari and Azzopardi (2007) showed the evidence of the non-existence of Taylor bubbles for extensive experimental conditions. Models developed to predict experimental behavior [Kocamustafaogullari et al. (1984), Jayanti and Hewitt. (1990) and Kjoolas et al. (2017)] suggest that Taylor bubbles may disappear at large diameters and high velocities. A 73-ft tall and 101.6-mm internal diameter test facility was used to conduct the experiments allowing holdup and pressure drop measurements at large L/D. Superficial liquid and gas velocities varied from 0.05-m/s to 0.2 m/s and 0.07 m/s to 7.5 m/s, respectively. Test section pressure varied from 38 psia to 84 psia. Gas compressibility effect was greatly reduced at 84 psia. The experimental program allowed to observe the flow patterns for flowing conditions near critical conditions predicted by previous models (air-water, 1016 mm ID, low mixture velocities). Flow patterns were observed in detail using wire-mesh sensor measurements. Slug-flow was observed for a narrow range of experimental conditions at low velocities. Churn-slug and churn-annular flows were observed for most of the experimental data-points. Cap-bubble flow was observed instead of bubbly flow at low vSg. Wire-mesh measurements showed that the liquid has a tendency to remain near to the walls. The standard deviation of radial holdup profile correlates to the flow pattern observed. For churn-slug flow, the profile is convex with a single maximum near the pipe center while it exhibits a concave shape with two symmetric maxima close to the wall for churn-annular flow. The translational velocity was measured by two consecutive wire-mesh sensor crosscorrelation. The results show linear trends at low mixture velocities and non-linear behaviors at high mixture velocities. The translational velocity trends seem to be related to the flow-pattern observed, namely to the ability of the gas to flow through the liquid structures. A simplified Taylor bubble stability model is proposed. The model allows to estimate under which conditions Taylor bubbles disappear, properly accounting for the diameter effect and velocity effect observed experimentally. In addition, annular flow distribution coefficient relating true holdup to centerline holdup in vertical flow is proposed. The proposed coefficient defines the tendency of the liquid to remain near the walls. This coefficient increases linearly with the void fraction.

Alteration Mineralogy of Adirondack-class Rocks in Gusev Crater, Mars

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; Ruff, S. W.

2009-12-01

The rock Adirondack is the type example of a class of basaltic rocks analyzed by the Mars Exploration Rover Spirit in Gusev crater. Thermal infrared spectra of Adirondack-class rocks acquired by the Mini-TES instrument are distinguishable from spectra of other rock classes by the presence of an emissivity peak at 430 cm-1 and a minimum near 510 cm-1, which are characteristic of olivine. This is the primary spectral class on the plains of Gusev, but spectra of rocks exhibiting similar low wavenumber spectral character have been acquired along the rover traverse in the Columbia Hills, and we have confirmed that these also are Adirondack-class. Linear mixture modeling of their infrared spectra (enabled by applying a correction for dust on the Mini-TES optics) suggests that they are mafic with sulfate minerals present as alteration phases (up to 25%) in the majority of these rocks, broadly consistent with APXS-measured chemistry. The RAT-brushed surface of an unusual plains rock referred to as Mazatzal exhibits a spectral shape and modeled mineralogy consistent with the absence of olivine and the presence of amorphous phases low in silica, and is a coating unlike any other observed on Mars. We have also used a previously-demonstrated factor analysis and target transformation (FATT) technique with Adirondack-class rock spectra to retrieve the spectral shapes of independently-varying components within the data set. Using this approach, we have identified four shapes attributable to two distinct surface components, fine particulate surface dust, and a second dust component similar to downwelling sky radiance and/or dust on the Mini-TES optics. The two surface shapes do not resemble those of the two canonical surface types measured from orbit. One of the surface shapes is very similar to that of the lherzolitic Shergottite ALH A77005. Preliminary linear mixture analysis of this shape shows that it is dominated by olivine (~57%, ~Fo45) and pyroxene (~28%), with minor amounts of oxides and basaltic glass (~15%). This ultramafic composition is similar to that derived from linear mixture modeling of the measured Mini-TES spectra, but differs in detail from the APXS-derived normative mineralogy and Mössbauer ol:px. These differences may be artifacts of the penetration depths and spot sizes of the measurements, or assumptions inherent in the conversions from chemistry and spectra to norms and abundances; work in progress is aimed at explaining these differences. The other shape is modeled with high-silica phases (29%), sulfates (~24%), olivine (~19%), pyroxene (~15%), and oxides (~12%), suggesting it represents a highly altered mineralogy. We linearly modeled the highest-quality measured spectra of Adirondack-class rocks using only the FATT-derived spectral shapes. Surface components are modeled by varying proportions of the two surface shapes, with all containing ≥40% of the ultramafic shape. These preliminary results suggest that Adirondack-class rocks are a single lithology exhibiting sulfate-bearing surface alteration that is variable from rock to rock. We are in the process of converting the mineralogies derived from measured and FATT-derived spectra into bulk oxides and will present quantitative comparisons with APXS data and qualitative comparisons with Mössbauer data.

Protein construct storage: Bayesian variable selection and prediction with mixtures.

PubMed

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

Viscosity and thermal conductivity of moderately dense gas mixtures.

NASA Technical Reports Server (NTRS)

Wakeham, W. A.; Kestin, J.; Mason, E. A.; Sandler, S. I.

1972-01-01

Derivation of a simple, semitheoretical expression for the initial density dependence of the viscosity and thermal conductivity of gaseous mixtures in terms of the appropriate properties of the pure components and of their interaction quantities. The derivation is based on Enskog's theory of dense gases and yields an equation in which the composition dependence of the linear factor in the density expansion is explicit. The interaction quantities are directly related to those of the mixture extrapolated to zero density and to a universal function valid for all gases. The reliability of the formulation is assessed with respect to the viscosity of several binary mixtures. It is found that the calculated viscosities of binary mixtures agree with the experimental data with a precision which is comparable to that of the most precise measurements.

Polynomial mixture method of solving ordinary differential equations

NASA Astrophysics Data System (ADS)

Shahrir, Mohammad Shazri; Nallasamy, Kumaresan; Ratnavelu, Kuru; Kamali, M. Z. M.

2017-11-01

In this paper, a numerical solution of fuzzy quadratic Riccati differential equation is estimated using a proposed new approach that provides mixture of polynomials where iteratively the right mixture will be generated. This mixture provide a generalized formalism of traditional Neural Networks (NN). Previous works have shown reliable results using Runge-Kutta 4th order (RK4). This can be achieved by solving the 1st Order Non-linear Differential Equation (ODE) that is found commonly in Riccati differential equation. Research has shown improved results relatively to the RK4 method. It can be said that Polynomial Mixture Method (PMM) shows promising results with the advantage of continuous estimation and improved accuracy that can be produced over Mabood et al, RK-4, Multi-Agent NN and Neuro Method (NM).

Modeling for CO poisoning of a fuel cell anode

NASA Technical Reports Server (NTRS)

Dhar, H. P.; Kush, A. K.; Patel, D. N.; Christner, L. G.

1986-01-01

Poisoning losses in a half-cell in the 110-190 C temperature range have been measured in 100 wt pct H3PO4 for various mixtures of H2, CO, and CO2 gases in order to investigate the polarization loss due to poisoning by CO of a porous fuel cell Pt anode. At a fixed current density, the poisoning loss was found to vary linearly with ln of the CO/H2 concentration ratio, although deviations from linearity were noted at lower temperatures and higher current densities for high CO/H2 concentration ratios. The surface coverages of CO were also found to vary linearly with ln of the CO/H2 concentration ratio. A general adsorption relationship is derived. Standard free energies for CO adsorption were found to vary from -14.5 to -12.1 kcal/mol in the 130-190 C temperature range. The standard entropy for CO adsorption was found to be -39 cal/mol per deg K.

Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.

PubMed

García-Gen, Santiago; Rodríguez, Jorge; Lema, Juan M

2014-12-01

Anaerobic co-digestion of multiple substrates has the potential to enhance biogas productivity by making use of the complementary characteristics of different substrates. A blending strategy based on a linear programming optimisation method is proposed aiming at maximising COD conversion into methane, but simultaneously maintaining a digestate and biogas quality. The method incorporates experimental and heuristic information to define the objective function and the linear restrictions. The active constraints are continuously adapted (by relaxing the restriction boundaries) such that further optimisations in terms of methane productivity can be achieved. The feasibility of the blends calculated with this methodology was previously tested and accurately predicted with an ADM1-based co-digestion model. This was validated in a continuously operated pilot plant, treating for several months different mixtures of glycerine, gelatine and pig manure at organic loading rates from 1.50 to 4.93 gCOD/Ld and hydraulic retention times between 32 and 40 days at mesophilic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

T-matrix modeling of linear depolarization by morphologically complex soot and soot-containing aerosols

NASA Astrophysics Data System (ADS)

Mishchenko, Michael I.; Liu, Li; Mackowski, Daniel W.

2013-07-01

We use state-of-the-art public-domain Fortran codes based on the T-matrix method to calculate orientation and ensemble averaged scattering matrix elements for a variety of morphologically complex black carbon (BC) and BC-containing aerosol particles, with a special emphasis on the linear depolarization ratio (LDR). We explain theoretically the quasi-Rayleigh LDR peak at side-scattering angles typical of low-density soot fractals and conclude that the measurement of this feature enables one to evaluate the compactness state of BC clusters and trace the evolution of low-density fluffy fractals into densely packed aggregates. We show that small backscattering LDRs measured with ground-based, airborne, and spaceborne lidars for fresh smoke generally agree with the values predicted theoretically for fluffy BC fractals and densely packed near-spheroidal BC aggregates. To reproduce higher lidar LDRs observed for aged smoke, one needs alternative particle models such as shape mixtures of BC spheroids or cylinders.

FT-IR and computer modeling study of hydrogen bonding in N-alkyl acrylamide-toluene binary mixtures

NASA Astrophysics Data System (ADS)

Rumyantsev, Misha; Kazantsev, Oleg A.; Kamorina, Sofia I.; Kamorin, Denis M.; Sivokhin, Alexey P.

2016-10-01

Degree of hydrogen bonding driven self-association of N-(n-butyl)acrylamide, N-(n-octyl)acrylamide, N-(sec-octyl)acrylamide and N-(tert-octyl)acrylamide in toluene was investigated using IR spectroscopy and computer modeling methods. Consistent results were demonstrated in the treatment of the Amide-I (νC=O), Amide-II (δN-H and νC-N) and Amide-A (νN-H) absorption bands in IR spectra. Thus, the content of non-bonded (free) amide groups decreases from 83-98% to 8-20% and the content of linear polyassociates increases to 80-90% with an increase in monomer concentration from 0.5 wt% to 50 wt%. The content of cyclic dimers was equal to the value between 5 and 10% regardless of the initial monomer concentration. Dependences of the association degree and the content of the linear polyassociates on the concentration were found to be similar for all of the studied amides.

Interactive graphical system for small-angle scattering analysis of polydisperse systems

NASA Astrophysics Data System (ADS)

Konarev, P. V.; Volkov, V. V.; Svergun, D. I.

2016-09-01

A program suite for one-dimensional small-angle scattering analysis of polydisperse systems and multiple data sets is presented. The main program, POLYSAS, has a menu-driven graphical user interface calling computational modules from ATSAS package to perform data treatment and analysis. The graphical menu interface allows one to process multiple (time, concentration or temperature-dependent) data sets and interactively change the parameters for the data modelling using sliders. The graphical representation of the data is done via the Winteracter-based program SASPLOT. The package is designed for the analysis of polydisperse systems and mixtures, and permits one to obtain size distributions and evaluate the volume fractions of the components using linear and non-linear fitting algorithms as well as model-independent singular value decomposition. The use of the POLYSAS package is illustrated by the recent examples of its application to study concentration-dependent oligomeric states of proteins and time kinetics of polymer micelles for anticancer drug delivery.

T-Matrix Modeling of Linear Depolarization by Morphologically Complex Soot and Soot-Containing Aerosols

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Liu, Li; Mackowski, Daniel W.

2013-01-01

We use state-of-the-art public-domain Fortran codes based on the T-matrix method to calculate orientation and ensemble averaged scattering matrix elements for a variety of morphologically complex black carbon (BC) and BC-containing aerosol particles, with a special emphasis on the linear depolarization ratio (LDR). We explain theoretically the quasi-Rayleigh LDR peak at side-scattering angles typical of low-density soot fractals and conclude that the measurement of this feature enables one to evaluate the compactness state of BC clusters and trace the evolution of low-density fluffy fractals into densely packed aggregates. We show that small backscattering LDRs measured with groundbased, airborne, and spaceborne lidars for fresh smoke generally agree with the values predicted theoretically for fluffy BC fractals and densely packed near-spheroidal BC aggregates. To reproduce higher lidar LDRs observed for aged smoke, one needs alternative particle models such as shape mixtures of BC spheroids or cylinders.

Thin layer chromatography-densitometric determination of some non-sedating antihistamines in combination with pseudoephedrine or acetaminophen in synthetic mixtures and in pharmaceutical formulations.

PubMed

El-Kommos, Michael E; El-Gizawy, Samia M; Atia, Noha N; Hosny, Noha M

2014-03-01

The combination of certain non-sedating antihistamines (NSA) such as fexofenadine (FXD), ketotifen (KET) and loratadine (LOR) with pseudoephedrine (PSE) or acetaminophen (ACE) is widely used in the treatment of allergic rhinitis, conjunctivitis and chronic urticaria. A rapid, simple, selective and precise densitometric method was developed and validated for simultaneous estimation of six synthetic binary mixtures and their pharmaceutical dosage forms. The method employed thin layer chromatography aluminum plates precoated with silica gel G 60 F254 as the stationary phase. The mobile phases chosen for development gave compact bands for the mixtures FXD-PSE (I), KET-PSE (II), LOR-PSE (III), FXD-ACE (IV), KET-ACE (V) and LOR-ACE (VI) [Retardation factor (Rf ) values were (0.20, 0.32), (0.69, 0.34), (0.79, 0.13), (0.36, 0.70), (0.51, 0.30) and (0.76, 0.26), respectively]. Spectrodensitometric scanning integration was performed at 217, 218, 218, 233, 272 and 251 nm for the mixtures I-VI, respectively. The linear regression data for the calibration plots showed an excellent linear relationship. The method was validated for precision, accuracy, robustness and recovery. Limits of detection and quantitation were calculated. Statistical analysis proved that the method is reproducible and selective for the simultaneous estimation of these binary mixtures. Copyright © 2013 John Wiley & Sons, Ltd.

Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals

NASA Astrophysics Data System (ADS)

Sameni, Reza; Clifford, Gari D.; Jutten, Christian; Shamsollahi, Mohammad B.

2007-12-01

A three-dimensional dynamic model of the electrical activity of the heart is presented. The model is based on the single dipole model of the heart and is later related to the body surface potentials through a linear model which accounts for the temporal movements and rotations of the cardiac dipole, together with a realistic ECG noise model. The proposed model is also generalized to maternal and fetal ECG mixtures recorded from the abdomen of pregnant women in single and multiple pregnancies. The applicability of the model for the evaluation of signal processing algorithms is illustrated using independent component analysis. Considering the difficulties and limitations of recording long-term ECG data, especially from pregnant women, the model described in this paper may serve as an effective means of simulation and analysis of a wide range of ECGs, including adults and fetuses.

Quantitative analysis of the mixtures of illicit drugs using terahertz time-domain spectroscopy

NASA Astrophysics Data System (ADS)

Jiang, Dejun; Zhao, Shusen; Shen, Jingling

2008-03-01

A method was proposed to quantitatively inspect the mixtures of illicit drugs with terahertz time-domain spectroscopy technique. The mass percentages of all components in a mixture can be obtained by linear regression analysis, on the assumption that all components in the mixture and their absorption features be known. For illicit drugs were scarce and expensive, firstly we used common chemicals, Benzophenone, Anthraquinone, Pyridoxine hydrochloride and L-Ascorbic acid in the experiment. Then illicit drugs and a common adulterant, methamphetamine and flour, were selected for our experiment. Experimental results were in significant agreement with actual content, which suggested that it could be an effective method for quantitative identification of illicit drugs.

Soil organic matter content: a non-liner control on microbial respiration in soils

NASA Astrophysics Data System (ADS)

Schnecker, Jörg; Grandy, Stuart

2016-04-01

It is widely assumed that microbial activity and respiration rates respond linearly to substrate concentrations, irrespective of substrate chemical characteristics, but this assumption remains largely untested. We know that microbial decomposition of soil organic matter (SOM) and the amount of CO2 respired from soil depends on substrate availability. While soils with high SOM concentrations will have higher respiration rates than soils with low SOM concentrations, the specific relationship between substrate quantity and CO2 respired and its underlying mechanisms has robust theoretical, modeling, and management implications. In a lab incubation experiment, we amended a mixture of agricultural soil and sand with increasing amounts of one of three plant residues differing in their C/N ratio (clover C/N 14; rye C/N 23 and wheat straw C/N 110). Keeping the soil/sand mixture at a constant ratio, we obtained 9 levels of organic carbon (OC) content ranging from 0.25% to 5.7%. The sand-soil-residue mixtures were then incubated at constant temperature and water contents for a total of 63 days. Our results show that across substrates CO2 production increased with increasing OC content following a sigmoidal curve function instead of the expected linear one. A breakpoint analysis for the respiration curve of rye revealed two significant break points at 1.3 and 3.8 % OC. The three individual linear relations might be shaped by spatial separation of substrate and microbes and the interaction of the microbes themselves. In the first "survival" phase up to 1.3 % OC, more substrate leads to the survival of more microbes. However, microbial growth does not result in the discovery of new resources. In the "expansion" phase (1.3 % OC to 3.8 % OC), microbial growth is successful and microbes can exploit new resources. Finally, in the "competition" phase microbes start to compete for space and resources, which leads to a decrease in decomposition and respiration. While the results for clover were similar to rye, different amounts of straw resulted in an almost linear relationship between OC content and respiratory loss. The low N content of straw may explain this, limiting microbial growth and the exploration for new resources. Microbes in the straw treatment likely remained in the "survival" phase. Our findings of a non-linear decrease of CO2 production with decreasing OC content indicate that spatial separation as an inherent property of SOM content is an important control on decomposition of soil organic matter. Knowledge of this controlling effect might be beneficial in many ways. For example, even small additions of plant residues to agricultural systems might strongly enhance N availability to microbes and plants. Further, the spatial distribution of new C inputs may regulate its potential to be decomposed or stabilized. Finally, our results will help to improve model parameterization and predictions about microbial limitations and potential changes in decomposition under a future climate.

Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions.

PubMed

Drouard, Vincent; Horaud, Radu; Deleforge, Antoine; Ba, Sileye; Evangelidis, Georgios

2017-03-01

Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth. Head-pose estimation is challenging, because it must cope with changing illumination conditions, variabilities in face orientation and in appearance, partial occlusions of facial landmarks, as well as bounding-box-to-face alignment errors. We propose to use a mixture of linear regressions with partially-latent output. This regression method learns to map high-dimensional feature vectors (extracted from bounding boxes of faces) onto the joint space of head-pose angles and bounding-box shifts, such that they are robustly predicted in the presence of unobservable phenomena. We describe in detail the mapping method that combines the merits of unsupervised manifold learning techniques and of mixtures of regressions. We validate our method with three publicly available data sets and we thoroughly benchmark four variants of the proposed algorithm with several state-of-the-art head-pose estimation methods.

The effect of binary mixtures of zinc, copper, cadmium, and nickel on the growth of the freshwater diatom Navicula pelliculosa and comparison with mixture toxicity model predictions.

PubMed

Nagai, Takashi; De Schamphelaere, Karel A C

2016-11-01

The authors investigated the effect of binary mixtures of zinc (Zn), copper (Cu), cadmium (Cd), and nickel (Ni) on the growth of a freshwater diatom, Navicula pelliculosa. A 7 × 7 full factorial experimental design (49 combinations in total) was used to test each binary metal mixture. A 3-d fluorescence microplate toxicity assay was used to test each combination. Mixture effects were predicted by concentration addition and independent action models based on a single-metal concentration-response relationship between the relative growth rate and the calculated free metal ion activity. Although the concentration addition model predicted the observed mixture toxicity significantly better than the independent action model for the Zn-Cu mixture, the independent action model predicted the observed mixture toxicity significantly better than the concentration addition model for the Cd-Zn, Cd-Ni, and Cd-Cu mixtures. For the Zn-Ni and Cu-Ni mixtures, it was unclear which of the 2 models was better. Statistical analysis concerning antagonistic/synergistic interactions showed that the concentration addition model is generally conservative (with the Zn-Ni mixture being the sole exception), indicating that the concentration addition model would be useful as a method for a conservative first-tier screening-level risk analysis of metal mixtures. Environ Toxicol Chem 2016;35:2765-2773. © 2016 SETAC. © 2016 SETAC.

Mixture Rasch Models with Joint Maximum Likelihood Estimation

ERIC Educational Resources Information Center

Willse, John T.

2011-01-01

This research provides a demonstration of the utility of mixture Rasch models. Specifically, a model capable of estimating a mixture partial credit model using joint maximum likelihood is presented. Like the partial credit model, the mixture partial credit model has the beneficial feature of being appropriate for analysis of assessment data…

High-performance liquid chromatography/high-resolution multiple stage tandem mass spectrometry using negative-ion-mode hydroxide-doped electrospray ionization for the characterization of lignin degradation products.

PubMed

Owen, Benjamin C; Haupert, Laura J; Jarrell, Tiffany M; Marcum, Christopher L; Parsell, Trenton H; Abu-Omar, Mahdi M; Bozell, Joseph J; Black, Stuart K; Kenttämaa, Hilkka I

2012-07-17

In the search for a replacement for fossil fuel and the valuable chemicals currently obtained from crude oil, lignocellulosic biomass has become a promising candidate as an alternative biorenewable source for crude oil. Hence, many research efforts focus on the extraction, degradation, and catalytic transformation of lignin, hemicellulose, and cellulose. Unfortunately, these processes result in the production of very complex mixtures. Further, while methods have been developed for the analysis of mixtures of oligosaccharides, this is not true for the complex mixtures generated upon degradation of lignin. For example, high-performance liquid chromatography/multiple stage tandem mass spectrometry (HPLC/MS(n)), a tool proven to be invaluable in the analysis of complex mixtures derived from many other biopolymers, such as proteins and DNA, has not been implemented for lignin degradation products. In this study, we have developed an HPLC separation method for lignin degradation products that is amenable to negative-ion-mode electrospray ionization (ESI doped with NaOH), the best method identified thus far for ionization of lignin-related model compounds without fragmentation. The separated and ionized compounds are then analyzed by MS(3) experiments to obtain detailed structural information while simultaneously performing high-resolution measurements to determine their elemental compositions in the two parts of a commercial linear quadrupole ion trap/Fourier-transform ion cyclotron resonance mass spectrometer. A lignin degradation product mixture was analyzed using this method, and molecular structures were proposed for some components. This methodology significantly improves the ability to analyze complex product mixtures that result from degraded lignin.

Selective removal of polyethylene or polypropylene from their blends based on difference in their adsorption behaviour.

PubMed

Macko, Tibor; Pasch, Harald; Brüll, Robert

2006-05-19

The adsorption of polyethylene and polypropylene on zeolites depends on the nature of zeolite, the solvent as well as the molar mass of the polymer sample. For example, linear polyethylene is strongly retained on zeolite SH-300 from decalin, while isotactic, syndiotactic or atactic polypropylene is fully eluted in this system. On the other hand, polypropylene is retained on zeolite CBV-780 from diphenylether, while linear polyethylene is eluted. These differences in the elution behaviour have been utilised for selective removal of either linear polyethylene or polypropylene from blends of both polymers. The desorption of the retained polymer is difficult, or at times impossible. However, the selected adsorption systems have complimentary character, i.e. either one or second component is eluted or fully retained. Thus these sorbent/solvent systems, identified herein, are the first isocratic chromatographic systems, which enable selectively to remove polyethylene or polypropylene from their mixture. Moreover, decalin/SH-300 enables the removal of both linear and branched polyethylene from mixtures with random ethylene/propylene copolymers (polyethylene fully retained, ethylene/propylene copolymers eluted).

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry

PubMed Central

Polanski, Andrzej; Marczyk, Michal; Pietrowska, Monika; Widlak, Piotr; Polanska, Joanna

2015-01-01

Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses. In this paper we present an efficient algorithm for Gaussian mixture modeling of proteomic mass spectra of different types (e.g., MALDI-ToF profiling, MALDI-IMS). The main idea is automated partitioning of protein mass spectral signal into fragments. The obtained fragments are separately decomposed into Gaussian mixture models. The parameters of the mixture models of fragments are then aggregated to form the mixture model of the whole spectrum. We compare the elaborated algorithm to existing algorithms for peak detection and we demonstrate improvements of peak detection efficiency obtained by using Gaussian mixture modeling. We also show applications of the elaborated algorithm to real proteomic datasets of low and high resolution. PMID:26230717

Stochastic and Geometric Reasoning for Indoor Building Models with Electric Installations - Bridging the Gap Between GIS and Bim

NASA Astrophysics Data System (ADS)

Dehbi, Y.; Haunert, J.-H.; Plümer, L.

2017-10-01

3D city and building models according to CityGML encode the geometry, represent the structure and model semantically relevant building parts such as doors, windows and balconies. Building information models support the building design, construction and the facility management. In contrast to CityGML, they include also objects which cannot be observed from the outside. The three dimensional indoor models characterize a missing link between both worlds. Their derivation, however, is expensive. The semantic automatic interpretation of 3D point clouds of indoor environments is a methodically demanding task. The data acquisition is costly and difficult. The laser scanners and image-based methods require the access to every room. Based on an approach which does not require an additional geometry acquisition of building indoors, we propose an attempt for filling the gaps between 3D building models and building information models. Based on sparse observations such as the building footprint and room areas, 3D indoor models are generated using combinatorial and stochastic reasoning. The derived models are expanded by a-priori not observable structures such as electric installation. Gaussian mixtures, linear and bi-linear constraints are used to represent the background knowledge and structural regularities. The derivation of hypothesised models is performed by stochastic reasoning using graphical models, Gauss-Markov models and MAP-estimators.

Simulating of the measurement-device independent quantum key distribution with phase randomized general sources

PubMed Central

Wang, Qin; Wang, Xiang-Bin

2014-01-01

We present a model on the simulation of the measurement-device independent quantum key distribution (MDI-QKD) with phase randomized general sources. It can be used to predict experimental observations of a MDI-QKD with linear channel loss, simulating corresponding values for the gains, the error rates in different basis, and also the final key rates. Our model can be applicable to the MDI-QKDs with arbitrary probabilistic mixture of different photon states or using any coding schemes. Therefore, it is useful in characterizing and evaluating the performance of the MDI-QKD protocol, making it a valuable tool in studying the quantum key distributions. PMID:24728000

Sonochemically synthesized iron-doped zinc oxide nanoparticles: Influence of precursor composition on characteristics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy, Anirban; Maitra, Saikat; Ghosh, Sobhan

Highlights: • Sonochemical synthesis of iron-doped zinc oxide nanoparticles. • Green synthesis without alkali at room temperature. • Characterization by UV–vis spectroscopy, FESEM, XRD and EDX. • Influence of precursor composition on characteristics. • Composition and characteristics are correlated. - Abstract: Iron-doped zinc oxide nanoparticles have been synthesized sonochemically from aqueous acetyl acetonate precursors of different proportions. Synthesized nanoparticles were characterized with UV–vis spectroscopy, X-ray diffraction and microscopy. Influences of precursor mixture on the characteristics have been examined and modeled. Linear correlations have been proposed between dopant dosing, extent of doping and band gap energy. Experimental data corroborated with themore » proposed models.« less

Development of a passive, in situ, integrative sampler for hydrophilic organic contaminants in aquatic environments

USGS Publications Warehouse

Alvarez, D.A.; Petty, J.D.; Huckins, J.N.; Jones-Lepp, T. L.; Getting, D.T.; Goddard, J.P.; Manahan, S.E.

2004-01-01

Increasingly it is being realized that a holistic hazard assessment of complex environmental contaminant mixtures requires data on the concentrations of hydrophilic organic contaminants including new generation pesticides, pharmaceuticals, personal care products, and many chemicals associated with household, industrial, and agricultural wastes. To address this issue, we developed a passive in situ sampling device (the polar organic chemical integrative sampler [POCIS]) that integratively concentrates trace levels of complex mixtures of hydrophilic environmental contaminants, enables the determination of their time-weighted average water concentrations, and provides a method of estimating the potential exposure of aquatic organisms to the complex mixture of waterborne contaminants. Using a prototype sampler, linear uptake of selected herbicides and pharmaceuticals with log KowS < 4.0 was observed for up to 56 d. Estimation of the ambient water concentrations of chemicals of interest is achieved by using appropriate uptake models and determination of POCIS sampling rates for appropriate exposure conditions. Use of POCIS in field validation studies targeting the herbicide diuron in the United Kingdom resulted in the detection of the chemical at estimated concentrations of 190 to 600 ng/L. These values are in agreement with reported levels found in traditional grab samples taken concurrently.

Application of the rotating cylinder electrode in molten LiCl-KCl eutectic containing uranium(III)- and magnesium(II)-chloride

NASA Astrophysics Data System (ADS)

Rappleye, Devin; Simpson, Michael F.

2017-04-01

The application of the rotating cylinder electrode (RCE) to molten LiCl-KCl eutectic mixtures for electroanalytical measurements is presented. This enabled the measurement of the limiting current which was observed to follow a linear trend with the rotational rate raised to 0.64-0.65 power on average, which closely agrees with existing RCE mass-transfer correlations. This is the first publication of electroanalytical RCE measurements in LiCl-KCl eutectic based molten salt mixtures, to our knowledge. These measurements were made in mixtures of molten LiCl-KCl eutectic containing UCl3 and MgCl2. Kinetic parameters were calculated for Mg2+ in LiCl-KCl eutectic. The exchange current density (io) of Mg2+ deposition varied with mole fraction (x) according to io(A cm-2) = 1.64x0.689. The parameters from RCE measurements were also applied in an electrochemical co-deposition model entitled DREP to detect and predict the deposition rate of U and Mg. DREP succeeded in detecting the co-deposition of U and Mg, even when Mg constituted less than 0.5 wt% of the deposit.

Optimization and characterization of stable lipid-based, oxygen-filled microbubbles by mixture design.

PubMed

Polizzotti, Brian D; Thomson, Lindsay M; O'Connell, Daniel W; McGowan, Francis X; Kheir, John N

2014-08-01

Tissue hypoxia is a final common pathway that leads to cellular injury and death in a number of critical illnesses. Intravenous injections of self-assembling, lipid-based oxygen microbubbles (LOMs) can be used to deliver oxygen gas, preventing organ injury and death from systemic hypoxemia. However, current formulations exhibit high polydispersity indices (which may lead to microvascular obstruction) and poor shelf-lives, limiting the translational capacity of LOMs. In this study, we report our efforts to optimize LOM formulations using a mixture response surface methodology (mRSM). We study the effect of changing excipient proportions (the independent variables) on microbubble diameter and product loss (the dependent variables). By using mRSM analysis, the experimental data were fit using a reduced Scheffé linear mixture model. We demonstrate that formulations manufactured from 1,2-distearoyl-sn-glycero-3-phosphocholine, corn syrup, and water produce micron-sized microbubbles with low polydispersity indices, and decreased product loss (relative to previously described formulations) when stored at room temperature over a 30-day period. Optimized LOMs were subsequently tested for their oxygen-releasing ability and found to have similar release kinetics as prior formulations. © 2014 Wiley Periodicals, Inc.

DEVELOPMENT OF A PASSIVE, IN SITU, INTEGRATIVE ...

EPA Pesticide Factsheets

Until recently, hydrophobic, bioconcentratable compounds have been the primary focus of most environmental organic contaminant investigations, There is an increasing realization that a holistic hazard assessment of complex environmental contaminant mixtures requires data on the concentrations of hydrophilic organic contaminants as well. This group of compounds includes a wide variety of chemicals, including potentially endocrine disrupting and estrogenic contaminants which have been shown to contribute to numerous abnormalities such as impaired reproduction in aquatic organisms exposed in environmental waters. To address this issue, we developed a passive, in situ, sampling device (the Polar Organic Chemical Integrative Sampler or POCIS) which integratively concentrates trace levels of complex mixtures of hydrophilic environmental contaminants, enables the determination of their time-weighted average water concentrations and provides a screening assessment of the toxicological significance of the complex mixture of waterborne contaminants. Using a prototype sampler (effective membrane sampling surface area = 18.2 cm 2) linear uptake of selected herbicides and pharmaceuticals was observed for up to 56 days. Estimation of the ambient water concentrations of chemicals of interest is achieved by using appropriate uptake models and determination of POCIS chemical sampling rates. The research focused on in the subtasks is the development and application of state-of

Application of D-optimal experimental design method to optimize the formulation of O/W cosmetic emulsions.

PubMed

Djuris, J; Vasiljevic, D; Jokic, S; Ibric, S

2014-02-01

This study investigates the application of D-optimal mixture experimental design in optimization of O/W cosmetic emulsions. Cetearyl glucoside was used as a natural, biodegradable non-ionic emulsifier in the relatively low concentration (1%), and the mixture of co-emulsifiers (stearic acid, cetyl alcohol, stearyl alcohol and glyceryl stearate) was used to stabilize the formulations. To determine the optimal composition of co-emulsifiers mixture, D-optimal mixture experimental design was used. Prepared emulsions were characterized with rheological measurements, centrifugation test, specific conductivity and pH value measurements. All prepared samples appeared as white and homogenous creams, except for one homogenous and viscous lotion co-stabilized by stearic acid alone. Centrifugation testing revealed some phase separation only in the case of sample co-stabilized using glyceryl stearate alone. The obtained pH values indicated that all samples expressed mild acid value acceptable for cosmetic preparations. Specific conductivity values are attributed to the multiple phases O/W emulsions with high percentages of fixed water. Results of the rheological measurements have shown that the investigated samples exhibited non-Newtonian thixotropic behaviour. To determine the influence of each of the co-emulsifiers on emulsions properties, the obtained results were evaluated by the means of statistical analysis (ANOVA test). On the basis of comparison of statistical parameters for each of the studied responses, mixture reduced quadratic model was selected over the linear model implying that interactions between co-emulsifiers play the significant role in overall influence of co-emulsifiers on emulsions properties. Glyceryl stearate was found to be the dominant co-emulsifier affecting emulsions properties. Interactions between the glyceryl stearate and other co-emulsifiers were also found to significantly influence emulsions properties. These findings are especially important as they can be used for development of the product that meets users' requirements, as represented in the study. © 2013 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

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

PubMed

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.

Modeling the effect of temperature on survival rate of Salmonella Enteritidis in yogurt.

PubMed

Szczawiński, J; Szczawińska, M E; Łobacz, A; Jackowska-Tracz, A

2014-01-01

The aim of the study was to determine the inactivation rates of Salmonella Enteritidis in commercially produced yogurt and to generate primary and secondary mathematical models to predict the behaviour of these bacteria during storage at different temperatures. The samples were inoculated with the mixture of three S. Enteritidis strains and stored at 5 degrees C, 10 degrees C, 15 degrees C, 20 degrees C and 25 degrees C for 24 h. The number of salmonellae was determined every two hours. It was found that the number of bacteria decreased linearly with storage time in all samples. Storage temperature and pH of yogurt significantly influenced survival rate of S. Enteritidis (p < 0.05). In samples kept at 5 degrees C the number of salmonellae decreased at the lowest rate, whereas at 25 degrees C the reduction in number of bacteria was the most dynamic. The natural logarithm of mean inactivation rates of Salmonella calculated from primary model was fitted to two secondary models: linear and polynomial. Equations obtained from both secondary models can be applied as a tool for prediction of inactivation rate of Salmonella in yogurt stored under temperature range from 5 to 25 degrees C; however, polynomial model gave the better fit to the experimental data.

Modeling abundance using multinomial N-mixture models

USGS Publications Warehouse

Royle, Andy

2016-01-01

Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values.

PubMed

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-05

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD=0.12], 0.67-23.19 [LOD=0.13] and 0.73-25.12 [LOD=0.15] μgmL(-1) for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values

NASA Astrophysics Data System (ADS)

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-01

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD = 0.12], 0.67-23.19 [LOD = 0.13] and 0.73-25.12 [LOD = 0.15] μg mL- 1 for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples.

Development of a Physiologically Based Pharmacokinetic and Pharmacodynamic Model to Determine Dosimetry and Cholinesterase Inhibition for a Binary Mixture of Chlorpyrifos and Diazinon in the Rat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timchalk, Chuck; Poet, Torka S.

2008-05-01

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models have been developed and validated for the organophosphorus (OP) insecticides chlorpyrifos (CPF) and diazinon (DZN). Based on similar pharmacokinetic and mode of action properties it is anticipated that these OPs could interact at a number of important metabolic steps including: CYP450 mediated activation/detoxification, and blood/tissue cholinesterase (ChE) binding/inhibition. We developed a binary PBPK/PD model for CPF, DZN and their metabolites based on previously published models for the individual insecticides. The metabolic interactions (CYP450) between CPF and DZN were evaluated in vitro and suggests that CPF is more substantially metabolized to its oxon metabolite than ismore » DZN. These data are consistent with their observed in vivo relative potency (CPF>DZN). Each insecticide inhibited the other’s in vitro metabolism in a concentration-dependent manner. The PBPK model code used to described the metabolism of CPF and DZN was modified to reflect the type of inhibition kinetics (i.e. competitive vs. non-competitive). The binary model was then evaluated against previously published rodent dosimetry and ChE inhibition data for the mixture. The PBPK/PD model simulations of the acute oral exposure to single- (15 mg/kg) vs. binary-mixtures (15+15 mg/kg) of CFP and DZN at this lower dose resulted in no differences in the predicted pharmacokinetics of either the parent OPs or their respective metabolites; whereas, a binary oral dose of CPF+DZN at 60+60 mg/kg did result in observable changes in the DZN pharmacokinetics. Cmax was more reasonably fit by modifying the absorption parameters. It is anticipated that at low environmentally relevant binary doses, most likely to be encountered in occupational or environmental related exposures, that the pharmacokinetics are expected to be linear, and ChE inhibition dose-additive.« less

Concentration addition and independent action model: Which is better in predicting the toxicity for metal mixtures on zebrafish larvae.

PubMed

Gao, Yongfei; Feng, Jianfeng; Kang, Lili; Xu, Xin; Zhu, Lin

2018-01-01

The joint toxicity of chemical mixtures has emerged as a popular topic, particularly on the additive and potential synergistic actions of environmental mixtures. We investigated the 24h toxicity of Cu-Zn, Cu-Cd, and Cu-Pb and 96h toxicity of Cd-Pb binary mixtures on the survival of zebrafish larvae. Joint toxicity was predicted and compared using the concentration addition (CA) and independent action (IA) models with different assumptions in the toxic action mode in toxicodynamic processes through single and binary metal mixture tests. Results showed that the CA and IA models presented varying predictive abilities for different metal combinations. For the Cu-Cd and Cd-Pb mixtures, the CA model simulated the observed survival rates better than the IA model. By contrast, the IA model simulated the observed survival rates better than the CA model for the Cu-Zn and Cu-Pb mixtures. These findings revealed that the toxic action mode may depend on the combinations and concentrations of tested metal mixtures. Statistical analysis of the antagonistic or synergistic interactions indicated that synergistic interactions were observed for the Cu-Cd and Cu-Pb mixtures, non-interactions were observed for the Cd-Pb mixtures, and slight antagonistic interactions for the Cu-Zn mixtures. These results illustrated that the CA and IA models are consistent in specifying the interaction patterns of binary metal mixtures. Copyright © 2017 Elsevier B.V. All rights reserved.

Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

PubMed Central

Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

2013-01-01

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals. PMID:23990906

A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

PubMed Central

2011-01-01

Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy. PMID:22208882

SI-traceable and dynamic reference gas mixtures for water vapour at polar and high troposphere atmospheric levels

NASA Astrophysics Data System (ADS)

Guillevic, Myriam; Pascale, Céline; Mutter, Daniel; Wettstein, Sascha; Niederhauser, Bernhard

2017-04-01

In the framework of METAS' AtmoChem-ECV project, new facilities are currently being developed to generate reference gas mixtures for water vapour at concentrations measured in the high troposphere and polar regions, in the range 1-20 µmol/mol (ppm). The generation method is dynamic (the mixture is produced continuously over time) and SI-traceable (i.e. the amount of substance fraction in mole per mole is traceable to the definition of SI-units). The generation process is composed of three successive steps. The first step is to purify the matrix gas, nitrogen or synthetic air. Second, this matrix gas is spiked with the pure substance using a permeation technique: a permeation device contains a few grams of pure water in liquid form and loses it linearly over time by permeation through a membrane. In a third step, to reach the desired concentration, the first, high concentration mixture exiting the permeation chamber is then diluted with a chosen flow of matrix gas with one or two subsequent dilution steps. All flows are piloted by mass flow controllers. All parts in contact with the gas mixture are passivated using coated surfaces, to reduce adsorption/desorption processes as much as possible. The mixture can eventually be directly used to calibrate an analyser. The standard mixture produced by METAS' dynamic setup was injected into a chilled mirror from MBW Calibration AG, the designated institute for absolute humidity calibration in Switzerland. The used chilled mirror, model 373LX, is able to measure frost point and sample pressure and therefore calculate the water vapour concentration. This intercomparison of the two systems was performed in the range 4-18 ppm water vapour in synthetic air, at two different pressure levels, 1013.25 hPa and 2000 hPa. We present here METAS' dynamic setup, its uncertainty budget and the first results of the intercomparison with MBW's chilled mirror.

Structure and Dynamics of Urea/Water Mixtures Investigated by Vibrational Spectroscopy and Molecular Dynamics Simulation

PubMed Central

Carr, J. K.; Buchanan, L. E.; Schmidt, J. R.; Zanni, M. T.; Skinner, J. L.

2013-01-01

Urea/water is an archetypical “biological” mixture, and is especially well known for its relevance to protein thermodynamics, as urea acts as a protein denaturant at high concentration. This behavior has given rise to an extended debate concerning urea’s influence on water structure. Based on a variety of methods and of definitions of water structure, urea has been variously described as a structure-breaker, a structure-maker, or as remarkably neutral towards water. Because of its sensitivity to microscopic structure and dynamics, vibrational spectroscopy can help resolve these debates. We report experimental and theoretical spectroscopic results for the OD stretch of HOD/H2O/urea mixtures (linear IR, 2DIR, and pump-probe anisotropy decay) and for the CO stretch of urea-D4/D2O mixtures (linear IR only). Theoretical results are obtained using existing approaches for water, and a modification of a frequency map developed for acetamide. All absorption spectra are remarkably insensitive to urea concentration, consistent with the idea that urea only very weakly perturbs water structure. Both this work and experiments by Rezus and Bakker, however, show that water’s rotational dynamics are slowed down by urea. Analysis of the simulations casts doubt on the suggestion that urea immobilizes particular doubly hydrogen bonded water molecules. PMID:23841646

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

NASA Technical Reports Server (NTRS)

Principe, Jose C.

2007-01-01

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

Detecting Mixtures from Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

ERIC Educational Resources Information Center

Henson, James M.; Reise, Steven P.; Kim, Kevin H.

2007-01-01

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…

Maximum likelihood estimation of finite mixture model for economic data

NASA Astrophysics Data System (ADS)

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.

Spectral Invariant Behavior of Zenith Radiance Around Cloud Edges Observed by ARM SWS

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Chiu, J. C.; Wiscombe, W. J.

2009-01-01

The ARM Shortwave Spectrometer (SWS) measures zenith radiance at 418 wavelengths between 350 and 2170 nm. Because of its 1-sec sampling resolution, the SWS provides a unique capability to study the transition zone between cloudy and clear sky areas. A spectral invariant behavior is found between ratios of zenith radiance spectra during the transition from cloudy to cloud-free. This behavior suggests that the spectral signature of the transition zone is a linear mixture between the two extremes (definitely cloudy and definitely clear). The weighting function of the linear mixture is a wavelength-independent characteristic of the transition zone. It is shown that the transition zone spectrum is fully determined by this function and zenith radiance spectra of clear and cloudy regions. An important result of these discoveries is that high temporal resolution radiance measurements in the clear-to-cloud transition zone can be well approximated by lower temporal resolution measurements plus linear interpolation.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

NASA Astrophysics Data System (ADS)

Qu, Rui; Liu, Shu-Shen; Zheng, Qiao-Feng; Li, Tong

2017-03-01

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDVequ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDVequ successfully predicted the toxicities of various types of binary mixtures.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

PubMed Central

Qu, Rui; Liu, Shu-Shen; Zheng, Qiao-Feng; Li, Tong

2017-01-01

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDVequ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDVequ successfully predicted the toxicities of various types of binary mixtures. PMID:28287626

Purification and Quantification of an Isomeric Compound in a Mixture by Collisional Excitation in Multistage Mass Spectrometry Experiments.

PubMed

Jeanne Dit Fouque, Dany; Maroto, Alicia; Memboeuf, Antony

2016-11-15

The differentiation, characterization, and quantification of isomers and/or isobars in mixtures is a recurrent problem in mass spectrometry and more generally in analytical chemistry. Here we present a new strategy to assess the purity of a compound that is susceptible to be contaminated with another isomeric side-product in trace levels. Providing one of the isomers is available as pure sample, this new strategy allows the detection of isomeric contamination. This is done thanks to a "gas-phase collisional purification" inside an ion trap mass spectrometer paving the way for an improved analysis of at least similar samples. This strategy consists in using collision induced dissociation (CID) multistage mass spectrometry (MS 2 and MS 3 ) experiments and the survival yield (SY) technique. It has been successfully applied to mixtures of cyclic poly( L -lactide) (PLA) with increasing amounts of its linear topological isomer. Purification in gas phase of PLA mixtures was established based on SY curves obtained in MS 3 mode: all samples gave rise to the same SY curve corresponding then to the pure cyclic component. This new strategy was sensitive enough to detect traces of linear PLA (<3%) in a sample of cyclic PLA that was supposedly pure according to other characterization techniques ( 1 H NMR, MALDI-HRMS, and size-exclusion chromatography). Moreover, in this case, the presence of linear isomer was undetectable according to MS/MS or MS/MS/MS analysis only as fragment ions are also of the same m/z values. This type of approach could easily be implemented in hyphenated mass spectrometric techniques to improve the structural and quantitative analysis of complex samples.

Rapid Quadrupole-Time-of-Flight Mass Spectrometry Method Quantifies Oxygen-Rich Lignin Compound in Complex Mixtures

NASA Astrophysics Data System (ADS)

Boes, Kelsey S.; Roberts, Michael S.; Vinueza, Nelson R.

2018-03-01

Complex mixture analysis is a costly and time-consuming task facing researchers with foci as varied as food science and fuel analysis. When faced with the task of quantifying oxygen-rich bio-oil molecules in a complex diesel mixture, we asked whether complex mixtures could be qualitatively and quantitatively analyzed on a single mass spectrometer with mid-range resolving power without the use of lengthy separations. To answer this question, we developed and evaluated a quantitation method that eliminated chromatography steps and expanded the use of quadrupole-time-of-flight mass spectrometry from primarily qualitative to quantitative as well. To account for mixture complexity, the method employed an ionization dopant, targeted tandem mass spectrometry, and an internal standard. This combination of three techniques achieved reliable quantitation of oxygen-rich eugenol in diesel from 300 to 2500 ng/mL with sufficient linearity (R2 = 0.97 ± 0.01) and excellent accuracy (percent error = 0% ± 5). To understand the limitations of the method, it was compared to quantitation attained on a triple quadrupole mass spectrometer, the gold standard for quantitation. The triple quadrupole quantified eugenol from 50 to 2500 ng/mL with stronger linearity (R2 = 0.996 ± 0.003) than the quadrupole-time-of-flight and comparable accuracy (percent error = 4% ± 5). This demonstrates that a quadrupole-time-of-flight can be used for not only qualitative analysis but also targeted quantitation of oxygen-rich lignin molecules in complex mixtures without extensive sample preparation. The rapid and cost-effective method presented here offers new possibilities for bio-oil research, including: (1) allowing for bio-oil studies that demand repetitive analysis as process parameters are changed and (2) making this research accessible to more laboratories. [Figure not available: see fulltext.

Slip and barodiffusion phenomena in slow flows of a gas mixture

NASA Astrophysics Data System (ADS)

Zhdanov, V. M.

2017-03-01

The slip and barodiffusion problems for the slow flows of a gas mixture are investigated on the basis of the linearized moment equations following from the Boltzmann equation. We restrict ourselves to the set of the third-order moment equations and state two general relations (resembling conservation equations) for the moments of the distribution function similar to the conditions used by Loyalka [S. K. Loyalka, Phys. Fluids 14, 2291 (1971), 10.1063/1.1693331] in his approximation method (the modified Maxwell method). The expressions for the macroscopic velocities of the gas mixture species, the partial viscous stress tensors, and the reduced heat fluxes for the stationary slow flow of a gas mixture in the semi-infinite space over a plane wall are obtained as a result of the exact solution of the linearized moment equations in the 10- and 13-moment approximations. The general expression for the slip velocity and the simple and accurate expressions for the viscous, thermal, diffusion slip, and baroslip coefficients, which are given in terms of the basic transport coefficients, are derived by using the modified Maxwell method. The solutions of moment equations are also used for investigation of the flow and diffusion of a gas mixture in a channel formed by two infinite parallel plates. A fundamental result is that the barodiffusion factor in the cross-section-averaged expression for the diffusion flux contains contributions associated with the viscous transfer of momentum in the gas mixture and the effect of the Knudsen layer. Our study revealed that the barodiffusion factor is equal to the diffusion slip coefficient (correct to the opposite sign). This result is consistent with the Onsager's reciprocity relations for kinetic coefficients following from nonequilibrium thermodynamics of the discontinuous systems.

Rapid Quadrupole-Time-of-Flight Mass Spectrometry Method Quantifies Oxygen-Rich Lignin Compound in Complex Mixtures

NASA Astrophysics Data System (ADS)

Boes, Kelsey S.; Roberts, Michael S.; Vinueza, Nelson R.

2017-12-01

Complex mixture analysis is a costly and time-consuming task facing researchers with foci as varied as food science and fuel analysis. When faced with the task of quantifying oxygen-rich bio-oil molecules in a complex diesel mixture, we asked whether complex mixtures could be qualitatively and quantitatively analyzed on a single mass spectrometer with mid-range resolving power without the use of lengthy separations. To answer this question, we developed and evaluated a quantitation method that eliminated chromatography steps and expanded the use of quadrupole-time-of-flight mass spectrometry from primarily qualitative to quantitative as well. To account for mixture complexity, the method employed an ionization dopant, targeted tandem mass spectrometry, and an internal standard. This combination of three techniques achieved reliable quantitation of oxygen-rich eugenol in diesel from 300 to 2500 ng/mL with sufficient linearity (R2 = 0.97 ± 0.01) and excellent accuracy (percent error = 0% ± 5). To understand the limitations of the method, it was compared to quantitation attained on a triple quadrupole mass spectrometer, the gold standard for quantitation. The triple quadrupole quantified eugenol from 50 to 2500 ng/mL with stronger linearity (R2 = 0.996 ± 0.003) than the quadrupole-time-of-flight and comparable accuracy (percent error = 4% ± 5). This demonstrates that a quadrupole-time-of-flight can be used for not only qualitative analysis but also targeted quantitation of oxygen-rich lignin molecules in complex mixtures without extensive sample preparation. The rapid and cost-effective method presented here offers new possibilities for bio-oil research, including: (1) allowing for bio-oil studies that demand repetitive analysis as process parameters are changed and (2) making this research accessible to more laboratories. [Figure not available: see fulltext.

Rapid Quadrupole-Time-of-Flight Mass Spectrometry Method Quantifies Oxygen-Rich Lignin Compound in Complex Mixtures.

PubMed

Boes, Kelsey S; Roberts, Michael S; Vinueza, Nelson R

2018-03-01

Complex mixture analysis is a costly and time-consuming task facing researchers with foci as varied as food science and fuel analysis. When faced with the task of quantifying oxygen-rich bio-oil molecules in a complex diesel mixture, we asked whether complex mixtures could be qualitatively and quantitatively analyzed on a single mass spectrometer with mid-range resolving power without the use of lengthy separations. To answer this question, we developed and evaluated a quantitation method that eliminated chromatography steps and expanded the use of quadrupole-time-of-flight mass spectrometry from primarily qualitative to quantitative as well. To account for mixture complexity, the method employed an ionization dopant, targeted tandem mass spectrometry, and an internal standard. This combination of three techniques achieved reliable quantitation of oxygen-rich eugenol in diesel from 300 to 2500 ng/mL with sufficient linearity (R 2 = 0.97 ± 0.01) and excellent accuracy (percent error = 0% ± 5). To understand the limitations of the method, it was compared to quantitation attained on a triple quadrupole mass spectrometer, the gold standard for quantitation. The triple quadrupole quantified eugenol from 50 to 2500 ng/mL with stronger linearity (R 2 = 0.996 ± 0.003) than the quadrupole-time-of-flight and comparable accuracy (percent error = 4% ± 5). This demonstrates that a quadrupole-time-of-flight can be used for not only qualitative analysis but also targeted quantitation of oxygen-rich lignin molecules in complex mixtures without extensive sample preparation. The rapid and cost-effective method presented here offers new possibilities for bio-oil research, including: (1) allowing for bio-oil studies that demand repetitive analysis as process parameters are changed and (2) making this research accessible to more laboratories. Graphical Abstract ᅟ.

Statistical Modeling Suggests that Antiandrogens in Effluents from Wastewater Treatment Works Contribute to Widespread Sexual Disruption in Fish Living in English Rivers

PubMed Central

Jobling, Susan; Burn, Robert. W.; Thorpe, Karen; Williams, Richard; Tyler, Charles

2009-01-01

Background The widespread occurrence of feminized male fish downstream of some wastewater treatment works has led to substantial interest from ecologists and public health professionals. This concern stems from the view that the effects observed have a parallel in humans, and that both phenomena are caused by exposure to mixtures of contaminants that interfere with reproductive development. The evidence for a “wildlife–human connection” is, however, weak: Testicular dysgenesis syndrome, seen in human males, is most easily reproduced in rodent models by exposure to mixtures of antiandrogenic chemicals. In contrast, the accepted explanation for feminization of wild male fish is that it results mainly from exposure to steroidal estrogens originating primarily from human excretion. Objectives We sought to further explore the hypothesis that endocrine disruption in fish is multicausal, resulting from exposure to mixtures of chemicals with both estrogenic and antiandrogenic properties. Methods We used hierarchical generalized linear and generalized additive statistical modeling to explore the associations between modeled concentrations and activities of estrogenic and antiandrogenic chemicals in 30 U.K. rivers and feminized responses seen in wild fish living in these rivers. Results In addition to the estrogenic substances, antiandrogenic activity was prevalent in almost all treated sewage effluents tested. Further, the results of the modeling demonstrated that feminizing effects in wild fish could be best modeled as a function of their predicted exposure to both antiandrogens and estrogens or to antiandrogens alone. Conclusion The results provide a strong argument for a multicausal etiology of widespread feminization of wild fish in U.K. rivers involving contributions from both steroidal estrogens and xenoestrogens and from other (as yet unknown) contaminants with antiandrogenic properties. These results may add further credence to the hypothesis that endocrine-disrupting effects seen in wild fish and in humans are caused by similar combinations of endocrine-disrupting chemical cocktails. PMID:19479024

Alfven wave dispersion behavior in single- and multicomponent plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rahbarnia, K.; Grulke, O.; Klinger, T.

Dispersion relations of driven Alfven waves (AWs) are measured in single- and multicomponent plasmas consisting of mixtures of argon, helium, and oxygen in a magnetized linear cylindrical plasma device VINETA [C. Franck, O. Grulke, and T. Klinger, Phys. Plasmas 9, 3254 (2002)]. The decomposition of the measured three-dimensional magnetic field fluctuations and the corresponding parallel current pattern reveals that the wave field is a superposition of L- and R-wave components. The dispersion relation measurements agree well with calculations based on a multifluid Hall-magnetohydrodynamic model if the plasma resistivity is correctly taken into account.

Rock elastic properties and near-surface structure at Taurus-Littrow. [strain measurement of lunar basalt and breccia

NASA Technical Reports Server (NTRS)

Trice, R.; Warren, N.; Anderson, O. L.

1974-01-01

Linear strain measurements are presented for two lunar basalts, 14310,82 and 71055,15 and one breccia, 15498,23 to 5 kb hydrostatic pressure. Compressional and shear acoustic velocities to 5 kb are also presented for the basalts, 14310,82 and 71055,15. These elastic properties, along with geological, seismological and rock mechanics considerations are consistent with a model of the structure of the Taurus-Littrow valley as follows, a thin surface regolith overlying a fractured mixture of basalt flows and ejecta material which in turn overlies a coherent breccia of highland ejecta debris.

Terahertz spectral detection of potassium sorbate in milk powder

NASA Astrophysics Data System (ADS)

Li, Pengpeng; Zhang, Yuan; Ge, Hongyi

2017-02-01

The spectral characteristics of potassium sorbate in milk powder in the range of 0.2 2.0 THz have been measured with THz time-domain spectroscopy(THz-TDS). Its absorption and refraction spectra are obtained at room temperature in the nitrogen atmosphere. The results showed that potassium sorbate at 0.98 THz obvious characteristic absorption peak. The simple linear regression(SLR) model was taken to analyze the content of potassium sorbate in milk powder. The results showed that the absorption coefficient increases as the mixture potassium sorbate increases. The research is important to food quality and safety testing.

Simultaneous quantification of Aroclor mixtures in soil samples by gas chromatography/mass spectrometry with solid phase microextraction using partial least-squares regression.

PubMed

Zhang, Mengliang; Harrington, Peter de B

2015-01-01

Multivariate partial least-squares (PLS) method was applied to the quantification of two complex polychlorinated biphenyls (PCBs) commercial mixtures, Aroclor 1254 and 1260, in a soil matrix. PCBs in soil samples were extracted by headspace solid phase microextraction (SPME) and determined by gas chromatography/mass spectrometry (GC/MS). Decachlorinated biphenyl (deca-CB) was used as internal standard. After the baseline correction was applied, four data representations including extracted ion chromatograms (EIC) for Aroclor 1254, EIC for Aroclor 1260, EIC for both Aroclors and two-way data sets were constructed for PLS-1 and PLS-2 calibrations and evaluated with respect to quantitative prediction accuracy. The PLS model was optimized with respect to the number of latent variables using cross validation of the calibration data set. The validation of the method was performed with certified soil samples and real field soil samples and the predicted concentrations for both Aroclors using EIC data sets agreed with the certified values. The linear range of the method was from 10μgkg(-1) to 1000μgkg(-1) for both Aroclor 1254 and 1260 in soil matrices and the detection limit was 4μgkg(-1) for Aroclor 1254 and 6μgkg(-1) for Aroclor 1260. This holistic approach for the determination of mixtures of complex samples has broad application to environmental forensics and modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

A predictive multi-linear regression model for organic micropollutants, based on a laboratory-scale column study simulating the river bank filtration process.

PubMed

Bertelkamp, C; Verliefde, A R D; Reynisson, J; Singhal, N; Cabo, A J; de Jonge, M; van der Hoek, J P

2016-03-05

This study investigated relationships between OMP biodegradation rates and the functional groups present in the chemical structure of a mixture of 31 OMPs. OMP biodegradation rates were determined from lab-scale columns filled with soil from RBF site Engelse Werk of the drinking water company Vitens in The Netherlands. A statistically significant relationship was found between OMP biodegradation rates and the functional groups of the molecular structures of OMPs in the mixture. The OMP biodegradation rate increased in the presence of carboxylic acids, hydroxyl groups, and carbonyl groups, but decreased in the presence of ethers, halogens, aliphatic ethers, methyl groups and ring structures in the chemical structure of the OMPs. The predictive model obtained from the lab-scale soil column experiment gave an accurate qualitative prediction of biodegradability for approximately 70% of the OMPs monitored in the field (80% excluding the glymes). The model was found to be less reliable for the more persistent OMPs (OMPs with predicted biodegradation rates lower or around the standard error=0.77d(-1)) and OMPs containing amide or amine groups. These OMPs should be carefully monitored in the field to determine their removal during RBF. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of relationships between test and training animals and among training animals on reliability of genomic prediction.

PubMed

Wu, X; Lund, M S; Sun, D; Zhang, Q; Su, G

2015-10-01

One of the factors affecting the reliability of genomic prediction is the relationship among the animals of interest. This study investigated the reliability of genomic prediction in various scenarios with regard to the relationship between test and training animals, and among animals within the training data set. Different training data sets were generated from EuroGenomics data and a group of Nordic Holstein bulls (born in 2005 and afterwards) as a common test data set. Genomic breeding values were predicted using a genomic best linear unbiased prediction model and a Bayesian mixture model. The results showed that a closer relationship between test and training animals led to a higher reliability of genomic predictions for the test animals, while a closer relationship among training animals resulted in a lower reliability. In addition, the Bayesian mixture model in general led to a slightly higher reliability of genomic prediction, especially for the scenario of distant relationships between training and test animals. Therefore, to prevent a decrease in reliability, constant updates of the training population with animals from more recent generations are required. Moreover, a training population consisting of less-related animals is favourable for reliability of genomic prediction. © 2015 Blackwell Verlag GmbH.

Power-law viscous materials for analogue experiments: New data on the rheology of highly-filled silicone polymers

NASA Astrophysics Data System (ADS)

Boutelier, D.; Schrank, C.; Cruden, A.

2008-03-01

The selection of appropriate analogue materials is a central consideration in the design of realistic physical models. We investigate the rheology of highly-filled silicone polymers in order to find materials with a power-law strain-rate softening rheology suitable for modelling rock deformation by dislocation creep and report the rheological properties of the materials as functions of the filler content. The mixtures exhibit strain-rate softening behaviour but with increasing amounts of filler become strain-dependent. For the strain-independent viscous materials, flow laws are presented while for strain-dependent materials the relative importance of strain and strain rate softening/hardening is reported. If the stress or strain rate is above a threshold value some highly-filled silicone polymers may be considered linear visco-elastic (strain independent) and power-law strain-rate softening. The power-law exponent can be raised from 1 to ˜3 by using mixtures of high-viscosity silicone and plasticine. However, the need for high shear strain rates to obtain the power-law rheology imposes some restrictions on the usage of such materials for geodynamic modelling. Two simple shear experiments are presented that use Newtonian and power-law strain-rate softening materials. The results demonstrate how materials with power-law rheology result in better strain localization in analogue experiments.

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

PubMed

Nagai, Takashi

2017-10-01

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC. © 2017 SETAC.

Application of a constant hole volume Sanchez-Lacombe equation of state to mixtures relevant to polymeric foaming.

PubMed

von Konigslow, Kier; Park, Chul B; Thompson, Russell B

2018-06-06

A variant of the Sanchez-Lacombe equation of state is applied to several polymers, blowing agents, and saturated mixtures of interest to the polymer foaming industry. These are low-density polyethylene-carbon dioxide and polylactide-carbon dioxide saturated mixtures as well as polystyrene-carbon dioxide-dimethyl ether and polystyrene-carbon dioxide-nitrogen ternary saturated mixtures. Good agreement is achieved between theoretically predicted and experimentally determined solubilities, both for binary and ternary mixtures. Acceptable agreement with swelling ratios is found with no free parameters. Up-to-date pure component Sanchez-Lacombe characteristic parameters are provided for carbon dioxide, dimethyl ether, low-density polyethylene, nitrogen, polylactide, linear and branched polypropylene, and polystyrene. Pure fluid low-density polyethylene and nitrogen parameters exhibit more moderate success while still providing acceptable quantitative estimations. Mixture estimations are found to have more moderate success where pure components are not as well represented. The Sanchez-Lacombe equation of state is found to correctly predict the anomalous reversal of solubility temperature dependence for low critical point fluids through the observation of this behaviour in polystyrene nitrogen mixtures.

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

Applying a probabilistic seismic-petrophysical inversion and two different rock-physics models for reservoir characterization in offshore Nile Delta

NASA Astrophysics Data System (ADS)

Aleardi, Mattia

2018-01-01

We apply a two-step probabilistic seismic-petrophysical inversion for the characterization of a clastic, gas-saturated, reservoir located in offshore Nile Delta. In particular, we discuss and compare the results obtained when two different rock-physics models (RPMs) are employed in the inversion. The first RPM is an empirical, linear model directly derived from the available well log data by means of an optimization procedure. The second RPM is a theoretical, non-linear model based on the Hertz-Mindlin contact theory. The first step of the inversion procedure is a Bayesian linearized amplitude versus angle (AVA) inversion in which the elastic properties, and the associated uncertainties, are inferred from pre-stack seismic data. The estimated elastic properties constitute the input to the second step that is a probabilistic petrophysical inversion in which we account for the noise contaminating the recorded seismic data and the uncertainties affecting both the derived rock-physics models and the estimated elastic parameters. In particular, a Gaussian mixture a-priori distribution is used to properly take into account the facies-dependent behavior of petrophysical properties, related to the different fluid and rock properties of the different litho-fluid classes. In the synthetic and in the field data tests, the very minor differences between the results obtained by employing the two RPMs, and the good match between the estimated properties and well log information, confirm the applicability of the inversion approach and the suitability of the two different RPMs for reservoir characterization in the investigated area.

ARS-Media for Excel: A Spreadsheet Tool for Calculating Media Recipes Based on Ion-Specific Constraints

PubMed Central

Niedz, Randall P.

2016-01-01

ARS-Media for Excel is an ion solution calculator that uses “Microsoft Excel” to generate recipes of salts for complex ion mixtures specified by the user. Generating salt combinations (recipes) that result in pre-specified target ion values is a linear programming problem. Excel’s Solver add-on solves the linear programming equation to generate a recipe. Calculating a mixture of salts to generate exact solutions of complex ionic mixtures is required for at least 2 types of problems– 1) formulating relevant ecological/biological ionic solutions such as those from a specific lake, soil, cell, tissue, or organ and, 2) designing ion confounding-free experiments to determine ion-specific effects where ions are treated as statistical factors. Using ARS-Media for Excel to solve these two problems is illustrated by 1) exactly reconstructing a soil solution representative of a loamy agricultural soil and, 2) constructing an ion-based experiment to determine the effects of substituting Na+ for K+ on the growth of a Valencia sweet orange nonembryogenic cell line. PMID:27812202

ARS-Media for Excel: A Spreadsheet Tool for Calculating Media Recipes Based on Ion-Specific Constraints.

PubMed

Niedz, Randall P

2016-01-01

ARS-Media for Excel is an ion solution calculator that uses "Microsoft Excel" to generate recipes of salts for complex ion mixtures specified by the user. Generating salt combinations (recipes) that result in pre-specified target ion values is a linear programming problem. Excel's Solver add-on solves the linear programming equation to generate a recipe. Calculating a mixture of salts to generate exact solutions of complex ionic mixtures is required for at least 2 types of problems- 1) formulating relevant ecological/biological ionic solutions such as those from a specific lake, soil, cell, tissue, or organ and, 2) designing ion confounding-free experiments to determine ion-specific effects where ions are treated as statistical factors. Using ARS-Media for Excel to solve these two problems is illustrated by 1) exactly reconstructing a soil solution representative of a loamy agricultural soil and, 2) constructing an ion-based experiment to determine the effects of substituting Na+ for K+ on the growth of a Valencia sweet orange nonembryogenic cell line.

Change of hydrogen bonding structure in ionic liquid mixtures by anion type

NASA Astrophysics Data System (ADS)

Cha, Seoncheol; Kim, Doseok

2018-05-01

Ionic liquid mixtures have gained attention as a way of tuning material properties continuously with composition changes. For some mixture systems, physicochemical properties such as excess molar volume have been found to be significantly different from the value expected by linear interpolation, but the origin of this deviation is not well understood yet. The microstructure of the mixture, which can range from an ideal mixture of two initial consisting ionic liquids to a different structure from those of pure materials, has been suggested as the origin of the observed deviation. The structures of several different ionic liquid mixtures are studied by IR spectroscopy to confirm this suggestion, as a particular IR absorption band (νC(2)-D) for the moiety participating in the hydrogen bonding changes sensitively with the change of the anion in the ionic liquid. The absorbance of νC(2)-D changes proportionally with the composition, and a relatively small excess molar volume is observed for the mixtures containing an electronegative halide anion. By contrast, the absorbance changes nonlinearly, and the excess molar volumes are larger for the mixtures of which one of the anions has multiple interaction sites.

Thermal effects in rapid directional solidification - Linear theory

NASA Technical Reports Server (NTRS)

Huntley, D. A.; Davis, S. H.

1993-01-01

We study the morphological instability of the planar solid/liquid interface for a unidirectionally-solidified dilute binary mixture. We use a model developed by Boettinger et al. (1985, 1986), Aziz (1982), and Jackson et al. (1980), which allows for nonequilibrium effects on the interface through velocity-dependent segregation and attachment kinetics. Two types of instabilities are found in the linear stability analysis: (1) a cellular instability, and (2) an oscillatory instability driven by disequilibrium effects. Merchant and Davis (1990) characterized these instabilities subject to the frozen-temperature approximation (FTA). The present work relaxes the FTA by including the effects of latent heat and the full temperature distribution. Thermal effects slightly postpone the onset of the cellular instability but dramatically postpone the onset of the oscillatory instability; however, the absolute-stability conditions, at which at high speed the cellular and oscillatory instabilities are suppressed, remain unchanged from the FTA.

Plastic strain is a mixture of avalanches and quasireversible deformations: Study of various sizes

NASA Astrophysics Data System (ADS)

Szabó, Péter; Ispánovity, Péter Dusán; Groma, István

2015-02-01

The size dependence of plastic flow is studied by discrete dislocation dynamical simulations of systems with various amounts of interacting dislocations while the stress is slowly increased. The regions between avalanches in the individual stress curves as functions of the plastic strain were found to be nearly linear and reversible where the plastic deformation obeys an effective equation of motion with a nearly linear force. For small plastic deformation, the mean values of the stress-strain curves obey a power law over two decades. Here and for somewhat larger plastic deformations, the mean stress-strain curves converge for larger sizes, while their variances shrink, both indicating the existence of a thermodynamical limit. The converging averages decrease with increasing size, in accordance with size effects from experiments. For large plastic deformations, where steady flow sets in, the thermodynamical limit was not realized in this model system.

Nonlinear, Incremental Structural Analysis of Olmsted Locks and Dams. Volume 1: Main Text

DTIC Science & Technology

1992-12-01

dependent functions, which are supplied as algebraic functions of time or as data arrays in ABAQUS user subroutines (Hibbitt, Karlsson, and Sorenson 1988...143.0 Thermal Prouerties 9. The heat transfer capability of ABAQUS uses the finite element method to numerically solve the governing differential...coefficient of linear thermal expansion which were conducted at WES for Olmsted mixtures 6 and 11 (Hammons et al. 1991). The different concrete mixture

Structural transformations, composition anomalies and a dramatic collapse of linear polymer chains in dilute ethanol-water mixtures.

PubMed

Banerjee, Saikat; Ghosh, Rikhia; Bagchi, Biman

2012-03-29

Water-ethanol mixtures exhibit many interesting anomalies, such as negative excess partial molar volume of ethanol, excess sound absorption coefficient at low concentrations, and positive deviation from Raoult's law for vapor pressure, to mention a few. These anomalies have been attributed to different, often contradictory origins, but a quantitative understanding is still lacking. We show by computer simulation and theoretical analyses that these anomalies arise from the sudden emergence of a bicontinuous phase that occurs at a relatively low ethanol concentration of x(eth) ≈ 0.06-0.10 (that amounts to a volume fraction of 0.17-0.26, which is a significant range!). The bicontinuous phase is formed by aggregation of ethanol molecules, resulting in a weak phase transition whose nature is elucidated. We find that the microheterogeneous structure of the mixture gives rise to a pronounced nonmonotonic composition dependence of local compressibility and nonmonotonic dependence in the peak value of the radial distribution function of ethyl groups. A multidimensional free energy surface of pair association is shown to provide a molecular explanation of the known negative excess partial volume of ethanol in terms of parallel orientation and hence better packing of the ethyl groups in the mixture due to hydrophobic interactions. The energy distribution of the ethanol molecules indicates additional energy decay channels that explain the excess sound attenuation coefficient in aqueous alcohol mixtures. We studied the dependence of the solvation of a linear polymer chain on the composition of the water-ethanol solvent. We find that there is a sudden collapse of the polymer at x(eth) ≈ 0.05-a phenomenon which we attribute to the formation of the microheterogeneous structures in the binary mixture at low ethanol concentrations. Together with recent single molecule pulling experiments, these results provide new insight into the behavior of polymer chain and foreign solutes, such as enzymes, in aqueous binary mixtures.

Modeling chemical vapor deposition of silicon dioxide in microreactors at atmospheric pressure

NASA Astrophysics Data System (ADS)

Konakov, S. A.; Krzhizhanovskaya, V. V.

2015-01-01

We developed a multiphysics mathematical model for simulation of silicon dioxide Chemical Vapor Deposition (CVD) from tetraethyl orthosilicate (TEOS) and oxygen mixture in a microreactor at atmospheric pressure. Microfluidics is a promising technology with numerous applications in chemical synthesis due to its high heat and mass transfer efficiency and well-controlled flow parameters. Experimental studies of CVD microreactor technology are slow and expensive. Analytical solution of the governing equations is impossible due to the complexity of intertwined non-linear physical and chemical processes. Computer simulation is the most effective tool for design and optimization of microreactors. Our computational fluid dynamics model employs mass, momentum and energy balance equations for a laminar transient flow of a chemically reacting gas mixture at low Reynolds number. Simulation results show the influence of microreactor configuration and process parameters on SiO2 deposition rate and uniformity. We simulated three microreactors with the central channel diameter of 5, 10, 20 micrometers, varying gas flow rate in the range of 5-100 microliters per hour and temperature in the range of 300-800 °C. For each microchannel diameter we found an optimal set of process parameters providing the best quality of deposited material. The model will be used for optimization of the microreactor configuration and technological parameters to facilitate the experimental stage of this research.

To kill a kangaroo: understanding the decision to pursue high-risk/high-gain resources.

PubMed

Jones, James Holland; Bird, Rebecca Bliege; Bird, Douglas W

2013-09-22

In this paper, we attempt to understand hunter-gatherer foraging decisions about prey that vary in both the mean and variance of energy return using an expected utility framework. We show that for skewed distributions of energetic returns, the standard linear variance discounting (LVD) model for risk-sensitive foraging can produce quite misleading results. In addition to creating difficulties for the LVD model, the skewed distributions characteristic of hunting returns create challenges for estimating probability distribution functions required for expected utility. We present a solution using a two-component finite mixture model for foraging returns. We then use detailed foraging returns data based on focal follows of individual hunters in Western Australia hunting for high-risk/high-gain (hill kangaroo) and relatively low-risk/low-gain (sand monitor) prey. Using probability densities for the two resources estimated from the mixture models, combined with theoretically sensible utility curves characterized by diminishing marginal utility for the highest returns, we find that the expected utility of the sand monitors greatly exceeds that of kangaroos despite the fact that the mean energy return for kangaroos is nearly twice as large as that for sand monitors. We conclude that the decision to hunt hill kangaroos does not arise simply as part of an energetic utility-maximization strategy and that additional social, political or symbolic benefits must accrue to hunters of this highly variable prey.

Device for measuring the fluid density of a two-phase mixture

DOEpatents

Cole, Jack H.

1980-01-01

A device for measuring the fluid density of a two-phase mixture flowing through a tubular member. A rotor assembly is rotatively supported within the tubular member so that it can also move axially within the tubular member. The rotor assembly is balanced against a pair of springs which exert an axial force in the opposite direction upon the rotor assembly. As a two-phase mixture flows through the tubular member it contacts the rotor assembly causing it to rotate about its axis. The rotor assembly is forced against and partially compresses the springs. Means are provided to measure the rotational speed of the rotor assembly and the linear displacement of the rotor assembly. From these measurements the fluid density of the two-phase mixture is calculated.

Novel spectrophotometric determination of chloramphenicol and dexamethasone in the presence of non labeled interfering substances using univariate methods and multivariate regression model updating

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Rezk, Mamdouh R.; Omran, Yasmin Rostom

2015-04-01

Smart and novel spectrophotometric and chemometric methods have been developed and validated for the simultaneous determination of a binary mixture of chloramphenicol (CPL) and dexamethasone sodium phosphate (DSP) in presence of interfering substances without prior separation. The first method depends upon derivative subtraction coupled with constant multiplication. The second one is ratio difference method at optimum wavelengths which were selected after applying derivative transformation method via multiplying by a decoding spectrum in order to cancel the contribution of non labeled interfering substances. The third method relies on partial least squares with regression model updating. They are so simple that they do not require any preliminary separation steps. Accuracy, precision and linearity ranges of these methods were determined. Moreover, specificity was assessed by analyzing synthetic mixtures of both drugs. The proposed methods were successfully applied for analysis of both drugs in their pharmaceutical formulation. The obtained results have been statistically compared to that of an official spectrophotometric method to give a conclusion that there is no significant difference between the proposed methods and the official ones with respect to accuracy and precision.

Parametric identification of the process of preparing ceramic mixture as an object of control

NASA Astrophysics Data System (ADS)

Galitskov, Stanislav; Nazarov, Maxim; Galitskov, Konstantin

2017-10-01

Manufacture of ceramic materials and products largely depends on the preparation of clay raw materials. The main process here is the process of mixing, which in industrial production is mostly done in cross-compound clay mixers of continuous operation with steam humidification. The authors identified features of dynamics of this technological stage, which in itself is a non-linear control object with distributed parameters. When solving practical tasks for automation of a certain class of ceramic materials production it is important to make parametric identification of moving clay. In this paper the task is solved with the use of computational models, approximated to a particular section of a clay mixer along its length. The research introduces a methodology of computational experiments as applied to the designed computational model. Parametric identification of dynamic links was carried out according to transient characteristics. The experiments showed that the control object in question is to a great extent a non-stationary one. The obtained results are problematically oriented on synthesizing a multidimensional automatic control system for preparation of ceramic mixture with specified values of humidity and temperature exposed to the technological process of major disturbances.

Direct injection analysis of fatty and resin acids in papermaking process waters by HPLC/MS.

PubMed

Valto, Piia; Knuutinen, Juha; Alén, Raimo

2011-04-01

A novel HPLC-atmospheric pressure chemical ionization/MS (HPLC-APCI/MS) method was developed for the rapid analysis of selected fatty and resin acids typically present in papermaking process waters. A mixture of palmitic, stearic, oleic, linolenic, and dehydroabietic acids was separated by a commercial HPLC column (a modified stationary C(18) phase) using gradient elution with methanol/0.15% formic acid (pH 2.5) as a mobile phase. The internal standard (myristic acid) method was used to calculate the correlation coefficients and in the quantitation of the results. In the thorough quality parameters measurement, a mixture of these model acids in aqueous media as well as in six different paper machine process waters was quantitatively determined. The measured quality parameters, such as selectivity, linearity, precision, and accuracy, clearly indicated that, compared with traditional gas chromatographic techniques, the simple method developed provided a faster chromatographic analysis with almost real-time monitoring of these acids. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Substrate temperature controls molecular orientation in two-component vapor-deposited glasses

DOE PAGES

Jiang, J.; Walters, D. M.; Zhou, D.; ...

2016-02-22

Vapor-deposited glasses can be anisotropic and molecular orientation is important for organic electronics applications. In organic light emitting diodes (OLEDs), for example, the orientation of dye molecules in two-component emitting layers significantly influences emission efficiency. Here we investigate how substrate temperature during vapor deposition influences the orientation of dye molecules in a model two-component system. We determine the average orientation of a linear blue light emitter 1,4-di-[4-( N,N-diphenyl)amino]styrylbenzene (DSA-Ph) in mixtures with aluminum-tris(8-hydroxyquinoline) (Alq 3) by spectroscopic ellipsometry and IR dichroism. We find that molecular orientation is controlled by the ratio of the substrate temperature during deposition and the glassmore » transition temperature of the mixture. Furthermore, these findings extend recent results for single component vapor-deposited glasses and suggest that, during vapor deposition, surface mobility allows partial equilibration towards orientations preferred at the free surface of the equilibrium liquid.« less

Accurate and scalable social recommendation using mixed-membership stochastic block models.

PubMed

Godoy-Lorite, Antonia; Guimerà, Roger; Moore, Cristopher; Sales-Pardo, Marta

2016-12-13

With increasing amounts of information available, modeling and predicting user preferences-for books or articles, for example-are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users' ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user's and item's groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets.

Accurate and scalable social recommendation using mixed-membership stochastic block models

PubMed Central

Godoy-Lorite, Antonia; Moore, Cristopher

2016-01-01

With increasing amounts of information available, modeling and predicting user preferences—for books or articles, for example—are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users’ ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user’s and item’s groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets. PMID:27911773

Cropping system diversification for food production in Mindanao rubber plantations: a rice cultivar mixture and rice intercropped with mungbean

PubMed Central

Elazegui, Francisco; Duque, Jo-Anne Lynne Joy E.; Mundt, Christopher C.; Vera Cruz, Casiana M.

2017-01-01

Including food production in non-food systems, such as rubber plantations and biofuel or bioenergy crops, may contribute to household food security. We evaluated the potential for planting rice, mungbean, rice cultivar mixtures, and rice intercropped with mungbean in young rubber plantations in experiments in the Arakan Valley of Mindanao in the Philippines. Rice mixtures consisted of two- or three-row strips of cultivar Dinorado, a cultivar with higher value but lower yield, and high-yielding cultivar UPL Ri-5. Rice and mungbean intercropping treatments consisted of different combinations of two- or three-row strips of rice and mungbean. We used generalized linear mixed models to evaluate the yield of each crop alone and in the mixture or intercropping treatments. We also evaluated a land equivalent ratio for yield, along with weed biomass (where Ageratum conyzoides was particularly abundant), the severity of disease caused by Magnaporthe oryzae and Cochliobolus miyabeanus, and rice bug (Leptocorisa acuta) abundance. We analyzed the yield ranking of each cropping system across site-year combinations to determine mean relative performance and yield stability. When weighted by their relative economic value, UPL Ri-5 had the highest mean performance, but with decreasing performance in low-yielding environments. A rice and mungbean intercropping system had the second highest performance, tied with high-value Dinorado but without decreasing relative performance in low-yielding environments. Rice and mungbean intercropped with rubber have been adopted by farmers in the Arakan Valley. PMID:28194318

Measurement and Structural Model Class Separation in Mixture CFA: ML/EM versus MCMC

ERIC Educational Resources Information Center

Depaoli, Sarah

2012-01-01

Parameter recovery was assessed within mixture confirmatory factor analysis across multiple estimator conditions under different simulated levels of mixture class separation. Mixture class separation was defined in the measurement model (through factor loadings) and the structural model (through factor variances). Maximum likelihood (ML) via the…

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

PubMed

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.

Experimental evidence for an effect of early-diagenetic interaction between labile and refractory marine sedimentary organic matter on nitrogen dynamics

NASA Astrophysics Data System (ADS)

Turnewitsch, Robert; Domeyer, Bettina; Graf, Gerhard

2007-05-01

In most natural sedimentary systems labile and refractory organic material (OM) occur concomitantly. Little, however, is known on how different kinds of OM interact and how such interactions affect early diagenesis in sediments. In a simple sediment experiment, we investigated how interactions of OM substrates of different degradability affect benthic nitrogen (N) dynamics. Temporal evolution of a set of selected biogeochemical parameters was monitored in sandy sediment over 116 days in three experimental set-ups spiked with labile OM (tissue of Mytilus edulis), refractory OM (mostly aged Zostera marina and macroalgae), and a 1:1 mixture of labile and refractory OM. The initial amounts of particulate organic carbon (POC) were identical in the three set-ups. To check for non-linear interactions between labile and refractory OM, the evolution of the mixture system was compared with the evolution of the simple sum of the labile and refractory systems, divided by two. The sum system is the experimental control where labile and refractory OM are virtually combined but not allowed to interact. During the first 30 days there was evidence for net dissolved-inorganic-nitrogen (DIN) production followed by net DIN consumption. (Here 'DIN' is the sum of ammonium, nitrite and nitrate.) After ˜ 30 days a quasi steady state was reached. Non-linear interactions between the two types of OM were reflected by three main differences between the early-diagenetic evolutions of nitrogen dynamics of the mixture and sum (control) systems: (1) In the mixture system the phases of net DIN production and consumption commenced more rapidly and were more intense. (2) The mixture system was shifted towards a more oxidised state of DIN products [as indicated by increased (nitrite + nitrate)/(ammonium) ratios]. (3) There was some evidence that more OM, POC and particulate nitrogen were preserved in the mixture system. That is, in the mixture system more particulate OM was preserved while a higher proportion of the decomposed particulate N was converted into inorganic N. It can be concluded that during the first days and weeks of early diagenesis the magnitude and composition of the flux of decompositional dissolved N-compounds from sediments into the overlying water was influenced by non-linear interactions of OM substrates of different degradability. Given these experimental results it is likely that the relative spatial distributions of OM of differing degradability in sediments control the magnitude and composition of the return flux of dissolved N-bearing compounds from sediments into the overlying water column.

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

NASA Astrophysics Data System (ADS)

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.

Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

USGS Publications Warehouse

Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

2011-01-01

Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys. 5. Overestimation of abundance by binomial mixture models owing to non-independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N-mixture models to ecological data.

A competitive binding model predicts the response of mammalian olfactory receptors to mixtures

NASA Astrophysics Data System (ADS)

Singh, Vijay; Murphy, Nicolle; Mainland, Joel; Balasubramanian, Vijay

Most natural odors are complex mixtures of many odorants, but due to the large number of possible mixtures only a small fraction can be studied experimentally. To get a realistic understanding of the olfactory system we need methods to predict responses to complex mixtures from single odorant responses. Focusing on mammalian olfactory receptors (ORs in mouse and human), we propose a simple biophysical model for odor-receptor interactions where only one odor molecule can bind to a receptor at a time. The resulting competition for occupancy of the receptor accounts for the experimentally observed nonlinear mixture responses. We first fit a dose-response relationship to individual odor responses and then use those parameters in a competitive binding model to predict mixture responses. With no additional parameters, the model predicts responses of 15 (of 18 tested) receptors to within 10 - 30 % of the observed values, for mixtures with 2, 3 and 12 odorants chosen from a panel of 30. Extensions of our basic model with odorant interactions lead to additional nonlinearities observed in mixture response like suppression, cooperativity, and overshadowing. Our model provides a systematic framework for characterizing and parameterizing such mixing nonlinearities from mixture response data.

General multi-group macroscopic modeling for thermo-chemical non-equilibrium gas mixtures.

PubMed

Liu, Yen; Panesi, Marco; Sahai, Amal; Vinokur, Marcel

2015-04-07

This paper opens a new door to macroscopic modeling for thermal and chemical non-equilibrium. In a game-changing approach, we discard conventional theories and practices stemming from the separation of internal energy modes and the Landau-Teller relaxation equation. Instead, we solve the fundamental microscopic equations in their moment forms but seek only optimum representations for the microscopic state distribution function that provides converged and time accurate solutions for certain macroscopic quantities at all times. The modeling makes no ad hoc assumptions or simplifications at the microscopic level and includes all possible collisional and radiative processes; it therefore retains all non-equilibrium fluid physics. We formulate the thermal and chemical non-equilibrium macroscopic equations and rate coefficients in a coupled and unified fashion for gases undergoing completely general transitions. All collisional partners can have internal structures and can change their internal energy states after transitions. The model is based on the reconstruction of the state distribution function. The internal energy space is subdivided into multiple groups in order to better describe non-equilibrium state distributions. The logarithm of the distribution function in each group is expressed as a power series in internal energy based on the maximum entropy principle. The method of weighted residuals is applied to the microscopic equations to obtain macroscopic moment equations and rate coefficients succinctly to any order. The model's accuracy depends only on the assumed expression of the state distribution function and the number of groups used and can be self-checked for accuracy and convergence. We show that the macroscopic internal energy transfer, similar to mass and momentum transfers, occurs through nonlinear collisional processes and is not a simple relaxation process described by, e.g., the Landau-Teller equation. Unlike the classical vibrational energy relaxation model, which can only be applied to molecules, the new model is applicable to atoms, molecules, ions, and their mixtures. Numerical examples and model validations are carried out with two gas mixtures using the maximum entropy linear model: one mixture consists of nitrogen molecules undergoing internal excitation and dissociation and the other consists of nitrogen atoms undergoing internal excitation and ionization. Results show that the original hundreds to thousands of microscopic equations can be reduced to two macroscopic equations with almost perfect agreement for the total number density and total internal energy using only one or two groups. We also obtain good prediction of the microscopic state populations using 5-10 groups in the macroscopic equations.

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

NASA Astrophysics Data System (ADS)

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.

Depletion forces drive polymer-like self-assembly in vibrofluidized granular materials†

PubMed Central

Nossal, Ralph

2011-01-01

Ranging from nano- to granular-scales, control of particle assembly can be achieved by limiting the available free space, for example by increasing the concentration of particles (“crowding”) or through their restriction to 2D environments. It is unclear, however, if self-assembly principles governing thermally-equilibrated molecules can also apply to mechanically-excited macroscopic particles in non-equilibrium steady-state. Here we show that low densities of vibrofluidized steel rods, when crowded by high densities of spheres and confined to quasi-2D planes, can self-assemble into linear polymer-like structures. Our 2D Monte Carlo simulations show similar finite sized aggregates in thermally equilibrated binary mixtures. Using theory and simulations, we demonstrate how depletion interactions create oriented “binding” forces between rigid rods to form these “living polymers.” Unlike rod-sphere mixtures in 3D that can demonstrate well-defined equilibrium phases, our mixtures confined to 2D lack these transitions because lower dimensionality favors the formation of linear aggregates, thus suppressing a true phase transition. The qualitative and quantitative agreement between equilibrium and granular patterning for these mixtures suggests that entropy maximization is the determining driving force for bundling. Furthermore, this study uncovers a previously unknown patterning behavior at both the granular and nanoscales, and may provide insights into the role of crowding at interfaces in molecular assembly. PMID:22039392

Simulation of linear mechanical systems

NASA Technical Reports Server (NTRS)

Sirlin, S. W.

1993-01-01

A dynamics and controls analyst is typically presented with a structural dynamics model and must perform various input/output tests and design control laws. The required time/frequency simulations need to be done many times as models change and control designs evolve. This paper examines some simple ways that open and closed loop frequency and time domain simulations can be done using the special structure of the system equations usually available. Routines were developed to run under Pro-Matlab in a mixture of the Pro-Matlab interpreter and FORTRAN (using the .mex facility). These routines are often orders of magnitude faster than trying the typical 'brute force' approach of using built-in Pro-Matlab routines such as bode. This makes the analyst's job easier since not only does an individual run take less time, but much larger models can be attacked, often allowing the whole model reduction step to be eliminated.

Relationships of soil, grass, and bedrock over the Kaweah Serpentinite Melange through spectral mixture analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Mustard, John F.

1993-01-01

A linear mixing model is used to model the spectral variability of an AVIRIS scene from the western foothills of the Sierra Nevada and calibrate these radiance data to reflectance. Five spectral endmembers from the AVIRIS data, plus an ideal 'shade' endmember were required to model the continuum reflectance of each pixel in the image. Three of the endmembers were interpreted to model the surface constituents green vegetation, dry grass, and illumination. Comparison of the fraction images to the bedrock geology maps indicates that substrate composition must be a factor contributing to the spectral properties of these endmembers. Detailed examination of the reflectance spectra of the three soil endmembers reveals that differences in the amount of ferric and ferrous iron and/or organic constituents in the soils is largely responsible for the differences in spectral properties of these endmembers.

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

NASA Astrophysics Data System (ADS)

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.

ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

PubMed Central

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

2014-01-01

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. PMID:24992156

Detonation Shock Dynamics Calibration for Non-Ideal He: Anfo

NASA Astrophysics Data System (ADS)

Short, Mark; Salyer, Terry R.; Aslam, Tariq D.; Kiyanda, Charles B.; Morris, John S.; Zimmerly, Tony

2009-12-01

Linear Dn-κ detonation shock dynamics (DSD) fitting forms are obtained for four ammonium nitrate-fuel oil (ANFO) mixtures involving variations in the ammonium nitrate prill properties and ANFO stoichiometries.

Applicability study of classical and contemporary models for effective complex permittivity of metal powders.

PubMed

Kiley, Erin M; Yakovlev, Vadim V; Ishizaki, Kotaro; Vaucher, Sebastien

2012-01-01

Microwave thermal processing of metal powders has recently been a topic of a substantial interest; however, experimental data on the physical properties of mixtures involving metal particles are often unavailable. In this paper, we perform a systematic analysis of classical and contemporary models of complex permittivity of mixtures and discuss the use of these models for determining effective permittivity of dielectric matrices with metal inclusions. Results from various mixture and core-shell mixture models are compared to experimental data for a titanium/stearic acid mixture and a boron nitride/graphite mixture (both obtained through the original measurements), and for a tungsten/Teflon mixture (from literature). We find that for certain experiments, the average error in determining the effective complex permittivity using Lichtenecker's, Maxwell Garnett's, Bruggeman's, Buchelnikov's, and Ignatenko's models is about 10%. This suggests that, for multiphysics computer models describing the processing of metal powder in the full temperature range, input data on effective complex permittivity obtained from direct measurement has, up to now, no substitute.

Modeling and analysis of personal exposures to VOC mixtures using copulas

PubMed Central

Su, Feng-Chiao; Mukherjee, Bhramar; Batterman, Stuart

2014-01-01

Environmental exposures typically involve mixtures of pollutants, which must be understood to evaluate cumulative risks, that is, the likelihood of adverse health effects arising from two or more chemicals. This study uses several powerful techniques to characterize dependency structures of mixture components in personal exposure measurements of volatile organic compounds (VOCs) with aims of advancing the understanding of environmental mixtures, improving the ability to model mixture components in a statistically valid manner, and demonstrating broadly applicable techniques. We first describe characteristics of mixtures and introduce several terms, including the mixture fraction which represents a mixture component's share of the total concentration of the mixture. Next, using VOC exposure data collected in the Relationship of Indoor Outdoor and Personal Air (RIOPA) study, mixtures are identified using positive matrix factorization (PMF) and by toxicological mode of action. Dependency structures of mixture components are examined using mixture fractions and modeled using copulas, which address dependencies of multiple variables across the entire distribution. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) are evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks are calculated for mixtures, and results from copulas and multivariate lognormal models are compared to risks calculated using the observed data. Results obtained using the RIOPA dataset showed four VOC mixtures, representing gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection by-products, and cleaning products and odorants. Often, a single compound dominated the mixture, however, mixture fractions were generally heterogeneous in that the VOC composition of the mixture changed with concentration. Three mixtures were identified by mode of action, representing VOCs associated with hematopoietic, liver and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10−3 for about 10% of RIOPA participants. Factors affecting the likelihood of high concentration mixtures included city, participant ethnicity, and house air exchange rates. The dependency structures of the VOC mixtures fitted Gumbel (two mixtures) and t (four mixtures) copulas, types that emphasize tail dependencies. Significantly, the copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy, and performed better than multivariate lognormal distributions. Copulas may be the method of choice for VOC mixtures, particularly for the highest exposures or extreme events, cases that poorly fit lognormal distributions and that represent the greatest risks. PMID:24333991

Evaluating Vegetation Type Effects on Land Surface Temperature at the City Scale

NASA Astrophysics Data System (ADS)

Wetherley, E. B.; McFadden, J. P.; Roberts, D. A.

2017-12-01

Understanding the effects of different plant functional types and urban materials on surface temperatures has significant consequences for climate modeling, water management, and human health in cities. To date, doing so at the urban scale has been complicated by small-scale surface heterogeneity and limited data. In this study we examined gradients of land surface temperature (LST) across sub-pixel mixtures of different vegetation types and urban materials across the entire Los Angeles, CA, metropolitan area (4,283 km2). We used AVIRIS airborne hyperspectral imagery (36 m resolution, 224 bands, 0.35 - 2.5 μm) to estimate sub-pixel fractions of impervious, pervious, tree, and turfgrass surfaces, validating them with simulated mixtures constructed from image spectra. We then used simultaneously imaged LST retrievals collected at multiple times of day to examine how temperature changed along gradients of the sub-pixel mixtures. Diurnal in situ LST measurements were used to confirm image values. Sub-pixel fractions were well correlated with simulated validation data for turfgrass (r2 = 0.71), tree (r2 = 0.77), impervious (r2 = 0.77), and pervious (r2 = 0.83) surfaces. The LST of pure pixels showed the effects of both the diurnal cycle and the surface type, with vegetated classes having a smaller diurnal temperature range of 11.6°C whereas non-vegetated classes had a diurnal range of 16.2°C (similar to in situ measurements collected simultaneously with the imagery). Observed LST across fractional gradients of turf/impervious and tree/impervious sub-pixel mixtures decreased linearly with increasing vegetation fraction. The slopes of decreasing LST were significantly different between tree and turf mixtures, with steeper slopes observed for turf (p < 0.05). These results suggest that different physiological characteristics and different access to irrigation water of urban trees and turfgrass results in significantly different LST effects, which can be detected at large scales in fractional mixture analysis.

Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography.

PubMed

Andrić, Filip; Šegan, Sandra; Dramićanin, Aleksandra; Majstorović, Helena; Milojković-Opsenica, Dušanka

2016-08-05

Soil-water partition coefficient normalized to the organic carbon content (KOC) is one of the crucial properties influencing the fate of organic compounds in the environment. Chromatographic methods are well established alternative for direct sorption techniques used for KOC determination. The present work proposes reversed-phase thin-layer chromatography (RP-TLC) as a simpler, yet equally accurate method as officially recommended HPLC technique. Several TLC systems were studied including octadecyl-(RP18) and cyano-(CN) modified silica layers in combination with methanol-water and acetonitrile-water mixtures as mobile phases. In total 50 compounds of different molecular shape, size, and various ability to establish specific interactions were selected (phenols, beznodiazepines, triazine herbicides, and polyaromatic hydrocarbons). Calibration set of 29 compounds with known logKOC values determined by sorption experiments was used to build simple univariate calibrations, Principal Component Regression (PCR) and Partial Least Squares (PLS) models between logKOC and TLC retention parameters. Models exhibit good statistical performance, indicating that CN-layers contribute better to logKOC modeling than RP18-silica. The most promising TLC methods, officially recommended HPLC method, and four in silico estimation approaches have been compared by non-parametric Sum of Ranking Differences approach (SRD). The best estimations of logKOC values were achieved by simple univariate calibration of TLC retention data involving CN-silica layers and moderate content of methanol (40-50%v/v). They were ranked far well compared to the officially recommended HPLC method which was ranked in the middle. The worst estimates have been obtained from in silico computations based on octanol-water partition coefficient. Linear Solvation Energy Relationship study revealed that increased polarity of CN-layers over RP18 in combination with methanol-water mixtures is the key to better modeling of logKOC through significant diminishing of dipolar and proton accepting influence of the mobile phase as well as enhancing molar refractivity in excess of the chromatographic systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation and Model Selection for Finite Mixtures of Latent Interaction Models

ERIC Educational Resources Information Center

Hsu, Jui-Chen

2011-01-01

Latent interaction models and mixture models have received considerable attention in social science research recently, but little is known about how to handle if unobserved population heterogeneity exists in the endogenous latent variables of the nonlinear structural equation models. The current study estimates a mixture of latent interaction…

Scale Mixture Models with Applications to Bayesian Inference

NASA Astrophysics Data System (ADS)

Qin, Zhaohui S.; Damien, Paul; Walker, Stephen

2003-11-01

Scale mixtures of uniform distributions are used to model non-normal data in time series and econometrics in a Bayesian framework. Heteroscedastic and skewed data models are also tackled using scale mixture of uniform distributions.

Structural distinction of diacyl-, alkylacyl, and alk-1-enylacyl glycerophosphocholines as [M - 15]⁻ ions by multiple-stage linear ion-trap mass spectrometry with electrospray ionization.

PubMed

Hsu, Fong-Fu; Lodhi, Irfan J; Turk, John; Semenkovich, Clay F

2014-08-01

We describe a linear ion-trap (LIT) multiple-stage (MS(n)) mass spectrometric approach towards differentiation of alkylacyl, alk-1-enylacyl- and diacyl-glycerophoscholines (PCs) as the [M - 15]⁻ ions desorbed by electrospray ionization (ESI) in the negative-ion mode. The MS⁴ mass spectra of the [M - 15 - R²'CH = CO]⁻ ions originated from the three PC subfamilies are readily distinguishable, resulting in unambiguous distinction of the lipid classes. This method is applied to two alkyl ether rich PC mixtures isolated from murine bone marrow neutrophils and kidney, respectively, to explore its utility in the characterization of complex PC mixture of biological origin, resulting in the realization of the detailed structures of the PC species, including various classes and many minor isobaric isomers.

A two phase Mach number description of the equilibrium flow of nitrogen in ducts

NASA Technical Reports Server (NTRS)

Bursik, J. W.; Hall, R. M.; Adcock, J. B.

1979-01-01

Some additional thermodynamic properties of the usual two-phase form which is linear in the moisture fraction are derived which are useful in the analysis of many kinds of duct flow. The method used is based on knowledge of the vapor pressure and Gibbs function as functions of temperature. With these, additional two-phase functions linear in moisture fraction are generated, which ultimately reveal that the squared ratio of mixture specific volume to mixture sound speed depends on liquid mass fraction and temperature in the same manner as do many weighted mean two-phase properties. This leads to a simple method of calculating two-phase Mach numbers for various duct flows. The matching of one- and two-phase flows at a saturated vapor point with discontinuous Mach number is also discussed.

Co-pyrolysis characteristics and kinetic analysis of organic food waste and plastic.

PubMed

Tang, Yijing; Huang, Qunxing; Sun, Kai; Chi, Yong; Yan, Jianhua

2018-02-01

In this work, typical organic food waste (soybean protein (SP)) and typical chlorine enriched plastic waste (polyvinyl chloride (PVC)) were chosen as principal MSW components and their interaction during co-pyrolysis was investigated. Results indicate that the interaction accelerated the reaction during co-pyrolysis. The activation energies needed were 2-13% lower for the decomposition of mixture compared with linear calculation while the maximum reaction rates were 12-16% higher than calculation. In the fixed-bed experiments, interaction was observed to reduce the yield of tar by 2-69% and promote the yield of char by 13-39% compared with linear calculation. In addition, 2-6 times more heavy components and 61-93% less nitrogen-containing components were formed for tar derived from mixtures. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

PubMed

Qin, Li-Tang; Chen, Yu-Han; Zhang, Xin; Mo, Ling-Yun; Zeng, Hong-Hu; Liang, Yan-Peng

2018-05-01

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC 50 ) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Cuticular hydrocarbons as a tool for the identification of insect species: Puparial cases from Sarcophagidae

PubMed Central

Braga, Marina Vianna; Pinto, Zeneida Teixeira; de Carvalho Queiroz, Margareth Maria; Matsumoto, Nana; Blomquist, Gary James

2013-01-01

The external surface of all insects is covered by a species-specific complex mixture of highly stable, very long chain cuticular hydrocarbons (CHCs). Gas chromatography coupled to mass spectrometry was used to identify CHCs from four species of Sarcophagidae, Peckia (Peckia) chrysostoma, Peckia (Pattonella) intermutans, Sarcophaga (Liopygia) ruficornis and Sarcodexia lambens. The identified CHCs were mostly a mixture of n-alkanes, monomethylalkanes and dimethylalkanes with linear chain lengths varying from 23 to 33 carbons. Only two alkenes were found in all four species. S. lambens had a composition of CHCs with linear chain lengths varying from C23 to C33, while the other three species linear chain lengths from 24 to 31 carbons. n-Heptacosane, n-nonacosane and 3-methylnonacosane, n-triacontane and n-hentriacontane occurred in all four species. The results show that these hydrocarbon profiles may be used for the taxonomic differentiation of insect species and are a useful additional tool for taxonomic classification, especially when only parts of the insect specimen are available. PMID:23932943

Biodiesel production from triolein and short chain alcohols through biocatalysis.

PubMed

Salis, Andrea; Pinna, Marcella; Monduzzi, Maura; Solinas, Vincenzo

2005-09-29

Oleic acid alkyl esters (biodiesel) were synthesised by biocatalysis in solvent-free conditions. Different commercial immobilised lipases, namely Candida antarctica B, Rizhomucor miehei, and Pseudomonas cepacia, were tested towards the reaction between triolein and butanol to produce butyl oleate. Pseudomonas cepacia lipase resulted to be the most active enzyme reaching 100% of conversion after 6h. Different operative conditions such as reaction temperature, water activity, and reagent stoichiometric ratio were investigated and optimised. These conditions were then used to investigate the effect of linear and branched short chain alcohols. Methanol and 2-butanol were the worst alcohols: the former, probably, due to its low miscibility with the oil and the latter because secondary alcohols usually are less reactive than primary alcohols. Conversely, linear and branched primary alcohols with short alkyl chains (C(2)--C(4)) showed high reaction rate and conversion. A mixture of linear and branched short chain alcohols that mimics the residual of ethanol distillation (fusel oil) was successfully used for oleic acid ester synthesis. These compounds are important in biodiesel mixtures since they improve low temperature properties.

Dielectric constant of liquid alkanes and hydrocarbon mixtures

NASA Technical Reports Server (NTRS)

Sen, A. D.; Anicich, V. G.; Arakelian, T.

1992-01-01

The complex dielectric constants of n-alkanes with two to seven carbon atoms have been measured. The measurements were conducted using a slotted-line technique at 1.2 GHz and at atmospheric pressure. The temperature was varied from the melting point to the boiling point of the respective alkanes. The real part of the dielectric constant was found to decrease with increasing temperature and correlate with the change in the molar volume. An upper limit to all the loss tangents was established at 0.001. The complex dielectric constants of a few mixtures of liquid alkanes were also measured at room temperature. For a pentane-octane mixture the real part of the dielectric constant could be explained by the Clausius-Mosotti theory. For the mixtures of n-hexane-ethylacetate and n-hexane-acetone the real part of the dielectric constants could be explained by the Onsager theory extended to mixtures. The dielectric constant of the n-hexane-acetone mixture displayed deviations from the Onsager theory at the highest fractions of acetone. The dipole moments of ethylacetate and acetone were determined for dilute mixtures using the Onsager theory and were found to be in agreement with their accepted gas-phase values. The loss tangents of the mixtures exhibited a linear relationship with the volume fraction for low concentrations of the polar liquids.

Dielectric and conformational studies of hydrogen bonded 2-ethoxyethanol and ethyl methyl ketone system

NASA Astrophysics Data System (ADS)

Pattebahadur, Kanchan. L.; Deshmukh, S. D.; Mohod, A. G.; Undre, P. B.; Patil, S. S.; Khirade, P. W.

2018-05-01

The Dielectric constant, density and refractive index of binary mixture of 2-ethoxy ethanol (2-EE) with ethyl methyl ketone (EMK) including those of the pure liquids were measured for 11 concentrations at 25°C temperature. The experimental data is used to calculate the Excess molar volume, Excess dielectric constant, Kirkwood correlation factor and Bruggemann factor. The excess parameters results were fitted to the Redlich-Kister type polynomial equation to derive its fitting coefficient. The Kirkwood correlation factor of the mixture has been discussed to yield information about solute solvent interaction. The Bruggeman plot shows a deviation from linearity. The FT-IR spectra of pure and their binary mixtures are also studied.

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

ERIC Educational Resources Information Center

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,…

Robust nonlinear system identification: Bayesian mixture of experts using the t-distribution

NASA Astrophysics Data System (ADS)

Baldacchino, Tara; Worden, Keith; Rowson, Jennifer

2017-02-01

A novel variational Bayesian mixture of experts model for robust regression of bifurcating and piece-wise continuous processes is introduced. The mixture of experts model is a powerful model which probabilistically splits the input space allowing different models to operate in the separate regions. However, current methods have no fail-safe against outliers. In this paper, a robust mixture of experts model is proposed which consists of Student-t mixture models at the gates and Student-t distributed experts, trained via Bayesian inference. The Student-t distribution has heavier tails than the Gaussian distribution, and so it is more robust to outliers, noise and non-normality in the data. Using both simulated data and real data obtained from the Z24 bridge this robust mixture of experts performs better than its Gaussian counterpart when outliers are present. In particular, it provides robustness to outliers in two forms: unbiased parameter regression models, and robustness to overfitting/complex models.

Development and validation of a metal mixture bioavailability model (MMBM) to predict chronic toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia.

PubMed

Nys, Charlotte; Janssen, Colin R; De Schamphelaere, Karel A C

2017-01-01

Recently, several bioavailability-based models have been shown to predict acute metal mixture toxicity with reasonable accuracy. However, the application of such models to chronic mixture toxicity is less well established. Therefore, we developed in the present study a chronic metal mixture bioavailability model (MMBM) by combining the existing chronic daphnid bioavailability models for Ni, Zn, and Pb with the independent action (IA) model, assuming strict non-interaction between the metals for binding at the metal-specific biotic ligand sites. To evaluate the predictive capacity of the MMBM, chronic (7d) reproductive toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia was investigated in four different natural waters (pH range: 7-8; Ca range: 1-2 mM; Dissolved Organic Carbon range: 5-12 mg/L). In each water, mixture toxicity was investigated at equitoxic metal concentration ratios as well as at environmental (i.e. realistic) metal concentration ratios. Statistical analysis of mixture effects revealed that observed interactive effects depended on the metal concentration ratio investigated when evaluated relative to the concentration addition (CA) model, but not when evaluated relative to the IA model. This indicates that interactive effects observed in an equitoxic experimental design cannot always be simply extrapolated to environmentally realistic exposure situations. Generally, the IA model predicted Ni-Zn-Pb mixture toxicity more accurately than the CA model. Overall, the MMBM predicted Ni-Zn-Pb mixture toxicity (expressed as % reproductive inhibition relative to a control) in 85% of the treatments with less than 20% error. Moreover, the MMBM predicted chronic toxicity of the ternary Ni-Zn-Pb mixture at least equally accurately as the toxicity of the individual metal treatments (RMSE Mix  = 16; RMSE Zn only  = 18; RMSE Ni only  = 17; RMSE Pb only  = 23). Based on the present study, we believe MMBMs can be a promising tool to account for the effects of water chemistry on metal mixture toxicity during chronic exposure and could be used in metal risk assessment frameworks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mixtures of bosonic and fermionic atoms in optical lattices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albus, Alexander; Dipartimento di Fisica, Universita di Salerno, Via S. Allende, I-84081 Baronissi; Illuminati, Fabrizio

2003-08-01

We discuss the theory of mixtures of bosonic and fermionic atoms in periodic potentials at zero temperature. We derive a general Bose-Fermi Hubbard Hamiltonian in a one-dimensional optical lattice with a superimposed harmonic trapping potential. We study the conditions for linear stability of the mixture and derive a mean-field criterion for the onset of a bosonic superfluid transition. We investigate the ground-state properties of the mixture in the Gutzwiller formulation of mean-field theory, and present numerical studies of finite systems. The bosonic and fermionic density distributions and the onset of quantum phase transitions to demixing and to a bosonic Mott-insulatormore » are studied as a function of the lattice potential strength. The existence is predicted of a disordered phase for mixtures loaded in very deep lattices. Such a disordered phase possessing many degenerate or quasidegenerate ground states is related to a breaking of the mirror symmetry in the lattice.« less

Mixtures of tense and relaxed state polymerized human hemoglobin regulate oxygen affinity and tissue construct oxygenation

PubMed Central

Belcher, Donald Andrew; Banerjee, Uddyalok; Baehr, Christopher Michael; Richardson, Kristopher Emil; Cabrales, Pedro; Berthiaume, François

2017-01-01

Pure tense (T) and relaxed (R) quaternary state polymerized human hemoglobins (PolyhHbs) were synthesized and their biophysical properties characterized, along with mixtures of T- and R-state PolyhHbs. It was observed that the oxygen affinity of PolyhHb mixtures varied linearly with T-state mole fraction. Computational analysis of PolyhHb facilitated oxygenation of a single fiber in a hepatic hollow fiber (HF) bioreactor was performed to evaluate the oxygenation potential of T- and R-state PolyhHb mixtures. PolyhHb mixtures with T-state mole fractions greater than 50% resulted in hypoxic and hyperoxic zones occupying less than 5% of the total extra capillary space (ECS). Under these conditions, the ratio of the pericentral volume to the perivenous volume in the ECS doubled as the T-state mole fraction increased from 50 to 100%. These results show the effect of varying the T/R-state PolyhHb mole fraction on oxygenation of tissue-engineered constructs and their potential to oxygenate tissues. PMID:29020036

Hydride compositions

DOEpatents

Lee, Myung W.

1995-01-01

A composition for use in storing hydrogen, and a method for making the composition. The composition comprises a mixture of two or more hydrides, each hydride having a different series of hydrogen sorption isotherms that contribute to the overall isotherms of the mixture. The hydrides are chosen so that the isotherms of the mixture have regions wherein the hydrogen equilibrium pressure increases with increasing hydrogen, preferably linearly. The isotherms of the mixture can be adjusted by selecting hydrides with different isotherms and by varying the amounts of the individual hydrides, or both. Preferably, the mixture is made up of hydrides that have isotherms with substantially flat plateaus and in nearly equimolar amounts. The composition is activated by degassing, exposing to hydrogen and then heating at a temperature below the softening temperature of any of the. constituents so that their chemical and structural integrity is preserved. When the composition is used to store hydrogen, its hydrogen content can be found simply by measuring P.sub.H.sbsb.2 and determining H/M from the isothermic function of the composition.

Hydride compositions

DOEpatents

Lee, Myung, W.

1994-01-01

Disclosed are a composition for use in storing hydrogen and a method for making the composition. The composition comprises a mixture of two or more hydrides, each hydride having a different series of hydrogen sorption isotherms that contribute to the overall isotherms of the mixture. The hydrides are chosen so that the isotherms of the mixture have regions wherein the H equilibrium pressure increases with increasing hydrogen, preferably linearly. The isotherms of the mixture can be adjusted by selecting hydrides with different isotherms and by varying the amounts of the individual hydrides, or both. Preferably, the mixture is made up of hydrides that have isotherms with substantially flat plateaus and in nearly equimolar amounts. The composition is activated by degassing, exposing to H, and then heating below the softening temperature of any of the constituents. When the composition is used to store hydrogen, its hydrogen content can be found simply by measuring P{sub H}{sub 2} and determining H/M from the isothermic function of the composition.

Adhesion of Mineral and Soot Aerosols can Strongly Affect their Scattering and Absorption Properties

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Jana M.

2012-01-01

We use the numerically exact superposition T-matrix method to compute the optical cross sections and the Stokes scattering matrix for polydisperse mineral aerosols (modeled as homogeneous spheres) covered with a large number of much smaller soot particles. These results are compared with the Lorenz-Mie results for a uniform external mixture of mineral and soot aerosols. We show that the effect of soot particles adhering to large mineral particles can be to change the extinction and scattering cross sections and the asymmetry parameter quite substantially. The effect on the phase function and degree of linear polarization can be equally significant.

A practically unconditionally gradient stable scheme for the N-component Cahn-Hilliard system

NASA Astrophysics Data System (ADS)

Lee, Hyun Geun; Choi, Jeong-Whan; Kim, Junseok

2012-02-01

We present a practically unconditionally gradient stable conservative nonlinear numerical scheme for the N-component Cahn-Hilliard system modeling the phase separation of an N-component mixture. The scheme is based on a nonlinear splitting method and is solved by an efficient and accurate nonlinear multigrid method. The scheme allows us to convert the N-component Cahn-Hilliard system into a system of N-1 binary Cahn-Hilliard equations and significantly reduces the required computer memory and CPU time. We observe that our numerical solutions are consistent with the linear stability analysis results. We also demonstrate the efficiency of the proposed scheme with various numerical experiments.

Quadratic Blind Linear Unmixing: A Graphical User Interface for Tissue Characterization

PubMed Central

Gutierrez-Navarro, O.; Campos-Delgado, D.U.; Arce-Santana, E. R.; Jo, Javier A.

2016-01-01

Spectral unmixing is the process of breaking down data from a sample into its basic components and their abundances. Previous work has been focused on blind unmixing of multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) datasets under a linear mixture model and quadratic approximations. This method provides a fast linear decomposition and can work without a limitation in the maximum number of components or end-members. Hence this work presents an interactive software which implements our blind end-member and abundance extraction (BEAE) and quadratic blind linear unmixing (QBLU) algorithms in Matlab. The options and capabilities of our proposed software are described in detail. When the number of components is known, our software can estimate the constitutive end-members and their abundances. When no prior knowledge is available, the software can provide a completely blind solution to estimate the number of components, the end-members and their abundances. The characterization of three case studies validates the performance of the new software: ex-vivo human coronary arteries, human breast cancer cell samples, and in-vivo hamster oral mucosa. The software is freely available in a hosted webpage by one of the developing institutions, and allows the user a quick, easy-to-use and efficient tool for multi/hyper-spectral data decomposition. PMID:26589467

Quadratic blind linear unmixing: A graphical user interface for tissue characterization.

PubMed

Gutierrez-Navarro, O; Campos-Delgado, D U; Arce-Santana, E R; Jo, Javier A

2016-02-01

Spectral unmixing is the process of breaking down data from a sample into its basic components and their abundances. Previous work has been focused on blind unmixing of multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) datasets under a linear mixture model and quadratic approximations. This method provides a fast linear decomposition and can work without a limitation in the maximum number of components or end-members. Hence this work presents an interactive software which implements our blind end-member and abundance extraction (BEAE) and quadratic blind linear unmixing (QBLU) algorithms in Matlab. The options and capabilities of our proposed software are described in detail. When the number of components is known, our software can estimate the constitutive end-members and their abundances. When no prior knowledge is available, the software can provide a completely blind solution to estimate the number of components, the end-members and their abundances. The characterization of three case studies validates the performance of the new software: ex-vivo human coronary arteries, human breast cancer cell samples, and in-vivo hamster oral mucosa. The software is freely available in a hosted webpage by one of the developing institutions, and allows the user a quick, easy-to-use and efficient tool for multi/hyper-spectral data decomposition. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Soret motion in non-ionic binary molecular mixtures

NASA Astrophysics Data System (ADS)

Leroyer, Yves; Würger, Alois

2011-08-01

We study the Soret coefficient of binary molecular mixtures with dispersion forces. Relying on standard transport theory for liquids, we derive explicit expressions for the thermophoretic mobility and the Soret coefficient. Their sign depends on composition, the size ratio of the two species, and the ratio of Hamaker constants. Our results account for several features observed in experiment, such as a linear variation with the composition; they confirm the general rule that small molecules migrate to the warm, and large ones to the cold.

Rasch Mixture Models for DIF Detection

PubMed Central

Strobl, Carolin; Zeileis, Achim

2014-01-01

Rasch mixture models can be a useful tool when checking the assumption of measurement invariance for a single Rasch model. They provide advantages compared to manifest differential item functioning (DIF) tests when the DIF groups are only weakly correlated with the manifest covariates available. Unlike in single Rasch models, estimation of Rasch mixture models is sensitive to the specification of the ability distribution even when the conditional maximum likelihood approach is used. It is demonstrated in a simulation study how differences in ability can influence the latent classes of a Rasch mixture model. If the aim is only DIF detection, it is not of interest to uncover such ability differences as one is only interested in a latent group structure regarding the item difficulties. To avoid any confounding effect of ability differences (or impact), a new score distribution for the Rasch mixture model is introduced here. It ensures the estimation of the Rasch mixture model to be independent of the ability distribution and thus restricts the mixture to be sensitive to latent structure in the item difficulties only. Its usefulness is demonstrated in a simulation study, and its application is illustrated in a study of verbal aggression. PMID:29795819

Investigating Stage-Sequential Growth Mixture Models with Multiphase Longitudinal Data

ERIC Educational Resources Information Center

Kim, Su-Young; Kim, Jee-Seon

2012-01-01

This article investigates three types of stage-sequential growth mixture models in the structural equation modeling framework for the analysis of multiple-phase longitudinal data. These models can be important tools for situations in which a single-phase growth mixture model produces distorted results and can allow researchers to better understand…

Mixture Modeling: Applications in Educational Psychology

ERIC Educational Resources Information Center

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…

Development and validation of chemometrics-assisted spectrophotometric and liquid chromatographic methods for the simultaneous determination of two multicomponent mixtures containing bronchodilator drugs.

PubMed

El-Gindy, Alaa; Emara, Samy; Shaaban, Heba

2007-02-19

Three methods are developed for the determination of two multicomponent mixtures containing guaiphenesine (GU) with salbutamol sulfate (SL), methylparaben (MP) and propylparaben (PP) [mixture 1]; and acephylline piperazine (AC) with bromhexine hydrochloride (BX), methylparaben (MP) and propylparaben (PP) [mixture 2]. The resolution of the two multicomponent mixtures has been accomplished by using numerical spectrophotometric methods such as partial least squares (PLS-1) and principal component regression (PCR) applied to UV absorption spectra of the two mixtures. In addition HPLC method was developed using a RP 18 column at ambient temperature with mobile phase consisting of acetonitrile-0.05 M potassium dihydrogen phosphate, pH 4.3 (60:40, v/v), with UV detection at 243 nm for mixture 1, and mobile phase consisting of acetonitrile-0.05 M potassium dihydrogen phosphate, pH 3 (50:50, v/v), with UV detection at 245 nm for mixture 2. The methods were validated in terms of accuracy, specificity, precision and linearity in the range of 20-60 microg ml(-1) for GU, 1-3 microg ml(-1) for SL, 20-80 microg ml(-1) for AC, 0.2-1.8 microgml(-1) for PP and 1-5 microg ml(-1) for BX and MP. The proposed methods were successfully applied for the determination of the two multicomponent combinations in laboratory prepared mixtures and commercial syrups.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

PubMed

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

VizieR Online Data Catalog: Supernova matter EOS (Buyukcizmeci+, 2014)

NASA Astrophysics Data System (ADS)

Buyukcizmeci, N.; Botvina, A. S.; Mishustin, I. N.

2017-03-01

The Statistical Model for Supernova Matter (SMSM) was developed in Botvina & Mishustin (2004, PhLB, 584, 233 ; 2010, NuPhA, 843, 98) as a direct generalization of the Statistical Multifragmentation Model (SMM; Bondorf et al. 1995, PhR, 257, 133). We treat supernova matter as a mixture of nuclear species, electrons, and photons in statistical equilibrium. The SMSM EOS tables cover the following ranges of control parameters: 1. Temperature: T = 0.2-25 MeV; for 35 T values. 2. Electron fraction Ye: 0.02-0.56; linear mesh of Ye = 0.02, giving 28 Ye values. It is equal to the total proton fraction Xp, due to charge neutrality. 3. Baryon number density fraction {rho}/{rho}0 = (10-8-0.32), giving 31 {rho}/{rho}0 values. (2 data files).

Increase in Dye:Dendrimer Ratio Decreases Cellular Uptake of Neutral Dendrimers in RAW Cells.

PubMed

Vaidyanathan, Sriram; Kaushik, Milan; Dougherty, Casey; Rattan, Rahul; Goonewardena, Sascha N; Banaszak Holl, Mark M; Monano, Janet; DiMaggio, Stassi

2016-09-12

Neutral generation 3 poly(amidoamine) dendrimers were labeled with Oregon Green 488 (G3-OG n ) to obtain materials with controlled fluorophore:dendrimer ratios (n = 1-2), a mixture containing mostly 3 dyes per dendrimer, a mixture containing primarily 4 or more dyes per dendrimer ( n = 4+), and a stochastic mixture ( n = 4 avg ). The UV absorbance of the dye conjugates increased linearly as n increased and the fluorescence emission decreased linearly as n increased. Cellular uptake was studied in RAW cells and HEK 293A cells as a function of the fluorophore:dendrimer ratio (n). The cellular uptake of G3-OG n ( n = 3, 4+, 4 avg ) into RAW cells was significantly lower than G3-OG n ( n = 1, 2). The uptake of G3-OG n ( n = 3, 4+, 4 avg ) into HEK 293A cells was not significantly different from G3-OG 1 . Thus, the fluorophore:dendrimer ratio was observed to change the extent of uptake in the macrophage uptake mechanism but not in the HEK 293A cell. This difference in endocytosis indicates the presence of a pathway in the macrophage that is sensitive to hydrophobicity of the particle.

Calibrating AIS images using the surface as a reference

NASA Technical Reports Server (NTRS)

Smith, M. O.; Roberts, D. A.; Shipman, H. M.; Adams, J. B.; Willis, S. C.; Gillespie, A. R.

1987-01-01

A method of evaluating the initial assumptions and uncertainties of the physical connection between Airborne Imaging Spectrometer (AIS) image data and laboratory/field spectrometer data was tested. The Tuscon AIS-2 image connects to lab reference spectra by an alignment to the image spectral endmembers through a system gain and offset for each band. Images were calibrated to reflectance so as to transform the image into a measure that is independent of the solar radiant flux. This transformation also makes the image spectra directly comparable to data from lab and field spectrometers. A method was tested for calibrating AIS images using the surface as a reference. The surface heterogeneity is defined by lab/field spectral measurements. It was found that the Tuscon AIS-2 image is consistent with each of the initial hypotheses: (1) that the AIS-2 instrument calibration is nearly linear; (2) the spectral variance is caused by sub-pixel mixtures of spectrally distinct materials and shade, and (3) that sub-pixel mixtures can be treated as linear mixtures of pure endmembers. It was also found that the image can be characterized by relatively few endmembers using the AIS-2 spectra.

Compressive Detection of Highly Overlapped Spectra Using Walsh-Hadamard-Based Filter Functions.

PubMed

Corcoran, Timothy C

2018-03-01

In the chemometric context in which spectral loadings of the analytes are already known, spectral filter functions may be constructed which allow the scores of mixtures of analytes to be determined in on-the-fly fashion directly, by applying a compressive detection strategy. Rather than collecting the entire spectrum over the relevant region for the mixture, a filter function may be applied within the spectrometer itself so that only the scores are recorded. Consequently, compressive detection shrinks data sets tremendously. The Walsh functions, the binary basis used in Walsh-Hadamard transform spectroscopy, form a complete orthonormal set well suited to compressive detection. A method for constructing filter functions using binary fourfold linear combinations of Walsh functions is detailed using mathematics borrowed from genetic algorithm work, as a means of optimizing said functions for a specific set of analytes. These filter functions can be constructed to automatically strip the baseline from analysis. Monte Carlo simulations were performed with a mixture of four highly overlapped Raman loadings and with ten excitation-emission matrix loadings; both sets showed a very high degree of spectral overlap. Reasonable estimates of the true scores were obtained in both simulations using noisy data sets, proving the linearity of the method.

Reduction of chemical formulas from the isotopic peak distributions of high-resolution mass spectra.

PubMed

Roussis, Stilianos G; Proulx, Richard

2003-03-15

A method has been developed for the reduction of the chemical formulas of compounds in complex mixtures from the isotopic peak distributions of high-resolution mass spectra. The method is based on the principle that the observed isotopic peak distribution of a mixture of compounds is a linear combination of the isotopic peak distributions of the individual compounds in the mixture. All possible chemical formulas that meet specific criteria (e.g., type and number of atoms in structure, limits of unsaturation, etc.) are enumerated, and theoretical isotopic peak distributions are generated for each formula. The relative amount of each formula is obtained from the accurately measured isotopic peak distribution and the calculated isotopic peak distributions of all candidate formulas. The formulas of compounds in simple spectra, where peak components are fully resolved, are rapidly determined by direct comparison of the calculated and experimental isotopic peak distributions. The singular value decomposition linear algebra method is used to determine the contributions of compounds in complex spectra containing unresolved peak components. The principles of the approach and typical application examples are presented. The method is most useful for the characterization of complex spectra containing partially resolved peaks and structures with multiisotopic elements.

Temperature and pressure influence on explosion pressures of closed vessel propane-air deflagrations.

PubMed

Razus, Domnina; Brinzea, Venera; Mitu, Maria; Oancea, Dumitru

2010-02-15

An experimental study on pressure evolution during closed vessel explosions of propane-air mixtures was performed, for systems with various initial concentrations and pressures ([C(3)H(8)]=2.50-6.20 vol.%, p(0)=0.3-1.2 bar). The explosion pressures and explosion times were measured in a spherical vessel (Phi=10 cm), at various initial temperatures (T(0)=298-423 K) and in a cylindrical vessel (Phi=10 cm; h=15 cm), at ambient initial temperature. The experimental values of explosion pressures are examined against literature values and compared to adiabatic explosion pressures, computed by assuming chemical equilibrium within the flame front. The influence of initial pressure, initial temperature and fuel concentration on explosion pressures and explosion times are discussed. At constant temperature and fuel/oxygen ratio, the explosion pressures are linear functions of total initial pressure, as reported for other fuel-air mixtures. At constant initial pressure and composition, both the measured and calculated (adiabatic) explosion pressures are linear functions of reciprocal value of initial temperature. Such correlations are extremely useful for predicting the explosion pressures of flammable mixtures at elevated temperatures and/or pressures, when direct measurements are not available.

EPA Unmix 6.0 Fundamentals & User Guide

EPA Pesticide Factsheets

Unmix seeks to solve the general mixture problem where the data are assumed to be a linear combination of an unknown number of sources of unknown composition, which contribute an unknown amount to each sample.

Estimating aquatic toxicity as determined through laboratory tests of great lakes sediments containing complex mixtures of environmental contaminants

USGS Publications Warehouse

1996-01-01

We developed and evaluated a total toxic units modeling approach for predicting mean toxicity as measured in laboratory tests for Great Lakes sediments containing complex mixtures of environmental contaminants (e.g., polychlorinated biphenyls, polycyclic aromatic hydrocarbons, pesticides, chlorinated dioxins, and metals). The approach incorporates equilibrium partitioning and organic carbon control of bioavailability for organic contaminants and acid volatile sulfide (AVS) control for metals, and includes toxic equivalency for planar organic chemicals. A toxic unit is defined as the ratio of the estimated pore-water concentration of a contaminant to the chronic toxicity of that contaminant, as estimated by U.S. Environmental Protection Agency Ambient Water Quality Criteria (AWQC). The toxic unit models we developed assume complete additivity of contaminant effects, are completely mechanistic in form, and were evaluated without any a posteriori modification of either the models or the data from which the models were developed and against which they were tested. A linear relationship between total toxic units, which included toxicity attributable to both iron and un-ionized ammonia, accounted for about 88% of observed variability in mean toxicity; a quadratic relationship accounted for almost 94%. Exclusion of either bioavailability components (i.e., equilibrium partitioning control of organic contaminants and AVS control of metals) or iron from the model substantially decreased its ability to predict mean toxicity. A model based solely on un-ionized ammonia accounted for about 47% of the variability in mean toxicity. We found the toxic unit approach to be a viable method for assessing and ranking the relative potential toxicity of contaminated sediments.

Local Solutions in the Estimation of Growth Mixture Models

ERIC Educational Resources Information Center

Hipp, John R.; Bauer, Daniel J.

2006-01-01

Finite mixture models are well known to have poorly behaved likelihood functions featuring singularities and multiple optima. Growth mixture models may suffer from fewer of these problems, potentially benefiting from the structure imposed on the estimated class means and covariances by the specified growth model. As demonstrated here, however,…

Environmentally relevant pyrethroid mixtures: A study on the correlation of blood and brain concentrations of a mixture of pyrethroid insecticides to motor activity in the rat.

PubMed

Hughes, Michael F; Ross, David G; Starr, James M; Scollon, Edward J; Wolansky, Marcelo J; Crofton, Kevin M; DeVito, Michael J

2016-06-01

Human exposure to multiple pyrethroid insecticides may occur because of their broad use on crops and for residential pest control. To address the potential health risk from co-exposure to pyrethroids, it is important to understand their disposition and toxicity in target organs such as the brain, and surrogates such as the blood when administered as a mixture. The objective of this study was to assess the correlation between blood and brain concentrations of pyrethroids and neurobehavioral effects in the rat following an acute oral administration of the pyrethroids as a mixture. Male Long-Evans rats were administered a mixture of β-cyfluthrin, cypermethrin, deltamethrin, esfenvalerate and cis- and trans-permethrin in corn oil at seven dose levels. The pyrethroid with the highest percentage in the dosing solution was trans-permethrin (31% of total mixture dose) while deltamethrin and esfenvalerate had the lowest percentage (3%). Motor activity of the rats was then monitored for 1h. At 3.5h post-dosing, the animals were euthanized and blood and brain were collected. These tissues were extracted and analyzed for parent pyrethroid using HPLC-tandem mass spectrometry. Cypermethrin and cis-permethrin were the predominate pyrethroids detected in blood and brain, respectively, at all dosage levels. The relationship of total pyrethroid concentration between blood and brain was linear (r=0.93). The pyrethroids with the lowest fraction in blood were trans-permethrin and β-cyfluthrin and in brain were deltamethrin and esfenvalerate. The relationship between motor activity of the treated rats and summed pyrethroid blood and brain concentration was described using a sigmoidal Emax model with the Effective Concentration50 being more sensitive for brain than blood. The data suggests summed pyrethroid rat blood concentration could be used as a surrogate for brain concentration as an aid to study the neurotoxic effects of pyrethroids administered as a mixture under the conditions used in this study. Published by Elsevier Ireland Ltd.

New simple spectrophotometric method for determination of the binary mixtures (atorvastatin calcium and ezetimibe; candesartan cilexetil and hydrochlorothiazide) in tablets.

PubMed

Belal, Tarek S; Daabees, Hoda G; Abdel-Khalek, Magdi M; Mahrous, Mohamed S; Khamis, Mona M

2013-04-01

A new simple spectrophotometric method was developed for the determination of binary mixtures without prior separation. The method is based on the generation of ratio spectra of compound X by using a standard spectrum of compound Y as a divisor. The peak to trough amplitudes between two selected wavelengths in the ratio spectra are proportional to concentration of X without interference from Y . The method was demonstrated by determination of two drug combinations. The first consists of the two antihyperlipidemics: atorvastatin calcium (ATV) and ezetimibe (EZE), and the second comprises the antihypertensives: candesartan cilexetil (CAN) and hydrochlorothiazide (HCT). For mixture 1, ATV was determined using 10 μg/mL EZE as the divisor to generate the ratio spectra, and the peak to trough amplitudes between 231 and 276 nm were plotted against ATV concentration. Similarly, by using 10 μg/mL ATV as divisor, the peak to trough amplitudes between 231 and 276 nm were found proportional to EZE concentration. Calibration curves were linear in the range 2.5-40 μg/mL for both drugs. For mixture 2, divisor concentration was 7.5 μg/mL for both drugs. CAN was determined using its peak to trough amplitudes at 251 and 277 nm, while HCT was estimated using the amplitudes between 251 and 276 nm. The measured amplitudes were linearly correlated to concentration in the ranges 2.5-50 and 1-30 μg/mL for CAN and HCT, respectively. The proposed spectrophotometric method was validated and successfully applied for the assay of both drug combinations in several laboratory-prepared mixtures and commercial tablets.

New simple spectrophotometric method for determination of the binary mixtures (atorvastatin calcium and ezetimibe; candesartan cilexetil and hydrochlorothiazide) in tablets

PubMed Central

Belal, Tarek S.; Daabees, Hoda G.; Abdel-Khalek, Magdi M.; Mahrous, Mohamed S.; Khamis, Mona M.

2012-01-01

A new simple spectrophotometric method was developed for the determination of binary mixtures without prior separation. The method is based on the generation of ratio spectra of compound X by using a standard spectrum of compound Y as a divisor. The peak to trough amplitudes between two selected wavelengths in the ratio spectra are proportional to concentration of X without interference from Y. The method was demonstrated by determination of two drug combinations. The first consists of the two antihyperlipidemics: atorvastatin calcium (ATV) and ezetimibe (EZE), and the second comprises the antihypertensives: candesartan cilexetil (CAN) and hydrochlorothiazide (HCT). For mixture 1, ATV was determined using 10 μg/mL EZE as the divisor to generate the ratio spectra, and the peak to trough amplitudes between 231 and 276 nm were plotted against ATV concentration. Similarly, by using 10 μg/mL ATV as divisor, the peak to trough amplitudes between 231 and 276 nm were found proportional to EZE concentration. Calibration curves were linear in the range 2.5–40 μg/mL for both drugs. For mixture 2, divisor concentration was 7.5 μg/mL for both drugs. CAN was determined using its peak to trough amplitudes at 251 and 277 nm, while HCT was estimated using the amplitudes between 251 and 276 nm. The measured amplitudes were linearly correlated to concentration in the ranges 2.5–50 and 1–30 μg/mL for CAN and HCT, respectively. The proposed spectrophotometric method was validated and successfully applied for the assay of both drug combinations in several laboratory-prepared mixtures and commercial tablets. PMID:29403805

Compost mixture influence of interactive physical parameters on microbial kinetics and substrate fractionation.

PubMed

Mohajer, Ardavan; Tremier, Anne; Barrington, Suzelle; Teglia, Cecile

2010-01-01

Composting is a feasible biological treatment for the recycling of wastewater sludge as a soil amendment. The process can be optimized by selecting an initial compost recipe with physical properties that enhance microbial activity. The present study measured the microbial O(2) uptake rate (OUR) in 16 sludge and wood residue mixtures to estimate the kinetics parameters of maximum growth rate mu(m) and rate of organic matter hydrolysis K(h), as well as the initial biodegradable organic matter fractions present. The starting mixtures consisted of a wide range of moisture content (MC), waste to bulking agent (BA) ratio (W/BA ratio) and BA particle size, which were placed in a laboratory respirometry apparatus to measure their OUR over 4 weeks. A microbial model based on the activated sludge process was used to calculate the kinetic parameters and was found to adequately reproduced OUR curves over time, except for the lag phase and peak OUR, which was not represented and generally over-estimated, respectively. The maximum growth rate mu(m), was found to have a quadratic relationship with MC and a negative association with BA particle size. As a result, increasing MC up to 50% and using a smaller BA particle size of 8-12 mm was seen to maximize mu(m). The rate of hydrolysis K(h) was found to have a linear association with both MC and BA particle size. The model also estimated the initial readily biodegradable organic matter fraction, MB(0), and the slower biodegradable matter requiring hydrolysis, MH(0). The sum of MB(0) and MH(0) was associated with MC, W/BA ratio and the interaction between these two parameters, suggesting that O(2) availability was a key factor in determining the value of these two fractions. The study reinforced the idea that optimization of the physical characteristics of a compost mixture requires a holistic approach. 2010 Elsevier Ltd. All rights reserved.

Polymer Mixtures and Films: Free Volume as a Driving Force for Miscibility and Glassiness

NASA Astrophysics Data System (ADS)

DeFelice, Jeffrey

The microscopic characteristics of polymer molecules are connected with many macro- scopic and mechanical properties of their liquid (pure or mixed) and solid states. How these properties are affected by the different molecular attributes of polymers is of particular interest for practical applications of polymer materials. In Part I of this thesis, the thermodynamics of polymer/supercritical CO2 mixtures and blends of linear and branched polymers are modeled using a lattice based equation of state approach. Analyses of trends in the pure component physical properties lead to insight regarding how changes in molecular architecture and/or isotopic labeling affect the relative compatibilities of the mixtures. This approach is also applied to the mixed state to predict the enthalpic and entropic changes of mixing, from which, information is provided about the role of pure component properties in controlling the underlying thermodynamics of the mixtures. In Part II, the focus of this thesis turns to how interfacial effects can shift a number of physical properties in glass forming fluids relative to those of the pure bulk material. One of the most notable deviations from bulk behavior that has been reported for these systems is a change in the glass transition temperature (Tg). In this work, interfacial effects on Tg are probed in film and polymer/additive systems using a simple kinetic lattice model that simulates free volume and mobility in glass forming fluids. For films, the thickness-dependent behavior of Tg is characterized for different types of interfaces, including films that are substrate supported, free- standing, and 'stacked'. Connections are drawn between the size of the region of enhanced mobility near a free surface and the distribution of local Tg values across a film. For polymer/additive systems, where the "interface" is dispersed throughout the material, trends in additive induced Tg changes are analyzed with respect to additive concentration and the strength of the additive's influence on the local mobility of the polymer matrix.

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

PubMed

Røge, Rasmus E; Madsen, Kristoffer H; Schmidt, Mikkel N; Mørup, Morten

2017-10-01

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 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 subsequently normalized. Thus, when performing model selection, the two models are not in agreement. Analyzing multisubject whole brain resting-state fMRI data from healthy adult subjects, we find that the vMF mixture model is considerably more reliable than the gaussian mixture model when comparing solutions across models trained on different groups of subjects, and again we find that the two models disagree on the optimal number of components. The analysis indicates that the fMRI data support more than a thousand clusters, and we confirm this is not a result of overfitting by demonstrating better prediction on data from held-out subjects. Our results highlight the utility of using directional statistics to model standardized fMRI data and demonstrate that whole brain segmentation of fMRI data requires a very large number of functional units in order to adequately account for the discernible statistical patterns in the data.

Stochastic search, optimization and regression with energy applications

NASA Astrophysics Data System (ADS)

Hannah, Lauren A.

Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.

Cluster kinetics model for mixtures of glassformers

NASA Astrophysics Data System (ADS)

Brenskelle, Lisa A.; McCoy, Benjamin J.

2007-10-01

For glassformers we propose a binary mixture relation for parameters in a cluster kinetics model previously shown to represent pure compound data for viscosity and dielectric relaxation as functions of either temperature or pressure. The model parameters are based on activation energies and activation volumes for cluster association-dissociation processes. With the mixture parameters, we calculated dielectric relaxation times and compared the results to experimental values for binary mixtures. Mixtures of sorbitol and glycerol (seven compositions), sorbitol and xylitol (three compositions), and polychloroepihydrin and polyvinylmethylether (three compositions) were studied.

Raman-spectroscopy-based chemical contaminant detection in milk powder

NASA Astrophysics Data System (ADS)

Dhakal, Sagar; Chao, Kuanglin; Qin, Jianwei; Kim, Moon S.

2015-05-01

Addition of edible and inedible chemical contaminants in food powders for purposes of economic benefit has become a recurring trend. In recent years, severe health issues have been reported due to consumption of food powders contaminated with chemical substances. This study examines the effect of spatial resolution used during spectral collection to select the optimal spatial resolution for detecting melamine in milk powder. Sample depth of 2mm, laser intensity of 200mw, and exposure time of 0.1s were previously determined as optimal experimental parameters for Raman imaging. Spatial resolution of 0.25mm was determined as the optimal resolution for acquiring spectral signal of melamine particles from a milk-melamine mixture sample. Using the optimal resolution of 0.25mm, sample depth of 2mm and laser intensity of 200mw obtained from previous study, spectral signal from 5 different concentration of milk-melamine mixture (1%, 0.5%, 0.1%, 0.05%, and 0.025%) were acquired to study the relationship between number of detected melamine pixels and corresponding sample concentration. The result shows that melamine concentration has a linear relation with detected number of melamine pixels with correlation coefficient of 0.99. It can be concluded that the quantitative analysis of powder mixture is dependent on many factors including physical characteristics of mixture, experimental parameters, and sample depth. The results obtained in this study are promising. We plan to apply the result obtained from this study to develop quantitative detection model for rapid screening of melamine in milk powder. This methodology can also be used for detection of other chemical contaminants in milk powders.

Spectrophotometric and chemometric methods for determination of imipenem, ciprofloxacin hydrochloride, dexamethasone sodium phosphate, paracetamol and cilastatin sodium in human urine

NASA Astrophysics Data System (ADS)

El-Kosasy, A. M.; Abdel-Aziz, Omar; Magdy, N.; El Zahar, N. M.

2016-03-01

New accurate, sensitive and selective spectrophotometric and chemometric methods were developed and subsequently validated for determination of Imipenem (IMP), ciprofloxacin hydrochloride (CIPRO), dexamethasone sodium phosphate (DEX), paracetamol (PAR) and cilastatin sodium (CIL) in human urine. These methods include a new derivative ratio method, namely extended derivative ratio (EDR), principal component regression (PCR) and partial least-squares (PLS) methods. A novel EDR method was developed for the determination of these drugs, where each component in the mixture was determined by using a mixture of the other four components as divisor. Peak amplitudes were recorded at 293.0 nm, 284.0 nm, 276.0 nm, 257.0 nm and 221.0 nm within linear concentration ranges 3.00-45.00, 1.00-15.00, 4.00-40.00, 1.50-25.00 and 4.00-50.00 μg mL- 1 for IMP, CIPRO, DEX, PAR and CIL, respectively. PCR and PLS-2 models were established for simultaneous determination of the studied drugs in the range of 3.00-15.00, 1.00-13.00, 4.00-12.00, 1.50-9.50, and 4.00-12.00 μg mL- 1 for IMP, CIPRO, DEX, PAR and CIL, respectively, by using eighteen mixtures as calibration set and seven mixtures as validation set. The suggested methods were validated according to the International Conference of Harmonization (ICH) guidelines and the results revealed that they were accurate, precise and reproducible. The obtained results were statistically compared with those of the published methods and there was no significant difference.

Fast and Scalable Gaussian Process Modeling with Applications to Astronomical Time Series

NASA Astrophysics Data System (ADS)

Foreman-Mackey, Daniel; Agol, Eric; Ambikasaran, Sivaram; Angus, Ruth

2017-12-01

The growing field of large-scale time domain astronomy requires methods for probabilistic data analysis that are computationally tractable, even with large data sets. Gaussian processes (GPs) are a popular class of models used for this purpose, but since the computational cost scales, in general, as the cube of the number of data points, their application has been limited to small data sets. In this paper, we present a novel method for GPs modeling in one dimension where the computational requirements scale linearly with the size of the data set. We demonstrate the method by applying it to simulated and real astronomical time series data sets. These demonstrations are examples of probabilistic inference of stellar rotation periods, asteroseismic oscillation spectra, and transiting planet parameters. The method exploits structure in the problem when the covariance function is expressed as a mixture of complex exponentials, without requiring evenly spaced observations or uniform noise. This form of covariance arises naturally when the process is a mixture of stochastically driven damped harmonic oscillators—providing a physical motivation for and interpretation of this choice—but we also demonstrate that it can be a useful effective model in some other cases. We present a mathematical description of the method and compare it to existing scalable GP methods. The method is fast and interpretable, with a range of potential applications within astronomical data analysis and beyond. We provide well-tested and documented open-source implementations of this method in C++, Python, and Julia.

Standoff detection of chemical and biological threats using laser-induced breakdown spectroscopy.

PubMed

Gottfried, Jennifer L; De Lucia, Frank C; Munson, Chase A; Miziolek, Andrzej W

2008-04-01

Laser-induced breakdown spectroscopy (LIBS) is a promising technique for real-time chemical and biological warfare agent detection in the field. We have demonstrated the detection and discrimination of the biological warfare agent surrogates Bacillus subtilis (BG) (2% false negatives, 0% false positives) and ovalbumin (0% false negatives, 1% false positives) at 20 meters using standoff laser-induced breakdown spectroscopy (ST-LIBS) and linear correlation. Unknown interferent samples (not included in the model), samples on different substrates, and mixtures of BG and Arizona road dust have been classified with reasonable success using partial least squares discriminant analysis (PLS-DA). A few of the samples tested such as the soot (not included in the model) and the 25% BG:75% dust mixture resulted in a significant number of false positives or false negatives, respectively. Our preliminary results indicate that while LIBS is able to discriminate biomaterials with similar elemental compositions at standoff distances based on differences in key intensity ratios, further work is needed to reduce the number of false positives/negatives by refining the PLS-DA model to include a sufficient range of material classes and carefully selecting a detection threshold. In addition, we have demonstrated that LIBS can distinguish five different organophosphate nerve agent simulants at 20 meters, despite their similar stoichiometric formulas. Finally, a combined PLS-DA model for chemical, biological, and explosives detection using a single ST-LIBS sensor has been developed in order to demonstrate the potential of standoff LIBS for universal hazardous materials detection.

Molecular factor computing for predictive spectroscopy.

PubMed

Dai, Bin; Urbas, Aaron; Douglas, Craig C; Lodder, Robert A

2007-08-01

The concept of molecular factor computing (MFC)-based predictive spectroscopy was demonstrated here with quantitative analysis of ethanol-in-water mixtures in a MFC-based prototype instrument. Molecular computing of vectors for transformation matrices enabled spectra to be represented in a desired coordinate system. New coordinate systems were selected to reduce the dimensionality of the spectral hyperspace and simplify the mechanical/electrical/computational construction of a new MFC spectrometer employing transmission MFC filters. A library search algorithm was developed to calculate the chemical constituents of the MFC filters. The prototype instrument was used to collect data from 39 ethanol-in-water mixtures (range 0-14%). For each sample, four different voltage outputs from the detector (forming two factor scores) were measured by using four different MFC filters. Twenty samples were used to calibrate the instrument and build a multivariate linear regression prediction model, and the remaining samples were used to validate the predictive ability of the model. In engineering simulations, four MFC filters gave an adequate calibration model (r2 = 0.995, RMSEC = 0.229%, RMSECV = 0.339%, p = 0.05 by f test). This result is slightly better than a corresponding PCR calibration model based on corrected transmission spectra (r2 = 0.993, RMSEC = 0.359%, RMSECV = 0.551%, p = 0.05 by f test). The first actual MFC prototype gave an RMSECV = 0.735%. MFC was a viable alternative to conventional spectrometry with the potential to be more simply implemented and more rapid and accurate.

Refractometry for quality control of anesthetic drug mixtures.

PubMed

Stabenow, Jennifer M; Maske, Mindy L; Vogler, George A

2006-07-01

Injectable anesthetic drugs used in rodents are often mixed and further diluted to increase the convenience and accuracy of dosing. We evaluated clinical refractometry as a simple and rapid method of quality control and mixing error detection of rodent anesthetic or analgesic mixtures. Dilutions of ketamine, xylazine, acepromazine, and buprenorphine were prepared with reagent-grade water to produce at least 4 concentration levels. The refraction of each concentration then was measured with a clinical refractometer and plotted against the percentage of stock concentration. The resulting graphs were linear and could be used to determine the concentration of single-drug dilutions or to predict the refraction of drug mixtures. We conclude that refractometry can be used to assess the concentration of dilutions of single drugs and can verify the mixing accuracy of drug combinations when the components of the mixture are known and fall within the detection range of the instrument.

Development and validation of new spectrophotometric ratio H-point standard addition method and application to gastrointestinal acting drugs mixtures.

PubMed

Yehia, Ali M

2013-05-15

New, simple, specific, accurate and precise spectrophotometric technique utilizing ratio spectra is developed for simultaneous determination of two different binary mixtures. The developed ratio H-point standard addition method (RHPSAM) was managed successfully to resolve the spectral overlap in itopride hydrochloride (ITO) and pantoprazole sodium (PAN) binary mixture, as well as, mosapride citrate (MOS) and PAN binary mixture. The theoretical background and advantages of the newly proposed method are presented. The calibration curves are linear over the concentration range of 5-60 μg/mL, 5-40 μg/mL and 4-24 μg/mL for ITO, MOS and PAN, respectively. Specificity of the method was investigated and relative standard deviations were less than 1.5. The accuracy, precision and repeatability were also investigated for the proposed method according to ICH guidelines. Copyright © 2013 Elsevier B.V. All rights reserved.

Development and validation of new spectrophotometric ratio H-point standard addition method and application to gastrointestinal acting drugs mixtures

NASA Astrophysics Data System (ADS)

Yehia, Ali M.

2013-05-01

New, simple, specific, accurate and precise spectrophotometric technique utilizing ratio spectra is developed for simultaneous determination of two different binary mixtures. The developed ratio H-point standard addition method (RHPSAM) was managed successfully to resolve the spectral overlap in itopride hydrochloride (ITO) and pantoprazole sodium (PAN) binary mixture, as well as, mosapride citrate (MOS) and PAN binary mixture. The theoretical background and advantages of the newly proposed method are presented. The calibration curves are linear over the concentration range of 5-60 μg/mL, 5-40 μg/mL and 4-24 μg/mL for ITO, MOS and PAN, respectively. Specificity of the method was investigated and relative standard deviations were less than 1.5. The accuracy, precision and repeatability were also investigated for the proposed method according to ICH guidelines.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yang, Jian; He, Yuhong

2017-02-01

Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.

Enthalpy-entropy compensation for the solubility of drugs in solvent mixtures: paracetamol, acetanilide, and nalidixic acid in dioxane-water.

PubMed

Bustamante, P; Romero, S; Pena, A; Escalera, B; Reillo, A

1998-12-01

In earlier work, a nonlinear enthalpy-entropy compensation was observed for the solubility of phenacetin in dioxane-water mixtures. This effect had not been earlier reported for the solubility of drugs in solvent mixtures. To gain insight into the compensation effect, the behavior of the apparent thermodynamic magnitudes for the solubility of paracetamol, acetanilide, and nalidixic acid is studied in this work. The solubility of these drugs was measured at several temperatures in dioxane-water mixtures. DSC analysis was performed on the original powders and on the solid phases after equilibration with the solvent mixture. The thermal properties of the solid phases did not show significant changes. The three drugs display a solubility maximum against the cosolvent ratio. The solubility peaks of acetanilide and nalidixic acid shift to a more polar region at the higher temperatures. Nonlinear van't Hoff plots were observed for nalidixic acid whereas acetanilide and paracetamol show linear behavior at the temperature range studied. The apparent enthalpies of solution are endothermic going through a maximum at 50% dioxane. Two different mechanisms, entropy and enthalpy, are suggested to be the driving forces that increase the solubility of the three drugs. Solubility is entropy controlled at the water-rich region (0-50% dioxane) and enthalpy controlled at the dioxane-rich region (50-100% dioxane). The enthalpy-entropy compensation analysis also suggests that two different mechanisms, dependent on cosolvent ratio, are involved in the solubility enhancement of the three drugs. The plots of deltaH versus deltaG are nonlinear, and the slope changes from positive to negative above 50% dioxane. The compensation effect for the thermodynamic magnitudes of transfer from water to the aqueous mixtures can be described by a common empirical nonlinear relationship, with the exception of paracetamol, which follows a separate linear relationship at dioxane ratios above 50%. The results corroborate earlier findings with phenacetin. The similar pattern shown by the drugs studied suggests that the nonlinear enthalpy-entropy compensation effect may be characteristic of the solubility of semipolar drugs in dioxane-water mixtures.

Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Passos de Figueiredo, Leandro, E-mail: leandrop.fgr@gmail.com; Grana, Dario; Santos, Marcio

We propose a Bayesian approach for seismic inversion to estimate acoustic impedance, porosity and lithofacies within the reservoir conditioned to post-stack seismic and well data. The link between elastic and petrophysical properties is given by a joint prior distribution for the logarithm of impedance and porosity, based on a rock-physics model. The well conditioning is performed through a background model obtained by well log interpolation. Two different approaches are presented: in the first approach, the prior is defined by a single Gaussian distribution, whereas in the second approach it is defined by a Gaussian mixture to represent the well datamore » multimodal distribution and link the Gaussian components to different geological lithofacies. The forward model is based on a linearized convolutional model. For the single Gaussian case, we obtain an analytical expression for the posterior distribution, resulting in a fast algorithm to compute the solution of the inverse problem, i.e. the posterior distribution of acoustic impedance and porosity as well as the facies probability given the observed data. For the Gaussian mixture prior, it is not possible to obtain the distributions analytically, hence we propose a Gibbs algorithm to perform the posterior sampling and obtain several reservoir model realizations, allowing an uncertainty analysis of the estimated properties and lithofacies. Both methodologies are applied to a real seismic dataset with three wells to obtain 3D models of acoustic impedance, porosity and lithofacies. The methodologies are validated through a blind well test and compared to a standard Bayesian inversion approach. Using the probability of the reservoir lithofacies, we also compute a 3D isosurface probability model of the main oil reservoir in the studied field.« less

The Potential of Growth Mixture Modelling

ERIC Educational Resources Information Center

Muthen, Bengt

2006-01-01

The authors of the paper on growth mixture modelling (GMM) give a description of GMM and related techniques as applied to antisocial behaviour. They bring up the important issue of choice of model within the general framework of mixture modelling, especially the choice between latent class growth analysis (LCGA) techniques developed by Nagin and…

Spectrofluorimetric determination of some water-soluble vitamins.

PubMed

Mohamed, Abdel-Maaboud I; Mohamed, Horria A; Abdel-Latif, Niveen M; Mohamed, Marwa R

2011-01-01

Two simple and sensitive spectrofluorimetric methods were developed for determination of three water-soluble vitamins (B1, B2, and B6) in mixtures in the presence of cyanocobalamin. The first one was for thiamine determination, which depends on the oxidation of thiamine HCl to thiochrome by iodine in an alkaline medium. The method was applied accurately to determine thiamine in binary, ternary, and quaternary mixtures with pyridoxine HCl, riboflavin, and cyanocobalamin without interference. In the second method, riboflavin and pyridoxine HCl were determined fluorimetrically in acetate buffer, pH 6. The three water-soluble vitamins (B1, B2, and B6) were determined spectrofluorimetrically in binary, ternary, and quaternary mixtures in the presence of cyanocobalamin. All variables were studied in order to optimize the reaction conditions. Linear relationship was obeyed for all studied vitamins by the proposed methods at their corresponding lambda(exc) or lambda(em). The linear calibration curves were obtained from 10 to 500 ng/mL; the correlation ranged from 0.9991 to 0.9999. The suggested procedures were applied to the analysis of the investigated vitamins in their laboratory-prepared mixtures and pharmaceutical dosage forms from different manufacturers. The RSD range was 0.46-1.02%, which indicates good precision. No interference was observed from common pharmaceutical additives. Good recoveries (97.6 +/- 0.7-101.2 +/- 0.8%) were obtained. Statistical comparison of the results with reported methods shows excellent agreement and indicates no significant difference in accuracy and precision.

The Influence of Individual Driver Characteristics on Congestion Formation

NASA Astrophysics Data System (ADS)

Wang, Lanjun; Zhang, Hao; Meng, Huadong; Wang, Xiqin

Previous works have pointed out that one of the reasons for the formation of traffic congestion is instability in traffic flow. In this study, we investigate theoretically how the characteristics of individual drivers influence the instability of traffic flow. The discussions are based on the optimal velocity model, which has three parameters related to individual driver characteristics. We specify the mappings between the model parameters and driver characteristics in this study. With linear stability analysis, we obtain a condition for when instability occurs and a constraint about how the model parameters influence the unstable traffic flow. Meanwhile, we also determine how the region of unstable flow densities depends on these parameters. Additionally, the Langevin approach theoretically validates that under the constraint, the macroscopic characteristics of the unstable traffic flow becomes a mixture of free flows and congestions. All of these results imply that both overly aggressive and overly conservative drivers are capable of triggering traffic congestion.

Luminescent screen composition and apparatus

NASA Technical Reports Server (NTRS)

Hilborn, E. H.

1970-01-01

Ultraviolet light projects photographically produced images on a screen composed of a mixture of linear and nonlinear phosphors whose spectral emissions are different. This allows the display of polychromatic luminescent images, which gives better discrimination of the objects being viewed.

Hydrogen-Detection Apparatus

NASA Technical Reports Server (NTRS)

Ross, H. Richard; Bourgeois, Chris M.

1995-01-01

Apparatus continuously monitors concentration of hydrogen, at level ranging from few parts per million to several percent, in mixture of gases. Simple and fast, providing high sensitivity and linear response. Used to alert technicians to potentially explosive concentrations of residual hydrogen.

Superabsorbing gel for actinide, lanthanide, and fission product decontamination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaminski, Michael D.; Mertz, Carol J.

The present invention provides an aqueous gel composition for removing actinide ions, lanthanide ions, fission product ions, or a combination thereof from a porous surface contaminated therewith. The composition comprises a polymer mixture comprising a gel forming cross-linked polymer and a linear polymer. The linear polymer is present at a concentration that is less than the concentration of the cross-linked polymer. The polymer mixture is at least about 95% hydrated with an aqueous solution comprising about 0.1 to about 3 percent by weight (wt %) of a multi-dentate organic acid chelating agent, and about 0.02 to about 0.6 molar (M)more » carbonate salt, to form a gel. When applied to a porous surface contaminated with actinide ions, lanthanide ions, and/or other fission product ions, the aqueous gel absorbs contaminating ions from the surface.« less

Resolving Mixed Algal Species in Hyperspectral Images

PubMed Central

Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

2014-01-01

We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

Development of PBPK Models for Gasoline in Adult and ...

EPA Pesticide Factsheets

Concern for potential developmental effects of exposure to gasoline-ethanol blends has grown along with their increased use in the US fuel supply. Physiologically-based pharmacokinetic (PBPK) models for these complex mixtures were developed to address dosimetric issues related to selection of exposure concentrations for in vivo toxicity studies. Sub-models for individual hydrocarbon (HC) constituents were first developed and calibrated with published literature or QSAR-derived data where available. Successfully calibrated sub-models for individual HCs were combined, assuming competitive metabolic inhibition in the liver, and a priori simulations of mixture interactions were performed. Blood HC concentration data were collected from exposed adult non-pregnant (NP) rats (9K ppm total HC vapor, 6h/day) to evaluate performance of the NP mixture model. This model was then converted to a pregnant (PG) rat mixture model using gestational growth equations that enabled a priori estimation of life-stage specific kinetic differences. To address the impact of changing relevant physiological parameters from NP to PG, the PG mixture model was first calibrated against the NP data. The PG mixture model was then evaluated against data from PG rats that were subsequently exposed (9K ppm/6.33h gestation days (GD) 9-20). Overall, the mixture models adequately simulated concentrations of HCs in blood from single (NP) or repeated (PG) exposures (within ~2-3 fold of measured values of

Reduced detonation kinetics and detonation structure in one- and multi-fuel gaseous mixtures

NASA Astrophysics Data System (ADS)

Fomin, P. A.; Trotsyuk, A. V.; Vasil'ev, A. A.

2017-10-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one-fuel (CH4/air) and (ii) multi-fuel gaseous mixtures (CH4/H2/air and CH4/CO/air) are developed for the first time. The models for multi-fuel mixtures are proposed for the first time. 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. Advantages of the kinetic model for detonation combustion of methane has been demonstrated via numerical calculations of a two-dimensional structure of the detonation wave in a stoichiometric and fuel-rich methane-air mixtures and stoichiometric methane-oxygen mixture. The dominant size of the detonation cell, determines in calculations, is in good agreement with all known experimental data.

Evaluation of a speaker identification system with and without fusion using three databases in the presence of noise and handset effects

NASA Astrophysics Data System (ADS)

S. Al-Kaltakchi, Musab T.; Woo, Wai L.; Dlay, Satnam; Chambers, Jonathon A.

2017-12-01

In this study, a speaker identification system is considered consisting of a feature extraction stage which utilizes both power normalized cepstral coefficients (PNCCs) and Mel frequency cepstral coefficients (MFCC). Normalization is applied by employing cepstral mean and variance normalization (CMVN) and feature warping (FW), together with acoustic modeling using a Gaussian mixture model-universal background model (GMM-UBM). The main contributions are comprehensive evaluations of the effect of both additive white Gaussian noise (AWGN) and non-stationary noise (NSN) (with and without a G.712 type handset) upon identification performance. In particular, three NSN types with varying signal to noise ratios (SNRs) were tested corresponding to street traffic, a bus interior, and a crowded talking environment. The performance evaluation also considered the effect of late fusion techniques based on score fusion, namely, mean, maximum, and linear weighted sum fusion. The databases employed were TIMIT, SITW, and NIST 2008; and 120 speakers were selected from each database to yield 3600 speech utterances. As recommendations from the study, mean fusion is found to yield overall best performance in terms of speaker identification accuracy (SIA) with noisy speech, whereas linear weighted sum fusion is overall best for original database recordings.

Fitting a Mixture Item Response Theory Model to Personality Questionnaire Data: Characterizing Latent Classes and Investigating Possibilities for Improving Prediction

ERIC Educational Resources Information Center

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2008-01-01

Mixture item response theory (IRT) models aid the interpretation of response behavior on personality tests and may provide possibilities for improving prediction. Heterogeneity in the population is modeled by identifying homogeneous subgroups that conform to different measurement models. In this study, mixture IRT models were applied to the…

Mechanics of adsorption-deformation coupling in porous media

NASA Astrophysics Data System (ADS)

Zhang, Yida

2018-05-01

This work extends Coussy's macroscale theory for porous materials interacting with adsorptive fluid mixtures. The solid-fluid interface is treated as an independent phase that obeys its own mass, momentum and energy balance laws. As a result, a surface strain energy term appears in the free energy balance equation of the solid phase, which further introduces the so-called adsorption stress in the constitutive equations of the porous skeleton. This establishes a fundamental link between the adsorption characteristics of the solid-fluid interface and the mechanical response of the porous media. The thermodynamic framework is quite general in that it recovers the coupled conduction laws, Gibbs isotherm and the Shuttleworth's equation for surface stress, and imposes no constraints on the magnitude of deformation and the functional form of the adsorption isotherms. A rich variety of coupling between adsorption and deformation is recovered as a result of combining different poroelastic models (isotropic vs. anisotropic, linear vs. nonlinear) and adsorption models (unary vs. mixture adsorption, uncoupled vs. stretch-dependent adsorption). These predictions are discussed against the backdrop of recent experimental data on coal swelling subjected to CO2 and CO2sbnd CH4 injections, showing the capability and versatility of the theory in capturing adsorption-induced deformation of porous materials.

Biophysical Characterization of Supported Lipid Bilayers Using Parallel Dual-Wavelength Surface Plasmon Resonance and Quartz Crystal Microbalance Measurements.

PubMed

Parkkila, Petteri; Elderdfi, Mohamed; Bunker, Alex; Viitala, Tapani

2018-06-25

Supported lipid bilayers (SLBs) have been used extensively as an effective model of biological membranes, in the context of in vitro biophysics research, and the membranes of liposomes, in the context of the development of nanoscale drug delivery devices. Despite numerous surface-sensitive techniques having been applied to their study, the comprehensive optical characterization of SLBs using surface plasmon resonance (SPR) has not been conducted. In this study, Fresnel multilayer analysis is utilized to effectively calculate layer parameters (thickness and refractive indices) with the aid of dual-wavelength and dispersion coefficient analysis, in which the linear change in the refractive index as a function of wavelength is assumed. Using complementary information from impedance-based quartz crystal microbalance experiments, biophysical properties, for example, area-per-lipid-molecule and the quantity of lipid-associated water molecules, are calculated for different lipid types and mixtures, one of which is representative of a raft-forming lipid mixture. It is proposed that the hydration layer beneath the bilayer is, in fact, an integral part of the measured optical signal. Also, the traditional Jung model analysis and the ratio of SPR responses are investigated in terms of assessing the structure of the lipid layer that is formed.

Linear mixed-effects modeling approach to FMRI group analysis

PubMed Central

Chen, Gang; Saad, Ziad S.; Britton, Jennifer C.; Pine, Daniel S.; Cox, Robert W.

2013-01-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance–covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance–covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. PMID:23376789

Linear mixed-effects modeling approach to FMRI group analysis.

PubMed

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. Published by Elsevier Inc.

Spectral separation of gaseous fluorocarbon mixtures and measurement of diffusion constants by 19F gas phase DOSY NMR.

PubMed

Marchione, Alexander A; McCord, Elizabeth F

2009-11-01

Diffusion-ordered (DOSY) NMR techniques have for the first time been applied to the spectral separation of mixtures of fluorinated gases by diffusion rates. A mixture of linear perfluoroalkanes from methane to hexane was readily separated at 25 degrees C in an ordinary experimental setup with standard DOSY pulse sequences. Partial separation of variously fluorinated ethanes was also achieved. The constants of self-diffusion of a set of pure perfluoroalkanes were obtained at pressures from 0.25 to 1.34 atm and temperatures from 20 to 122 degrees C. Under all conditions there was agreement within 20% of experimental self-diffusion constant D and values calculated by the semiempirical Fuller method.

Microstructure and hydrogen bonding in water-acetonitrile mixtures.

PubMed

Mountain, Raymond D

2010-12-16

The connection of hydrogen bonding between water and acetonitrile in determining the microheterogeneity of the liquid mixture is examined using NPT molecular dynamics simulations. Mixtures for six, rigid, three-site models for acetonitrile and one water model (SPC/E) were simulated to determine the amount of water-acetonitrile hydrogen bonding. Only one of the six acetonitrile models (TraPPE-UA) was able to reproduce both the liquid density and the experimental estimates of hydrogen bonding derived from Raman scattering of the CN stretch band or from NMR quadrupole relaxation measurements. A simple modification of the acetonitrile model parameters for the models that provided poor estimates produced hydrogen-bonding results consistent with experiments for two of the models. Of these, only one of the modified models also accurately determined the density of the mixtures. The self-diffusion coefficient of liquid acetonitrile provided a final winnowing of the modified model and the successful, unmodified model. The unmodified model is provisionally recommended for simulations of water-acetonitrile mixtures.

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

PubMed

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.

Gender Differences in Anxiety Trajectories from Middle to Late Adolescence

PubMed Central

Ohannessian, Christine McCauley; Milan, Stephanie; Vannucci, Anna

2016-01-01

Although developmental trajectories of anxiety symptomatology have begun to be explored, most research has focused on total anxiety symptom scores during childhood and early adolescence, using racially/ethnically homogenous samples. Understanding the heterogeneous courses of anxiety disorder symptoms during middle to late adolescence has the potential to clarify developmental risk models of anxiety and to inform prevention programs. Therefore, this study specifically examined gender differences in developmental trajectories of anxiety disorder symptoms (generalized anxiety disorder, panic disorder, and social anxiety disorder) from middle to late adolescence in a diverse community sample (N=1,000; 57% female; 65% White), assessed annually over two years. Latent growth curve modeling revealed that girls exhibited a slight linear decrease in generalized anxiety disorder, panic disorder, and social anxiety disorder symptoms, whereas boys exhibited a stable course. These models suggested that one trajectory was appropriate for panic disorder symptoms in both girls and boys. Growth mixture models indicated the presence of four latent generalized anxiety disorder symptom trajectory classes: low increasing, moderate decreasing slightly, high decreasing, and very high decreasing rapidly. Growth mixture models also suggested the presence of five latent social anxiety disorder symptom trajectory classes: a low stable trajectory class and four classes that were qualitatively similar to the latent generalized anxiety disorder trajectories. For both generalized anxiety disorder and social anxiety disorder symptoms, girls were significantly more likely than boys to be in trajectory classes characterized by moderate or high initial symptoms that subsequently decreased over time. These findings provide novel information regarding the developmental course of anxiety disorder symptoms in adolescents. PMID:27889856

Applications of the Simple Multi-Fluid Model to Correlations of the Vapor-Liquid Equilibrium of Refrigerant Mixtures Containing Carbon Dioxide

NASA Astrophysics Data System (ADS)

Akasaka, Ryo

This study presents a simple multi-fluid model for Helmholtz energy equations of state. The model contains only three parameters, whereas rigorous multi-fluid models developed for several industrially important mixtures usually have more than 10 parameters and coefficients. Therefore, the model can be applied to mixtures where experimental data is limited. Vapor-liquid equilibrium (VLE) of the following seven mixtures have been successfully correlated with the model: CO2 + difluoromethane (R-32), CO2 + trifluoromethane (R-23), CO2 + fluoromethane (R-41), CO2 + 1,1,1,2- tetrafluoroethane (R-134a), CO2 + pentafluoroethane (R-125), CO2 + 1,1-difluoroethane (R-152a), and CO2 + dimethyl ether (DME). The best currently available equations of state for the pure refrigerants were used for the correlations. For all mixtures, average deviations in calculated bubble-point pressures from experimental values are within 2%. The simple multi-fluid model will be helpful for design and simulations of heat pumps and refrigeration systems using the mixtures as working fluid.

Excess thermodynamics of mixtures involving xenon and light linear alkanes by computer simulation.

PubMed

Carvalho, A J Palace; Ramalho, J P Prates; Martins, Luís F G

2007-06-14

Excess molar enthalpies and excess molar volumes as a function of composition for liquid mixtures of xenon + ethane (at 161.40 K), xenon + propane (at 161.40 K) and xenon + n-butane (at 182.34 K) have been obtained by Monte Carlo computer simulations and compared with available experimental data. Simulation conditions were chosen to closely match those of the corresponding experimental results. The TraPPE-UA force field was selected among other force fields to model all the alkanes studied, whereas the one-center Lennard-Jones potential from Bohn et al. was used for xenon. The calculated H(m)(E) and V(m)(E) for all systems are negative, increasing in magnitude as the alkane chain length increases. The results for these systems were compared with experimental data and with other theoretical calculations using the SAFT approach. An excellent agreement between simulation and experimental results was found for xenon + ethane system, whereas for the remaining two systems, some deviations that become progressively more significant as the alkane chain length increases were observed.

Colloid-polymer mixtures under slit confinement.

PubMed

Pérez-Ramírez, Allan; Figueroa-Gerstenmaier, Susana; Odriozola, Gerardo

2017-03-14

We report a NVT molecular dynamic study of colloid-polymer mixtures under slit confinement. For this purpose, we are employing the Asakura-Oosawa model for studying colloidal particles, polymer coils, and hard walls as the external confining field. The colloid-polymer size ratio, q, is varied in the range 1⩾q⩾0.4 and the confinement distance, H, in 10σ c ⩾H⩾3σ c , σ c being the colloidal diameter. Vapor-liquid coexistence properties are assessed, from which phase diagrams are built. The obtained data fulfill the corresponding states law for a constant H when q is varied. The shift of the polymer and colloidal chemical potentials of coexistence follows a linear relationship with (H-σ c ) -1 for H≳4σ c . The confined vapor-liquid interfaces can be fitted with a semicircular line of curvature (H-σ c ) -1 , from which the contact angle can be obtained. We observe complete wetting of the confining walls for reservoir polymer concentrations above and close to the critical value, and partial wetting for reservoir polymer concentrations above and far from it.

A unified Bayesian semiparametric approach to assess discrimination ability in survival analysis

PubMed Central

Zhao, Lili; Feng, Dai; Chen, Guoan; Taylor, Jeremy M.G.

2015-01-01

Summary The discriminatory ability of a marker for censored survival data is routinely assessed by the time-dependent ROC curve and the c-index. The time-dependent ROC curve evaluates the ability of a biomarker to predict whether a patient lives past a particular time t. The c-index measures the global concordance of the marker and the survival time regardless of the time point. We propose a Bayesian semiparametric approach to estimate these two measures. The proposed estimators are based on the conditional distribution of the survival time given the biomarker and the empirical biomarker distribution. The conditional distribution is estimated by a linear dependent Dirichlet process mixture model. The resulting ROC curve is smooth as it is estimated by a mixture of parametric functions. The proposed c-index estimator is shown to be more efficient than the commonly used Harrell's c-index since it uses all pairs of data rather than only informative pairs. The proposed estimators are evaluated through simulations and illustrated using a lung cancer dataset. PMID:26676324

Colloid-polymer mixtures under slit confinement

NASA Astrophysics Data System (ADS)

Pérez-Ramírez, Allan; Figueroa-Gerstenmaier, Susana; Odriozola, Gerardo

2017-03-01

We report a NVT molecular dynamic study of colloid-polymer mixtures under slit confinement. For this purpose, we are employing the Asakura-Oosawa model for studying colloidal particles, polymer coils, and hard walls as the external confining field. The colloid-polymer size ratio, q, is varied in the range 1 ⩾q ⩾0.4 and the confinement distance, H, in 10 σc ⩾H ⩾3 σc , σc being the colloidal diameter. Vapor-liquid coexistence properties are assessed, from which phase diagrams are built. The obtained data fulfill the corresponding states law for a constant H when q is varied. The shift of the polymer and colloidal chemical potentials of coexistence follows a linear relationship with (H-σc ) -1 for H ≳4 σc . The confined vapor-liquid interfaces can be fitted with a semicircular line of curvature (H-σc ) -1, from which the contact angle can be obtained. We observe complete wetting of the confining walls for reservoir polymer concentrations above and close to the critical value, and partial wetting for reservoir polymer concentrations above and far from it.

Laminar Flame Velocity and Temperature Exponent of Diluted DME-Air Mixture

NASA Astrophysics Data System (ADS)

Naseer Mohammed, Abdul; Anwar, Muzammil; Juhany, Khalid A.; Mohammad, Akram

2017-03-01

In this paper, the laminar flame velocity and temperature exponent diluted dimethyl ether (DME) air mixtures are reported. Laminar premixed mixture of DME-air with volumetric dilutions of carbon dioxides (CO2) and nitrogen (N2) are considered. Experiments were conducted using a preheated mesoscale high aspect-ratio diverging channel with inlet dimensions of 25 mm × 2 mm. In this method, flame velocities are extracted from planar flames that were stabilized near adiabatic conditions inside the channel. The flame velocities are then plotted against the ratio of mixture temperature and the initial reference temperature. A non-linear power law regression is observed suitable. This regression analysis gives the laminar flame velocity at the initial reference temperature and temperature exponent. Decrease in the laminar flame velocity and increase in temperature exponent is observed for CO2 and N2 diluted mixtures. The addition of CO2 has profound influence when compared to N2 addition on both flame velocity and temperature exponent. Numerical prediction of the similar mixture using a detailed reaction mechanism is obtained. The computational mechanism predicts higher magnitudes for laminar flame velocity and smaller magnitudes of temperature exponent compared to experimental data.

An auxiliary adaptive Gaussian mixture filter applied to flowrate allocation using real data from a multiphase producer

NASA Astrophysics Data System (ADS)

Lorentzen, Rolf J.; Stordal, Andreas S.; Hewitt, Neal

2017-05-01

Flowrate allocation in production wells is a complicated task, especially for multiphase flow combined with several reservoir zones and/or branches. The result depends heavily on the available production data, and the accuracy of these. In the application we show here, downhole pressure and temperature data are available, in addition to the total flowrates at the wellhead. The developed methodology inverts these observations to the fluid flowrates (oil, water and gas) that enters two production branches in a real full-scale producer. A major challenge is accurate estimation of flowrates during rapid variations in the well, e.g. due to choke adjustments. The Auxiliary Sequential Importance Resampling (ASIR) filter was developed to handle such challenges, by introducing an auxiliary step, where the particle weights are recomputed (second weighting step) based on how well the particles reproduce the observations. However, the ASIR filter suffers from large computational time when the number of unknown parameters increase. The Gaussian Mixture (GM) filter combines a linear update, with the particle filters ability to capture non-Gaussian behavior. This makes it possible to achieve good performance with fewer model evaluations. In this work we present a new filter which combines the ASIR filter and the Gaussian Mixture filter (denoted ASGM), and demonstrate improved estimation (compared to ASIR and GM filters) in cases with rapid parameter variations, while maintaining reasonable computational cost.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnham, A K; Weese, R K; Andrzejewski, W J

Decomposition kinetics are determined for HMX (nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and CP (2-(5-cyanotetrazalato) pentaammine cobalt (III) perchlorate) separately and together. For high levels of thermal stress, the two materials decompose faster as a mixture than individually. This effect is observed both in high-temperature thermal analysis experiments and in long-term thermal aging experiments. An Arrhenius plot of the 10% level of HMX decomposition by itself from a diverse set of experiments is linear from 120 to 260 C, with an apparent activation energy of 165 kJ/mol. Similar but less extensive thermal analysis data for the mixture suggests a slightly lower activation energy formore » the mixture, and an analogous extrapolation is consistent with the amount of gas observed in the long-term detonator aging experiments, which is about 30 times greater than expected from HMX by itself for 50 months at 100 C. Even with this acceleration, however, it would take {approx}10,000 years to achieve 10% decomposition at {approx}30 C. Correspondingly, negligible decomposition is predicted by this kinetic model for a few decades aging at temperatures slightly above ambient. This prediction is consistent with additional sealed-tube aging experiments at 100-120 C, which are estimated to have an effective thermal dose greater than that from decades of exposure to temperatures slightly above ambient.« less

The linear interplay of intrinsic and extrinsic noises ensures a high accuracy of cell fate selection in budding yeast

PubMed Central

Li, Yongkai; Yi, Ming; Zou, Xiufen

2014-01-01

To gain insights into the mechanisms of cell fate decision in a noisy environment, the effects of intrinsic and extrinsic noises on cell fate are explored at the single cell level. Specifically, we theoretically define the impulse of Cln1/2 as an indication of cell fates. The strong dependence between the impulse of Cln1/2 and cell fates is exhibited. Based on the simulation results, we illustrate that increasing intrinsic fluctuations causes the parallel shift of the separation ratio of Whi5P but that increasing extrinsic fluctuations leads to the mixture of different cell fates. Our quantitative study also suggests that the strengths of intrinsic and extrinsic noises around an approximate linear model can ensure a high accuracy of cell fate selection. Furthermore, this study demonstrates that the selection of cell fates is an entropy-decreasing process. In addition, we reveal that cell fates are significantly correlated with the range of entropy decreases. PMID:25042292

Polycyclic aromatic hydrocarbons in ambient air, surface soil and wheat grain near a large steel-smelting manufacturer in northern China.

PubMed

Liu, Weijian; Wang, Yilong; Chen, Yuanchen; Tao, Shu; Liu, Wenxin

2017-07-01

The total concentrations and component profiles of polycyclic aromatic hydrocarbons (PAHs) in ambient air, surface soil and wheat grain collected from wheat fields near a large steel-smelting manufacturer in Northern China were determined. Based on the specific isomeric ratios of paired species in ambient air, principle component analysis and multivariate linear regression, the main emission source of local PAHs was identified as a mixture of industrial and domestic coal combustion, biomass burning and traffic exhaust. The total organic carbon (TOC) fraction was considerably correlated with the total and individual PAH concentrations in surface soil. The total concentrations of PAHs in wheat grain were relatively low, with dominant low molecular weight constituents, and the compositional profile was more similar to that in ambient air than in topsoil. Combined with more significant results from partial correlation and linear regression models, the contribution from air PAHs to grain PAHs may be greater than that from soil PAHs. Copyright © 2016. Published by Elsevier B.V.

Global dynamics for switching systems and their extensions by linear differential equations

NASA Astrophysics Data System (ADS)

Huttinga, Zane; Cummins, Bree; Gedeon, Tomáš; Mischaikow, Konstantin

2018-03-01

Switching systems use piecewise constant nonlinearities to model gene regulatory networks. This choice provides advantages in the analysis of behavior and allows the global description of dynamics in terms of Morse graphs associated to nodes of a parameter graph. The parameter graph captures spatial characteristics of a decomposition of parameter space into domains with identical Morse graphs. However, there are many cellular processes that do not exhibit threshold-like behavior and thus are not well described by a switching system. We consider a class of extensions of switching systems formed by a mixture of switching interactions and chains of variables governed by linear differential equations. We show that the parameter graphs associated to the switching system and any of its extensions are identical. For each parameter graph node, there is an order-preserving map from the Morse graph of the switching system to the Morse graph of any of its extensions. We provide counterexamples that show why possible stronger relationships between the Morse graphs are not valid.

Global dynamics for switching systems and their extensions by linear differential equations.

PubMed

Huttinga, Zane; Cummins, Bree; Gedeon, Tomáš; Mischaikow, Konstantin

2018-03-15

Switching systems use piecewise constant nonlinearities to model gene regulatory networks. This choice provides advantages in the analysis of behavior and allows the global description of dynamics in terms of Morse graphs associated to nodes of a parameter graph. The parameter graph captures spatial characteristics of a decomposition of parameter space into domains with identical Morse graphs. However, there are many cellular processes that do not exhibit threshold-like behavior and thus are not well described by a switching system. We consider a class of extensions of switching systems formed by a mixture of switching interactions and chains of variables governed by linear differential equations. We show that the parameter graphs associated to the switching system and any of its extensions are identical. For each parameter graph node, there is an order-preserving map from the Morse graph of the switching system to the Morse graph of any of its extensions. We provide counterexamples that show why possible stronger relationships between the Morse graphs are not valid.

Calculation and characteristic analysis on synergistic effect of CF3I gas mixtures

NASA Astrophysics Data System (ADS)

Su, ZHAO; Yunkun, DENG; Yuhao, GAO; Dengming, XIAO

2018-06-01

CF3I is a potential SF6 alternative gas. In order to study the insulation properties and synergistic effects of CF3I/N2 and CF3I/CO2 gas mixtures, two-term approximate Boltzmann equations were used to obtain the ionization coefficient α, attachment coefficient η and the critical equivalent electrical field strength (E/N)cr. The results show that the (E/N)cr of CF3I gas at 300 K is 1.2 times that of SF6 gas, and CF3I/N2 and CF3I/CO2 gas mixtures both have synergistic effect occurred. The synergistic effect coefficient of CF3I/CO2 gas mixture was higher than that of CF3I/N2 gas mixture. But the (E/N)cr of CF3I/N2 is higher than that of CF3I/CO2 under the same conditions. When the content of CF3I exceeds 20%, the (E/N)cr of CF3I/N2 and CF3I/CO2 gas mixture increase linearly with the increasing of CF3I gas content. The breakdown voltage of CF3I/N2 gas mixture is also higher than that of CF3I/CO2 gas mixture in slightly non-uniform electrical field under power frequency voltage, but the synergistic effect coefficients of the two gas mixtures are basically the same.

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

PubMed Central

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-01-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science. PMID:25387525

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

NASA Astrophysics Data System (ADS)

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Further improvements to linear mixed models for genome-wide association studies.

PubMed

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-12

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Different Approaches to Covariate Inclusion in the Mixture Rasch Model

ERIC Educational Resources Information Center

Li, Tongyun; Jiao, Hong; Macready, George B.

2016-01-01

The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning. A Monte Carlo…

A compressibility based model for predicting the tensile strength of directly compressed pharmaceutical powder mixtures.

PubMed

Reynolds, Gavin K; Campbell, Jacqueline I; Roberts, Ron J

2017-10-05

A new model to predict the compressibility and compactability of mixtures of pharmaceutical powders has been developed. The key aspect of the model is consideration of the volumetric occupancy of each powder under an applied compaction pressure and the respective contribution it then makes to the mixture properties. The compressibility and compactability of three pharmaceutical powders: microcrystalline cellulose, mannitol and anhydrous dicalcium phosphate have been characterised. Binary and ternary mixtures of these excipients have been tested and used to demonstrate the predictive capability of the model. Furthermore, the model is shown to be uniquely able to capture a broad range of mixture behaviours, including neutral, negative and positive deviations, illustrating its utility for formulation design. Copyright © 2017 Elsevier B.V. All rights reserved.

A manifold learning approach to target detection in high-resolution hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.

Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into the adaptive LLE transformation; the artificial target manifold helps to guide the separation of the target data from the background data in the new, lower-dimensional manifold coordinates. Then, target detection is performed in the manifold space.

Extracting Spurious Latent Classes in Growth Mixture Modeling with Nonnormal Errors

ERIC Educational Resources Information Center

Guerra-Peña, Kiero; Steinley, Douglas

2016-01-01

Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…

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

PubMed

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.

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

PubMed Central

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. PMID:26941699

Solubility modeling of refrigerant/lubricant mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michels, H.H.; Sienel, T.H.

1996-12-31

A general model for predicting the solubility properties of refrigerant/lubricant mixtures has been developed based on applicable theory for the excess Gibbs energy of non-ideal solutions. In our approach, flexible thermodynamic forms are chosen to describe the properties of both the gas and liquid phases of refrigerant/lubricant mixtures. After an extensive study of models for describing non-ideal liquid effects, the Wohl-suffix equations, which have been extensively utilized in the analysis of hydrocarbon mixtures, have been developed into a general form applicable to mixtures where one component is a POE lubricant. In the present study we have analyzed several POEs wheremore » structural and thermophysical property data were available. Data were also collected from several sources on the solubility of refrigerant/lubricant binary pairs. We have developed a computer code (NISC), based on the Wohl model, that predicts dew point or bubble point conditions over a wide range of composition and temperature. Our present analysis covers mixtures containing up to three refrigerant molecules and one lubricant. The present code can be used to analyze the properties of R-410a and R-407c in mixtures with a POE lubricant. Comparisons with other models, such as the Wilson or modified Wilson equations, indicate that the Wohl-suffix equations yield more reliable predictions for HFC/POE mixtures.« less

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

PubMed

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

2014-06-01

Emission sources of volatile organic compounds (VOCs*) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are known to affect VOC exposures, many personal, environmental, and socioeconomic determinants remain to be identified, and the significance and applicability of the determinants reported in the literature are uncertain. To help answer these unresolved questions and overcome limitations of previous analyses, this project used several novel and powerful statistical modeling and analysis techniques and two large data sets. The overall objectives of this project were (1) to identify and characterize exposure distributions (including extreme values), (2) evaluate mixtures (including dependencies), and (3) identify determinants of VOC exposure. METHODS VOC data were drawn from two large data sets: the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study (1999-2001) and the National Health and Nutrition Examination Survey (NHANES; 1999-2000). The RIOPA study used a convenience sample to collect outdoor, indoor, and personal exposure measurements in three cities (Elizabeth, NJ; Houston, TX; Los Angeles, CA). In each city, approximately 100 households with adults and children who did not smoke were sampled twice for 18 VOCs. In addition, information about 500 variables associated with exposure was collected. The NHANES used a nationally representative sample and included personal VOC measurements for 851 participants. NHANES sampled 10 VOCs in common with RIOPA. Both studies used similar sampling methods and study periods. Specific Aim 1. To estimate and model extreme value exposures, extreme value distribution models were fitted to the top 10% and 5% of VOC exposures. Health risks were estimated for individual VOCs and for three VOC mixtures. Simulated extreme value data sets, generated for each VOC and for fitted extreme value and lognormal distributions, were compared with measured concentrations (RIOPA observations) to evaluate each model's goodness of fit. Mixture distributions were fitted with the conventional finite mixture of normal distributions and the 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). 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 distributions, adaptively selecting the number of needed clusters, and providing uncertainty estimates. Although the results apply to the RIOPA data set, GEV distributions and mixture models appear more broadly applicable. These models can be used to simulate VOC distributions, which are neither normally nor lognormally distributed, and they accurately represent the highest exposures, which may have the greatest health significance. Specific Aim 2. Four VOC mixtures were identified and apportioned by PMF; they represented gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection byproducts, and cleaning products and odorants. The last mixture (cleaning products and odorants) accounted for the largest fraction of an individual's total exposure (average of 42% across RIOPA participants). Often, a single compound dominated a mixture but the mixture fractions were heterogeneous; that is, the fractions of the compounds changed with the concentration of the mixture. Three VOC mixtures were identified by toxicologic mode of action and represented VOCs associated with hematopoietic, liver, and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10(-3) for about 10% of RIOPA participants. The dependency structures of the VOC mixtures in the RIOPA data set fitted Gumbel (two mixtures) and t copulas (four mixtures). These copula types emphasize dependencies found in the upper and lower tails of a distribution. The copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy and performed better than multivariate lognormal distributions. Specific Aim 3. In an analysis focused on the home environment and the outdoor (close to home) environment, home VOC concentrations dominated personal exposures (66% to 78% of the total exposure, depending on VOC); this was largely the result of the amount of time participants spent at home and the fact that indoor concentrations were much higher than outdoor concentrations for most VOCs. In a different analysis focused on the sources inside the home and outside (but close to the home), it was assumed that 100% of VOCs from outside sources would penetrate the home. Outdoor VOC sources accounted for 5% (d-limonene) to 81% (carbon tetrachloride [CTC]) of the total exposure. Personal exposure and indoor measurements had similar determinants depending on the VOC. Gasoline-related VOCs (e.g., benzene and methyl tert-butyl ether [MTBE]) were associated with city, residences with attached garages, pumping gas, wind speed, and home air exchange rate (AER). Odorant and cleaning-related VOCs (e.g., 1,4-DCB and chloroform) also were associated with city, and a residence's AER, size, and family members showering. Dry-cleaning and industry-related VOCs (e.g., tetrachloroethylene [or perchloroethylene, PERC] and trichloroethylene [TCE]) were associated with city, type of water supply to the home, and visits to the dry cleaner. These and other relationships were significant, they explained from 10% to 40% of the variance in the measurements, and are consistent with known emission sources and those reported in the literature. Outdoor concentrations of VOCs had only two determinants in common: city and wind speed. Overall, personal exposure was dominated by the home setting, although a large fraction of indoor VOC concentrations were due to outdoor sources. City of residence, personal activities, household characteristics, and meteorology were significant determinants. Concentrations in RIOPA were considerably lower than levels in the nationally representative NHANES for all VOCs except MTBE and 1,4-DCB. Differences between RIOPA and NHANES results can be explained by contrasts between the sampling designs and staging in the two studies, and by differences in the demographics, smoking, employment, occupations, and home locations. (ABSTRACT TRUNCATED)

A rapid Fourier transform infrared spectroscopic method for analysis of certain proton pump inhibitors in binary and ternary mixtures

NASA Astrophysics Data System (ADS)

Khashaba, Pakinaz Y.; Ali, Hassan Refat H.; El-Wekil, Mohamed M.

2018-02-01

A simple and non-destructive FTIR method was used to determine certain proton pump inhibitors (PPIs) in binary and ternary mixtures. Proton pump inhibitors (PPIs); omeprazole (OMZ), esomeprazole (EZM), lansoprazole (LAN), pantoprazole sodium (PAN sodium) and rabeprazole sodium (RAB sodium) in binary mixture with domperidone (DOM) and ternary mixture of OMZ, clarithromycin (CLM) and tinidazole (TNZ) were determined in the solid-state by FTIR spectroscopy for the first time. The method was validated according to ICH-guidelines where linearity was ranged from 20 to 850 μg/g and 20-360 μg/g for PPIs and DOM, respectively in binary mixtures and 10-400, 100-8000 and 150-14,000 μg/g for OMZ, CLM and TNZ, respectively. Limits of detection were found to be 6-100 and 9-100 μg/g for PPIs and DOM, respectively and 4, 40 and 50 μg/g for OMZ, CLM and TNZ, respectively. The method was applied successfully for determination of the cited drugs in their respective pharmaceutical dosage forms.

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures.

PubMed

Chundawat, Shishir P S; Lipton, Mary S; Purvine, Samuel O; Uppugundla, Nirmal; Gao, Dahai; Balan, Venkatesh; Dale, Bruce E

2011-10-07

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

Development of mass measurement equipment using an electronic mass-comparator for gravimetric preparation of reference gas mixtures

NASA Astrophysics Data System (ADS)

Matsumoto, Nobuhiro; Watanabe, Takuro; Maruyama, Masaaki; Horimoto, Yoshiyuki; Maeda, Tsuneaki; Kato, Kenji

2004-06-01

The gravimetric method is the most popular method for preparing reference gas mixtures with high accuracy. We have designed and manufactured novel mass measurement equipment for gravimetric preparation of reference gas mixtures. This equipment consists of an electronic mass-comparator with a maximum capacity of 15 kg and readability of 1 mg and an automatic cylinder exchanger. The structure of this equipment is simpler and the cost is much lower than a conventional mechanical knife-edge type large balance used for gravimetric preparation of primary gas mixtures in Japan. This cylinder exchanger can mount two cylinders alternatively on the weighing pan of the comparator. In this study, the performance of the equipment has been evaluated. At first, the linearity and repeatability of the mass measurement were evaluated using standard mass pieces. Then, binary gas mixtures of propane and nitrogen were prepared and compared with those prepared with the conventional knife-edge type balance. The comparison resulted in good consistency at the compatibility criterion described in ISO6143:2001.

An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data

USGS Publications Warehouse

Toribo, S.G.; Gray, B.R.; Liang, S.

2011-01-01

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

The isotropic-nematic and nematic-nematic phase transition of binary mixtures of tangent hard-sphere chain fluids: An analytical equation of state

NASA Astrophysics Data System (ADS)

van Westen, Thijs; Vlugt, Thijs J. H.; Gross, Joachim

2014-01-01

An analytical equation of state (EoS) is derived to describe the isotropic (I) and nematic (N) phase of linear- and partially flexible tangent hard-sphere chain fluids and their mixtures. The EoS is based on an extension of Onsager's second virial theory that was developed in our previous work [T. van Westen, B. Oyarzún, T. J. H. Vlugt, and J. Gross, J. Chem. Phys. 139, 034505 (2013)]. Higher virial coefficients are calculated using a Vega-Lago rescaling procedure, which is hereby generalized to mixtures. The EoS is used to study (1) the effect of length bidispersity on the I-N and N-N phase behavior of binary linear tangent hard-sphere chain fluid mixtures, (2) the effect of partial molecular flexibility on the binary phase diagram, and (3) the solubility of hard-sphere solutes in I- and N tangent hard-sphere chain fluids. By changing the length bidispersity, two types of phase diagrams were found. The first type is characterized by an I-N region at low pressure and a N-N demixed region at higher pressure that starts from an I-N-N triphase equilibrium. The second type does not show the I-N-N equilibrium. Instead, the N-N region starts from a lower critical point at a pressure above the I-N region. The results for the I-N region are in excellent agreement with the results from molecular simulations. It is shown that the N-N demixing is driven both by orientational and configurational/excluded volume entropy. By making the chains partially flexible, it is shown that the driving force resulting from the configurational entropy is reduced (due to a less anisotropic pair-excluded volume), resulting in a shift of the N-N demixed region to higher pressure. Compared to linear chains, no topological differences in the phase diagram were found. We show that the solubility of hard-sphere solutes decreases across the I-N phase transition. Furthermore, it is shown that by using a liquid crystal mixture as the solvent, the solubility difference can by maximized by tuning the composition. Theoretical results for the Henry's law constant of the hard-sphere solute are in good agreement with the results from molecular simulation.

Effect of water vapor on sound absorption in nitrogen at low frequency/pressure ratios

NASA Technical Reports Server (NTRS)

Zuckerwar, A. J.; Griffin, W. A.

1981-01-01

Sound absorption measurements were made in N2-H2O binary mixtures at 297 K over the frequency/pressure range f/P of 0.1-2500 Hz/atm to investigate the vibrational relaxation peak of N2 and its location on f/P axis as a function of humidity. At low humidities the best fit to a linear relationship between the f/P(max) and humidity yields an intercept of 0.013 Hz/atm and a slope of 20,000 Hz/atm-mole fraction. The reaction rate constants derived from this model are lower than those obtained from the extrapolation of previous high-temperature data.

The thinning of viscous liquid threads.

NASA Astrophysics Data System (ADS)

Castrejon-Pita, J. Rafael; Castrejon-Pita, Alfonso A.; Hutchings, Ian M.

2012-11-01

The thinning neck of dripping droplets is studied experimentally for viscous Newtonian fluids. High speed imaging is used to measure the minimum neck diameter in terms of the time τ to breakup. Mixtures of water and glycerol with viscosities ranging from 20 to 363 mPa s are used to model the Newtonian behavior. The results show the transition from potential to inertial-viscous regimes occurs at the predicted values of ~Oh2. Before this transition the neck contraction rate follows the inviscid scaling law ~τ 2 / 3 . After the transition, the neck thinning tends towards the linear viscous scaling law ~ τ . Project supported by the EPSRC-UK (EP/G029458/1) and Cambridge-KACST.

The underlying toxicological mechanism of chemical mixtures: A case study on mixture toxicity of cyanogenic toxicants and aldehydes to Photobacterium phosphoreum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Dayong; Department of Chemical and Environmental Engineering, Anyang Institute of Technology, Anyang 455000; Lin, Zhifen, E-mail: lzhifen@tongji.edu.cn

Intracellular chemical reaction of chemical mixtures is one of the main reasons that cause synergistic or antagonistic effects. However, it still remains unclear what the influencing factors on the intracellular chemical reaction are, and how they influence on the toxicological mechanism of chemical mixtures. To reveal this underlying toxicological mechanism of chemical mixtures, a case study on mixture toxicity of cyanogenic toxicants and aldehydes to Photobacterium phosphoreum was employed, and both their joint effects and mixture toxicity were observed. Then series of two-step linear regressions were performed to describe the relationships between joint effects, the expected additive toxicities and descriptorsmore » of individual chemicals (including concentrations, binding affinity to receptors, octanol/water partition coefficients). Based on the quantitative relationships, the underlying joint toxicological mechanisms were revealed. The result shows that, for mixtures with their joint effects resulting from intracellular chemical reaction, their underlying toxicological mechanism depends on not only their interaction with target proteins, but also their transmembrane actions and their concentrations. In addition, two generic points of toxicological mechanism were proposed including the influencing factors on intracellular chemical reaction and the difference of the toxicological mechanism between single reactive chemicals and their mixtures. This study provided an insight into the understanding of the underlying toxicological mechanism for chemical mixtures with intracellular chemical reaction. - Highlights: • Joint effects of nitriles and aldehydes at non-equitoxic ratios were determined. • A novel descriptor, ligand–receptor interaction energy (E{sub binding}), was employed. • Quantitative relationships for mixtures were developed based on a novel descriptor. • The underlying toxic mechanism was revealed based on quantitative relationships. • Two generic points of toxicological mechanism were elucidated.« less

Process Dissociation and Mixture Signal Detection Theory

ERIC Educational Resources Information Center

DeCarlo, Lawrence T.

2008-01-01

The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

Investigating Approaches to Estimating Covariate Effects in Growth Mixture Modeling: A Simulation Study

ERIC Educational Resources Information Center

Li, Ming; Harring, Jeffrey R.

2017-01-01

Researchers continue to be interested in efficient, accurate methods of estimating coefficients of covariates in mixture modeling. Including covariates related to the latent class analysis not only may improve the ability of the mixture model to clearly differentiate between subjects but also makes interpretation of latent group membership more…

Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

ERIC Educational Resources Information Center

de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

2010-01-01

We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

Approximation of the breast height diameter distribution of two-cohort stands by mixture models I Parameter estimation

Treesearch

Rafal Podlaski; Francis A. Roesch

2013-01-01

Study assessed the usefulness of various methods for choosing the initial values for the numerical procedures for estimating the parameters of mixture distributions and analysed variety of mixture models to approximate empirical diameter at breast height (dbh) distributions. Two-component mixtures of either the Weibull distribution or the gamma distribution were...

Selecting Surrogates for an Alkylphenol Ethoxylate Analytical Method in Sewage and Soil Matrices

EPA Science Inventory

Alkylphenol ethoxylates (APEs) are nonionic surfactants commonly used in industrial detergents. These products contain complex mixtures of branched and linear chains. APEs and their degradation products, alkylphenols, are highly toxic to aquatic organisms, potentially estrogeni...

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling.

PubMed

Odegård, J; Jensen, J; Madsen, P; Gianola, D; Klemetsdal, G; Heringstad, B

2003-11-01

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnham, A K; Weese, R K; Adrzejewski, W J

Accelerated aging tests play an important role in assessing the lifetime of manufactured products. There are two basic approaches to lifetime qualification. One tests a product to failure over range of accelerated conditions to calibrate a model, which is then used to calculate the failure time for conditions of use. A second approach is to test a component to a lifetime-equivalent dose (thermal or radiation) to see if it still functions to specification. Both methods have their advantages and limitations. A disadvantage of the 2nd method is that one does not know how close one is to incipient failure. Thismore » limitation can be mitigated by testing to some higher level of dose as a safety margin, but having a predictive model of failure via the 1st approach provides an additional measure of confidence. Even so, proper calibration of a failure model is non-trivial, and the extrapolated failure predictions are only as good as the model and the quality of the calibration. This paper outlines results for predicting the potential failure point of a system involving a mixture of two energetic materials, HMX (nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and CP (2-(5-cyanotetrazalato) pentaammine cobalt (III) perchlorate). Global chemical kinetic models for the two materials individually and as a mixture are developed and calibrated from a variety of experiments. These include traditional thermal analysis experiments run on time scales from hours to a couple days, detonator aging experiments with exposures up to 50 months, and sealed-tube aging experiments for up to 5 years. Decomposition kinetics are determined for HMX (nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and CP (2-(5-cyanotetrazalato) pentaammine cobalt (III) perchlorate) separately and together. For high levels of thermal stress, the two materials decompose faster as a mixture than individually. This effect is observed both in high-temperature thermal analysis experiments and in long-term thermal aging experiments. An Arrhenius plot of the 10% level of HMX decomposition by itself from a diverse set of experiments is linear from 120 to 260 C, with an apparent activation energy of 165 kJ/mol. Similar but less extensive thermal analysis data for the mixture suggests a slightly lower activation energy for the mixture, and an analogous extrapolation is consistent with the amount of gas observed in the long-term detonator aging experiments, which is about 30 times greater than expected from HMX by itself for 50 months at 100 C. Even with this acceleration, however, it would take {approx}10,000 years to achieve 10% decomposition at {approx}30 C. Correspondingly, negligible decomposition is predicted by this kinetic model for a few decades aging at temperatures slightly above ambient. This prediction is consistent with additional sealed-tube aging experiments at 100-120 C, which are estimated to have an effective thermal dose greater than that from decades of exposure to temperatures slightly above ambient.« less

Modeling pinchoff and reconnection in a Hele-Shaw cell. I. The models and their calibration

NASA Astrophysics Data System (ADS)

Lee, Hyeong-Gi; Lowengrub, J. S.; Goodman, J.

2002-02-01

This is the first paper in a two-part series in which we analyze two model systems to study pinchoff and reconnection in binary fluid flow in a Hele-Shaw cell with arbitrary density and viscosity contrast between the components. The systems stem from a simplification of a general system of equations governing the motion of a binary fluid (NSCH model [Lowengrub and Truskinovsky, Proc. R. Soc. London, Ser. A 454, 2617 (1998)]) to flow in a Hele-Shaw cell. The system takes into account the chemical diffusivity between different components of a fluid mixture and the reactive stresses induced by inhomogeneity. In one of the systems we consider (HSCH), the binary fluid may be compressible due to diffusion. In the other system (BHSCH), a Boussinesq approximation is used and the fluid is incompressible. In this paper, we motivate, present and calibrate the HSCH/BHSCH equations so as to yield the classical sharp interface model as a limiting case. We then analyze their equilibria, one dimensional evolution and linear stability. In the second paper [paper II, Phys. Fluids 14, 514 (2002)], we analyze the behavior of the models in the fully nonlinear regime. In the BHSCH system, the equilibrium concentration profile is obtained using the classical Maxwell construction [Rowlinson and Widom, Molecular Theory of Capillarity (Clarendon, Oxford, 1979)] and does not depend on the orientation of the gravitational field. We find that the equilibria in the HSCH model are somewhat surprising as the gravitational field actually affects the internal structure of an isolated interface by driving additional stratification of light and heavy fluids over that predicted in the Boussinesq case. A comparison of the linear growth rates indicates that the HSCH system is slightly more diffusive than the BHSCH system. In both, linear convergence to the sharp interface growth rates is observed in a parameter controlling the interface thickness. In addition, we identify the effect that each of the parameters, in the HSCH/BHSCH models, has on the linear growth rates. We then show how this analysis may be used to suggest a set of modified parameters which, when used in the HSCH/BHSCH systems, yield improved agreement with the sharp interface model at a finite interface thickness. Evidence of this improved agreement may be found in paper II.

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L

2014-01-01

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633

A method for matching the refractive index and kinematic viscosity of a blood analog for flow visualization in hydraulic cardiovascular models.

PubMed

Nguyen, T T; Biadillah, Y; Mongrain, R; Brunette, J; Tardif, J C; Bertrand, O F

2004-08-01

In this work, we propose a simple method to simultaneously match the refractive index and kinematic viscosity of a circulating blood analog in hydraulic models for optical flow measurement techniques (PIV, PMFV, LDA, and LIF). The method is based on the determination of the volumetric proportions and temperature at which two transparent miscible liquids should be mixed to reproduce the targeted fluid characteristics. The temperature dependence models are a linear relation for the refractive index and an Arrhenius relation for the dynamic viscosity of each liquid. Then the dynamic viscosity of the mixture is represented with a Grunberg-Nissan model of type 1. Experimental tests for acrylic and blood viscosity were found to be in very good agreement with the targeted values (measured refractive index of 1.486 and kinematic viscosity of 3.454 milli-m2/s with targeted values of 1.47 and 3.300 milli-m2/s).

Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Zhao, Yongqiang; Chu, Genbai; Xi, Tao; Shui, Min; Lu, Feng; Gu, Yuqiu

2017-06-01

This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.

Optimization of technological procedure for amygdalin isolation from plum seeds (Pruni domesticae semen)

PubMed Central

Savic, Ivan M.; Nikolic, Vesna D.; Savic-Gajic, Ivana M.; Nikolic, Ljubisa B.; Ibric, Svetlana R.; Gajic, Dragoljub G.

2015-01-01

The process of amygdalin extraction from plum seeds was optimized using central composite design (CCD) and multilayer perceptron (MLP). The effect of time, ethanol concentration, solid-to-liquid ratio, and temperature on the amygdalin content in the extracts was estimated using both mathematical models. The MLP 4-3-1 with exponential function in hidden layer and linear function in output layer was used for describing the extraction process. MLP model was more superior compared with CCD model due to better prediction ability. According to MLP model, the suggested optimal conditions are: time of 120 min, 100% (v/v) ethanol, solid-to liquid ratio of 1:25 (m/v) and temperature of 34.4°C. The predicted value of amygdalin content in the dried extract (25.42 g per 100 g) at these conditions was experimentally confirmed (25.30 g per 100 g of dried extract). Amygdalin (>90%) was isolated from the complex extraction mixture and structurally characterized by FT-IR, UV, and MS methods. PMID:25972881

Modelling diameter distributions of two-cohort forest stands with various proportions of dominant species: a two-component mixture model approach.

Treesearch

Rafal Podlaski; Francis Roesch

2014-01-01

In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components,...

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

NASA Astrophysics Data System (ADS)

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 the suspended load will also make great contributions to the topography change in the surf zone, which is usually neglected in some previous researches.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio, E-mail: drpqam@cid.csic.es

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 usedmore » 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 mixtures of goitrogens.« less

Predictive models attribute effects on fish assemblages to toxicity and habitat alteration.

PubMed

de Zwart, Dick; Dyer, Scott D; Posthuma, Leo; Hawkins, Charles P

2006-08-01

Biological assessments should both estimate the condition of a biological resource (magnitude of alteration) and provide environmental managers with a diagnosis of the potential causes of impairment. Although methods of quantifying condition are well developed, identifying and proportionately attributing impairment to probable causes remain problematic. Furthermore, analyses of both condition and cause have often been difficult to communicate. We developed an approach that (1) links fish, habitat, and chemistry data collected from hundreds of sites in Ohio (USA) streams, (2) assesses the biological condition at each site, (3) attributes impairment to multiple probable causes, and (4) provides the results of the analyses in simple-to-interpret pie charts. The data set was managed using a geographic information system. Biological condition was assessed using a RIVPACS (river invertebrate prediction and classification system)-like predictive model. The model provided probabilities of capture for 117 fish species based on the geographic location of sites and local habitat descriptors. Impaired biological condition was defined as the proportion of those native species predicted to occur at a site that were observed. The potential toxic effects of exposure to mixtures of contaminants were estimated using species sensitivity distributions and mixture toxicity principles. Generalized linear regression models described species abundance as a function of habitat characteristics. Statistically linking biological condition, habitat characteristics including mixture risks, and species abundance allowed us to evaluate the losses of species with environmental conditions. Results were mapped as simple effect and probable-cause pie charts (EPC pie diagrams), with pie sizes corresponding to magnitude of local impairment, and slice sizes to the relative probable contributions of different stressors. The types of models we used have been successfully applied in ecology and ecotoxicology, but they have not previously been used in concert to quantify impairment and its likely causes. Although data limitations constrained our ability to examine complex interactions between stressors and species, the direct relationships we detected likely represent conservative estimates of stressor contributions to local impairment. Future refinements of the general approach and specific methods described here should yield even more promising results.

Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times.

PubMed

Molenaar, Dylan; de Boeck, Paul

2018-06-01

In item response theory modeling of responses and response times, it is commonly assumed that the item responses have the same characteristics across the response times. However, heterogeneity might arise in the data if subjects resort to different response processes when solving the test items. These differences may be within-subject effects, that is, a subject might use a certain process on some of the items and a different process with different item characteristics on the other items. If the probability of using one process over the other process depends on the subject's response time, within-subject heterogeneity of the item characteristics across the response times arises. In this paper, the method of response mixture modeling is presented to account for such heterogeneity. Contrary to traditional mixture modeling where the full response vectors are classified, response mixture modeling involves classification of the individual elements in the response vector. In a simulation study, the response mixture model is shown to be viable in terms of parameter recovery. In addition, the response mixture model is applied to a real dataset to illustrate its use in investigating within-subject heterogeneity in the item characteristics across response times.

Acute effects of an organic solvent mixture on the human central nervous system.

PubMed

Muttray, Axel; Martus, P; Schachtrup, S; Müller, E; Mayer-Popken, O; Konietzko, J

2005-09-12

At workplaces, organic solvents are often used as mixtures. Nevertheless, there is limited knowledge of their acute effects on human central nervous system. Here we report the effects of a toluene-acetone mixture. In a parallel design, subgroups of 12 healthy men each were exposed to a mixture containing 25 ppm acetone and 250 ppm toluene or to air (control) in an exposure chamber for 4.5 hours. Concentrations corresponded to the German TLV (TRGS 403). Concentrations of toluene and acetone in venous blood were measured by headspace gas chromatography. Subjects were sedentary. The following tests were performed before and at the end of exposure: Questionnaires, simple reaction time, vigilance, quantitative analysis of EEG with open and closed eyes and during the Color Word Stress test, and visual evoked potentials (VEP). Blood levels were 0.14 (+/- 0.04 SD) mg toluene/l and 5.43 (+/- 1.37 SD) mg acetone/l at the end of solvent exposure. Scores of neurotoxic and irritating symptoms were not elevated during solvent exposure. Exposed subjects performed as well as control subjects on the simple reaction time test and on the vigilance test, neither reaction time nor number of hits differed significantly. A general linear model on log transformed spectral power values showed insignificant changes in EEG. In the alpha subset2-band an average reduction to 86 % was observed in exposed as compared to non exposed subjects with closed eyes, a reduction to 88 % in the theta-band with open eyes, and a reduction to 92 % in the theta-band during the Color Word Stress test. VEP P 100 latencies and amplitudes did not change. The mixture consisting of toluene and acetone did not cause any adverse acute effect. With respect to EEG data, possible subclinical effects on central nervous system cannot be excluded.

Blind source separation by sparse decomposition

NASA Astrophysics Data System (ADS)

Zibulevsky, Michael; Pearlmutter, Barak A.

2000-04-01

The blind source separation problem is to extract the underlying source signals from a set of their linear mixtures, where the mixing matrix is unknown. This situation is common, eg in acoustics, radio, and medical signal processing. We exploit the property of the sources to have a sparse representation in a corresponding signal dictionary. Such a dictionary may consist of wavelets, wavelet packets, etc., or be obtained by learning from a given family of signals. Starting from the maximum a posteriori framework, which is applicable to the case of more sources than mixtures, we derive a few other categories of objective functions, which provide faster and more robust computations, when there are an equal number of sources and mixtures. Our experiments with artificial signals and with musical sounds demonstrate significantly better separation than other known techniques.

A stochastic evolutionary model generating a mixture of exponential distributions

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Levene, Mark; Loizou, George

2016-02-01

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in [T. Fenner, M. Levene, G. Loizou, J. Stat. Mech. 2015, P08015 (2015)] so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model.

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

PubMed

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.

An NCME Instructional Module on Latent DIF Analysis Using Mixture Item Response Models

ERIC Educational Resources Information Center

Cho, Sun-Joo; Suh, Youngsuk; Lee, Woo-yeol

2016-01-01

The purpose of this ITEMS module is to provide an introduction to differential item functioning (DIF) analysis using mixture item response models. The mixture item response models for DIF analysis involve comparing item profiles across latent groups, instead of manifest groups. First, an overview of DIF analysis based on latent groups, called…

Effects of three veterinary antibiotics and their binary mixtures on two green alga species.

PubMed

Carusso, S; Juárez, A B; Moretton, J; Magdaleno, A

2018-03-01

The individual and combined toxicities of chlortetracycline (CTC), oxytetracycline (OTC) and enrofloxacin (ENF) have been examined in two green algae representative of the freshwater environment, the international standard strain Pseudokichneriella subcapitata and the native strain Ankistrodesmus fusiformis. The toxicities of the three antibiotics and their mixtures were similar in both strains, although low concentrations of ENF and CTC + ENF were more toxic in A. fusiformis than in the standard strain. The toxicological interactions of binary mixtures were predicted using the two classical models of additivity: Concentration Addition (CA) and Independent Action (IA), and compared to the experimentally determined toxicities over a range of concentrations between 0.1 and 10 mg L -1 . The CA model predicted the inhibition of algal growth in the three mixtures in P. subcapitata, and in the CTC + OTC and CTC + ENF mixtures in A. fusiformis. However, this model underestimated the experimental results obtained in the OTC + ENF mixture in A. fusiformis. The IA model did not predict the experimental toxicological effects of the three mixtures in either strain. The sum of the toxic units (TU) for the mixtures was calculated. According to these values, the binary mixtures CTC + ENF and OTC + ENF showed an additive effect, and the CTC + OTC mixture showed antagonism in P. subcapitata, whereas the three mixtures showed synergistic effects in A. fusiformis. Although A. fusiformis was isolated from a polluted river, it showed a similar sensitivity with respect to P. subcapitata when it was exposed to binary mixtures of antibiotics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Selective recovery of tagatose from mixtures with galactose by direct extraction with supercritical CO2 and different cosolvents.

PubMed

Montañés, Fernando; Fornari, Tiziana; Martín-Alvarez, Pedro J; Corzo, Nieves; Olano, Agustin; Ibañez, Elena

2006-10-18

A selective fractionation method of carbohydrate mixtures of galactose/tagatose, using supercritical CO(2) and isopropanol as cosolvent, has been evaluated. Optimization was carried out using a central composite face design and considering as factors the extraction pressure (from 100 to 300 bar), the extraction temperature (from 60 to 100 degrees C), and the modifier flow rate (from 0.2 to 0.4 mL/min, which corresponded to a total cosolvent percentage ranging from 4 to 18% vol). The responses evaluated were the amount (milligrams) of tagatose and galactose extracted and their recoveries (percent). The statistical analysis of the results provided mathematical models for each response variable. The corresponding parameters were estimated by multiple linear regression, and high determination coefficients (>0.96) were obtained. The optimum conditions of the extraction process to get the maximum recovery of tagatose (37%) were 300 bar, 60 degrees C, and 0.4 mL/min of cosolvent. The predicted value was 24.37 mg of tagatose, whereas the experimental value was 26.34 mg, which is a 7% error from the predicted value. Cosolvent polarity effects on tagatose extraction from mixtures of galactose/tagatose were also studied using different alcohols and their mixtures with water. Although a remarkable increase of the amount of total carbohydrate extracted with polarity was found, selective extraction of tagatose decreased with increase of polarity of assayed cosolvents. To improve the recovery of extracted tagatose, additional experiments outside the experimental domain were carried out (300 bar, 80 degrees C, and 0.6 mL/min of isopropanol); recoveries >75% of tagatose with purity >90% were obtained.